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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

"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."

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

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."

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CDP vs DMP vs CRM: Which one is best for your business?

In this one‑page comparison guide, you'll get the pocket‑sized know-how to summarize, differentiate, help identify the data platform that's right for you.

What Exactly Is a Customer Data Platform?

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 a customer data platform different from dmp and crm, customer data platform types and usage: deep dive, standalone cdp, customer data & experience platform (cdxp), difference between enterprise-grade cdp and small business cdps, how to use a customer data platform (key 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, how to choose the right cdp for your company, why choose exponea as your new cdp.

What’s a customer data platform? The definitive guide to CDPs (2021)

Everything You Wanted to Know About Customer Data Platforms

You’ve heard the buzz. 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. We’re here to give you all the info you need.

Table of Contents

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A Customer Data Platform (CDP) is a type of software. Specifically, it’s a kind of database software: one that creates persistent, unified records of all your customers, their attributes, and their data. A good CDP should both 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 1st party customer data (transactional, behavioral, demographic) 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 3rd party tools or built-in marketing automation tools ( check Standalone CDP vs CDXP ) to execute marketing activities and analyze their performance .

CDP Characteristics

• 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

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 3rd Parties

Data contained within a CDP is ready for use in 3rd party systems focused on adtech and campaign delivery.

The most challenging barrier to Marketing Automation success is data integration between the various marketing systems of an organization.

CDP Skill Requirements

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, setting up emailing, helping with integrations. Knowledge of HTML, CSS, and Javascript is also helpful for building powerful weblayers.
• Analytical Person: a person that knows how to work with data, and knows what to track in custom dashboards, how to analyze A/B test, 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.

Customer Data Platform & Exponea (Video):

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 90’s, and allowed companies to manage their interactions with both current and potential customers. These platforms could also perform data analysis that could help drive retention and sales. While useful, these tools had some limitations: they only managed data for registered clients, and they only used predefined first-party data. 

Things changed in the 2000’s 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 omni-channel 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 the company 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.

Exponea: A CDP Since 2012

Recent announcements from major companies have pushed CDPs into the spotlight. But CDPs have already existed for a number of years. Exponea built its CDP from the ground up, starting in 2012. Years of experience have allowed Exponea to refine and improve its platform, and build powerful tools on top of it. Thanks to years of hard work and growth, Exponea has an industry-leading CDP, made even more powerful by user-centric analytics, predictions, recommendations and marketing automation layers. We call it a Customer Data & Experience Platform (CDXP).

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 it. A consistent customer experience across channels, appropriate recommendations, tailored communications: for today’s customers these are necessary. 

Not many companies can actually deliver these 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 CDPs 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: including 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, 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), customer data platforms (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.

CDP vs DMP vs CRM: Table Explained

• Holistic Customer Data: Does the platform combine customer data from all available sources (behavioral, demographic, personal, transactional, device, etc)?
• Lasting Customer Profiles: Does the platform retain customer 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: DMPs by design work with anonymized customer data. CRMs and CDPs work with identified customers, and allow for granularized views of individual customers.
• Identity Resolution: Does the platform allow you to connect the behavior of anonymous visitors with known customers after they have given their consent? Does the platform recognize customers across devices?
• Data priority – First Party: Does the platform primarily deal with data from 1st party sources?
• Data priority – Third Party: Does the platform primarily deal with data from 3rd party sources?
• Requires IT Support: Does day-to-day operation of the software require support from IT?

Author's note

Finding the right platform is no easy task, but we’ve got you covered.

In our One-Page Knowledge Card , you’ll get pocket-sized know-how on Customer Data Platforms (CDPs), Data Management Platforms (DMPs) and Customer Relationship Management Platforms (CRMs). Grab the Knowledge Card now to summarize, differentiate and help identify the data platform that’s right for you.

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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.

Standalone CDP vs Customer Data & Experience Platform (CDXP)

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 is exactly what it sounds like: a customer data platform without extra capabilities . It ingests all of a company’s first-party data and uses that to build complete pictures of all of your customers (also known as 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 the help of 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 might want to consider a CDXP.

Standalone CDP (Visualization):

A Customer Data and Experience Platform (CDXP) is the next generation of the CDP. It combines all the benefits of a Standalone CDP with an experience cloud , creating a single, powerful, customer-centric marketing platform.

A CDXP gives marketers the complete toolset they need for creating incredible customer experiences, by bringing together AI-driven marketing automation, real-time analytics and UX optimization with a best-in-class CDP.

A CDXP simplifies workflows and increases productivity by collecting frequently used tools into one integrated interface. But a CDXP is also flexible, and can fit into your existing tech stack. It molds around what you already have and fills gaps, creating the perfect solution for your company.

Key Benefits Of CDXP:

• Provides a foundation for a 360-degree customer view
• Makes customer-loyalty-driven decision making possible
• 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

Customer Data & Experience Platform (Visualization):

Exponea: The Most Versatile CDP on The Market

Exponea offers you the flexibility to pick and choose which features you want to use; it’s not an “all or nothing” solution. Although Exponea is Customer Data & Experience Platform (CDXP), it can act as a standalone CDP , providing a unified source of customer data to the clients existing technology stack (analytics, campaign execution), or it can be used to handle all marketing activities using the additional layers of campaign execution and analytics.

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 that question.

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 quickly and accurately. This means that a CDP needs to be built for scale from the very beginning – it needs a scalable architecture.

Flexibility. No two companies are the same. For enterprise-level companies, a plug-and-play type solution will almost never be suitable for the unique needs of a company – therefore flexibility in a CDP is a must-have. A CDP 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 of the company that uses it – 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.

