Everything You Need to Know About CDPs

What Is a CDP? The Complete Guide to Customer Data Platforms

A CDP is an application that collects and stores customer data from across the organization and multiple channels into a single database for data unification and identity resolution, analyzation, and activation.

Essentially, a Customer Data Platform (CDP) is a database often used by marketers and customer experience teams to ingest customer data from relevant platforms, channels, and devices, including marketing, product, sales, and support systems to provide a single, unified view of your customers—a “golden record” or “unified customer profile.” Based on segmentation within the CDP, companies are able to activate hyper-personalized and data-driven consumer engagement across various marketing channels.

A visual representation of how a CDP is used to collect, unify, analyze and activate customer data.

A visual representation of how a CDP is used to collect, unify, analyze and activate customer data.

What is a CDP’s Function?

CDPs manage first-party data, second-party data (from partners), as well as third-party data (e.g. demographic or location data that enriches first-party data). The CDP unifies customer profile data to create a single version of truth—the golden record—on any particular customer or account. It then makes this data available to other systems to create personalized, relevant customer experiences.

CDP functionality typically includes:

  • Data Ingestion: Ingests customer data from marketing, sales, and product systems, including CRM, web and mobile app logs, email marketing, ecommerce, IoT, and more
  • ID Unification: Unifies customer data under one unique identifier, including products purchased, web pages viewed, ads clicked, and resolves duplicate profiles by combining them into a single profile
  • Segmentation: Analyzes customer data using a rule-based model, or leverages artificial intelligence (AI) and machine learning (ML) to find key segments based on common attributes
  • Customer Data Analytics: Uses machine learning recommendations, affinity, and predictive scoring to analyze customer data and provide a better view of the customer journey across channels, uncovering trends and correlations to help improve the experience
  • Reporting: Enables customized dashboards that provide key insights on customer profiles, targets and segments, journey maps, and more
  • Activation: Provides real-time profile data to marketing systems to deliver personalized, targeted experiences across all channels and devices

“54% of companies say their biggest barrier to leveraging data is fragmented or siloed data, which makes it difficult to get an accurate, integrated view of the customer journey.” —Survey Report: The State of the Customer Journey in 2019

What is a CDP’s Data Collection Capability?

A CDP connects to a wide range of systems and data sources across an organization using built-in connectors, SDKs, webhooks, and APIs. It collects all types of data, including profile data and real-time interaction data (behavioral, demographics, transactional), campaign data, product data, customer support data, mobile and device data, IoT data, and more.

A CDP collects data from a wide range of data sources.

A CDP collects data from a wide range of data sources.

This customer data comes in many formats—structured, unstructured, semi-structured—and a CDP must integrate these sources to build a single customer profile. By using schemaless ingestion, the CDP can collect raw, event-level data without needing to create predefined tables. This speeds up the collection process as well as conforms to changes made at the data source.

Customer data is collected in several ways. It is collected in batches for a period of time and then loaded into the system in a single batch. Batch processing is automated through workflows as a part of a data pipeline. You can also set up incremental batch processing to only bring in the last set of data since the previous load.

Data can also be streamed into the CDP as it’s recorded in web logs and mobile applications, giving marketers real-time access to changes in customer profiles.

“IDC predicts that the Global Datasphere will grow from 33 Zettabytes (ZB) in 2018 to 175 ZB by 2025.” —The Digitization of the World From Edge to Core

What Is a CDP’s Data Unification Methodology?

How does a CDP unify data? Once in a CDP, customer data must be unified into a single customer profile using a process known as customer identity resolution or data unification. Customer identity resolution includes sophisticated algorithms to stitch identifiers from multiple systems. Identity stitching automates identity graph creation and continuously unifies data into profiles as your customers continue to engage.

A CDP unifies customer identifiers and data sources to create a single customer profile.

A CDP unifies customer identifiers and data sources to create a single customer profile.

During the unification process, customer data is validated, cleaned, and deduped to create a single customer profile. The identity resolution process is done in two ways:

  • Deterministically: Unique IDs for customer records in each system are matched using common information, such as an email address or name. This high confidence approach works best when first-party data is readily available.
  • Probabilistically: This approach analyzes a variety of customer data points to estimate the statistical likelihood that two identities are the same customer. While statistical connections aren’t as definitive as authenticated IDs, they can be extremely helpful when first-party data is limited.

Profiles are then enriched with second- and third-party data sources that fill in missing attributes and update other attributes with more recent information.

