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Falabella Group is a leading global Retail and Financial services company with over 100 years of legacy. To achieve their vision of "One Company and One Customer," they partnered with Publicis Sapient to develop a scalable customer data platform (CDP) unifying shopper data to deliver 360-degree insights and superior brand experiences. Above, view highlights from our Google Cloud webinar on Harnessing Data in Retail, with key takeaways from Falabella’s Chief Data Officer, or  watch the full episode here.

Falabella Group

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Falabella at a Glance

case study customer data platform

"Siloed data existed across all our business units spanning seven countries in Latin America. We had 40,000 tables with no catalog/metadata and 60,000 ETL’s with limited documentation, as well as duplication of data, which wasted resources and risked error. We were also unable to link semi and unstructured data from internal and external sources and experienced significant constraints in capacity, with lengthy processing times of the EDW platform, which directly impacted resource consumption efforts."

case study customer data platform

The Imperative for Change

When approaching their goal, Falabella Group realized they faced a major problem. Siloed data across the business made it difficult to manage customer engagement and growth. To solve this, they envisioned a CDP that integrated and enriched customer data under one unified platform, fueling their transformation strategy.

The Transformative Solution

Publicis Sapient built a custom CDP solution leveraging Google Cloud. The solution solved for several areas of data transformation, including:

  • Data ingestion, transformation, consumption and entities unification
  • Modular/customizable machine learning, logging/monitoring, scheduling, DevOps and test automation frameworks
  • Customer 360 applications, including customer unification/profile, order, product and transactional analysis
  • A cloud agnostic/self-service custom ML to perform predictive data analytics, measure customer lifetime value, product and channel affinity for acquisition, personalization and retention

case study customer data platform

The Business Impact

Powered by the customer insights that the CDP provides, Falabella has already started to identify and activate strategies to realize tangible business benefits through improved marketing effectiveness – reducing customer churn, providing best customer offers and superior personalization. 

The CDP solution has laid a solid foundation for Falabella to accelerate their journey to become a true Algorithmic Retailer, with the ability to extend data-driven culture to other areas of its business and drive sustained growth through competitive advantage, enhanced customer-brand connection and improved profitability.

"Publicis Sapient has been an amazing partner in the data-led transformation at Falabella. Their expertise, people, partners and accelerators delivered a world-class CDP on the same week as originally forecast despite global challenges and COVID-19. Their work has delivered millions in business benefits to Falabella Group today, and serves as a strategic foundation for us for the next decade."

Hilding Anderson

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What Is a Customer Data Platform (CDP)? The Definitive Guide

By Jordan Torpy

A binder with data on a CDP

Table of Contents

What Is a Customer Data Platform?

How to build a customer data platform, cdp characteristics, cdp skill requirements, what is the history of customer data platforms, why is customer data important, what kind of customer data does a cdp work with, what makes customer data platforms different from dmp and crm, types of customer data platforms, the difference between enterprise-grade cdps and small business cdps, the benefits of a customer data platform (key cdp use cases), how can a cdp improve customer lifetime value and foster customer loyalty, how long does it take to implement a customer data platform, the 3 necessary stages to implementing a cdp, how to choose the right cdp for your company, why choose bloomreach engagement.

You’ve heard the buzz about customer data platforms. You’ve heard the letters CDP bandied about. Maybe your boss asked you if your company needs a CDP. Maybe you’re a boss wondering the same thing.

Whatever questions you have about CDPs, you've come to the right place. We’re here to give you all the info you need on this crucial marketing technology.

  • A CDP is a smart, user-friendly software that confidently consolidates and manages all customer data, creating a unified, enduring record of each customer's attributes.
  • Unlike some other database software programs, a CDP is a tool built mainly for marketers. But having access to technical support will be essential for integration and operation concerns.
  • While a CDP is similar to customer relationship management (CRM) software, it is also distinctly different and a CDP with marketing automation capabilities gives marketers additional options to power e-commerce personalization.

A Customer Data Platform (CDP) is a type of marketing technology software. Specifically, it’s a kind of unified customer database software: one that creates persistent, consolidated records of all your customers, their attributes, and their data. A good CDP should easily integrate with your existing data and allow for easy retrieval of the data it stores.

A CDP builds a complete picture of your customers on an individual level. It collects first-party customer data (transactional, demographic, and behavioral data) from a multitude of sources and systems, and links that information to the customer that created it.

This creates a 360-degree customer profile , also called a single customer view , which can then be used by third-party tools or built-in marketing automation tools to execute marketing campaigns and analyze their performance .

A computer displaying a marketer’s single customer view, connecting, tracking, and unifying data from all online and offline sources for individual customers.

So, how do you build a CDP? For any customer data platform to function, there are three main steps involved:

Integration

First and foremost, compiling and assembling all relevant data into a single database is the primary task of any CDP. It works to solve the problem of disconnected data sets by linking all your sources and systems together in one place.

Organization

Once your data is integrated, a CDP needs quality control protocols. It needs to identify and address any missing information, remove duplicate data sets, and cross-check for accuracy so that segments and audiences can be identified.

Identity Resolution

After connecting all the dots, merging data from multiple sources and attributing it to specific customer profiles is where a customer data platform really shines. This is called data unification and it lets you build complete profiles of every individual customer, where you can build and expand on insights as they interact with your business.

There are a variety of businesses offering various CDP offerings, but the best of the best provide a few essential characteristics that every marketer should look for:

  • Ready‑to‑Use Solution

All customer data is neatly organized and available for immediate use. Some technical resources are required to set up and maintain the CDP, but it does not require a high level of technical skill compared to a traditional data warehouse.

  • Single Customer View

Customer data collected and organized with a CDP is visualized through individual data profiles for each user. This 360-degree view of the customer is possible due to the fact that all customer data is located in one central location.

  • Customer Data Unification

Inconsistent data from multiple online and offline sources is combined to create a unified single customer view .

  • Accessible Data for Third Parties

Data contained within a CDP is ready for use in third-party systems focused on adtech and campaign delivery.

Unlike some other database software programs, a CDP is a tool built mainly for marketers. That doesn’t necessarily mean that a CDP can be operated without any technical support. To get the most out of a CDP, an organization will typically need these three roles:

  • Marketer: a person who understands the market and can suggest business-tailored use cases for the CDP.
  • IT Person: someone to help support the marketer during the implementation phase of the CDP, and can help manage tasks like using webhooks, deploying recommendations on the web, or helping with integrations. Knowledge of HTML, CSS, and Javascript is also helpful for building powerful weblayers.
  • Analytical Person: someone that knows how to work with data and what to track in custom dashboards, how to analyze A/B tests, and can report results to the marketing team.

These don’t have to be three separate people, but for maximum value from a CDP you’ll need all those skills.

A team that best utilizes a customer data platform incorporates marketing, IT, and analytics roles and skillsets.

Managing customer data is nothing new. From handwritten filing cards and massive independent mainframes to modern cloud-based solutions, the search for the best tool has been going strong for decades. Modern computing power has significantly increased the pace of progress, allowing for more and more useful tools.

Online customer relationship management (CRM) software was introduced in the 90s and allowed companies to manage their interactions with both current and potential customers. These customer relationship management platforms could also perform customer data analysis that could help drive retention and sales. While useful, these tools had some limitations: They only managed data for registered clients and only used predefined first-party data.

Things changed in the 2000s with the rise of data management platforms (DMPs) . These were aimed towards advertisers and helped with the planning and execution of media campaigns. Unlike CRMs, DMPs worked with second- and third-party data, and could segment anonymous IDs.

The customer data platform (CDP) was introduced a few years back as a reaction to the demand for an improved customer experience and omnichannel marketing initiatives. Older tools, while useful for their purposes, had created data silos. CRM data was one thing, DMP data was another — and marketers weren’t able to productively use all the data they had access to.

CDPs solved this problem by offering a unified customer view that gathers a company’s first-party data (and to some extent, second- and third-party data) into a single, comprehensive platform. A major advantage of CDPs is their ability to store extremely granular first-party data, such as events on a website.

Bloomreach Engagement: A CDP Since 2012

Bloomreach acquired Exponea in early 2021 , a SaaS company that built its CDP architecture from the ground up starting in 2012. This has allowed Bloomreach to refine and improve its customer data platform, and build powerful tools on top of it to help modern businesses manage customer data and harness its utmost potential.

Thanks to years of hard work and growth, Bloomreach has an industry-leading CDP, made even more powerful by user-centric analytics, predictions, recommendations, and marketing automation layers. We call it Bloomreach Engagement .

Today’s customers expect a lot from companies. They’ve experienced good personalized service, and if you want to keep their business, you need to provide that elevated standard. A consistent customer experience across channels, appropriate recommendations, tailored communications — for today’s customers, these are necessary.

A customer receiving a personalized marketing message on their phone that creates a consistent experiences across multiple marketing channels.

Not many companies can actually deliver these personalized experiences. But if you can’t meet customers heightened expectations, you have a problem. If customers think you don’t care about them, they’ll take their business somewhere else — and they won’t be coming back. The fight to win those customers back will be much more difficult than getting their business in the first place.

This is why it’s so crucial to have well-maintained, accessible, and insightful customer data. And now, a good CDP makes that possible. It’s only a matter of getting the right data.

The sheer volume and speed of digital data is hard to comprehend, and overwhelms traditional database software. A CDP, however, is purpose-built to manage this flow of data.

The most reliable way for a CDP to collect this type of data is via their own SDK, but most CDPs can also ingest data from other systems via JSON or batch ETL transfers.