Exponea: An Enterprise-Grade CDP

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

Scalability: Exponea’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: Exponea easily adapts to the needs of enterprise-class businesses. A quick onboarding process integrates Exponea with existing data. A rich API makes 3rd party integrations smooth and painless. And native integrations with best-in-class tools means Exponea works with the tools you already use.

Security: Privacy and security have been core values of Exponea from the very beginning. Exponea is the first GDPR-certified SaaS company in the world, and undergoes regular audits to maintain this status, as well as ISO 27017 and 27018 certifications.

The large number of CDP vendors on the market can be overwhelming. When choosing a vendor, it can be helpful to consider the list of 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), 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 below.

1. Online to Offline Connection

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

2. Customer Segmentation & Personalization

Segment customers according to their behavior (RFM, LTV prediction) and subsequently deliver a personalized, omni-channel experience throughout the entire customer lifecycle.

Further Reading: Customer Segmentation: Options Marketers Should Know

3. Predictive Customer Scoring

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

Further Reading: The Latest Predictive Marketing Techniques to Boost Your E-Commerce!

4. Smart Behavioral Retargeting & Lookalike Advertising

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

Further Reading: Advanced Remarketing Explained: Enriched Retargeting Strategy

5. Product Recommendations

Create and use 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.

Further Reading: The Leading Product Recommendation Methods For E-Commerce

6. Conversion Rate Optimization & 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.

Further Reading: 14 E-Commerce Personalization Tactics to Dominate Your Competition!

7. Omni-Channel Automation

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

Further Reading: How to Foster Customer Loyalty Through Omni-Channel Communication

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.

Further Reading: Improve Your Email Deliverability With These 10 Proven Tactics

9. Reviews Optimization

Get better and more online reviews from your customers through personalized omni-channel 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, siloed data. 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 omni-channel experience customers expect, with up-to-date interactions regardless of which channel the customer communicates through.

Further Reading: The Importance of Customer Lifetime Value (CLV) in Marketing

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

The long answer? Without knowing the details of your organization and business needs, there’s no one-size-fits-all answer to this question. 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
• 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, goals, and structure – so it’s 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.

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.a. Integration Phase (CDP Integration)

2.1. 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 Exponea, this is very simple: just paste a snippet of code into the header of your website. Other solutions might look quite different.

2.2. Customer IDs & 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.

2.3. 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.

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

   – Customer Feed and consents import from 3th party tools

   – Product Feed import

2.b. Integration Phase (3rd Party Tools  Integration)

Standalone 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 Customer Data & Experience Platform, since analytics and marketing automation abilities are part of CDXP.

No Integration Needed!

CDXPs don’t require any integration with analytics and execution tools, since those capabilities are part of a Customer Data & Experience Platform. As soon as the CDXP is integrated, you can begin analyzing data and executing automated marketing campaigns.

Note: If you want to keep some of your existing 3rd-party tools, you can integrate them with the CDXP, 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 CDP/CDXP to power insightful analytics and marketing automation.

Standalone CDP (integrated with 3rd-party analytics and marketing platforms)

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 Omni-Channel Orchestration
• Delays in Response

A CDXP offers some advantages here. Thanks to an all-in-one solution, marketers can expect:

• One User Interface
• Unified Technnology
• Bidirectional Data Flow
• Easy Omni-Channel 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 to 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.

Further Reading: Learn How to Choose & Implement a Customer Data Platform

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 personalization capabilities (CDXP)? 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.

G2 Grid® for Customer Data Platform

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.

Be wary of hype around customer data platforms. The power and capabilities of customer data platforms are enticing. Companies wanting to get in on the hype might disguise themselves as customer data platform without actually being one. If you decide to become customer-centric, be sure to do your research on available solutions.

While other companies have recently decided to jump on the CDP bandwagon, Exponea has offered an industry-leading CDP since 2012. Other CDPs are Frankenstein-like programs, built from a series of acquisitions and mergers, Exponea is entirely homegrown. All parts of the platform were built to work together, which means faster integrations, smooth operation, and better results.

Exponea is scalable, flexible, and secure . As the world’s first GDPR-certified SaaS company, you can be confident that your customer data will not just drive growth for your company, but that it will do so securely. That’s why companies like Missguided, Desigual, T-Mobile, and the Arcadia group have already chosen Exponea to make the most of their data and create win-win relationships with their customers.

Watch this 3‑minute video of Exponea’s main CDXP features and learn how it enables you to use in‑depth customer intelligence contained in a unified single customer view, delivering personalized experiences that are relevant and unified across all channels and devices.

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What Should You Read Next? Author's Hand-Picked Recommendation:

Meet the authors, f requently a sked q uestions, what is a customer data platform.

A Customer Data Platform is a system that ingests, consolidates and normalizes customer data from multiple online and offline sources, regardless of the data’s structure or identifier (email, cookie, etc). The data is centralized, wrangled and enriched so other systems (usually 3rd party tools) can understand and utilize them for custom analytics, marketing campaigns, and other data-related business needs.

What is a Customer Data & Experience Platform?

A Customer Data & Experience Platform (CDXP) is the evolution of a traditional CDP. A CDXP unifies customer data into a single customer view in real-time. Additionally, it has the ability to enrich this data through customer-centric analytics and AI, and instantly utilize that data for personalized communication via its own built‑in omni-channel marketing systems. These processes are all interconnected and managed from a single user-friendly interface.

CDXP = CDP + ESP + AI + UX

CDP vs CRM vs DMP: What's the Difference?

CDP:  Collects 1st party data from online and offline sources in real‑time to create a unified customer view, powering highly‑personalized marketing campaigns.

DMP: Segment anonymous 3rd‑party data to power retargeting campaigns.