Treasure Talks: Identity Resolution with Arm Treasure Data Customer Data Platform (CDP)

How Do CDPs Analyze Data? And How Do Predictive Analytics Work?

A CDP is more than a database to store customer information; it can analyze and segment customer profiles using rules or machine learning, perform predictive scoring, as well as provide journey orchestration. Some customer data platforms enable machine learning (ML) and artificial intelligence (AI) for advanced predictive analytics. Plus CDPs make it possible to visualize data through other BI tools with seamless integration.

Marketers have access to rich data sets enabling them to create segments based on attributes and behaviors. They can manually define segments using a rule-based approach or leverage predictive analytics.

Journey orchestration enables marketers to analyze customer interactions throughout the entire customer journey and deliver the right messages at the right time on the right channels.

“Forty-four percent report that a customer data platform is helping drive loyalty and ROI in their organization.” —Forbes Insights: Data versus Goliath

What Is a CDP’s Data Activation Capability?

Finally, a CDP makes customer data available to other systems for activation, the execution of campaigns, and communications that improve customer experiences. Marketers can use the data to personalize website experiences, send targeted emails, provide relevant recommendations, implement retargeting, and much more.

Who uses a CDP?

A CDP makes customer data available to teams across an organization, allowing optimization of various business processes, including:

  • Audience management
  • Campaign management
  • Customer service & support
  • Product development
  • Prospecting & sales

B2C companies have been quicker than B2B firms to deploy CDPs, according to Understanding CDP Users: CDP Institute Member Survey 2019. But many B2C and B2B companies alike are in the process of deploying or plan to deploy a CDP, the report said.

What Is a CDP’s Most Common Use Case?

Why do you need a Customer Data Platform? The two most common uses for CDPs are personalized customer experiences and targeted advertising. Why? Because you can’t deliver great customer experiences if you don’t have a complete view of your customers and your relationship with them. A CDP’s greatest strength is that it helps you get that complete unified customer view and accomplish targeted personalization on a mass scale, so you can provide a great customer experience to each customer efficiently using AI, machine learning, and marketing automation. Let’s look at how that works in practice. First, let’s think through the elements of a profitable customer experience.

What makes a customer experience great?

It’s relevant.
It's relevant.

You understand where your customers are in the purchase process, and you provide them with the right messages and information.

It’s contextual.
It's contextual.

You can customize messages to the customer by channel, time of day, the weather, their past behavior or purchase history, and other attributes.

It’s personalized.
It's personalized.

You segment your customers using common attributes and tailor messages and information to those segments; in some cases, you send one-to-one messages.

It’s consistent.
It's consistent.

Regardless of the engagement channel or device, the experience and information you provide your customers is consistent.

It’s timely.
It's timely.

The right messages reach your customers at precisely the right moment, whether they are close by, in your store, or on the website.

Creating exceptional customer experiences requires companies to overcome their customer data challenges. Without a CDP, customer data is often:

  • Difficult to locate
  • Siloed by fragmented systems (such as channel)
  • Separated by various marketing functions
  • Hard to unify
  • Nearly impossible to analyze

A unified view of the customer is no longer a nice to have. It is now mission-critical, and if your business is going to survive and thrive, you need to figure out how to create it.

What Is a CDP’s Role in Customer Experience?

You need a customer data platform to:

  • Deliver a consistent experience across multiple channels and devices
  • Deal with complex customer journeys that include high volumes of customers and multiple interactions
  • Improve personalization and targeting, ensuring you are providing relevant messaging to the right customers at the right time and in the right manner

Could you do all these things without a CDP? Possibly, but it wouldn’t be easy. Consider the time and effort required to engage your IT team to build a unified customer profile from all of your systems. They would have to find all the data sources, develop and maintain multiple integrations to ingest disparate types of data into a single location, associate it to the right customer, clean and validate it. That much work alone could take months, maybe longer.

Now imagine engaging data scientists and engineers to help you streamline that process continually, analyze and segment the data to enable your marketing team to create and deliver marketing programs relevant to each customer. Those months could stretch into the years needed to keep your marketing operations running.

A CDP reduces the time and effort to connect data sources and build a complete, unified customer profile. It enriches that profile with additional data sources and includes capabilities to analyze and segment profiles appropriately. It then makes that data available to external systems for activation and execution.

