The 2022 Customer Data Platform buying guide

Think your organization might benefit from a CDP, but don't know where to start? In this guide we'll get you up to speed on standard terminology, guide you through the CDP market, and help you prepare for a successful CDP implementation.

Welcome

Congratulations on taking your first step towards maximizing the value of your customer data. Maybe you’re a marketer who wants easier access to better data. Maybe you’re an engineer who wants to spend less time fulfilling data shipping requests. Maybe you googled “CDP HELP!!1!” and found yourself here—whichever broad generalization you find yourself in, welcome!

It’s a common story: As your business has grown, customer data has gotten siloed in different tools, becoming inconsistent and difficult to activate. You want to access that data cross-functionally throughout your organization, need better data governance, and need to understand what your data means. Today, you’re ready to turn data chaos into data order and bravely whisper “I think I need a CDP.” We’re here to help you figure out what’s next.

In this guide, you’ll learn: 

  1. What a Customer Data Platform (CDP) is and why it’s important for your data strategy 
  2. How to assemble your internal CDP team (and how to build a CDP business case internally) 
  3. Whether you should buy or build your CDP
  4. How to choose the right CDP for your business

The CDP market is complex and rapidly evolving. We’ve seen organizations investing valuable time and resources into products that only solve their data problems of the moment, and often not all of those problems. But for a CDP implementation to be successful, you need to implement a solution that not only solves the challenges of today but also provides you with the adaptability to solve the challenges of tomorrow. Our goal here is to guide you through the process of choosing the right CDP for your team, sharing some helpful resources along the way. Let’s start with the basics.

Wait... what’s a Customer Data Platform?

The definition of a CDP has evolved and expanded since it was first coined in 2013. The current description provided by Gartner is that a CDP ingests data from multiple sources, aggregating and organizing that data, before sending it to downstream partners for activation. Different CDPs tackle this job differently, but we would argue that the most effective CDPs centralize data collection, quality management, and identity resolution, thereby making it easy to connect unified customer profiles to any tool in the stack via productized integrations. This level of functionality means that whether you’re building a dashboard in your analytics tool or handling a support ticket in your customer service tool, you’re able to access the same data set.

Why do you need a Customer Data Platform?

In recent years, businesses across industries have set the imperative to invest in digital experiences, specifically focusing on leveraging customer data to deliver more personalized, relevant campaigns. To accomplish this effectively at scale, you need a data strategy that defines what data will be tracked and how that data will solve specific use cases and support the various applications that consume it.

Defining a data strategy when your business is just beginning to scale is manageable. Over time, however, things change:

  • Requests for additional events start to emerge as new questions need to be answered
  • Experiments are created, and results need to be ingested and connected across applications
  • Campaigns are run, and engagement also needs to be connected to various applications for closed-loop analysis 
  • New and existing privacy requirements create additional workflows 
  • New applications are requested to help teams continue to push the limits; thus new integrations are requested 

Soon, the task of executing a data strategy becomes split into two parts. An easy part—segmenting and activating data to deliver personalized experiences; and a hard part—managing factors such as data quality, data connectivity, and data governance as your data landscape changes rapidly. 

Amidst the pressure to demonstrate improved digital experiences and ROI, it’s tempting to focus exclusively on the easy part–it’s a quick “win.” As new use cases are launched, however, new tools will be required and the number of data objects being tracked will increase exponentially. Furthermore, the amount of maintenance related to API changes will also increase, not to mention the up-front implementation costs required for every new tool. And all of this will take place in a market environment in which privacy requirements and restrictions are continually evolving. It will soon become impossible to tell what your data means and who your customers are, making any attempts to actually use that data ineffective at best.

Focusing on data activation while failing to address the hard challenges related to data quality, identity resolution, and data governance will lead to an abrupt descent into data chaos. The right CDP can help you turn this chaos into order, providing you with the adaptability required to ensure customer data remains valuable, actionable, and accurate over time.