The types of data a CDP can work with include:

  • Events: behavioral data that arises from a user’s actions in a session on a website, in an app, or on a mobile browser.
  • Customer Attributes: this includes names, addresses, contact details, birthdays, etc. Advanced CDPs can also store machine learning-powered predictions, such as likelihood to purchase.
  • Transactional Data: purchases, returns, and other info from e-commerce or POS systems.
  • Campaign Metrics: engagement, reach, impressions, and other metrics from campaigns.
  • Customer Service Data: live chat data, number and length of interactions, frequency, NPS scores, and other data from CRM systems.

When comparing data gathering software, it’s easy to get overwhelmed. There’s a sea of similar acronyms, product descriptions that look almost the same, and lots of claims about which program best suits your needs.

You might have come across customer relationship software (CRM), CDPs, and data management platforms (DMP). While their capabilities might sound similar, it’s important to understand the distinctions between them so you can evaluate vendors and choose the right product for your business needs.

A comparison table showing the similarities and differences between a CDP vs a DMP vs a CRM

CDP vs. DMP vs. CRM: Table Explained

  • Holistic Customer Data: Does the platform manage customer data from all available sources (behavioral, demographic, personal, transactional, device, etc.)?
  • Lasting Customer Profiles: Does the platform retain data for a long period of time?
  • Packaged System: Can the platform exist as a ready-to-use piece of software?
  • Real-time Capability: Does the platform update data in real time, allowing for quick reactions to changes?
  • Open Platform: Is it simple to get data into the platform? Is it easy to share data from the platform with other services?
  • Cross-channel Personalization: Does the platform allow for the personalization of messages across different customer touchpoints?
  • Only Anonymized Data: A data management platform by design works with anonymized customer data. CRMs and CDPs work with identified customers, and allow for granular views of individual customers.
  • Identity Resolution: Does the platform allow you to connect the customer behavior of anonymous visitors with known customers after they have given their consent? Does the platform recognize customers across devices?
  • First-party Data Priority: Does the platform primarily deal with data from first-party sources?
  • Third-party Data Priority: Does the platform primarily deal with data from third-party sources?
  • Requires IT Support: Does day-to-day operation of the software require support from IT?

Finding the right platform is no easy task. But understanding what you can expect your CDP to do for you on a daily basis helps.

In our knowledge card , you’ll get essential know-how on CDPs and learn more about the features that your company should be looking for in its CDP.

The customer data platform market has matured, leading to a number of different providers. These providers are differentiated based on their target market and their intended use cases. Let’s take a look at some of the differences.

A Standalone CDP vs. CDP + Marketing Automation

A key distinction among CDP vendors is whether they provide a product which is only a CDP, or a CDP plus other capabilities. It’s crucial to understand what your vendor is providing, because this distinction can cause large differences in how your business uses the CDP.

A Standalone CDP

A standalone CDP is exactly what it sounds like: a customer data platform without extra capabilities . It ingests all of a company’s first-party data and builds complete pictures of all of your customers (a single customer view). Usually, a standalone CDP will offer analytics capabilities, allowing for granular segmentations of your audience.

This data is accessible for use by other systems, but the standalone CDP cannot execute campaigns . It needs dedicated tools that can make use of the comprehensive data it collects.

For companies that already have campaign execution tools, a standalone CDP might make sense. But companies that lack those capabilities should consider a CDP + marketing automation platform.

A visualization of a standalone customer data platform, illustrating how ingests all of a company’s first-party data and uses that to build complete pictures of customers

CDP + Marketing Automation

A customer data platform coupled with marketing automation is the next generation of the CDP. It combines all the benefits of a standalone CDP with marketing campaign tools , creating a single, powerful, customer-centric marketing platform.

This gives marketers the complete toolset they need for creating incredible customer experiences by bringing together AI-driven marketing capabilities, real-time analytics, and UX optimization with a CDP.

A CDP combined with marketing automation simplifies workflows and increases productivity by collecting frequently used tools into one integrated interface. But it is also flexible and can fit into your existing tech stack — it molds around what you already have and fills gaps.

Key Benefits:

  • Provides a foundation for a 360-degree customer view
  • Makes customer loyalty-driven decision making possible
  • Facilitates more precise targeting and higher-quality interactions with customers
  • Allows for meaningful analysis of marketing initiatives across different channels
  • Enables agile responses to changes in the market or customer preferences

A visualization of a CDP with marketing automation, illustrating how it collects marketing tools into one integrated interface.

Bloomreach Engagement: The Most Versatile Platform on the Market

Bloomreach offers you the flexibility to pick and choose which features you want to use; it’s not an “all-or-nothing” solution. Although Bloomreach is a CDP + marketing automation, it can act as a standalone CDP to provide a unified source of customer data to an existing technology stack, or it can be used to handle all marketing activities using the additional layers of campaign execution and analytics.

If you already have a CDP, Bloomreach Engagement’s customer data engine can help you fully activate your data and maximize the ROI of your e-commerce marketing efforts. Our customer data engine is what makes our platform truly stand out with capabilities that go beyond the standard scope of marketing toolsets. Our powerful data core combines CDP capabilities and advanced analytics to help marketers understand the customer journey in real time and create omnichannel campaigns that drive results.

There are multiple CDP providers out there, each with differing purposes and capabilities.

A key consideration when choosing a CDP is the intended scale of the software. Is it built for small businesses? Or is it a full-fledged enterprise solution? There are some key points to remember when answering these questions:

Scalability. Enterprise-level companies need to work with massive amounts of data. That data can change quickly, and for a CDP to be useful, it needs to respond to those changes swiftly and accurately. This means that CDP architecture needs to be built for scale from the very beginning.

Flexibility. No two companies are the same. For enterprise-level companies, a plug-and-play solution will almost never be suitable for the unique needs of a company — therefore flexibility in a CDP is a must-have. A customer data platform must be able to ingest a company’s data from all its unique sources, as well as interface successfully with the platforms the company uses to function.

Integrity. A CDP needs to be trusted with the sensitive data it uses, and that can mean data for millions of customers. This requires rigorous security protocols and a dedication to privacy. These need to be core values of the CDP provider if they are to be trusted with customer data.

Bloomreach Engagement: An Enterprise-grade CDP

Bloomreach Engagement was built from the ground up as an enterprise-grade CDP. Thoughtful product planning and experience with world-class clients has made Bloomreach an industry leader in customer data platforms for the most demanding of applications.

Scalability: Bloomreach’s agile in-memory framework is scalable by design and is ready to handle massive volumes of rapidly changing data at the speeds necessary for business success.

Flexibility: Bloomreach easily adapts to the needs of enterprise-class businesses. A quick onboarding process integrates Bloomreach with existing data. A rich API makes third-party integrations smooth and painless. And native integrations with best-in-class tools means Bloomreach works with the tools you already use.

Security: Privacy and security have been core values of Bloomreach from the very beginning. Bloomreach undergoes regular audits to maintain our status as a leader in this area.

There's a mutlitude of benefits to using a CDP, but most the types of advantages you get from a platform really boils down to the way your business wants to employ it.

And just as there are numerous benefits, there is the large number of CDP vendors on the market, which can be overwhelming. When choosing a vendor, it's helpful to consider the use cases you hope to accomplish with a help of CDP.

While it’s important to have high-level goals (improve the customer experience, foster loyalty, etc.), you also need to know how a CDP can help you achieve those goals through lower-level use cases.

We’ve collected what we believe to be some of the most important use cases, and benefits, below.

CDP Use Cases:

1. Online to Offline Connection

Merge online and offline activities to create an accurate customer profile. Identify customers from online activities when they enter a brick and mortar store.

2. Customer Segmentation and Personalization

Segment customers according to their behavior (RFM, LTV prediction) to deliver a personalized, omnichannel experience throughout the entire customer lifecycle.

Read This Next: E-Commerce Personalization: Your Complete Guide

case study customer data platform

3. Predictive Customer Scoring

Enrich your customer profiles with predictive data (probability of purchase, churn, visit, email open rates).

4. Smart Behavioral Retargeting and Lookalike Advertising

Integration with Facebook Ads, Google Ads, Google Analytics, and Doubleclick enables you to leverage insights and run powerful acquisition and retention (lookalike) campaigns outside of your website.

Read This Next: Weird Fish Increases Facebook Ads Revenue by 82% With Bloomreach

case study customer data platform

5. Product Recommendations

Create different recommendation models such as “similar products” or “customers also bought” and deliver the best shopping experience to drive engagement, increase brand loyalty, and sell, up-sell, or cross-sell your products or services.

Read This Next: Why Product Recommendations Are Key to Winning With E-Commerce

case study customer data platform

6. Conversion Rate Optimization and A/B Testing

Quickly transform the appearance of your pages. Use our smart website overlays (pop-ups) or send cart abandonment emails to increase your ROI. Create different designs and determine which variant performs better with the automatic A/B testing feature.

7. Omnichannel Automation

Guide your customers through their entire lifecycle with personalized messages sent to their preferred channel, significantly enhancing your opportunities to both acquire and keep a loyal customer.

Read This Next: What Is Omnichannel Commerce? Definition, Benefits, and Trends

case study customer data platform

8. Email Deliverability Enhancement

Increase email open rates. Thanks to an AI-powered algorithm, you can determine the ideal distribution time for each user based on their email opening habits and reach them at this optimal hour.

9. Reviews Optimization

Get better and more frequent online reviews from your customers through personalized omnichannel communication and NPS survey analysis.

The most effective way to foster customer loyalty is to give your customers exactly what they’re looking for: a consistent, high-quality, and personalized experience. Customer data platforms make it possible to deliver these experiences at scale, personalizing the journey of each customer.

CDPs enable loyalty-building strategies by solving the problem of fragmented data silos. They arrange customer data in a way that makes personalization at scale possible (though personalization tools themselves are not always part of a CDP).