A CDP enables:

  • Democratization of data: CDPs make customer data accessible to everyone in the company that can benefit from it.
  • Flexibility and agility: It enables the connection of new data sources quickly and updates profiles and segments in real-time.
  • Operational efficiency: CDPs reduce the need and time it takes for IT to compile, validate, and make customer data available.
  • Reduced marketing costs and optimized budgets: It helps marketing teams focus on the right customers and implement the right campaigns and programs.
  • Increased revenue: CDPs give sales and service teams the information they need to recognize high-quality prospects and cross-sell and upsell opportunities quickly.

What Is a CDP Myth Many People Mistakenly Believe?

Many people assume implementing a customer data platform requires a “rip and replace” of existing applications. But this is a myth. A CDP sits central to existing applications as the customer intelligence hub. It ingests customer data from relevant systems and then provides a consolidated view of all customer data back to the systems that deliver customer experiences.

Does everyone need a CDP?

While it’s clear a CDP brings value to an organization; it isn’t necessarily for everyone.

You may not need a CDP if:

  • All of your audience management needs are taken care of with a system of record for individual customer profiles.
  • Your marketing technology stack is limited, and you don’t have a lot of different technologies capturing customer data and delivering customer experiences.
  • Your customer data is simple and easy to unify and analyze.
  • Personalization is not a requirement or goal for your organization.

What Is a CDP’s Greatest Advantage over CRMs and DMPs?

There is often confusion between a customer data platform (CDP) and other marketing and sales technology, specifically, CRMs (customer relationship management systems) and DMPs (data management platforms). Before we talk more about CDPs, let’s clear up any confusion.

A Customer Data Platforms (CDP) is a unified customer database that builds rich customer profiles using data collected from systems across the company. It provides these profiles back to these systems to improve customer experiences.

A Data Management Platform (DMP) is a solution used by marketers to improve advertising, retargeting, and media buying. Data collected is primarily anonymous data from cookies, devices, and IP addresses, and it’s only stored for a limited time (typically 90 days). DMP data is often fed into a CDP to improve customer profiles. There are other differences between CDPs and DMPs, summarized in the table that follows.

A Customer Relationship Management (CRM) is a solution for tracking and managing interactions with prospects and customers. It is primarily a sales tool used for contact management and sales management. Marketing activity can be fed into the CRM through predefined connectors. Most data is user generated through sales people entering contact engagement and sales activity manually.

What Is a CDP’s Advantage over DMPs and CRMs? CDP vs. DMP vs. CRM

These solutions sound similar but have very different capabilities and are used for different purposes. The following table explains the CDP vs. DMP question, as well as the CDP vs. CRM issue.

Table 1. Comparison chart showing the similarities and differences of the often confused technologies of CDPs, DMPs, and CRMs.

Table 1. While often confused, CDPs, DMPs, and CRMs have very different capabilities and purposes as outlined in this chart.

When you look closely, what you see is that these technologies are complementary:

  • A CDP can enrich its customer profiles by ingesting second- and third-party data from a DMP.
  • A DMP can ingest CDP customer data to improve ad targeting.
  • A CDP can ingest customer data from a CRM.

If you’re looking for more on best practices involving CDPs, DMPs, and other martech, you might find this article on bridging martech and adtech helpful.

How Does a Customer Data Platform Work?

Let’s go under the hood of a customer data platform and look at its architecture and key capabilities.

Illustration showing how a CDP works.

Treasure Data CDP collects, unifies, and segments customer data from anywhere so enterprise teams can activate hyper-personalized and profitable campaigns.

Data Collection & Integration

The first step is getting first-party customer data into the CDP, including basic profile data, engagement data, and transaction data. First-party data comes from systems and channels such as web and mobile, email and marketing automation, CRM, surveys, ecommerce systems, and more. The data comes in many formats, structured and unstructured.

Most CDPs will offer pre-defined integrations to common data sources and systems from marketing, sales, and support. The data is ingested in real-time or batches, continually feeding the CDP with current customer data.

Customer Data Cleansing/Transformation

Collecting data is the first part. Once ingested, some CDPs have the capability to clean the data, ensuring it’s consistent and correct. Data cleansing includes resolving identities, deduplicating profiles, discarding inaccurate data (including fake profiles), and resolving discrepancies. Some CDPs also include extract, transform, and load (ETL) capabilities that can be used to build data pipelines for these activities.

Customer Profile Enrichment

Once the profile is complete, a CDP can enrich the profile by integrating second- and third-party data sources. This type of data comes from organizations like Bombora and Dun & Bradstreet (business data), Acxiom and Neilsen (demographics data), weather, interest data, and other sources. Enriching the profile with this type of data helps fill in missing or inaccurate attributes and remove duplicate information. It also helps with building a richer set of seed segments for advertising platforms—enhancing prospecting activities with higher match rates and market reach.