From a data sharing perspective, if we aren’t using a vendor for marketing, why would we share data with that vendor? We paused marketing with our social media advertiser, which was a pretty big switch. We use a tag manager for the web integration, and I had to go into the tag manager to find and pause all the social media platform pixels. This took hours. In mParticle, for the necessary integrations, all I had to do was pause the connection, which took a minute.

Judith Henrichsmann

Product Manager, Growth at Airbnb

Data as a team sport: drafting your internal Customer Data Platform team

First, it’s important to establish your data strategy and assemble your internal CDP task force. Doing so will ensure you identify all the criteria you should be considering in your CDP evaluation.

As you decide how to approach your CDP implementation, it’s important to include the right internal stakeholders in the discussion. Building an internal CDP team will make it easier to align the project to business goals, identify evaluation criteria, and sell the CDP business case internally. 

Implementing a CDP represents a fundamental shift in the way data is accessed across the organization. Your CDP team will not only drive the initial implementation of the platform, but it will also roll out new business processes and workflows that help departments across the organization use customer data for their respective initiatives.

Because internal structures vary across companies, it’s helpful to think about the roles that should be in the conversation. Depending on your organization’s size, multiple roles may be owned by the same person:

Data consumers

  • Person in charge of customer communications both paid and owned
  • Person responsible for building marketing segments
  • Person who owns the digital customer experience

Implementers

  • Person responsible for implementing marketing and analytics tools

Orchestrators

  • Person who owns the roadmap
  • Person who manages developer resources
  • Person who owns customer data privacy
  • Person who’s responsible for data quality and identity resolution

Forming a task force with this group will not only help you create a complete requirement list, but it will also make it easier to present a strong business case to senior stakeholders.

The most successful CDP evaluations include input from stakeholders across all teams that interact with customer data, collaborating on decisions around data planning, data governance, and implementation roadmaps.

Defining your customer data strategy

The first task of your CDP team is to review and update your customer data strategy. It is helpful to have your data strategy defined before you begin thoroughly evaluating specific CDP options, as your data strategy can help you determine which features are requirements for your implementation and which are nice-to-haves. 

Set your customer data goals

Customer data can be leveraged in an infinite number of ways, from powering marketing campaigns, to improving customer support, to building customer intelligence into the product experience. 

To make the most of your customer data, it’s important to work with your cross-functional CDP team and evaluate all the ways in which customer data will be leveraged across various departments. Next, you’ll want to establish the specific use cases and KPIs that you plan to execute or optimize through the adoption of a CDP so that you can measure impact. You may also want to look out for use cases you are already executing and see if any could be made more efficient with a CDP in place.

Prioritize and plan phases of implementation

A Customer Data Platform can help you accomplish the most advanced data use cases, such as machine learning recommendations and building real-time customer data intelligence directly into your product experience. 

This doesn’t mean, however, that you need to begin using your CDP for these use cases overnight. The most successful CDP implementations we’ve seen have followed a crawl, walk, run approach that accounts for the design, implementation, training, and activation needed for each use case. 

To follow this framework, clearly define implementation stages based on your teams’ needs, capacity, skillset and more. For the best results, define how your teams will measure success at each stage.

Highlight potential dependencies or blockers

Occasionally, there is additional work required beyond the implementation of a CDP to fully operationalize your customer data architecture. Internal systems may require updates before they can be integrated with your CDP. Major customer-facing features may need to be shipped before you implement CDP vendor SDKs. It’s important to identify these potential dependencies or blockers so that you can plan accordingly.

Assess your customer data landscape

To maximize the value of your Customer Data Platform, it needs to be integrated seamlessly with your existing infrastructure and processes. Identifying where data comes from, and what information you’re tracking is important to success.  Determine what your universal data layer will need to include in order to service all consumers, and identify gaps in your current data set.  By planning your possible implementation, you’ll have a better idea of the needs you have, be able to choose the right CDP solution for your needs, and there won’t be any surprises.

Identify all sources of customer data

Identify the various sources of customer data and each source’s integration capabilities. These may be apps, websites, internal databases, or other tools in your stack, and each may have different capabilities in terms of how customer data can be collected and integrated. For example, data can often be collected directly from apps and websites via client-side SDKs, whereas backend databases will require server-side integration. Surfacing these channel-level requirements will help you define the scope of your CDP implementation.