CRM: Enable customer-facing teams (sales, customer support, etc.) to manage customer relationships.

Further Reading (Knowledge Card): Learn How to Choose & Implement a Customer Data Platform

How Are CDPs Used?

The most frequent business needs covered by CDPs are:

• Ingesting the right volume and speed of data for your business.
• Combining cross-channel data.
• Enabling omni-channel orchestration.
• Providing audience insights and discovery to non-technical/analytical users.
• Using insights to inform customer interactions in real-time.
• Providing data visibility, clarity, and compliance.
• Extending customer insights beyond the marketing department.

What Are Some of the Customer Data & Experience Platform Use Cases?

• Online to Offline Connection
• Customer Segmentation & Personalization
• Predictive Customer Scoring
• Smart Behavioral Retargeting & Lookalike Advertising
• Product Recommendations
• Conversion Rate Optimization & A/B Testing
• Omni-Channel Automation
• Email Deliverability Enhancement
• Reviews Optimization

How to Successfully Choose the Right CDP?

• Be clear about what you expect from a CDP (even before you look at vendors)
• Think beyond the short-term, and look for a future-proof solution
• Understand your options and look into vendor history (do they actually have CDP capabilities?)
• Success depends on the right mindset and attitude

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Learn how to choose & implement a customer data platform (cdp), how we used our competitive advantage to build the cdp of the future, the ultimate guide to mastering email deliverability (2021), email marketing analytics deep dive: metrics, goals, kpis & reports for 2021, email a/b testing – the quickest method to increasing your email performance and revenue, organizational customer-centric marketing: this time it’s personal, what is customer lifecycle marketing / management (clm), create your own fully automated omni-channel customer experience, conversion funnels: analysis and optimization for e-commerce in 2021, e-commerce conversion optimization in 2021 – a complete guide, the leading product recommendation methods for e-commerce, watch exponea demo video explore the customer data & experience platform b2c leaders love to use.

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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.

• 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.

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Global beverage giant AB InBev uses Treasure Data Customer Data Cloud to power global marketing and analytics, speed digital transformation, and securely handle customer data privacy compliance at scale. AB InBev’s Luiz Gama and Lucas Borges discuss better segmentation through Treasure Data’s “smart attributes” feature, and the benefits of real-time marketing.

Leading Adult Beverages Company

How a global CPG company used Treasure Data to overcome marketing inefficiency

Leading Online Game Developer

Discover how an online gaming leader boosted ROAS 65% with personalization.

Athletic Apparel Retailer

Increasing revenue per email by 760%, reducing churn, and growing engagement.

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Unifying customer data to fuel revenue growth & maximize marketing efficiency.

Global Gaming Company

Centralizing customer data & creating unified profiles creates $15M in savings.

Danone Indonesia

Connecting fragmented data sources to boost marketing and lower cost per lead.

Global Life Sciences Leader

Increasing re-engagement, maximizing LTV, and boosting ROI with a CDP.

Trifecta Nutrition

The DTC company uses its CDP to cut churn, feed growth, broadcast frequently…

Anheuser-Busch InBev

How the global beverage giant busts silos, speeds digital transformation, and…

Maruti Suzuki India Limited

Maruti Suzuki drives results, cuts ad spending, and creates profitable customer…

Stripe International Inc.

See how apparel retailer and lifestyle brand Stripe International Inc. sells…

Credit Saison

Treasure Data helps Credit Saison build accurate profiles from multiple large…

CPG giant Lion Corp. uses a CDP to detect shifting consumer behavior.

Omnichannel personalization fuels retail marketing.

Dentsu transformed how their Fortune 500 clients run their business with…

MUJI unifies millions of customer profiles across web, mobile and 400+ stores…

Shiseido unifies data on experience, demographics, and offline purchases with…

Subaru puts data in the driver’s seat with Treasure Data.

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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What is a Customer Data Platform and how does it elevate Customer Experience?

Customer Experience Analytics

Date : 08/26/2022

A CDP platform helps businesses aggregate customer data into a single location for all teams to view and act on it and deliver personalized customer experiences

AUTHOR - FOLLOW Abhishek Kumar Associate Manager, Marketing

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Table of contents, what is a customer data platform, how does a customer data platform work, benefits of a customer data platform for customer experience management.

Data is vital to scale enterprises’ daily operations. In order to take advantage of Data, it is necessary to break down data silos. Despite sitting on piles of data, large enterprises lack insights. Consequently, many retailers and CPG companies struggle to account for their information assets. Data siloing limits their ability to leverage and use data for analytics to drive competitive advantage.

To break data silos, enterprises need to consolidate data from their databases, platforms, and other sources into a central repository to get a 360-degree customer view. Later, they can embed it with AI-/ML-based behavior prediction models to democratize customer data & insights.

But, h ow to do it?

Organizations need a scalable and agile customer data platform. Before diving deeper, let’s explore what it means and why it is important for omnichannel visibility.

A customer data platform (CDP) is a software application that collects, manages, and unifies customer data from multiple touchpoints to present a coherent, 360-degree view of each customer profile, also known as a single customer view (SCV), to all teams in the organization. A CDP platform helps a business in more intelligent and effective decision-making.

CDP Institute defines a customer data platform as “a packaged software that creates a persistent, unified customer database accessible to other systems.”

Unifying customer data points and interactions such as user feedback, marketing clouds, service software, campaign metrics, POS, IoT data, etc., from disparate sources is incredibly cumbersome. Hence, Customer Data Platform Solutions are one of the fastest-growing categories in MarTech.

Where’s the challenge?