Customer Segmentation

A CDP provides tools for marketers to define audience segments based on attributes and behaviors. You use segments to improve targeting and personalization. Segments are rules-based, or they are built using machine learning and AI. Predictive scoring is one example of a machine learning algorithm. With predictive scores, marketers can enrich their profiles with data they wouldn’t be able to tabulate on their own and create more robust target audiences.

Using the segmentation capabilities of a CDP, you can do things like:

  • Identify advocates
  • Predict customer churn
  • Identify potential upsell and cross-sell opportunities
  • Identify top-performing customers
  • Deliver relevant recommendations based on a profile’s purchase history

Illustration showing the segmentation capabilities of a CDP.

The segmentation capabilities of a CDP helps marketers optimize the entire customer journey from discovery through advocacy.

There are many different ways to analyze and segment profile data. Look for a CDP that provides out of the box components, prebuilt code, and visualizations for faster deployment.

Customer Journey Orchestration

Customer segmentation in a customer data platform

Some CDPs also provide customer journey orchestration capabilities. Through the creation of customer journey stages, marketers can visualize the engagement consumers have with their brand, giving them deeper insights into the channels used, and the messages and information that work best to engage and convert at each stage in their customer journey maps.

Customer segmentation in a customer data platform

Real-time segmentation helps marketers execute hyper-personalized campaigns.

What Is CDP Data Activation and Execution?

Data activation and execution are all about making the data available to external systems through prebuilt connectors or via a REST API. The CDP makes individual profile data, segments, or all customer data available to social media, website and mobile apps, email marketing systems, advertising systems, business intelligence tools, and others. The data can be pushed to these systems on a schedule or pulled from your website, social, advertising, and A/B testing tools in real-time.

What Is a CDP Dashboard?

Some CDPs provide reporting and dashboards to identify KPIs, trends, and other relevant information. Most will enable reporting through BI integrations and include embedded reporting such as audience management and segmentation dashboards. These types of embedded visualizations help marketers make faster decisions as they work to create segments and activate them. If advanced reporting is needed for executive briefings or campaign status updates, look for a CDP that empowers you to create customizable reports and dashboards, including data visualizations and drill-down reports.

What Is a CDP’s Underlying Architecture?

A customer data platform can store petabytes and more of data, so the platform needs to be flexible. Cloud-based solutions are a popular choice for CDPs due to the inherent scalability of the cloud, as well as data lake technology that provides the ability to support the volume, velocity, and variety of data marketers need.

Not only does the CDP store a lot of data, but that data is in different formats, which means your CDP must be flexible enough to support many data types, including unstructured data. Look for a CDP that provides schemaless ingestion, which means you store the raw, event-level data without the need to organize it into tables before it is available to your marketers. Schemaless ingestion ensures that your data is always available even if there are changes in the source systems. And, you save time ensuring access to the customer data regardless of when it was created.

What Is a CDP’s Role In Security Architecture? How to Pick a Secure CDP

Security is another crucial element of a robust CDP architecture. With the number of cyberattacks increasing every year, the last thing you need is for hackers to steal your customer data. Here are some tips for picking a secure CDP:

  1. Look for a CDP that provides advanced policy-based access control with industry standard protocols such as SAML 2.0 for both authorization and authentication.
  2. Make sure there are strong security frameworks in place to prevent data loss and threats. These should be backed by multiple certifications through third-party authorities such as ISO/IEC 27001 and SOC 2 Type 2.
  3. You should also make sure that all data transferred between the CDP and other applications is encrypted in transit and at rest.
  4. Finally, you’ll want the ability to set user permissions to the platform by organization, role, and region to ensure you have audit logs to track changes to data throughout the system.

Your enterprise CDP must provide a level of security that complies with the tightest security protocols and compliance mandates of your company.

What is a CDP Myth that Prevents Better Marketing Use of Customer Data?

There’s a myth that CDPs take a long time to set up. In fact, enterprise CDPs provide the tools and resources needed to get up and running quickly. This includes out-of-the-box integrations for quickly connecting with external data sources, a library of prebuilt sets of code and applications for specific use cases, and trained professional service teams to ensure your implementation goes smoothly.

What Is a CDP’s Role in Customer Data Privacy and Compliance?