Determine your identity resolution architecture

Building unified customer profiles requires the union of multiple identifiers across your data sources. To understand your ideal approach to identity resolution, you should catalog what identifiers are available from each data source. Once the full set of identifiers is compiled, you should define which ones can be used to accurately identify registered users versus anonymous users, as well as which identifiers should take priority when multiple are available.

It’s also important to establish the situations in which you do and don’t want to merge known and anonymous profiles. For example, if a customer signs up and is linked to a known profile, will you unify their pre-sign up browsing activity, which is linked to an anonymous profile, to the new known profile, or will you keep them separate? Your profile merge strategy will depend on the nuances of your customer journey and data governance policy.

Define what your universal data layer will look like

One of the biggest delays to time-to-data-value is bad data quality. It’s highly recommended that you create a comprehensive data plan that defines the data points you’ll be collecting and naming conventions for each data point, across platforms and properties. 

As you create the data plan, take time to align with both data engineers and business users on what data to expect and in what format. Ideally, you’ll create and maintain a single dictionary or catalog for your customer data so that all teams can understand what the data represents. 

Best-in-class CDPs will enable you to upload your plan into your CDP and enforce it as data is being collected, and also to download your data plan in the formats that meet the needs of teams across the organization.

Identify customer data activation systems

Being able to get data out of your CDP is as important as getting data into it. For that reason, it’s critical to identify the downstream data activations systems that your team would like to feed customer data to through your CDP. These could be tools that you’re already using today, or tools that you’d like to start using once you have your CDP in place. Make sure to tie this step back to the use cases that you hope to execute with your CDP.

Once you’ve identified the tools that will make-up your customer data technology stack, make sure the CDPs you’re evaluating can support integrations with these systems, both internal and external to your organization.

Account for privacy regulations and considerations

In order to stay compliant with data privacy rules and regulations, you should review any regulations that apply to your company and account for those in the design of your customer data architecture. A Customer Data Platform can help you securely integrate your data from point to point, but it’s essential that your data collection and federation reflect both regulatory requirements, e.g. CCPA and GDPR, as well as your company values.

Should you build or buy your Customer Data Platform?

Some organizations are well equipped to build their CDP. For most companies, though, it can be more time consuming, more expensive, and ultimately a lot less adaptable than working with a CDP vendor. 

What are the benefits of building your own Customer Data Platform?

If your team has domain expertise in building data infrastructure, there are some benefits to building your own Customer Data Platform. First, you’re able to build a system that is completely customized to your environment–you can prioritize building the connections that are most important to you, and you can ensure that your CDP works well with your existing architecture. You can also build integrations with highly custom data sources or internal systems that you don’t want to connect with a third-party. If you do not require the complete feature set that a third-party vendor provides, you can focus on the capabilities that are essential to your needs without paying for unnecessary features.

Second, the product trajectory of your in-house Customer Data Platform will be completely in your hands. If there are any features that you’d like to add to your CDP, or any existing aspects that you’d like to change, you can update the platform yourself and don’t have to request your CDP vendor to modify their product roadmap.

What are the downsides of building your own Customer Data Platform?

First, even if you do have deep domain expertise in building data infrastructure, developing a Customer Data Platform in-house is at best a 6-12 month project, according to the Customer Data Platform Institute. Without deep domain expertise, the build can easily take 18-24 months, if not more. There are many risks that can compromise such a long-term project, such as personnel turnover, shifts in organizational priorities, and budget constraints. End users that requested the platform initially may not get access to a solution for a year or more.

It’s also a complicated project. Success will depend on collaboration between multiple departments across the organization, and on working with external partners to build API connections. Gartner notes that “homegrown CDPs require the full range of IT development roles, including the ability to build a business-friendly user interface.” It’s often senior, more experienced team members that have extensive experience with your existing architecture and institution that will have to dedicate significant time to building the CDP, increasing the cost of each hour invested.