Let’s face it: Almost 60% of the global population is connected online, and the customer is in more control than ever. Customers want more and more personalized experiences and real-time solutions to their pain points. It’s now table stakes for organizations to deliver on these all-time high customer expectations

The challenge here is that the customers now interact with brands across multiple sources – website, in-store visits, mobile applications, social media, email campaigns and many more. Hence, customer data sets (transactional, behavioral, demographic) are now diverse and available in structured, unstructured, and semi-structured formats.

The truth is that many organizations are still grappling with a number of legacy systems and technologies that don’t just cut anymore. Hence, the result is a disconnected customer experience that significantly hurts business growth.

It’s, thus, increasingly becoming important for businesses to invest in a c ustomer data platform that can aggregate and structure critical, real-time data from first-party sources for all teams to access in one centralized location, and get a holistic view into your individual customer’s attributes, needs, and preferences .

A robust CDP platform easily integrates with your technology ecosystem and existing data sources via built-in connectors, webhooks, and APIs, and facilitates smooth retrieval of the data stored.

A customer data platform solution binds identifiers from varied systems, validates and cleans the disparate data sets collected from a multitude of offline and online sources to autonomously build single customer view (SCV) profiles. This unification process is known as identity resolution. The customer profiles are then supplemented with second- and third-party data sources to plug in the missing key attributes and the SCV profiles are updated with the most recent information.

Know how Tredence helped a major retailer serving +100M households by developing a Customer Data Platform .

A CDP platform, thus, demolishes data silos within an organization. Often data silos surface when the technology stack fails to match the pace at which the business scales up, thus creating a less collaborative work environment.

It’s a common myth that a customer data platform is a data management platform. It’s NOT. A CDP platform works with both:

• Personally identifiable users
• Anonymous users

Using the latest AI/ML , predictive analytics and audience segmentation capabilities, a customer data platform analyzes and segments SCVs throughout the customer life cycle to deliver the right message to the right customer on the right channel at the right time.

Before deep diving into the benefits of a customer data platform solution, let’s take a moment to understand what makes the customer experience great.

Imagine your customers are in the buying process, and you offer them contextual and consistent experience throughout by delivering them right messages on their preferred channels of content consumption at the right time of the day, based on their previous purchase history or behavioural patterns.

In today’s hyperconnected age, customer experience management is at the heart of every business strategy. In fact, customer experience management  is one of the most common business use cases of a customer data platform.

By unifying all forms of data (structured, unstructured, online, offline) and building a centralized view of the customer, a CDP platform helps different departments collaborate to achieve the common goal – delivering personalized customer experiences or integrated customer engagement.

Did you know? Businesses that manage to deliver personalization drive a 5-15% increase in revenue and a 10-30% increase in marketing spend efficiency.

A customer data platform can help your business:

• Deliver a consistent brand experience across different channels and devices.
• Effectively manage non-linear customer journeys that include multitudes of sources or interactions
• Boost personalization, segmentation and targeting for delivering relevant content to the customer at the right time on the channel of their choice.
• Leverage it as an engagement platform for optimizing customer interactions.
• Boost retention rates
• Improve revenue

Conclusion: Improve conversion, increase retention and maximize the efficiency with an AI-led CDP platform

A business can’t deliver a 5-star customer experience if its teams don’t have a uniform, consistent view of its customers’ profiles. But, that requires a business to overcome its data challenges as it can be immensely tough to locate, or it can exist in silos due to fractured processes or disparate systems.

A customer data platform rationalizes customer data records by associating different identifiers with each customer to build a holistic and persistent customer identity and reduce ad spend waste, while delivering personalized experiences across varied channels based on segmentation and activity.

Having a 360-degree view of the customer profile is no longer a nice-to-have but mission-critical for a business to deal with ever-increasing volumes of customers and multiple interactions during complex purchase journeys.

The moot question here is – would you be able to deliver superior customer experiences without a CDP platform today?

Talk to us and schedule a demo to reboot your data strategy with a customer data platform solution.?

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January 15, 2021

The Beginners Guide to Customer Data Platforms

Author: Operations NewDeep

Today’s marketer has access to a vast amount of information about their customers — including behavioural, transactional and demographic data. This data provides the fuel required to power uber-relevant marketing campaigns. But many companies store their data in a disjointed way, largely due to legacy software and antiquated IT systems. The inability to marry up different customer data sets presents a huge barrier to growth. Research by Gartner suggests that 52% of the marketing leaders surveyed said that data integration and formatting is one of their most time-consuming activities. So how can a customer data platform solve these problems to unlock new opportunities to increase revenue and lifetime value? Let’s dive in…

Table of contents:

What is a customer data platform, what types of data go into a cdp, what’s the difference between cdp and crm, what’s the difference between cdp and dmp.

• Benefits of a customer data platform
• Summing up customer data platforms

A customer data platform (CDP) is software that collates vast sources of data into a central warehouse that provides a unified, persistent view of the customer.

What makes a CDP different from other types of martech or analytics software is that a CDP aims to foster long-term loyalty by presenting a holistic view across every single customer touchpoint. Forrester’s research indicates 39% of marketers polled struggle with the integration of online and offline data. CDPs help to bridge the gap between online channels and the in-store experience. Assembling data within a CDP allows companies to build up a comprehensive profile of a single shopper, and better understand how an individual customer interacts with the business across multiple channels. The process of collecting different customer identifiers across devices and touchpoints is known as “identity resolution”. Building a consistent, omnichannel view allows brands to deliver a more relevant experience to their customers

Typically, a CDP can ingest data from many different sources. The types of data can include the following…

Behavioural data

Behavioural data encompasses the information that’s generated from the user’s actions across different touchpoints. This includes:

• Transactional data – for example, the number of products previously purchased, abandoned carts and purchase frequency.
• Campaign behaviour – e.g. number of clicks on email campaigns, open rates and optimal send times.
• Online activity – for example, user engagement on-site, site navigation, as well as receptiveness on social media or response to specific campaigns.
• Customer service data – e.g. customer service contact and past service history, leading through to issue resolution.