Customers are demanding better experiences. But they don’t want them at the expense of their privacy. And that means you can’t have a discussion about unifying customer data without talking about privacy and compliance. Data privacy is about more than being compliant with privacy regulations; data privacy is about building trust with your customers.

Ensuring Compliance: How a CDP Helps

Whether you are working to comply with GDPR, CCPA, or another data privacy and compliance regulation, you have to keep track of the customer data you capture and how you use it. You likely have a consent management system in place to capture a customer’s consent to collect their information, but that system doesn’t track where you store that customer data once permission is given. CDPs integrate with consent management systems to ensure only systems and people with the appropriate consent can activate the information it manages.

A customer data platform acts like a data catalog providing a map of data sources with details on the data ingested from each source as well as where each item is used in the consolidated data model. It also uses permissions to perform data policy enforcement, ensuring only those people and systems that should have access to personal customer information have it.

Learn more about how a CDP can support your privacy requirements: Powering Privacy Compliance with a Customer Data Platform

What is a CDP’s Role in Building Trust?

Privacy and compliance present an opportunity for marketers to build trust with their customers and prospects. According to a recent study by Deloitte, half of the consumers surveyed don’t feel they have control of their personal data. They also indicated that they are more likely to share personal data with retailers they trust.

By getting a handle on privacy and compliance with the help of a CDP, marketers can show customers that their information is properly cared for and used only to improve their experience.

What Is a CDP’s Role in Breaking Down Data Silos? Key Customer Data Platform Integrations

No single marketing technology provides all the capabilities a marketer needs to create exceptional customer experiences. And yet we still have ongoing discussions about platforms versus suites.

Yes, there are some marketing platforms available that provide a suite of tools used by marketers. Some of these suites offer rudimentary CDP capabilities. But it’s important to understand that suites typically offer a small subset of the capabilities you need from any single tool, including a CDP.

The best approach to ensure you are getting all the capabilities you need to deliver the right customer experiences is to integrate best-of-breed solutions. In fact, a recent survey from Campaign Monitor shows that most marketers prefer to buy best-of-breed technologies.

Stat showing 82 percent of marketers prefer to use best-of-breed technology stacks

More than 80 percent of marketers use best-of-breed technology instead of a single vendor marketing cloud, according to a recent survey from Campaign Monitor.

Today’s marketing technology landscape includes a plethora of technologies marketers use when building their own martech stack. The challenge with using multiple best-of-breed solutions is connecting the dots between them. When information can’t be shared between systems, data silos are created.

In Gartner’s 2019 Marketing Technology Survey, 28 percent of both B2C and B2B respondents said integration between marketing technologies is their biggest impediment to delivering against marketing and business objectives.

A CDP eases the best-of-breed challenge by enabling the collection of customer data from multiple systems into a central location. This CDP “back-end” acts like the central intelligence hub for all of your marketing systems. Modern digital marketing and sales solutions provide APIs that make it easy to connect to the CDP and export and import customer data to build personalized marketing programs. The CDP you select should provide out-of-the-box integrations to commonly used systems, including:

  • Marketing automation platforms
  • Databases
  • CRMs
  • Web analytics
  • Ecommerce
  • Social media
  • Data management platforms
  • Advertising
  • IoT and sensor data
  • BI platforms

Another Common CDP Myth: 

Another myth is that buying a CDP locks you into that vendor’s platform. This may be true if you are purchasing a suite solution that includes a CDP. But with a standalone CDP that provides all data and analytics to drive day-to-day marketing operations, you continue to use your data anywhere you want.

Customer Data Platform Use Cases

In the backdrop of digital channel proliferation, marketers often find themselves amidst a perfect storm. How do you increase the customer lifetime value (CLV) with very minimum investments while justifying the spend? Driven by data, a successful CDP solution must always work with the existing marketing stack to increase customer loyalty while maximizing marketing ROI. A CDP, when implemented well, often pays for itself within a short time after deployment. A unified customer view is at the heart of a CDP. A unified customer view derived from noisy duplicate profiles is what powers granular customer segmentations that drive a wide range of campaigns and marketing programs. Add in advanced machine learning capabilities and what you have is a modern-day equivalent of a “crystal ball.”

Marketing use cases:

  • Real-time personalization: Delight your customer with the right message at the right time and right place.
  • Cross-channel orchestration: Identify the channels a customer or segment uses in a customer journey, ensuring the messaging and information is consistent across those channels.
  • Behavioral retargeting: Segment customers by shopping behaviors like products viewed, content read, or past purchases, and retarget them with new products and services.
  • Lookalike advertising: Define customer segments with similar product purchases, shopping behavior, demographics, and more to help find similar customers to target.
  • Account-based marketing: Segment accounts in the CDP to help you understand and prioritize where to focus, as well as track account and contact interactions with your company across channels and campaigns.