If your data is siloed, you can’t create a consistent experience for your customers. Without that central data hub, you can’t provide the omnichannel experience customers expect, which is receiving up-to-date interactions regardless of which channel the customer communicates through.

An illustration of visitor nurturing illustrating how a CDP with marketing automation can improve customer lifetime value

Read This Next: 3 CDP Personalization Tactics to Fuel Your Marketing

The short answer? It depends. A very rough estimate would be 4-12 weeks.

The long answer? Without knowing the details of your organization and business needs, there’s no one-size-fits-all answer. There are a few things you’ll need to take into consideration:

  • Integration complexity — how many tools will you need to integrate with?
  • CDP output requirements — what will you need from the CDP?
  • Current state of your data — data cleansing can lead to a longer implementation
  • Unique business rules — are there business-specific stipulations to consider?
  • Identity merging needs — siloed data can lead to a single customer having multiple profiles across different platforms, and merging these profiles takes time
  • Level of detail in data attributes

Every business that wants the benefits of a CDP will have different requirements and goals, making it impossible to give a precise answer to how long the implementation process will take.

Nevertheless, most businesses can expect to go through a similar set of steps when implementing a CDP.

Let’s walk through the typical steps in the process of implementing a CDP.

We’ll also look at the differences between implementing a standalone CDP and CDP with built-in campaign execution and analytics capabilities.

An illustration of the three necessary stages to implement a customer data platform

1. Planning Phase

All the necessary groundwork for integrating a CDP needs to be taken care of before any technical work can begin. Some necessary parts of this stage include:

Project Scope Creation: describe business goals, use cases , step-by-step integration and implementation.

Tracking Document Creation: describe customer attributes, consents, and custom events to be tracked.

2. Integration Phase

Once ouy lay the groundwork, it's time for the technical integrations to begin. Most of the integration steps will be standard for any data collection tool, but this process will vary slightly depending on what type of CDP you choose. Let's go over the routine integration steps first:

CDP Initialization: This is the process of connecting the CDP to your online & offline data sources, allowing you to identify your customers and analyze their actions. With Bloomreach, this is very simple: just paste a snippet of code into the header of your website. Other solutions might look quite different.

Customer IDs and Attributes Tracking: After initializing the CDP, set up customer IDs and attributes tracking for the information you’ve decided to collect. This data is helpful for segmenting your audience, triggering campaigns, sending personalized information, and more.

Events Tracking: Follow and get insight into customer behavior by tracking purchases, clicks, returns, browsing behavior, and more. Connect this to a customer’s unique identifier to build complete pictures of each customer.

Data Imports: Connect all your existing data (customer data, event data, product catalogs) to your new platform.

The steps in this importing process depend entirely on your CDP.

If you are using a Standalone CDP , you will want to integrate it with your other tools and platforms so you can make the most of its capabilities. Consider which of the below platforms you want to use. They will each need to be integrated with the CDP.

  • ESP Integration
  • Business Intelligence Platform
  • Web Optimization Platform
  • Recommendation Platform
  • Predictive Analytics Platform
  • Advertising Platform
  • Mobile Marketing Platform

These integrations are unnecessary with a CDP + marketing automation, since analytics and automation abilities are built in.

If you are using a CDP + Marketing Automation , there's no further integration process needed. A CDP + marketing automation platform doesn't require any integration with analytics and execution tools, since those capabilities are native. As soon as the platform is integrated, you can begin analyzing data and executing automated marketing campaigns.

Note: If you want to keep some of your existing third-party tools, you can integrate them with Bloomreach Engagement, just like a standalone CDP.

3. Execution Phase

You’ve finished initializing your CDP, you’ve set up customer identifiers and event tracking, you’ve integrated all your tools and platforms — now you can start using your platform to power insightful analytics and marketing automation.

But again, this process will look different depending on what type of CDP you employ.

Because a standalone CDP was not built together with your analytics and execution platforms, you can expect the following:

  • Many User Interfaces
  • Different Technologies
  • Unidirectional Data Flow
  • Difficult Omnichannel Orchestration
  • Delays in Response

A CDP + marketing automation offers some advantages for execution. Thanks to an all-in-one solution, marketers can expect:

  • One User Interface
  • Unified Technology
  • Bidirectional Data Flow
  • Easy Omnichannel Orchestration
  • Real-time Response

After you’ve decided that a CDP is the right tool for your business, you’ve got to decide which vendor to choose. The number of possible vendors might make the choice seem overwhelming, so it’s important to have a plan for your buying process.

Each company will have different requirements and use cases , but some parts of the buying process should look the same for most businesses.

First, you need to define your use cases . How do you plan to use a CDP? Do you want a CDP with execution layers and e-commerce personalization capabilities? Or do you just need identity resolution and customer segmentation (standalone CDP)? Answering this question will help you better understand your requirements.

Once you’ve done that, you can start to match your requirements to potential vendors . Can they handle the use cases that you require? This allows you to create a short list of candidates.

Next, evaluate the vendors you’ve selected. Ask them to demonstrate their platform executing a use case that you require, instead of relying on a canned demo that only showcases the best that platform has to offer. This will show you if a potential solution is right for you or not.

Finally you can make your decision . This might involve an RFP or a pilot project to make sure that the solution you’ve chosen actually meets your needs. If it has, congratulations! You’re ready to start taking advantage of all a CDP has to offer.

While other companies have recently decided to jump on the CDP bandwagon, Bloomreach offers a CDP + marketing automation solution that has been in existence since 2012. Our Engagement platform is entirely homegrown — all parts of the platform were built to work together, which means faster integrations, smooth operation, and better results.

Bloomreach Engagement is scalable, flexible, and secure . Companies from around the world have opted in for Bloomreach to unify their customer data and power their customer experiences. This includes Sofology , Yves Rocher , BrewDog , and so many more.

To learn more about how Bloomreach Engagement can help your company, schedule a personalized demo today .

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case study customer data platform

Jordan Torpy

Technical CDXP Specialist

case study customer data platform

Lukas Sitar

Senior Content Operations Manager

Jordan works closely with the content team and Bloomreach experts to create material that brings value to readers. With a background in teaching, training, and marketing, Jordan uses case studies, presentations, newsletters and more to illustrate what's possible in the martech world today.

Lukas is the Senior Content Operations Manager contracted with Bloomreach, where he prepares B2B content strategies. Lukas has years of experience in online marketing fields such as analytics, inbound marketing, customer lifecycle marketing and customer experience. His passion is psychology and behavioural economics and he is currently developing his skills in these areas.

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case study customer data platform

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Customer Data Platform Case Studies: How These 3 Awesome Businesses Reimagined Customer Journeys with CDPs

Data drives growth. Every day, customers all over the world make purchase decisions—and every day, marketers strive to understand which factors impact those decisions most. With the right data delivered at the right time, you can reimagine the customer journey, accessing insights that inform your strategy, make your marketing more efficient, and drive more sales.

Treasure Data’s enterprise customer data platform (CDP) helps marketers collect, analyze and activate real-time customer data to improve the efficiency and effectiveness of your efforts. But what does that really look like in an actual business?

3 Companies that Dreamed Bigger with Data, CDPs

Here are three customer data platform case studies that show how enterprise brands found success with Treasure Data.

Wish Builds a Data-Driven Ecommerce Empire

Known as the “Shopping Mall in Your Pocket,” Wish.com and the Wish app are two of the most popular ecommerce platforms in the world, with more than 15 million daily active users (DAU). How did Wish grow to become an ecommerce empire? The secret’s in the data.

The biggest difference between Wish and other ecommerce apps is the browsing experience. Instead of focusing on search queries, the mobile shopping experience on Wish centers around browsing, with the intent to buy. Leveraging Treasure Data’s enterprise CDP, Wish takes in more than 17 billion events per day, each pointing to a simple truth: customers want a more personalized shopping experience.

Using customer data to inform personalized recommendations, nine out of 10 of Wish’s mobile purchases don’t originate with a search query. And that’s not all. Optimized algorithms contributed to 2x conversion growth year-over-year and a 7 percent boost in sales. Peter Szulczewski, CEO and Co-Founder of Wish.com, says, “The more we invest in data to personalize the recommendation experience, the more we see improvement in conversion rates.”

Shiseido Unites 80 Years of Collected Data

Shiseido’s customer loyalty program launched in 1937, serving as the crux of the beauty brand’s customer communication and branding strategy for more than 80 years. However, it wasn’t until 2012 that the brand took the loyalty program online—which meant moving and analyzing 80 years’ worth of data. To keep pace, Shiseido turned to Treasure Data.

Leveraging Treasure Data’s enterprise CDP allowed Shiseido to analyze historical customer purchase data, demographic information, and recent behavior all at the same time, and in one place. Shiseido executives wanted to make their new customer loyalty app experience was highly personalized, so they analyzed data to understand customers’ evolving preferences, and adapt accordingly.

Accurately analyzing and correlating data with customer behavior helped Shiseido accomplish its goal, driving a 20 percent in-store revenue increase per loyalty program member over the course of a year, an 11 percent overall revenue increase, and a 38 percent growth in net income year-over-year.

Subaru Maximizes Click-Through-Rates

Vehicle company Subaru has won accolades like “Best Overall Brand,” “Most Trusted Brand,” and “Best Performance Brand.” How does Subaru continue to score big and deliver exceptional brand value year after year? Customer data plays a critical role.

To maintain its winning streak, the Subaru team knew it needed to more accurately understand the customer journey, as well as a customer’s readiness to purchase a new model. To accomplish this goal—and to drive growth, retention, and monetization— Subaru used Treasure Data’s enterprise CDP to create behavior-based audience segments that allow for direct, personalized communications to different targets.