Identity and personal data

In the CDP, personal data acts as a marker for identifying individual customers. This data can include simple information such as name and address. It can also include professional data (such as place of work) and account information specific to the website or company involved. The CDP can incorporate descriptive data, such as career information, lifestyle data, information about hobbies and interests, or data from surveys. The software aggregates data streams to build up a complete picture of an individual customer — also known as a single customer view .

To better understand the function of a CDP, we need to define the key differences between a CDP and a CRM system. CDP and CRM technologies have different aims and objectives.  A traditional CRM system is a centralised data warehouse that’s used to store information about prospects or existing customers. Typically a CRM database will be used to power specific activities like email marketing or track a sales pipeline. A CDP, on the other hand, is designed to ingest data from a wide variety of sources (including CRM tools) to help deliver more engaging customer experiences across a variety of touch points. CDPs can integrate both online and offline data, but a CRM system can only incorporate offline data when an employee manually uploads the information to the database. In contrast, a CDP can collect data to build integrated customer profiles autonomously, whereas CRM systems track customer actions via manual entry. In many ways, CDPs represent the next stage in the evolution of marketing automation platforms. Many marketing automation systems can plug into CRM software and can simplify the work of marketers. While marketing automation tools can fuel data-driven campaigns, the software mostly works using predefined rules set by marketers. Automation platforms make links between some channels; in contrast, CDPs aggregate data from an extensive range of different sources. Marketing automation tools may store information in silos, rather than undertaking an integrated approach. CDPs go one step further than marketing automation software by fusing sophisticated, advanced AI algorithms with data from many different sources to deliver bespoke consumer experiences — often in real-time.

A DMP (data management platform) collects first, second, and third-party audience data. The data from DMPs is made available to ad exchanges and demand-side platform, to be used for targeted advertising and tailored content. A CDP aims to provide data for all types of cross-functional marketing, whereas a DMP is much more focused on audience insights for ad targeting.  CDPs use personal and specific customer identifiers, whereas DMPs use anonymous data. CDPs also empower marketers to make the most of their data. They give organisations a holistic view of how the customer interacts with their brand throughout the buying cycle. Essentially, CDPs have a long-term focus. DMPs focus on short-term goals like building targeted ads for a specific marketing campaign.

Five key benefits of a CDP

• Gives a cohesive, omnichannel view of the customer, saving time and increasing operational efficiency.
• Breaks down organisational silos between different teams and departments.
• Improves marketing by providing a highly targeted and personalised customer experience.
• Boosts customer lifetime value by creating engaging customer relationships.
• Allows marketers to work with big data sets without the need of a dedicated data analysts.

Summing up CDPs

Customer data platforms are fast-becoming an essential part of the marketing toolkit. They help CRM, data, and marketing teams to store their data in an easily digestible format.  The technology also allows leaders to have a coherent data governance strategy. This makes is much simpler to share insights across different business functions. Incorporating CDPs into the mar-tech stack is critical for powering a data-driven approach. It puts the customer at the heart of marketing.

Alex Quaye is a digital marketing expert with 10 years experience in data analytics, tag management, and growth marketing. He’s helped companies like Gousto, John Lewis, and Hotel Chocolat to acquire more customers with digital marketing. Follow Alex on LinkedIn .

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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.

How to know what you don’t know, now

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.

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What is a Customer Data Platform (CDP)?

This blog was co-written by Alex Roed, Luke Kline, Sam Hall, Alec Haase, and Christian Franklin.

Modern marketing is changing. Consumers are expecting more personalized experiences, and marketers are managing more channels than ever. The depreciation of third-party cookies has only compounded this problem, leaving companies scrambling to figure out how to implement the systems needed to power growth with their first-party customer data .

For years, marketing teams across industries have turned to implementing traditional Customer Data Platforms (CDPs) as separate systems purpose-built to unlock growth with first-party data.

However, thanks to the recent rise of modern cloud data warehouses like the  Snowflake Data Cloud  and powerful tools like  Hightouch , Fivetran, and dbt, many organizations are now realizing they can simply implement CDP features on top of their existing data infrastructure, thus giving birth to a new solution that marries the best of both data and marketing worlds: the  Composable CDP

In this guide, we’ll break down everything you need to know about CDPs and discuss why companies everywhere are racing to adopt this new architecture.

What is a Customer Data Platform?

Before covering the broader CDP landscape, it’s important to first provide some context on what a CDP is.

A CDP has historically been an all-in-one platform designed to help companies collect, store, and unify customer data within a hosted database so that marketing and business teams can easily build audiences and activate data to downstream operational tools.

The market is full of different CDP vendors, each specializing in slightly different verticals or use cases. However, almost all CDPs aim to perform the same four functions:

1. Event Tracking : Capturing behavioral events such as page views, add-to-cart, signup, purchase, subscription, etc.

2. Identity Resolution : Merging behavioral events and customer identifiers in an identity graph to create a single comprehensive customer profile.

3. Audience Management: Building and segmenting cohorts based on events, attributes, and user traits (e.g., an audience of high LTV users in the United States who abandoned their shopping cart in the last seven days.)

4. Activation: Automating data syncs (events and audiences) to operational and marketing tools so marketing teams can drive business value and personalization.

These functions work together with a promised mission of enabling businesses to leverage their customer data to drive more effective marketing and deliver personalized experiences.

What’s Driving CDP Adoption?