It’s not only marketers who benefit from a CDP. There are many use cases for sales, support, IT, and others. Here are a few more examples of how a CDP improves customer experience.

Sales

Sales can improve margins and profitability by using a CDP to obtain greater insights on prospects and existing customers. A CDP integrates data from CRM, ERP, sales enablement software, and support and customer service interactions, enriching the customer profile with additional attributes from marketing systems and other third-party data providers.

A few uses cases where the CDP supports sales teams:

  • Score and prioritize prospects: Sales teams can focus the majority of their efforts on high-quality prospects and those customers with a higher affinity to purchase.
  • Cross-sell and upsell opportunities: Understand which products and services an existing customer might be interested in purchasing by looking at recent purchases, browsing activities, and more.

Support

Support teams can leverage unified customer profiles—that include insights from sales and marketing—and start conversations with a deeper understanding of customer needs. This allows customer service teams to be proactive and specific with the offers and service they provide.

  • Improve call center response times: Provide call center agents with a unified customer profile to help support customer needs faster.
  • Decrease churn: Identify customers most likely to abandon a product, service or brand, and create programs to connect and re-engage the customer.

IT

Even the IT group benefits from a customer data platform:

  • Reduce development efforts: CDPs connect to disparate systems across the organization, and build a single view of the customer, reducing the time and effort required by IT to develop custom integrations.
  • Unify datasets: CDPs can ingest structured and unstructured data, and if the CDP provides schemaless ingestion, IT doesn’t need to manage changes to data sources.
  • Automated workflows for data collection and unification: A CDP reduces the need for IT to manage the flow of data between systems. Automated workflows ensure the data sources are consistently ingested, cleaned, and validated.

Common CDP Myth: You Have to be a Data Scientist to Use a CDP

The best CDPs democratize customer data. An easy-to-use and intuitive user interface helps make valuable customer insights available to marketers and other teams without requiring a data scientist. While a data scientist may be helpful in certain complex situations, it’s more the exception than the norm.

What Is a CDP’s Best Use Case? CDP Customer Stories Across Industries

The best way to understand the uses and benefits of a CDP is through the eyes of its users. CDPs are now used to market everything from cosmetics to cars, and from beverages to gaming gear. In particular, a growing trend is CDP use in retail, financial services, CPG marketing, and the automotive industry.

Subaru: What Is a CDP Doing Under the Hood for Automakers?

Customer Type: B2C Automotive Industry

Subaru initially implemented a CDP to unify customer data for operational improvement and website optimization. The automaker wanted to make use of all its first- and third-party data to improve how it targeted and interacted with customers across the entire customer journey.

To date, Subaru has unified over 800 data points and 80 billion records and collected 8 million new transactions daily.

  • By targeting customer behavior rather than devices, Subaru achieved a 350 percent increase in advertising click-through rates (CTRs)
  • Increased conversion rates from 18 percent to 31 percent
  • Leveraged ML to help dealers focus on the shoppers most likely to buy, boosting closing rates by 14 percent

“Using machine learning, we’ve improved our forecast reliability by as much as 30 percent for ‘likely’ buyers. That information greatly improves sales efficiency, helping dealers better allocate always-limited staffing resources.” —Oishi Masami, Engineer of Digital Innovation at Subaru

Read how Subaru drives bigger profits. 

Linden Lab: What Is a CDP Doing to Power B2C Gaming and Reduce Gamer Churn?

Customer Type: B2C Gaming Industry

Linden Lab develops virtual experience platforms, including Second Life, the largest user-generated 3D virtual world. It implemented a CDP to help acquire and retain customers, as well as to support remarketing for deeper product engagement.

With a CDP, Linden Lab:

  • Unified siloed gaming data and activated that data across 25 targets, including Mailchimp, Facebook, and Google Ads
  • Unified product usage with marketing data to drive marketing strategy, reduce costs, and grow ROI by 300 percent

“The efficiencies enabled by the Arm Treasure Data platform allow us to run more and better campaigns, do more testing, leverage our most valuable marketing channels to their full potential, and connect more deeply and personally with our users—all of the high-impact marketing activities that just weren’t possible before.” —Darren Helton, Sr. Marketing Manager, Second Life, Linden Lab

Read how Linden Lab leverages a CDP for Second Life.