“We started thinking about people, not devices,” says Atsushi Yasumuro, senior manager of digital marketing at Subaru. “Buyers who just started to consider and those who are almost decided are quite different in character, and using the same advertisement for both is not effective.” Not only did Treasure Data’s CDP provide Subaru with an easy, plug-and-play solution, after implementing the CDP, Subaru’s click-through rate (CTR) on ads skyrocketed 350 percent.

What Can Data Do For You?

Whether you’re looking to create a personalized ecommerce experience, analyze decades’ worth of data to improve your site experience, or better understand the factors driving customer purchasing decisions, the right CDP can help you accomplish even your loftiest marketing goals. See a lot more CDP case studies here as well including ABInbev, Pioneer and Stripe International!

Ready to write your own customer data platform case study? Contact Treasure Data today to learn more.

JC Quiambao

  • Wish to Become the #1 Shopping App? Use Treasure Data The #1 shopping app on iOS and Android in the US is not Amazon. It’s Wish.com. How did this startup founded in 2011 become the leading mobile e-commerce platform in North America and Europe?...
  • A Baby with a Royal Platinum Card? Personalization Fails and How to Stop Them Ever think of getting your kid to charge your next vacation on his credit card? That might have been a possibility for the parents of 2-year-old Evan Hart, who were bemused when their little boy was offered a credit card with thousands of frequent-flyer miles...
  • Customer Data Answers National Auto Dealers’ Big Questions and Show Sales Gains Auto dealerships and national auto brands are increasingly using customer data platforms (CDPs) to understand customer behavior, and the CDPs are getting great results, reducing ad spend & boosting conversion.

customer data platform use cases

10 Customer Data Platform Use Cases

From email marketing and CRMs to data analytics platforms and website analytics, marketers have access to more data than ever before. Having more data is a good thing, however, many companies struggle to make the most of their data. That’s because data is often siloed in different platforms, making it nearly impossible to get a clear view of who your customers are and the impact of our marketing. Fortunately, there’s a solution to this challenge: customer data platforms, also called CPDs. CDPs centralize data from multiple platforms and then aggregate, normalize, and enrich the data to provide a clearer vision of who your customers are and how they interact with you. Once you have that data, you can leverage it in a multitude of ways. Here are ten use cases for CDP.

1. Enhance Ad Performance

CDP data can help you better understand who your audience is and what types of ads they will respond to. For example, a marketing team might see users in a specific geographical area spend more. Moving forward, they might choose to increase spending for audiences in that area. Data from CDP can improve ad targeting. For example, by exporting an audience segment from the CPD and uploading it to platforms like Facebook or Google Ads as a custom audience. Or, you can A/B test similar ads on multiple platforms to see which has a higher ROI.

2. Create Personalized Experiences

CDP data can be used to segment your audience based on behavior, location, and many other characteristics. By connecting your CDP to personalization platforms , marketers can build personalized ads, content, and other assets. For example, say site visitors read three blog posts about building a sales team. The next time they visit your site, you could offer a content upgrade of a sales team management handbook or a guide to building better sales teams. You know those users will likely be interested, increasing your conversion rate and building a list of more qualified leads.

3. Connect Online and In-Person Data

Brands have long struggled to connect online and offline behavior. CDPs can help by gathering data from a reward program or point-of-sale platform. That data can then be connected with online behavior, providing a 360-degree view of your customer journey. For example, a store might allow users to place an order in an app and pick it up in person. When the user arrives, they may see customized recommended products in their app or discounts based on in-app behavior. (Starbucks’ reward app is a fantastic example of this in action.)

4. Reduce Churn

There’s no question: acquisition costs more than retention. Using data from your CDP, you can spot users at risk of churn and work to retain them. For example, you might notice customers who don’t log in to your software system at least twice in the first week are unlikely to stay. When you see customers exhibiting this behavior, you can preemptively send training videos or have a salesperson reach out to help with onboarding. Or, you could create an email segment list of at-risk customers and deliver a drip campaign focused on showing the value your brand delivers. This entire process can be automated by automatically adding users who take specific actions to the list.

5. Improve Omnichannel Marketing

Omnichannel marketing helps businesses provide users with a consistent, useful experience across all channels. Bringing data from multiple channels together has always been a challenge—but no longer. Using a CDP, you can easily see when customers have requested support across multiple channels, focus your efforts on higher-value channels, and track customer journeys as they progress—even if users weave back and forth

6. Real-Time Lead Scoring

Lead scoring helps marketers and sales teams focus on the right leads at the right time. By unifying data from several platforms, your marketing and sales team see which leads are of higher value. For example, an ecommerce company can see which leads have engaged with their brand on multiple platforms or which leads are in their target audience through data enrichment. This data can be used to create a trigger for an automated email sequence or to improve retargeting ads. Lead scoring is also critical for B2B companies looking to prioritize high-value leads. Using AI and machine learning, a CDP can predict which leads are most likely to convert.

7. Power Other Marketing Channels

Paid ads perform better when you have access to more data. When data is siloed, for example in Facebook Ads, TikTok, Google Ads, or Bing Ads, it’s difficult to see which campaigns drive the most ROI. Using a CDP, businesses can combine data in one place and use it to drive strategy across the board. For example, a subscription company might notice ads featuring a specific item get more impressions on Facebook. As a result, they can test that same strategy in search ads.

8. Predict Future Customer Behavior

In the past, analytics platforms only tracked activities that already occurred. For example, Google Analytics can tell you how many people visited a page, but not how many might next week. CDPs combine data from multiple platforms and then use machine learning and AI to make future predictions based on past consumer behavior. This information can help businesses prepare for higher traffic or order volume or understand how to allocate their marketing budget in the future. Predictive data can also foretell the probability a visitor will convert, churn, or even open an email.

9. Increase Cross-Selling and Upselling

By gathering data about specific transactions, a CDP can help online sellers offer personalized recommendations and increase cross-selling and upselling opportunities. For example, an ecommerce company might see a customer has purchased a pair of running shoes and recommend socks or a running belt. Or, a sales tool might notice their enterprise company is on a smaller plan and would be better served by a larger one.

10. Build Lookalike Audiences to Expand Brand Reach

The data from your CDP can also improve targeting options across platforms. By combining data from multiple platforms, CDPs allow businesses to target ads more efficiently and find new audiences. For example, you could export an audience segment from Google Ads and use it to build a lookalike audience in Facebook ads, or vise-versa. Zeta Global CPD+ accelerates brand growth by delivering an actionable view of your customers and enriched, intent-based scoring. Learn how we help businesses build personalized experiences at scale.

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Modernizing our data platform

  • Call for Change
  • When Tech Meets Human Ingenuity
  • A Valuable Difference
  • Related Capabilities

Call for change

Running a business today is all about managing dynamic data. Accenture wanted to make better use of platform services that could develop, run and manage applications in the cloud and make data more visible and secure. Data empowers our people and drives innovation for our evolving business.

After just three years of use, the Accenture Global IT organization recognized its analytics platform was fast becoming obsolete. The platform was managed by Accenture but hosted in the cloud. Yet, increasingly, it was difficult to upgrade and grow, creating greater overheads for managing storage and presenting a high learning curve for developers. We were struggling to stay technologically current. Our people were spending valuable time on operations, troubleshooting and maintenance instead of generating insights to drive our business.

Accenture made the strategic decision to move to Google Cloud’s Platform-as-a-Service (PaaS) model to support our IT strategy to be platform powered, cloud first and intelligence driven. The program team needed to determine how to create a secure, cost-effective and scalable architecture in the cloud while also driving the migration of data and applications from the legacy system.

Using Google Cloud, we could modernize data capabilities to unlock the promise of advanced analytics, increase cost savings via a pay-as-you-go model and drive cutting-edge performance that enables a digital Accenture.

"We decided to migrate our data platform to Google Cloud for sustainability and performance reasons. But the platform does so much more—it gives us enhancements and capabilities that are delivering new business value." — LUIS POLANCO , Director – Global IT, Technology Platforms, Accenture

When tech meets human ingenuity

Without doubt, technology—and how the world uses it—has changed dramatically in the last five years. So, too, has the demand for data insights. Accenture began the journey to improve its analytics platform by assessing if cloud-hosted PaaS offerings could address the cost, performance, and scalability challenges of the legacy data lake. Today, Accenture IT infrastructure runs in the hybrid cloud to take advantage of its scale efficiencies.

The Global IT team selected Google Cloud as the platform for its new analytics data lake, taking advantage of its established solutions and technologies and its flexible cloud platform offerings that power applied intelligence. Google Cloud enables options for deploying the right server sizing and configuration to meet the analytics’ job requirements. The Global IT team, partnering with Google, designed a modernized platform with the ability to deploy services faster, realizing improved performance and stability for the applications powered by the data lake.

As part of the transformation journey, the platform architecture and processes had to be created to align with our security needs to make sure that the data coming in and the data going out was secure at the enterprise level. With the move to Google Cloud, Accenture has created a foundation to store and analyze its enterprise data in the data lake—with room to grow.

To take advantage of the architecture, we needed to address who could access the data and who and how we deploy analytics into production. A new data security model, along with project governance, was created, while adhering to our data compliance and audit requirements. In line with industry standards, Accenture adopted a Site Reliability Engineering (SRE) model where teams can build, operate and run their own environments and services. Cloud native services, driven via code, meant that the cloud could optimize efficiency.

Moving to this model means that teams can use repeatable infrastructure deployments, avoid manual configuration and introduce greater consistency. Compliance and security checks before deployment means teams can work with a unified set of practices and tools to deliver applications and their supporting infrastructure rapidly, reliably, at scale and while minimizing vulnerabilities to the systems.