The push towards adopting CDPs stems from a universal realization among marketing and data professionals: the necessity for a unified system that seamlessly collects and integrates customer data throughout the business. 

This need has positioned CDPs as the preferred tool for crafting personalized marketing strategies–becoming the defacto answer when CMOs face personalization challenges. The driving forces behind this adoption can be distilled into several key areas:

Data Fragmentation: Companies no longer want to hop back and forth between tools to try and gain the full context. They want one platform that houses all of their customer data across all of their sources.

Customer 360 : Every company is constantly trying to merge and link the different actions of their customers into a single unified profile that can be leveraged across the business.

Business Alignment: Data and marketing teams have traditionally worked in silos, but companies are realizing that marketing teams need access to data to run campaigns.

Personalization: In order to deliver personalized experiences, marketing teams need and want a central platform where they can build audiences, manage campaigns, and orchestrate customer journeys.

Data Governance: With the phase-out of third-party cookies and new privacy laws arising, companies are coming under increased pressure to ensure compliance with regulations like GDPR, HIPAA, and CCPA.

Lifecycle Marketing: Marketing doesn’t just take place on one single channel any more. Campaigns are becoming more and more sophisticated as marketers are increasingly asked to build and deliver consistent experiences across ads, email, SMS, push, etc.

ROI: Data is no longer just an analytics asset for strategic decision-making. Companies want to leverage insights to drive action that translates into business value and, ultimately, revenue.

Understanding the CDP Market

If you’re evaluating CDPs today, there are two main options: Traditional CDPs vs. Composable CDPs .

Traditional CDPs: These platforms are out-of-the-box solutions designed to gather and house their own data store – separate from your core data infrastructure. Characterized by their plug-and-play nature, traditional CDPs often come with lengthy and costly setup processes predicated on rigid data model prerequisites.

Engineered primarily for the accumulation and preservation of behavioral events, their rigid architecture and out-of-the-box models may not accommodate the nuanced demands of modern businesses beyond standard customer and account information. 

Composable CDPs: In contrast, Composable CDPs present a more flexible and integrated approach, seamlessly integrating with your existing data ecosystem. These platforms excel in ingesting, organizing, and deploying data directly from and to your cloud data warehouse, thereby preserving the integrity and accessibility of your customer data within your own cloud infrastructure.

The Composable CDP empowers organizations to utilize their pre-existing data investments and analytical frameworks, offering a tailored and scalable solution that evolves with changing business needs and demands.

Components of a Composable CDP

A Composable CDP has the same goal as a traditional CDP: activating unified customer data to downstream tools. But rather than operating as a separate entity and storing data outside of your current data infrastructure like a traditional CDP, a Composable CDP lets you create audiences, personalize journeys, and send your existing customer data directly from your data warehouse to your many marketing tools.

The components of a Composable CDP can be broken down as follows:

Data Collection: For batch data sources like SaaS applications and on-prem systems, Fivetran is the standard. The ELT platform offers 200+ pre-built connections to centralize data to any data platform. For behavioral data , Hightouch offers an event tracking SDK to deploy an SDK across your web, server, and mobile apps.

Data Storage: The Composable CDP can work with any cloud data platform, but many companies tend to use Snowflake due to its ease of use, scalability, and flexibility.

Data Modeling: For data modeling, there are two core use cases: (1) transforming your data into structured tables and models to understand your business and (2) performing identity resolution to merge and deduplicate known and unknown user profiles to create a unified customer profile. dbt has become the standard for modeling. Hightouch additionally offers an identity resolution feature that lets you build and maintain an identity graph directly within your existing data platform.

Activation: Activation is the final and most important aspect of a Composable CDP because it’s the actual interface that allows your marketers to self-serve off of the warehouse. Most companies rely on Hightouch because the platform offers no-code audience and journey builders for non-technical users to deploy audiences and data to over 200 destinations.

Choosing your CDP

Ultimately, the decision between a Composable and a traditional CDP should be based on a thorough assessment of your organization’s current capabilities, future growth plans, and the specific goals you aim to achieve through the implementation of a CDP. While every CDP is different, this framework should help you evaluate vendors more efficiently.

Security: Does the platform ensure high standards of data protection and compliance with privacy regulations? Consider if owning data storage within your own infrastructure is important to meet your organization’s security requirements.

Flexibility: Evaluate the CDP’s adaptability in meeting your marketing needs and if it integrates with your current and future technologies (ad platforms, CRMs etc). Additionally, consider if the CDP can accommodate your organizations data models without significant workarounds and engineering effort.

Time-to-Value: How quickly can the CDP be implemented, and how soon can you start extracting value from it? Assess if the solution lets you immediately power use cases with the data already residing within your warehouse.

Scalability: Consider the platform’s capacity to handle larger volumes of data and complexity as your business grows. Determine whether you prefer a solution that allows for easy modification and expansion–avoiding the risk of investing in all-in-one technology that may become obsolete or inadequate as your needs evolve.

For organizations that prioritize data ownership, rapid time to value, and prefer to integrate closely with their data warehouse, Composable CDPs offer a more suitable solution. These platforms are designed to quickly and easily integrate with an organization’s existing data infrastructure, facilitating immediate use and flexibility.

Conversely, traditional CDPs may be more appropriate for smaller organizations at an earlier stage of data maturity or those with no desire for data ownership. They provide a structured, out-of-the-box solution that can simplify the early process of centralizing customer data, making them a practical entry point for early-stage businesses just beginning to explore first-party data strategies.

What Factors Impact Cost?