Success: How Does 300% Marketing ROI (MROI) Improvement Sound?

Wish: What Is a CDP’s Role in Ecommerce?

Customer Type: B2C Ecommerce

Wish started as a mobile shopping app, quickly growing into a full web and mobile ecommerce platform with more than 15 million daily active users (DAU) within 18 months. The company implemented a CDP to help it provide more personalized shopping experiences for its users.

The CDP ingests 17 billion events per day and processes exponentially in the trillions. Wish.com uses customer behavior data and ML-powered recommendation technology based on analytics to ensure that 95 percent of products that cross the consumer’s field of vision are relevant.

  • Optimized algorithms that drive continuous 2X conversion growth year over year
  • Boosted sales by 7 percent with the addition of one field and 15 minutes of work

“The more we invest in data to personalize the recommendation experience, the more we see improvement in conversion rates.” —Peter Szulczewski, CEO and Co-Founder, Wish.com

Read how Wish built an $8B ecommerce experience.

How to Get Started with a CDP

The CDP sits alongside all your other martech solutions, which means you don’t have to replace existing systems to get it up and running. The best approach to getting started is to implement it in phases. We recommend the following steps to get started on the right path.

> Define and prioritize your business goals

Before you do anything, it’s critical to understand your strategic business plans and the KPIs of the organization. A CDP supports more than your marketing programs. It can inform your product strategy, provide critical insights to your sales team, and help customer support deliver seamless support experiences.

As a company, you have defined goals, plans, and key KPIs you need to reach. The work you do with your CDP and the use cases you implement should support those goals and KPIs.

> Set up your team

A CDP supports the entire organization and pulls data from systems across the organization, so it’s crucial to create a cross-functional, cross-organization team to implement and work with the CDP.

Leading the team should be someone with enough seniority to manage conflicting priorities and make sure the project stays on track. Next, you’ll want representation from marketing, IT, data science, product, customer service, and sales to develop an approach to centralizing customer data from the various source systems.

> Identify the use cases you will focus on

You will likely identify many use cases that will benefit from your CDP. A successful implementation is one where you don’t try to support all your use cases at once. There’s just too much you’ll need to do.

You may want to start with one or two simple use cases to learn how the CDP works, such as creating segments for email marketing campaigns or personalizing the website. Or, you may want to select one critical use case that helps prove the value of the CDP to the executive team. The important thing is to focus on one or two key use cases to start and build out from there.

> Create an inventory of data sources

Do you have a list of all the data sources that can feed your customer profile? Chances are you could list most of them quickly, but you might be surprised by how many other systems located across the organization also contain customer information.

Create an inventory of data sources, including the location of the source, the type of customer information it stores, and the format of that data (structured or unstructured). Make a note of how often the data structure of that data source changes. Some CDPs can ingest raw data in its native format, while others require data be transformed into specific data types and configurations.

> Map out the omnichannel ecosystem and the data that will be managed

How many channels do you use to communicate and engage with your customers? What data is collected and used in each channel? To create a unified view of the customer, you will need to map out the entire omnichannel ecosystem, including identifying the data your CDP will need to manage.

> Identify cross-functional dependencies

Your marketing team is separated into different groups, each responsible for a different marketing activity—content marketing, website management, email marketing, advertising, account-based marketing, and so on. Spend some time identifying the cross-functional dependencies between these groups to help you map out the dependencies with your customer data and how each group contributes to that data.

> Define security requirements

Your CDP will store personal customer information, which means you need to define the security requirements clearly. Who should have access to the CDP? What roles and permissions do they require?

> Outline governance and compliance requirements

How are you managing compliance with privacy regulations? If you are a global company, you are dealing with different compliance regulations, including GDPR, CCPA, CASL, and others. Each regulation has different requirements for capturing and storing customer data and how that data can be used. Your CDP must be able to support these different requirements.

> Start with a Proof of Concept

Start with a proof of concept (POC) to demonstrate that the CDP can support your use cases.

  • Identify the use case (or cases) to include in your POC, focusing on the key use cases you plan to support. If the POC can’t support your high priority use cases, then it’s the wrong CDP.
  • Unify the most important data sources supporting the use case (or cases).
  • If some of your use cases are complex, you may want to include one of these to ensure the CDP can support it.
  • Identify one key performance indicator (KPI) for each use case to show the value of the CDP.
  • Communicate the POC and its outcomes across the organization so others can see and understand the value a unified customer view can bring to their efforts.