Now, Accenture has advanced our cloud capabilities with self-service analytics, real-time integration across various platforms, such as ServiceNow and Salesforce , and moved into a PaaS model with a cloud native infrastructure.

case study customer data platform

How to know what you don’t know, now

case study customer data platform

Data migration

In addition to setting up the new architecture, Accenture needed to execute a migration strategy to move hundreds of terabytes of data from the existing infrastructure to Google Cloud. Sitting on top of the existing analytics platform were more than 50 applications driving insights to users all over the globe. The team needed to manage a seamless transition with minimal impact and no downtime to the 40,000 global consumers of those analytics applications.

Accenture wanted to take advantage of cloud native components quickly and reduce administrative complexity, so the migration team reshaped the current applications to use on-demand infrastructure concepts and on-demand resources optimized for cloud computing. In a phased, targeted approach, applications were evaluated to reimplement the data ingestion and store strategy. Processing code remained the same, but data warehouse interfaces were moved fully to automated services such as Google BigQuery (which gives us the security and control we need when sharing data) and Google Cloud Composer to run workflows.

Since executing a multi-year program to remove silos and make data available, we’ve moved from zero data in the lake to 460 datasets with more than 400 terabytes of business data available to our end users.

As part of the rationalization of existing apps, Accenture has enabled more than 150 source applications and more than 250 business applications.

Applications now available via Google Cloud include:

Accenture Legal Intelligent Contract Exploration (ALICE): Our 2,800-strong Accenture legal teams need to understand our rights and obligations across contracts with clients and precisely how they are documented. The award-winning ALICE tool combines natural language processing (NLP) and artificial intelligence (AI) to help analyze more than 250,000 documents so that legal leaders can quickly evaluate client contracts. ALICE is delivering major time savings, unleashing data that was previously not easily accessible and offering knowledge at the moments that matter.

Manage myBusiness: A self-service analytics dashboard that gives our business unit and client account leads real-time, easy and secure access to the information that they need to manage business performance. The application uses AI to provide an interactive experience that enables our business leads to analyze key performance indicators, connect to a wide suite of diagnostics and drill down to transaction systems.

Manage myContracts: A simple way to track and manage contracts through shared data, reporting and dashboards. This collaboration hub uses an intuitive visual representation of a contract health score to enable our teams to quickly understand the overall health of a contract. By better tracking and monitoring the status of a specific contract, curated mitigations can help to avoid risks becoming issues. Shared oversight helps contract managers to help support delivery, work smarter with account teams, inform business planning and manage ever-increasing contract volumes. The application integrates with our contracting tool Manage myDeal and the legal tool ALICE .

Anomaly detection: We process approximately 25 million expense lines annually. Every report is analyzed by a manually designed rules-based system to check for expense compliance. Roughly 10% of expenses are flagged for potential noncompliance and then audited by the Accenture compliance team. Traditional rules-based systems—while effective at detecting known and recurring patterns of noncompliance—can be unreliable or exploited by fraudulent behavior. We developed an anomaly detection solution for our expense reporting system that more accurately identifies noncompliant expenses, reduces false positives and easily identifies hidden patterns using AI.

Skill diversity

When Accenture made the decision to move to Google Cloud, the leadership team recognized this would represent a major change, touching all our processes and the skills of our team. Indeed, data analytics is far from being all about technology—it demands skill diversity and a data culture—and we knew we needed to transform how our people work with the technology.

The team chose to tackle the culture, talent and change barriers to successful cloud adoption. The focus was on preparing the teams to transition to the cloud, assessing the current and desired cloud skills, developing tailored learning paths and creating and enabling a continuous training plan. Transformation leaders were selected across roles, locations and functions to provide 360-degree feedback loops and accelerate the time to development.

The Global IT team recognized that to be a cloud-first organization we needed to shift our talent focus to crafting analytics solutions that bridge Google Cloud capabilities with our internal systems.

Today, skill diversity is helping us to implement the right business cases that are making data analytics shine in our company. We have more than 260 data projects on the Google Cloud platform, more than 60 data science projects and we have created 75 predictive models.

A valuable difference

We embrace innovation while knowing that it is most effective when we adopt a “fail fast and early” approach through purposeful, measured experimentation.

We also understand the important of knowing our customers to provide personalized product offerings that are useful for them.

And we recognize that if we want to be agile in our business, we need to adopt a transparent, as-a-service approach—one that demands the right information at the right time. For example, in the early weeks of the COVID-19 pandemic, our Global IT team delivered value-added analytics quickly to numerous enterprise functions and this enabled our organization to respond with data-driven decision making.

Google Cloud Platform with its open architecture approach is giving our teams greater freedom to:

  • Democratize data: We want to make data accessible to all our people. By providing more autonomy to our users and the ability to quickly explore our data and create analytics insights to answer business questions, our people can reduce their dependencies on our IT teams to deliver analytics products.
  • Manage data as a product: Our business data lake in Google Cloud is helping us to understand ourselves and mature toward managing our data as a product. We aim to give more ownership and visibility to every team that produces data to ensure we have people who know their data best.
  • Reduce administrative complexity: We can reduce the infrastructure that we manage and pay for, adjusting to meet our changing size and scale. Upgrades and patches take time and effort—our Operations and Architecture team need to investigate, pull systems down, find fixes and implement upgrades. With the stability of Google Cloud, our people—and our operational overheads—are freed up.
  • Improve cost efficiency: We now have a platform that is faster and more intuitive—and cost effective. It’s easy to upscale or downscale. A pay-as-you-go model gives our organization cost efficiency and elasticity—we only pay for the compute time used and we receive discounted prices for long-running workloads.
  • Enable insights at speed: We can take advantage of the ecosphere of other innovative solutions and plan our roadmap accordingly. We are moving our people to become skilled on an industry-relevant platform that can meet the evolving needs of our business.

Throughout the data transformation process, we have discovered that meaningful data matters more than data volume. And we have learned to be patient and consider the technologies we are already using rather than migrating to the next “shiny toy” technology.

Today, through due diligence and careful planning, the Global IT organization has completely transformed its analytics platform—reducing overheads, decreasing costs in server storage and providing our people with cutting-edge, advanced analytics.

Going forward, Accenture intends to continue to transform and strengthen the big data insight capabilities we offer, explore the full value of the cloud ecosystem and open the door to more innovative solutions.

of business data available to Accenture end users

faster in executing high-volume queries

data projects active on the Google Cloud platform

data science projects developed

predictive analytics models created

reduction in operational incidents in production environments

Meet the team

case study customer data platform

Karen Odegaard

case study customer data platform

Luis Polanco

Related capabilities, how accenture does it, accenture google business group, cloud services.

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Customer Stories / Advertising & Marketing Technology

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Salesforce Creates a Single Source of Data Truth for Its Customer Data Platform Using AWS

Salesforce  is a cloud-based software company that provides customer relationship management services and a complementary suite of enterprise applications focused on customer service, marketing automation, analytics, and application development.

In this video at AWS Summit in San Francisco, Muralidhar Krishnaprasad, executive vice president (EVP) of engineering for Salesforce, describes how the company creates a single source of truth for customer data in the company's Customer Data Platform (CDP), utilizing AWS services such as  Amazon Relational Database Service (Amazon RDS),  Amazon DynamoDB , and  Amazon EMR  to provide marketers with a detailed view of their consumers and improve business outcomes.

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Security is paramount and we do use AWS Security to do the defense in depth, but above and beyond al that is AWS has been a trusted partner for us helping us in need and working together as we launch these new services."

Muralidhar Krishnaprasad Executive Vice President Engineering, Salesforce

AWS Services Used

Amazon relational database service (amazon rds).

Amazon Relational Database Service (Amazon RDS) is a collection of managed services that makes it simple to set up, operate, and scale databases in the cloud.

Learn more »

Amazon DynamoDB

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale Learn more »

Amazon EMR is the industry-leading cloud big data solution for petabyte-scale data processing, interactive analytics, and machine learning using open-source frameworks such as Apache Spark, Apache Hive, and Presto. Learn more »

Explore Salesforce's journey of innovation using AWS

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Customer Analytics Through a Cloud Data Platform

We architected a cloud data platform to enable trusted, real-time advanced analytics, client’s challenge.

  • Legacy data environment lacked agility resulting in long time-to-market for new analytical solutions and higher operating costs
  • Gaps in customer data created a disjointed customer experience leading to missed cross selling and conversion opportunities
  • Data was poorly understood, scattered across a variety of repositories, and delivered in batches with limited access to real-time data
  • Legacy platforms in data center and private cloud could not scale and had increasing costs
  • Security and privacy risks for the data platforms were managed reactively

OUR APPROACH

  • Delivered multi-layered architecture for a Cloud Data Platform including a data lake, streaming hub, data refineries, data warehouse, user sandboxes, analytic workbenches, and data governance tools
  • Introduced best practices for team-based architecture work including decision management and architect core hours
  • Guided delivery teams using enterprise and data architecture as “North Star”
  • Enabled automated ingestion and lineage for data lake using a data registry
  • Architected solutions for security, access control, monitoring, data tokenization, and individual rights
  • Applied agile delivery principles and orchestrated a multi-team program; provided Scrum training and coaching
  • Established operational data governance framework

SKILLS AND TECHNOLOGIES LEVERAGED

The results.