Pricing can vary substantially across CDP vendors; unfortunately, it’s not an “apples-to-apples” comparison. Based on our experience working with many different vendors, two main factors impact the cost:

The number of features/capabilities you need (e.g., event collection, audience management, identity resolution, activation, etc.)

The amount of data you collect and store.

Note: With a Composable CDP, every feature is decoupled, which means you can purchase components individually rather than being forced to pay for shelfware. Additionally, because Composable CDPs simply connect to your data infrastructure, you don’t have to pay for storage, like you would with a traditional CDP.

The most basic version of a traditional CDP usually starts at around $50,000 to $150,000 annually. However, depending on your data volume, this number can quickly skyrocket into millions, which is another reason why companies are switching to Composable CDPs that read directly from their existing store of data. 

How Do You Get Started with the Composable CDP?

One of the biggest advantages of the Composable CDP is that it works on any infrastructure at any data maturity level. At phData, we can help you begin by thoroughly understanding your requirements, assessing current data capabilities, defining business objectives, and prioritizing use cases.

We’ve worked with companies across all industries and verticals to help them activate the data in the warehouse across their operational tools, and as such, we’ve developed a structured approach to help you go from zero to 100 in a matter of weeks to ensure the highest probability of success for your business.

We’ll help you prioritize CDP capabilities based on your business goals and construct a compelling business case by performing ROI and cost-benefit analyses to align internal stakeholders. We’ll also walk you through a thorough proof-of-concept (POC) so you can choose the right Composable CDP–all with hands-on training so your team can start driving value immediately.

First-party data matters more than ever before. Thanks to the rise of the Composable CDP, organizations now have the choice to bring their marketing and data investments together with a Composable CDP. One of the biggest advantages of the Composable CDP is that it works on any infrastructure at any maturity level.

If you want to learn more about the Composable CDP, you can schedule an introductory conversation or book a demo with a solution engineer to see how phData and Hightouch can help. 

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Key findings

• Understanding methane emissions
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Methane emissions from the energy sector remained near a record high in 2023

We estimate that the production and use of fossil fuels resulted in close to 120 million tonnes (Mt) of methane emissions in 2023, while a further 10 Mt came from bioenergy – largely stemming from the traditional use of biomass. Emissions have remained around this level since 2019, when they reached a record high. Since fossil fuel supply has continued to expand since then, this indicates that the average methane intensity of production globally has declined marginally during this period.

The latest IEA Global Methane Tracker is based on the most recently available data on methane emissions from the energy sector and incorporates new scientific studies, measurement campaigns, and information collected from satellites.

Analysis of this data reveals both signs of progress and some worrying trends. On one hand, more governments and fossil fuel companies have committed to take action on methane. Global efforts to report emissions estimates consistently and transparently are strengthening, and studies suggest emissions are falling in some regions. However, overall emissions remain far too high to meet the world’s climate goals. Large methane emissions events detected by satellites also rose by more than 50% in 2023 compared with 2022, with more than 5 Mt of methane emissions detected from major fossil fuel leaks around the world – including a major well blowout in Kazakhstan that went on for more than 200 days. 

Methane emissions from energy, 2000-2023

Close to 70% of methane emissions from fossil fuels come from the top 10 emitting countries.

Of the nearly 120 Mt of emissions we estimate were tied to fossil fuels in 2023, around 80 Mt came from countries that are among the top 10 emitters of methane globally. The United States is the largest emitter of methane from oil and gas operations, closely followed by the Russian Federation (hereafter “Russia”). The People’s Republic of China (hereafter “China”) is by far the highest emitter in the coal sector. The amount of methane lost in fossil fuel operations globally in 2023 was 170 billion cubic metres, more than Qatar’s natural gas production.

The methane emissions intensity of oil and gas production varies widely. The best-performing countries score more than 100 times better than the worst. Norway and the Netherlands have the lowest emissions intensities. Countries in the Middle East, such as Saudi Arabia and the United Arab Emirates, also have relatively low emissions intensities. Turkmenistan and Venezuela have the highest. High emissions intensities are not inevitable; they can be addressed cost-effectively through a combination of high operational standards, policy action and technology deployment. On all these fronts, best practices are well established.

Methane emissions from oil and gas production and methane intensity for selected producers, 2023

Cutting methane emissions from fossil fuels by 75% by 2030 is vital to limit warming to 1.5 °c.

The energy sector accounts for more than one third of total methane emissions attributable to human activity, and cutting emissions from fossil fuel operations has the most potential for major reductions in the near term. We estimate that around 80 Mt of annual methane emissions from fossil fuels can be avoided through the deployment of known and existing technologies, often at low – or even negative – cost.

In our Net Zero Emissions by 2050 (NZE) Scenario – which sees the global energy sector achieving net zero emissions by mid-century, limiting the temperature rise to 1.5 °C – methane emissions from fossil fuel operations fall by around 75% by 2030. By that year, all fossil fuel producers have an emissions intensity similar to the world’s best operators today. Targeted measures to reduce methane emissions are necessary even as fossil fuel use begins to decline; cutting fossil fuel demand alone is not enough to achieve the deep and sustained reductions needed.

Methane abatement potential to 2030

Main sources of methane emissions, full implementation of cop28 and other pledges would cut fossil fuel methane emissions by 50%.

The COP28 climate summit in Dubai produced a host of new pledges to accelerate action on methane. Importantly, the outcome of the first Global Stocktake called for countries to substantially reduce methane emissions by 2030. Additionally, more than 50 oil and gas companies launched the Oil and Gas Decarbonization Charter (OGDC) to speed up emissions reductions within the industry, new countries joined the Global Methane Pledge, and new finance was mobilised to support the reduction of methane and greenhouse gases (GHGs) other than carbon dioxide (CO 2 ).