Selecting a CDP: Key Questions to Ask

You’ve decided it’s time to purchase a CDP. You understand the value it brings to your marketing programs, as well as sales and support. How do you choose the right CDP? How do you create a CDP shortlist?

Ask the Right Questions

Ask vendors these key CDP questions:

  1. What data sources does the CDP integrate with and does it maintain these integrations? List the ones you know you need, including any that you know you have but haven’t been able to leverage in current programs. Also include data sources that you might not yet use but are on your roadmap.
  2. Does the CPD track both anonymous visitors and known customers across devices? Web and mobile analytics track both known and unknown visitors. Make sure the CDP has web and mobile SDKs to collect event data and support identity-based (email, user names, etc.) and cookie-based (browser cookies, IDFA, etc.) tracking.
  3. How does the CDP support privacy and compliance? Does the CDP integrate with consent management systems (name the one you use)? How does it help with data requests?
  4. What is the data retention schedule for the CDP? You are looking for unlimited data retention to improve your understanding of your customers over long periods.
  5. Are the tools to develop customer segments intuitive and easy to use? A CDP should not require a data scientist or IT person to help you define your segments.
  6. Does it provide access to the raw, unfiltered data? There may be times when you need to dig deep into the raw data to understand your customer better. Sometimes you don’t even know what data you have about your customers without examining the raw data.
  7. Does an enterprise CDP have artificial intelligence (AI) and machine learning (ML) engines? Do you have access to the ML/AI segmentation in a way that’s easy for you to understand?
  8. What type of security does the CDP provide? You are dealing with a customer’s personal information, so you need to know what security protocols the vendor has in place to ensure that information is secure.
  9. Do you provide training, professional services, and support? Ask the vendor what training programs they offer to learn how to use the CDP, whether professional services are available for custom work, and what learning and support channels are available once the CDP is in place.

Download this free, comprehensive RFP template.

Common CDP Deployment Pitfalls

Before you go, let’s take a quick look at some of the common pitfalls you might face when selecting and implementing a CDP. By understanding these pitfalls now, you have a better chance of avoiding them.

> Choosing the wrong CDP for your company

There are different types of CDPs available, so it’s critical you understand your requirements before you select one. One of the biggest pitfalls is selecting an SMB solution when you really need an enterprise solution. For companies with massive data volume, scalability of the CDP becomes a key factor, and some data models don’t scale well. In addition, enterprise solutions will provide more security and the ability to manage permissions.

> Not defining the data sources you plan to use and the use cases you want to go after

It’s critical to identify your data sources, key integrations, and the types of use cases the CDP needs to support. The data sources and use cases will give you a good idea of the amount of data the CDP will need to store and process, providing an indicator of the type of CDP you need.

> Not getting senior-level sponsorship

A CDP is cross-functional by nature, and when you deal with cross-functional platforms, you need the support of your executive team to ensure buy-in and collaboration from all departments and groups to make progress.

> Trying to solve everything at once

You’ve heard the term “boil the ocean.” When you try to do everything at once, it rarely works out. Implement your CDP in phases: connect your data from key data sources, unify it, then focus on your first use cases. When you are ready, enrich the profile with additional third-party sources, or add additional use cases. The point is, take it slow and easy to make sure everything is working as expected, and you see benefits from the start.

> Confusing a CDP with a CRM or a DMP

A CDP is not a DMP is not a CRM. Sometimes what you are looking for is not a CDP that manages a unified customer profile but a DMP that helps you improve advertising targeting. Or maybe you are looking for a solution to manage customers throughout the sales cycle (CRM). Know what you want before you go out and make a purchase—re-read “CDP vs. CRM vs. DMP” if you aren’t sure.

Read the CDP Deployment Guide: Lessons from the Field from the CDP Institute.

Next Steps to a Unified Customer View

A customer data platform provides excellent value to any organization that wants to improve customer experiences and keep operations effective and efficient. It unifies customer data across all your systems and data sources and gives you a single view of the customer. With this unified customer view, you can more easily analyze customers and identify critical segments to deliver relevant, contextual, personalized, and consistent messaging.

It starts with understanding your goals and use cases and selecting the right CDP to support those use cases. Then you connect your data sources, unify and enrich your customer profiles, segment and activate those segments in marketing programs, sales activities, customer support programs, and more.

Are you ready to get started? See how Treasure Data boosts sales and customer lifetime value. Request a demo today.