  • Enabled agile analytical solutions: Every day, 1000+ datasets are automatically ingested from files and streams, 40 data scientists are developing models, hundreds of data pipelines populate data warehouse tables for user queries and dashboards
  • $7.5M – 30M projected revenue uplift expected as a result of optimized global marketing
  • The platform enabled improved propensity and acquisition models resulting in a +8.5-10% lift
  • Enabled retirement of legacy systems resulting in over $3M savings in operating costs and deferred investments

case study customer data platform

Embracing AI Transformation: How customers and partners are driving pragmatic innovation to achieve business outcomes with the Microsoft Cloud

Jan 29, 2024 | Judson Althoff - Executive Vice President and Chief Commercial Officer

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This past year was one of technology’s most exciting with the emergence of generative AI, as leaders everywhere considered the possibilities it represented for their organizations. Many recognized its value and are eager to continue innovating, while others are inspired by what it has unlocked and are seeking ways to adopt it. At Microsoft, we are focused on developing responsible AI strategies grounded in pragmatic innovation and enabling AI Transformation for our customers. As I talk to customers and partners about the outcomes they are seeing — and rationalize those against Microsoft’s generative AI capabilities — we have identified four areas of opportunity for organizations to empower their AI Transformation: enriching employee experiences, reinventing customer engagement, reshaping business processes and bending the curve on innovation . With these as a foundation, it becomes easier to see how to bring pragmatic AI innovation to life, and I am proud of the impact we have made with customers and partners around the world. From developing customer-focused AI and cloud services for millions across Europe and Africa with Vodafone , to empowering customers and employees with generative AI capabilities with Walmart , I look forward to what we will help you achieve in the year ahead.

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Enriching employee experiences and shaping the future of work with copilot technology

Bayer employees are collaborating better on worldwide research projects and saving time on daily tasks with Copilot for Microsoft 365, while Finnish company Elisa is helping knowledge workers across finance, sales and customer service streamline routine tasks. Banreservas is driving employee productivity and enhancing decision-making, and Hong Kong’s largest transportation companies — Cathay and MTR — are streamlining workflows, improving communications, and reducing time-consuming administrative tasks. Across professional services, KPMG has seen a 50% jump in employee productivity, Dentsu is saving hundreds of employees up to 30 minutes per day on creative visualization processes, and EY is making it easier to generate reports and access insights in near real-time with Copilot for Microsoft 365. In Malaysia, financial services organization PNB is saving employees time searching through documents and emails and AmBank employees are enhancing the quality and impact of their work. At Hargreaves Lansdown , financial advisers are using Copilot for Microsoft 365 and Teams to drive productivity and make meetings more inclusive. Avanade is helping sellers save time updating contact records and summarizing email threads with Copilot for Dynamics 365, while HSO Group, Vixxo, and 9altitudes are streamlining work for field and service teams.

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Reinventing customer engagement with generative AI to deliver greater value and increased satisfaction

MECOMS is making it possible for utility customers to ask questions and get suggestions about how to reduce power consumption using Microsoft Fabric and copilot on their Power Pages portal. Schneider Electric has built a Resource Advisor copilot to equip customers with enhanced data analysis, visualization, decision support and performance optimization. California State University San Marcos is finding ways to better understand and personalize the student journey while driving engagement with parents and alumni using Dynamics 365 Customer Insights and Copilot for Dynamics 365. With Azure OpenAI Service, Adecco Group is bolstering its services and solutions to enable worker preparedness as generative AI reshapes the workforce, UiPath has already helped one of its insurance customers save over 90,000 hours through more efficient operations, and Providence has developed a solution for clinicians to respond to patient messages up to 35% faster. Organizations are building generative AI assistants to help employees save time, improve customer service and focus on more complex work, including Domino’s , LAQO and OCBC . Within a few weeks of introducing its copilot to personalize customer service, Atento has increased customer satisfaction by 30% while reducing operational errors by nearly 20%, and Turkey-based Setur is personalizing travel planning with a chatbot to customize responses in multiple languages for its 60,000 daily users. In the fashion industry, Coats Digital launched an AI assistant in six weeks to make customer onboarding easier. Greece-based ERGO Insurance partnered with EBO to provide 24/7 personalized assistance with its virtual agent, and H&R Block introduced AI Tax Assist to help individuals and small business owners file and manage their taxes confidently while saving costs.

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Reshaping business processes to uncover efficiencies, improve developer creativity and spur AI innovation

Siemens built its own industrial copilot to simplify virtual collaboration of design engineers and front-line workers, accelerate simulation times and reduce tasks from weeks to minutes. With help from Neudesic , Hanover Research designed a custom AI-powered research tool to streamline workflows and identify insights up to 10 times faster. With Microsoft Fabric, organizations like the London Stock Exchange Group and Milliman are reshaping how teams create more value from data insights, while Zeiss is streamlining analytics workflows to help teams make more customer-centric decisions. Volvo Group has saved more than 10,000 manual hours by launching a custom solution built with Azure AI to simplify document processing. By integrating GitHub Copilot, Carlsber g has significantly enhanced productivity across its development team; and Hover , SPH Media , Doctolib and CloudZero have improved their workflows within an agile and secure environment. Mastery Logistics Systems and Novo Nordisk are using GitHub Copilot to automate repetitive coding tasks for developers, while Intertech is pairing it with Azure OpenAI Service to enhance coding accuracy and reduce daily emails by 50%. Swiss AI-driven company Unique AG is helping financial industry clients reduce administrative work, speed up existing processes and improve IT support; and PwC is simplifying its audit process and increasing transparency for clients with Azure OpenAI Service.  By leveraging Power Platform, including AI and Copilot features, Epiq has automated employee processes, saving over $500,000 in annual costs and 2,000 hours of work each month, PG&E is addressing up to 40% of help desk demands to save more than $1 million annually, and Nsure is building automations that reduce manual processing times by over 60% and costs by 50%. With security top of mind, WTW is using Microsoft Copilot for Security to accelerate its threat-hunting capabilities by making it possible for cyber teams to ask questions in natural language, while LTIMindtree is planning on using it to reduce training time and strengthen security analyst expertise.

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Bending the curve on innovation across industries with differentiated AI offerings

To make disaster response more efficient, nonprofit Team Rubicon is quickly identifying and engaging the right volunteers in the right locations with the help of Copilot for Dynamics 365. Netherlands-based TomTom is bringing the benefits of generative AI to the global automotive industry by developing an advanced AI-powered voice assistant to help drivers with tasks like navigation and temperature control. In Vietnam, VinBrain has developed one of the country’s first comprehensive AI-powered copilots to support medical professionals with enhanced screening and detection processes and encourage more meaningful doctor-patient interactions. Rockwell Automation is delivering industry-first capabilities with Azure OpenAI Service to accelerate time-to-market for customers building industrial automation systems. With a vision to democratize AI and reach millions of users, Perplexity.AI has brought its conversational answer engine to market in six months using Azure AI Studio. India’s biggest online fashion retailer, Myntra , is solving the open-ended search problem facing the industry by using generative AI to help shoppers figure out what they should wear based on occasion. In Japan, Aisin Corp has developed a generative AI app to empower people who are deaf or hard of hearing with tasks like navigation, communication and translation; and Canada-based startup Natural Reader is making education more accessible on-the-go for students with learning differences by improving AI voice quality with Azure AI. To solve one of the most complex engineering challenges — the design process for semiconductors — Synopsys is bringing in the power of generative AI to help engineering teams accelerate time-to-market.

As organizations continue to embrace AI Transformation, it is critical they develop clarity on how best to apply AI to meet their most pressing business needs. Microsoft is committed to helping our customers and partners accelerate pragmatic AI innovation and I am excited by the opportunities before us to enrich employee experiences, reinvent customer engagement, reshape business processes and bend the curve on innovation. As a technology partner of choice — from our differentiated copilot capabilities to our unparalleled partner ecosystem and unique co-innovation efforts with customers — we remain in service to your successful outcomes. We are also dedicated to preserving the trust we have built through our partnership approach, responsible AI solutions and commitments to protecting your data, privacy and IP. We believe this era of AI innovation allows us to live truer to our mission than ever before, and I look forward to continuing on this journey with you to help you achieve more.

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The ROI in a Customer Data Platform

Investing in customer data management is a sure path to success as proven by these customer data platform case studies.

Organizations in many different industries are finding big value by unifying and processing information through an enterprise customer data platform , or CDP. Here are just a few examples from some of the clients we have the pleasure of working with:

  • In a single campaign, Subaru used our enterprise CDP to generate a 15% conversion rate increase—and $26 million in sales.
  • By using our CDP to improve targeting and personalization, lifestyle retailer Muji increased in-store revenue by 46%.
  • Shiseido, the multinational cosmetics company, uses the Treasure Data enterprise CDP to increase customer retention and saw an overall increase in revenue of 11% after one year.

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Data Definitely Drives Revenue

Complex enterprises are at a disadvantage if they can’t get a handle on their data. According to a joint survey between Treasure Data and Forbes Insights , the challenges that prevent U.S. marketers from making better use of customer intelligence include the following:

  • Outdated technology
  • Siloed applications and data
  • Lack of quality data

Fortunately, these challenges can be overcome—and new opportunities exploited—with the adoption of an enterprise CDP. The natural evolution of CRM systems and data management platforms, CDPs unify data from disparate silos in a single, centralized repository, providing a 360-degree view of each customer, each lead—even each anonymous web visitor.

The customer data platform case studies at the top of this page show how just a few of our clients have used our enterprise CDP to gain market share and increase revenue. Download the paper now to get more details, and discover other examples you can use to generate enthusiasm for what’s possible in your own organization. Whether you are looking to grow by increasing your conversion rate, acquiring more customers, convincing your customers to buy more from you, or any combination of these, our enterprise CDP can improve the metrics that matter most to your business.

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How to write a case study — examples, templates, and tools

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It’s a marketer’s job to communicate the effectiveness of a product or service to potential and current customers to convince them to buy and keep business moving. One of the best methods for doing this is to share success stories that are relatable to prospects and customers based on their pain points, experiences, and overall needs.

That’s where case studies come in. Case studies are an essential part of a content marketing plan. These in-depth stories of customer experiences are some of the most effective at demonstrating the value of a product or service. Yet many marketers don’t use them, whether because of their regimented formats or the process of customer involvement and approval.