Second, your Customer Data Platform’s evolution will be yours to execute once the initial platform is live. New API connections, product features, and more will likely be requested from end users of your CDP on an ongoing basis. If there are any changes in government regulations or market conditions, your organization’s platform requirements may change. Frequent CDP maintenance and integration builds will pull resources away from other projects, increasing CDP cost and impacting the productivity of the team as a whole. As your customer base grows, you will need to ensure that your CDP has the data processing scalability required. Although you will have the flexibility to focus on updates that are most important to your organization, it will also be up to you to build them. 

The benefits of buying a Customer Data Platform

Many organizations, both enterprises and startups, that turn to Customer Data Platforms consider working with a leading CDP vendor. There are several benefits to doing so.

Time-to-value

One of the biggest benefits is the speed at which you can have your CDP up and running. Instead of allocating resources to build your Customer Data Platform, your engineers are able to implement packaged SDKs in your digital properties or set up API connections once and then return to core development. 

For an example of what these look like, you can see mParticle’s SDK and API documentation here.

Furthermore, some CDP vendors will offer professional services support to assist with the implementation and ensure that adopting a CDP doesn’t necessitate strains on engineering. mParticle offers implementation support designed to help you go from kickoff call to production in 90 days or less.

Here is an outline of mParticle’s four step Quick Start implementation roadmap:

Cost

Working with a Customer Data Platform vendor can also be cost effective. As noted previously, building a CDP internally is expensive, as it requires dedicated hours from senior engineers. Any delays in the build process will only make the project more expensive. Working with a CDP vendor will allow you to access the capabilities you and your team need at a subscription cost, eliminating the opportunity cost of the build process. 

Beyond the initial launch, working with a CDP vendor will also reduce costs on an ongoing basis. Packaged CDPs with extensive integration ecosystems and friendly UIs will make it easy for non-technical teams to connect data to new tools without engineering support. CDPs with data quality and audience segmentation tooling will allow non-technical stakeholders to build high quality audience segments without having to submit requests to data engineering or data science.

Flexibility for data consumers

Data strategies evolve over time. It’s important for Customer Data Platforms to accelerate your team’s evolution, not prohibit it. 

With secure data collection and extensive integration ecosystems, packaged CDPs make it easy to shift or evolve your data pipeline. Business teams are able to collect data from new sources, such as a POS system, with little-to-no engineering work required, and trial or A/B test new vendors by sending limited data sets to them in just a few clicks.

When you need to instrument a new event, CDP developer tools such as mParticle’s Smartype make it easier for you to translate your data schema into type-safe code to help you ensure proper event collection at run time. Business users are able to get access to high quality customer data sooner, and you’re able to work faster while reducing technical debt.

Adaptability to changes in data strategy

Finally, one of the biggest values of working with a CDP vendor is adaptability. Third-party CDPs allow teams to remain flexible to the dynamic needs of the organization. As privacy changes, platform updates, and market shifts arise, you can continue to execute on your data strategy without pausing for a development update. For example, if your marketing team needs to test a new tool, you can connect a CDP’s packaged integration without any custom development. When Google changes their API, you can rest assured that your CDP partner will take on the integration update.

Questions to ask when considering build vs buy

What are the competitive advantages you seek by having a CDP?

If you’re competing in a mature market, an excellent way to differentiate is by investing in technology that enables better customer experiences. You may have some of the resources to build your own solution, but legacy infrastructure or organizational restrictions may make it difficult to move forward. 

If you’re operating in an emerging market, speed to market is important. The sooner you can implement a viable solution, the sooner you can begin delivering results.
Are you planning on using a CDP to power real-time customer experiences such as transactional emails and fraud prevention? If so, it’s important to consider the requirements for building real-time data collection and integration versus batch processing.

What available resources do you have, and what is your track record of tech development?

Many organizations consistently adopt to build their own tools, and therefore have the resources and processes in place to do so again successfully. If you don’t have a track record of developing data infrastructure, however, it’s important to consider whether you have the resources and processes in place to build something as foundational as a Customer Data Platform.

What are your CDP time-to-market requirements?