Substantial new policies and regulations on methane were also established or announced in 2023, including by the United States , Canada , and the European Union and China published an action plan dedicated to methane emission control. A series of supportive initiatives have been launched to accompany these efforts, such as the Methane Alert and Response System and the Oil and Gas Climate Initiative’s Satellite Monitoring Campaign .

Taken together, we estimate that if all methane policies and pledges made by countries and companies to date are implemented and achieved in full and on time, methane emissions from fossil fuels would decline by around 50% by 2030. However, in most cases, these pledges are not yet backed up by detailed plans, policies and regulations. The detailed methane policies and regulations that currently exist would cut emissions from fossil fuel operations by around 20% from 2023 levels by 2030. The upcoming round of updated Nationally Determined Contributions (NDCs) under the Paris Agreement, which will see countries set climate goals through 2035, presents a major opportunity for governments to set bolder targets on energy-related methane and lay out plans to achieve them.

Reductions in methane emissions from fossil fuel operations from existing policies and pledges, 2020-2030

Around 40% of today’s methane emissions from fossil fuels could be avoided at no net cost.

Methane abatement in the fossil fuel industry is one of the most pragmatic and lowest cost options to reduce greenhouse gas emissions. The technologies and measures to prevent emissions are well known and have already been deployed successfully around the world. Around 40% of the 120 Mt of methane emissions from fossil fuels could be avoided at no net cost, based on average energy prices in 2023. This is because the required outlays for abatement measures are less than the market value of the additional methane gas captured and sold or used. The share is higher for oil and natural gas (50%) than for coal (15%).

There are many possible reasons why companies are not deploying these measures even though they pay for themselves. For example, the return on investment for methane abatement projects may be longer than for other investment opportunities. There may also be a lack of awareness regarding the scale of methane emissions and the cost-effectiveness of abatement. Sometimes infrastructure or institutional arrangements are inadequate, making it difficult for companies to receive the income from avoided emissions.

Regardless of the value of captured gas, we estimate that it would be cost-effective to deploy nearly all fossil fuel methane abatement measures if emissions are priced at about USD 20/tonne CO 2 ‑equivalent. Tapping into this potential will require new regulatory frameworks, financing mechanisms and improved emissions tracking.

Marginal abatement cost curve for methane from coal, 2023

Marginal abatement cost curve for methane from oil and natural gas operations, 2023, delivering the 75% cut in methane emissions requires usd 170 billion in spending to 2030.

We estimate that around USD 170 billion in spending is needed to deliver the methane abatement measures deployed by the fossil fuel industry in the NZE Scenario. This includes around USD 100 billion of spending in the oil and gas sector and USD 70 billion in the coal industry. Through 2030, roughly USD 135 billion goes towards capital expenditures, while USD 35 billion is for operational expenditures.

Fossil fuel companies should carry the primary responsibility for financing these abatement measures, given that the amount of spending needed represents less than 5% of the income the industry generated in 2023. Nonetheless, we estimate that about USD 45 billion of spending in low- and middle-income countries requires particular attention, as sources of finance are likely to be more limited. To date, we estimate that external sources of finance targeted at reducing methane in the fossil fuel industry total less than USD 1 billion, although this should catalyse a far greater level of spending.

Spending for methane abatement in coal operations in the Net Zero Scenario, 2024-2030

Spending for methane abatement in oil and gas operations in the net zero scenario, 2024-2030, new tools to track emissions will bring a step change in transparency.

Better and more transparent data based on measurements of methane emissions is becoming increasingly accessible and will support more effective mitigation. In 2023, Kayrros , an analytics firm, released a tool based on satellite imagery that quantifies large methane emissions on a daily basis and provides country-level oil and gas methane intensities. GHGSat , another technology company, increased its constellation of satellites in orbit to 12 and started to offer targeted monitoring of offshore methane emissions, while the United Nations Environment Programme (UNEP) Methane Alert and Response System (MARS) ramped up usage of satellites to detect major methane emission events and alert government authorities and involved operators.

Despite this progress, little or no measurement-based data is used to report emissions in most parts of the world – which is an issue since measured emissions tend to be higher than reported emissions. For example, if companies that report emissions to UNEP’s Oil & Gas Methane Partnership 2.0 were to be fully representative of the industry globally, this would imply that global oil and gas methane emissions in 2023 were around 5 Mt, 95% lower than our estimate. Total oil and gas emissions levels reported by countries to the UN Framework Convention on Climate Change are close to 40 Mt, about 50% lower than our 2023 estimate. There are many possible reasons for these major discrepancies, but they will only be resolved through more systematic and transparent use of measured data.

Regardless, all assessments make clear that methane emissions from fossil fuels operations are a major issue and that renewed action – by governments, companies, and financial actors – is essential.

Methane emissions from global oil and gas supply

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• Archive a study version and decommission a study

Recommission a study

Scenarios may arise that require your organization to review or action study data in the Oracle Clinical One Platform after study decommissioning. For information about how to recommission a study, reach out to your Sales Representative, Customer Success Manager (CSM) or Services Project Manager or send an email to, [email protected].

• A study, decommissioned in an earlier version, can still function when recommissioned in a newer version. However, the user interface and underlying tech stack may have evolved, so it is not guaranteed the data will maintain the same layout once recommissioned. For more information on study decommission, see Decommission a production study
• Once the study has been recommissioned, follow the standard process to add users. For more information, see Create user accounts in Oracle Clinical One Platform .
• Oracle Clinical One Digital Gateway integrations and the Oracle Central Coding integration will not be reactivated for a recommissioned study, however, Oracle CRF Submit and Oracle Clinical One Analytics will be.

Parent topic: Archive a study version and decommission a study