A case study is a powerful tool for showcasing your hard work and the success your customer achieved. But writing a great case study can be difficult if you’ve never done it before or if it’s been a while. This guide will show you how to write an effective case study and provide real-world examples and templates that will keep readers engaged and support your business.

In this article, you’ll learn:

What is a case study?

How to write a case study, case study templates, case study examples, case study tools.

A case study is the detailed story of a customer’s experience with a product or service that demonstrates their success and often includes measurable outcomes. Case studies are used in a range of fields and for various reasons, from business to academic research. They’re especially impactful in marketing as brands work to convince and convert consumers with relatable, real-world stories of actual customer experiences.

The best case studies tell the story of a customer’s success, including the steps they took, the results they achieved, and the support they received from a brand along the way. To write a great case study, you need to:

  • Celebrate the customer and make them — not a product or service — the star of the story.
  • Craft the story with specific audiences or target segments in mind so that the story of one customer will be viewed as relatable and actionable for another customer.
  • Write copy that is easy to read and engaging so that readers will gain the insights and messages intended.
  • Follow a standardized format that includes all of the essentials a potential customer would find interesting and useful.
  • Support all of the claims for success made in the story with data in the forms of hard numbers and customer statements.

Case studies are a type of review but more in depth, aiming to show — rather than just tell — the positive experiences that customers have with a brand. Notably, 89% of consumers read reviews before deciding to buy, and 79% view case study content as part of their purchasing process. When it comes to B2B sales, 52% of buyers rank case studies as an important part of their evaluation process.

Telling a brand story through the experience of a tried-and-true customer matters. The story is relatable to potential new customers as they imagine themselves in the shoes of the company or individual featured in the case study. Showcasing previous customers can help new ones see themselves engaging with your brand in the ways that are most meaningful to them.

Besides sharing the perspective of another customer, case studies stand out from other content marketing forms because they are based on evidence. Whether pulling from client testimonials or data-driven results, case studies tend to have more impact on new business because the story contains information that is both objective (data) and subjective (customer experience) — and the brand doesn’t sound too self-promotional.

89% of consumers read reviews before buying, 79% view case studies, and 52% of B2B buyers prioritize case studies in the evaluation process.

Case studies are unique in that there’s a fairly standardized format for telling a customer’s story. But that doesn’t mean there isn’t room for creativity. It’s all about making sure that teams are clear on the goals for the case study — along with strategies for supporting content and channels — and understanding how the story fits within the framework of the company’s overall marketing goals.

Here are the basic steps to writing a good case study.

1. Identify your goal

Start by defining exactly who your case study will be designed to help. Case studies are about specific instances where a company works with a customer to achieve a goal. Identify which customers are likely to have these goals, as well as other needs the story should cover to appeal to them.

The answer is often found in one of the buyer personas that have been constructed as part of your larger marketing strategy. This can include anything from new leads generated by the marketing team to long-term customers that are being pressed for cross-sell opportunities. In all of these cases, demonstrating value through a relatable customer success story can be part of the solution to conversion.

2. Choose your client or subject

Who you highlight matters. Case studies tie brands together that might otherwise not cross paths. A writer will want to ensure that the highlighted customer aligns with their own company’s brand identity and offerings. Look for a customer with positive name recognition who has had great success with a product or service and is willing to be an advocate.

The client should also match up with the identified target audience. Whichever company or individual is selected should be a reflection of other potential customers who can see themselves in similar circumstances, having the same problems and possible solutions.

Some of the most compelling case studies feature customers who:

  • Switch from one product or service to another while naming competitors that missed the mark.
  • Experience measurable results that are relatable to others in a specific industry.
  • Represent well-known brands and recognizable names that are likely to compel action.
  • Advocate for a product or service as a champion and are well-versed in its advantages.

Whoever or whatever customer is selected, marketers must ensure they have the permission of the company involved before getting started. Some brands have strict review and approval procedures for any official marketing or promotional materials that include their name. Acquiring those approvals in advance will prevent any miscommunication or wasted effort if there is an issue with their legal or compliance teams.

3. Conduct research and compile data

Substantiating the claims made in a case study — either by the marketing team or customers themselves — adds validity to the story. To do this, include data and feedback from the client that defines what success looks like. This can be anything from demonstrating return on investment (ROI) to a specific metric the customer was striving to improve. Case studies should prove how an outcome was achieved and show tangible results that indicate to the customer that your solution is the right one.

This step could also include customer interviews. Make sure that the people being interviewed are key stakeholders in the purchase decision or deployment and use of the product or service that is being highlighted. Content writers should work off a set list of questions prepared in advance. It can be helpful to share these with the interviewees beforehand so they have time to consider and craft their responses. One of the best interview tactics to keep in mind is to ask questions where yes and no are not natural answers. This way, your subject will provide more open-ended responses that produce more meaningful content.

4. Choose the right format

There are a number of different ways to format a case study. Depending on what you hope to achieve, one style will be better than another. However, there are some common elements to include, such as:

  • An engaging headline
  • A subject and customer introduction
  • The unique challenge or challenges the customer faced
  • The solution the customer used to solve the problem
  • The results achieved
  • Data and statistics to back up claims of success
  • A strong call to action (CTA) to engage with the vendor

It’s also important to note that while case studies are traditionally written as stories, they don’t have to be in a written format. Some companies choose to get more creative with their case studies and produce multimedia content, depending on their audience and objectives. Case study formats can include traditional print stories, interactive web or social content, data-heavy infographics, professionally shot videos, podcasts, and more.

5. Write your case study

We’ll go into more detail later about how exactly to write a case study, including templates and examples. Generally speaking, though, there are a few things to keep in mind when writing your case study.

  • Be clear and concise. Readers want to get to the point of the story quickly and easily, and they’ll be looking to see themselves reflected in the story right from the start.
  • Provide a big picture. Always make sure to explain who the client is, their goals, and how they achieved success in a short introduction to engage the reader.
  • Construct a clear narrative. Stick to the story from the perspective of the customer and what they needed to solve instead of just listing product features or benefits.
  • Leverage graphics. Incorporating infographics, charts, and sidebars can be a more engaging and eye-catching way to share key statistics and data in readable ways.
  • Offer the right amount of detail. Most case studies are one or two pages with clear sections that a reader can skim to find the information most important to them.
  • Include data to support claims. Show real results — both facts and figures and customer quotes — to demonstrate credibility and prove the solution works.

6. Promote your story

Marketers have a number of options for distribution of a freshly minted case study. Many brands choose to publish case studies on their website and post them on social media. This can help support SEO and organic content strategies while also boosting company credibility and trust as visitors see that other businesses have used the product or service.

Marketers are always looking for quality content they can use for lead generation. Consider offering a case study as gated content behind a form on a landing page or as an offer in an email message. One great way to do this is to summarize the content and tease the full story available for download after the user takes an action.

Sales teams can also leverage case studies, so be sure they are aware that the assets exist once they’re published. Especially when it comes to larger B2B sales, companies often ask for examples of similar customer challenges that have been solved.

Now that you’ve learned a bit about case studies and what they should include, you may be wondering how to start creating great customer story content. Here are a couple of templates you can use to structure your case study.

Template 1 — Challenge-solution-result format

  • Start with an engaging title. This should be fewer than 70 characters long for SEO best practices. One of the best ways to approach the title is to include the customer’s name and a hint at the challenge they overcame in the end.
  • Create an introduction. Lead with an explanation as to who the customer is, the need they had, and the opportunity they found with a specific product or solution. Writers can also suggest the success the customer experienced with the solution they chose.
  • Present the challenge. This should be several paragraphs long and explain the problem the customer faced and the issues they were trying to solve. Details should tie into the company’s products and services naturally. This section needs to be the most relatable to the reader so they can picture themselves in a similar situation.
  • Share the solution. Explain which product or service offered was the ideal fit for the customer and why. Feel free to delve into their experience setting up, purchasing, and onboarding the solution.
  • Explain the results. Demonstrate the impact of the solution they chose by backing up their positive experience with data. Fill in with customer quotes and tangible, measurable results that show the effect of their choice.
  • Ask for action. Include a CTA at the end of the case study that invites readers to reach out for more information, try a demo, or learn more — to nurture them further in the marketing pipeline. What you ask of the reader should tie directly into the goals that were established for the case study in the first place.

Template 2 — Data-driven format

  • Start with an engaging title. Be sure to include a statistic or data point in the first 70 characters. Again, it’s best to include the customer’s name as part of the title.
  • Create an overview. Share the customer’s background and a short version of the challenge they faced. Present the reason a particular product or service was chosen, and feel free to include quotes from the customer about their selection process.
  • Present data point 1. Isolate the first metric that the customer used to define success and explain how the product or solution helped to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
  • Present data point 2. Isolate the second metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
  • Present data point 3. Isolate the final metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
  • Summarize the results. Reiterate the fact that the customer was able to achieve success thanks to a specific product or service. Include quotes and statements that reflect customer satisfaction and suggest they plan to continue using the solution.
  • Ask for action. Include a CTA at the end of the case study that asks readers to reach out for more information, try a demo, or learn more — to further nurture them in the marketing pipeline. Again, remember that this is where marketers can look to convert their content into action with the customer.

While templates are helpful, seeing a case study in action can also be a great way to learn. Here are some examples of how Adobe customers have experienced success.

Juniper Networks

One example is the Adobe and Juniper Networks case study , which puts the reader in the customer’s shoes. The beginning of the story quickly orients the reader so that they know exactly who the article is about and what they were trying to achieve. Solutions are outlined in a way that shows Adobe Experience Manager is the best choice and a natural fit for the customer. Along the way, quotes from the client are incorporated to help add validity to the statements. The results in the case study are conveyed with clear evidence of scale and volume using tangible data.