As noted earlier, there is a significant time differential between building and buying a customer data platform. If you are operating in an evolving industry and are facing pressure to keep up with the competition, it may be difficult to allocate 12-18 months to building your own solution (if not longer). Working with the right CDP vendor can allow you to get to market in as quickly as 90 days.

What will the labor costs of developing and maintaining a solution be for your organization?

Once your initial CDP solution is built, you’ll still be responsible for building new integrations, maintaining existing connections, ensuring your infrastructure can scale, and introducing the feature updates your team needs. To properly forecast a CDP build, it’s important to estimate the number of updates you’ll need to make a year (based on your team’s historical vendor selections) as well as your projected tracked user growth, and calculate what the labor costs of those updates will be.

How to navigate the Customer Data Platform market

Once you have your data strategy outlined, you can more successfully evaluate your CDP options. Because this continues to be a team effort at your organization, we’ve categorized suggested considerations into three functional roles: Implementers, Data Consumers, and Orchestrators.

Implementers

To determine which CDP vendor is right for your organization, it’s important to validate that the CDP integrates well with your existing systems. Without a sustainable implementation, any downstream benefits that a CDP promises to business teams are nullified.

Beyond initial instrumentation, you also need to confirm that the CDP will make engineer’s lives easier in the long run. Implementation of new events should be simple, and any embedded kit integrations should be easy to add to the existing implementation. Furthermore, certain CDPs empower engineering users with developer tools such as linting and CLIs, making it easier to adhere to your data schema and ensure that high-quality data is logged to your workspace.

Questions that implementers can consider when evaluating a CDP

  • Does the CDP provide SDKs and APIs that I can easily deploy into our systems?
  • Does the CDP provide integrations that will allow us to move third-party vendor code from the client-side to the server-side?
  • Does the CDP provide developer tools that will enable our engineers to manage the implementation more easily?
  • Does the CDP vendor provide developer documentation that will allow us to work with the tool independently?

Data Consumers

Growth Marketing leaders and other data consumers are heavily involved in Customer Data Platform evaluations because they are the role that is most active in the CDP once it has been implemented. Specifically, functions such as setting up event forwarding, profile lookups, and audience building are all completed by Marketing stakeholders within the CDP UI. When evaluating vendors, data consumers should inspect how easy it is to carry out these core functions in each CDP, and confirm that they can be completed without developer support.

For integration capabilities in particular, marketers and other data consumers should validate that the CDP integrates with all the tools and systems across their tech stack. If there are gaps that the CDP provider promises to fill, it’s important to assess their capability on delivering those updates. Additionally, it’s important to confirm that integrations are easy to connect, and that you’ll have the ability to control which events are sent to each destination within the UI.

When evaluating a CDP’s audience building capabilities, it’s important to validate that the platform’s UI makes it easy to build segments and connect them to downstream systems in real time for activation. Advanced audience features that you can look out for are audience size estimation, audience A/B testing, and audience downloading. 

Questions that marketing stakeholders can consider when evaluating a CDP

  • Is the UI clear and easy to use?
  • Does the CDP make it possible to access a unified view of the customer without developer support?
  • Does the CDP have an intuitive audience builder that enables you to build segments without developer support?
  • Does the CDP have packaged integrations with all of the other tools in your growth stack, and do those integrations enable you to forward events and audiences in real time?
  • Will having the CDP in place make it easier to deliver personalized customer experiences?
  • Can you use the CDP on a day-to-day basis without involving a developer?

Orchestrators

Customer Data Platforms provide value to Product Managers and other orchestrators in several ways, and at the enterprise level it’s not uncommon for distinct teams within the Product org to leverage the CDP for a variety of defined purposes. 

For Product Managers focused on using data to understand user engagement in an analytics application such as Amplitude or a BI tool such as Looker, CDPs provide the data infrastructure that enable you to connect data to downstream tools based on your forwarding choices so that it can be used to draw meaningful conclusions. When evaluating CDPs for this purpose, it’s important to investigate not only data collection and integration capabilities, but also each vendor’s data quality features. Without clean, accurate, and consistent data flowing into your analytics systems, all insights may be compromised. 