A Lenovo case study showing statistics, a pull quote and featured headshot, the headline "The customer is king.," and Adobe product links.

The story of Lenovo’s journey with Adobe is one that spans years of planning, implementation, and rollout. The Lenovo case study does a great job of consolidating all of this into a relatable journey that other enterprise organizations can see themselves taking, despite the project size. This case study also features descriptive headers and compelling visual elements that engage the reader and strengthen the content.

Tata Consulting

When it comes to using data to show customer results, this case study does an excellent job of conveying details and numbers in an easy-to-digest manner. Bullet points at the start break up the content while also helping the reader understand exactly what the case study will be about. Tata Consulting used Adobe to deliver elevated, engaging content experiences for a large telecommunications client of its own — an objective that’s relatable for a lot of companies.

Case studies are a vital tool for any marketing team as they enable you to demonstrate the value of your company’s products and services to others. They help marketers do their job and add credibility to a brand trying to promote its solutions by using the experiences and stories of real customers.

When you’re ready to get started with a case study:

  • Think about a few goals you’d like to accomplish with your content.
  • Make a list of successful clients that would be strong candidates for a case study.
  • Reach out to the client to get their approval and conduct an interview.
  • Gather the data to present an engaging and effective customer story.

Adobe can help

There are several Adobe products that can help you craft compelling case studies. Adobe Experience Platform helps you collect data and deliver great customer experiences across every channel. Once you’ve created your case studies, Experience Platform will help you deliver the right information to the right customer at the right time for maximum impact.

To learn more, watch the Adobe Experience Platform story .

Keep in mind that the best case studies are backed by data. That’s where Adobe Real-Time Customer Data Platform and Adobe Analytics come into play. With Real-Time CDP, you can gather the data you need to build a great case study and target specific customers to deliver the content to the right audience at the perfect moment.

Watch the Real-Time CDP overview video to learn more.

Finally, Adobe Analytics turns real-time data into real-time insights. It helps your business collect and synthesize data from multiple platforms to make more informed decisions and create the best case study possible.

Request a demo to learn more about Adobe Analytics.

https://business.adobe.com/blog/perspectives/b2b-ecommerce-10-case-studies-inspire-you

https://business.adobe.com/blog/basics/business-case

https://business.adobe.com/blog/basics/what-is-real-time-analytics

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Some virtual care companies putting patient data at risk, new study finds

Canadian researchers have patient privacy concerns as industry grows post-covid.

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This story is part of CBC Health's Second Opinion, a weekly analysis of health and medical science news emailed to subscribers on Saturday mornings. If you haven't subscribed yet, you can do that by  clicking here .

If you visit a doctor virtually through a commercial app, the information you submit in the app could be used to promote a particular drug or service, says the leader of a new Canadian study involving industry insiders.

The industry insiders "were concerned that care might not be designed to be the best care for patients, but rather might be designed to increase uptake of the drug or vaccine to meet the pharmaceutical company objectives," said Dr. Sheryl Spithoff, a physician and scientist at Women's College Hospital in Toronto.

Virtual care took off as a convenient way to access health care during the COVID-19 pandemic, allowing patients to consult with a doctor by videoconference, phone call or text.

It's estimated that more than one in five adults in Canada —  or 6.5 million people — don't have a family physician or nurse practitioner they can see regularly, and virtual care is helping to fill the void.

But the study's researchers and others who work in the medical field have raised concerns that some virtual care companies aren't adequately protecting patients' private health information from being used by drug companies and shared with third parties that want to market products and services.

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Spithoff co-authored the study in this week's BMJ Open , based on interviews with 18 individuals employed or affiliated with the Canadian virtual care industry between October 2021 and January 2022. The researchers also analyzed 31 privacy documents from the websites of more than a dozen companies.

The for-profit virtual care industry valued patient data and "appears to view data as a revenue stream," the researchers found.

One employee with a virtual care platform told the researchers that the platform, "at the behest of the pharmaceutical company, would conduct 'A/B testing' by putting out a new version of software to a percentage of patients to see if the new version improved uptake of the drug."

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Many virtual care apps pushing products, selling personal data, research finds

Concerns about how data might be shared.

Matthew Herder, director of the Health Law Institute at Dalhousie University in Halifax, said he hopes the study draws the public's attention to what's behind some of these platforms.

"All of this is happening because of a business model that sees value in collecting that data and using it in a variety of ways that have little to do with patient care and more to do in building up the assets of that company," Herder said.

Bearded man standing in front of a chalkboard.

Other industry insiders were concerned about how data, such as browsing information, might be shared with third parties such as Google and Meta, the owner of Facebook, for marketing purposes, Spithoff said.

The study's authors said companies placed data in three categories:

  • Registration data, such as name, email address and date of birth.
  • User data, such as how, when and where you use the website, on what device and your internet protocol or IP address.
  • De-identified personal health information, such as removing the name and date of birth and modifying the postal code.

Some companies considered the first two categories as assets that could be monetized, employees told the researchers.

  • Many Canadians welcomed virtual health care. Where does it fit in the system now?
  • Virtual urgent care didn't divert Ontario patients from ER visits during pandemic, study suggests

Not all of the companies treated the third category the same way. Some used personal health information only for the primary purpose of a patient's virtual exchange with a physician, while others used it for commercial reasons, sharing analytics or de-identified information with third parties.

The study's authors said while each individual data point may not provide much information, advertisers and data analytic companies amalgamate data from browsing history and social media accounts to provide insights into an individual's mental health status, for example.

One study participant described how a partnership for targeted ads might work: "If an individual is coming through our service looking for mental health resources, how can we lean them into some of our partnerships with corporate counselling services?"

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Nurses’ union says virtual care is a move toward privatization of health care

Conflict-of-interest questions.

Lorian Hardcastle, an associate professor of law and medicine at the University of Calgary, studied  uptake of virtual care in 2020. She highlighted issues of continuity of care, privacy legislation and consent policies.

Since then, she said, uptake in virtual care accelerated during the COVID-19 pandemic.

"I think that the commercialization of the health-care system raises concerns around conflicts of interest between what is best for patients on the one hand and then on the other hand, what has the best return for shareholders," said Hardcastle, who was not involved in the BMJ Open study.

A woman with long brown hair wearing a blouse and jacket.

Hardcastle said it is helpful to have industry insiders acknowledge problems that health professionals and academics have expressed about commercialization.

The Office of the Privacy Commissioner of Canada, which funded the study, said in an email that privately funded health professionals are generally considered to be conducting commercial activities.

Hospitals, long-term care facilities and home care services that are publicly funded are not considered to be engaged in commercial activities and are covered by provincial privacy legislation, the office said. Health information falls into many categories and may be subject to different privacy laws across various jurisdictions.

Hardcastle also suggested that self-regulatory bodies, such as provincial colleges of physicians and surgeons, may need to revisit policies around relationships between health providers and industry.

Virtual care industry responds

CBC News heard from some Canadian virtual care companies that said they take the privacy of individuals seriously.

"Patient data is only used with patients' explicit consent and only when it's required for health-care interactions between a patient and a doctor," a spokesperson for virtual care platform Maple said. "We do not exploit patient data for marketing or commercial gain."

  • Is virtual care a cure for Canada's battered health-care system?

In a statement, Rocket Doctor said it is important to note that the company "does not do any of the things listed by the researchers as common in the telehealth industry."

Telus said that all of the data collected from its virtual care service is treated as personal health information.

"Telus Health doesn't receive any funds from pharmaceutical companies for our virtual care service and we do not sell any patient data collected," said Pamela Snively, the company's chief data and trust officer.

Source of information hard to pin down

Hardcastle said it may be difficult for some people to distinguish between receiving reliable and accurate information from a health-care provider on an app and getting services marketed to them that the health provider may or may not find useful.

"Your family doctor isn't trying to collect superfluous information in order to market services to you," she said.

Some provinces and territories pay for the virtual services. In other cases, patients pay themselves or are covered by employer or private insurance.

  • Patients tapping into alternative care options, but N.S. emergency departments still face challenges

Nova Scotia's government, for example, has a contract with Maple to provide residents without a primary care provider with unlimited virtual visits. Those who do have a regular provider can have two visits per year paid for by the province.

Tara Sampalli, senior scientific director at Nova Scotia Health Innovation Hub, said the province's contract with Maple means residents' data can't be used in other ways, such as by third-party providers.

The province doesn't have that level of control over other providers of virtual care, said Sampalli, who holds a PhD in health informatics.

Calls for an opt-out choice

Herder, of Dalhousie University, said users should be able to easily opt out of having their data used for commercial purposes. He also said that if the data doesn't represent the full diversity of Canada, algorithms shaping clinical decision-making could be racially biased.

Spithoff said while patient awareness is important, patients aren't in a position to fix this problem.

  • 140,000 Nova Scotians are waiting for a family doctor. Can virtual care help?

"We need better legislation, regulation, and we need better funding for primary care," she said. "Or people can get virtual care integrated into their offline care."

Spithoff and her co-authors said self-regulation by the industry is unlikely to lead to change. 

The researchers acknowledged they were limited to publicly available documents and that they did not interview those affiliated with the third-party advertisers.

case study customer data platform

Canadian Medical Association calls for health-care system overhaul

Corrections.

  • An earlier version of this story suggested that all health professionals conduct commercial activities under federal legislation. In fact, some publicly funded health services are not commercial and are covered by various other legislation. Feb 12, 2024 6:11 PM ET

ABOUT THE AUTHOR

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Amina Zafar covers medical sciences and health topics, including infectious diseases, for CBC News. She holds an undergraduate degree in environmental science and a master's in journalism.

With files from CBC's Christine Birak

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