For Data Product Managers focused on improving the integrity of the data pipeline, Customer Data Platforms present a transformation of the way in which customer data is managed. By eliminating data silos, creating a unified view of the customer, and providing Marketing with instant access to real-time customer data without Engineering dependency, CDPs make the vision of building an interconnected, best-in-class tech stack a reality. However, with a cluttered and confusing CDP market, it’s important to differentiate between which CDP providers are providing reality and which are providing a facade. The best way to do so, besides evaluating a vendor’s capabilities for collection, identity resolution, and integration, is to conduct customer references and trial specific use cases.

Customer Data Platforms also benefit Product organizations by improving developer productivity. Without a CDP in place, developers are consistently called to assist business teams with vendor SDK implementations and updates, .csv data uploads, data quality management, and other tedious tasks. These requests pull developers away from core development, introducing the impact of context switching, delaying the launch of customer-facing initiatives, and putting the product roadmap at risk. By enabling non-technical users to connect data to downstream applications within the UI, CDPs free developers from having to support ad-hoc requests from Marketing. When evaluating a CDP, validate with your developers that the CDP provider’s client-side SDKs are well built and will fit into your existing architecture. This will ensure that the CDP will truly free developers from ongoing third-party code management. 

Questions that product stakeholders can consider when evaluating a CDP

  • Does the CDP have the capability to collect all of the data I need to understand product performance and user engagement
  • Will the CDP help you save engineering resources in the long run?
  • How will the CDP implementation impact app/website load speed?
  • Will the CDP enable us to resolve cross-channel data to unique customer profiles?
  • Will the CDP enable us to process Data Subject Requests, collect customer consent state, and control data forwarding based on consent or any other chosen lawful basis?
  • Does the CDP integrate well with the tools and systems used across our growth stack?

What about roles that are harder to define?

Because you’ve built your internal CDP team with stakeholders from across your organization, you may have members that don’t neatly fit into the above categories. Their input will be just as valuable, and their expertise will guide what area should be their evaluation focus. For instance, when building your internal CDP team, you brought in the “Person who owns customer data privacy.” This Data Privacy Officer can use their expertise to ask questions like:

  • Does the CDP offer data localization tools to choose what country or region the data is stored?
  • What sort of data privacy controls does the CDP offer and is it sufficient for our business (and the future of our business)?
  • Does it offer the GDPR, CCPA, or other regional compliance that our business needs?
  • How does it support AppTracking Transparency and similar upcoming platform changes?

Asking these sorts of questions for each of your team members’ area of focus may seem exhaustive, but it will establish the shared foundation to accomplish the next step: Prioritization.

Prioritizing the features that are most important for you

Hopefully, the preceding questions have started the gears in your mind turning. Ideally, at this stage you should be looking at your organization, your unique business needs, and weighing your options.

It can be difficult to consider what your ideal personalization or CDP experience looks like, so a good trick is to instead imagine your ideal customer experience. How do you want your customer to feel when they interact with your company, whether through an email, a push notification, a display ad, or natively in your app? Now think about the path to delivering that interaction.

To help you with this step of your evaluation, we’ve created a CDP Vendor Comparison Tool. This tool is a simple Excel sheet which allows you to easily prioritize the features that are important to you, and then track which CDPs support your requirements.

Ensuring long-term success of your Customer Data Platform

Just because you’ve finished implementing a CDP doesn’t mean you should dissolve your internal CDP team! Building a data-driven culture within your organization requires the introduction of new procedures, and your CDP team will have the best insight to design those workflows. For example, with a CDP in place, business owners of individual data activation platforms (such as email or analytics tools) will no longer individually own the collection of data at the source. In this case, there may be a need for a central owner of the data collection across all sources, to which the data consumers subscribe and provide requirements.

It may also make sense for your CDP team to create a new customer data workflow for the business’ internal teams. This can entail creating processes to manage new data sources, data requests, and data consumers as they develop.

Need assistance building your CDP business case, or want to learn how mParticle is different from other CDPs? Connect with our team.

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