Build or Buy: Decoding the Best CDP Strategy for Your B2C Enterprise

Speakers:

• Janet Jaiswal: VP of Marketing, Blueshift (also Moderator)
• David Raab: Founder, Customer Data Platform (CDP) Institute
• Todd Illberg: VP of Customer Success, Blueshift

Welcome and Introductions

Janet Jaiswal: Hello, everyone. Thank you for joining us. Today's webinar will discuss the topic: "Build or Buy, Decoding the Best CDP Strategy for Your B2C Enterprise." We have three presenters today:

First, David Raab, Founder of the CDP Institute. Welcome, David. Second, Todd Illberg, VP of Customer Success at Blueshift. And I will be doing double duty, presenting and moderating this session. My name is Janet Jaiswal, VP of Marketing at Blueshift.

Housekeeping Notes

First, a copy of this presentation and the session recording will be sent to all who have registered. Next, you can submit questions through the Q&A box at any time. We will answer these at the end of the webinar.

About the Organizations

Janet Jaiswal: I want to give you a quick overview of the two organizations involved in today's call.

Blueshift

• Founded: 2014, headquartered in San Francisco.
• Recognitions: Recognized by the Gartner MQ for CDPs, a leader in GigaOm Radar for CDPs, and recognized by Deloitte Technology Fast 500 for the past four years.
• Offering: Provides a CDP platform with an optional cross-channel marketing platform for activation. Blueshift has patented AI technology for smarter decisions across the entire customer journey.

CDP Institute

• Founded: 2016.
• Mission: A vendor-neutral organization dedicated to helping companies manage customer data. They are thought leaders in CDPs.
• Global Presence: Has chapters in Europe, APAC, LATAM, and the US.

Understanding the CDP: A Maturity Model and Core Capabilities

Janet Jaiswal: Now, let's provide an overview of the CDP to set the context.

CDP Maturity Model

(Chart displayed: Maturity model with "Amount of Data" on Y-axis and "Customer and Relationship Management Complexity" on X-axis)

Janet Jaiswal: Keep in mind that there are multiple customer data management tools, and most companies store customer data in many different places. They often wonder: "What's the best way to manage all that customer data?" It comes down to two primary factors:

1. Amount of Data: Measuring the volume of data being managed, aggregated, and processed.
2. Customer and Relationship Management Complexity: Measuring the complexity and sophistication of managing customer interactions, relationships, and personalized experiences.

Depending on where you are as a company across that X and Y axis, you'll want to utilize different tools. Some companies will have multiple customer data management tools, which also makes sense, as each tool is likely utilized for a different need. As you can see, the CDP is best or ideal for providing comprehensive data aggregation from multiple sources, real-time processing, advanced segmentation, and personalized marketing capabilities. CDPs excel in managing both high volumes of data and complex customer and relationship management needs.

Now, let me turn things over to David to further expand on a CDP's capabilities.

What a CDP Does

David Raab: Great, thank you, Janet. As I just said, the CDP really excels at high volume, complex customer data management. But what goes on inside?

Fundamentally, a CDP takes data from your various data sources (CRM, web, order management, external sources) and runs it through a process in the middle that creates customer profiles. This involves:

1. Capture and Ingestion: Getting the data in.
2. Preparation: Including data quality checks.
3. Storage: Linking data associated with the same customer from different systems.
4. Profile Building: Attaching all other details to those linked profiles.
5. Sharing & Integration: Integrating the shared data with other systems.
6. Segmentation: All CDPs do segmentation.

The output is then shared with your various delivery systems (CRM, website, mobile apps, data management platforms, or other systems that use customer data). It's pretty straightforward, though easier said than done.

The reality is a little more complicated because other things happen to the data between building profiles and sharing with delivery systems:

• Analytical Activities: We explore data, classify it, do predictions, recommendations, measurements, and campaign optimization. All of these rely on the good customer profiles the CDP builds.
• Message Delivery (Campaigning): We do personalized content, create outbound audiences, run real-time interactions, orchestrate over time and across channels, and arbitrate (picking the best message among many possibilities for a given customer at a given time). These make sense as central functions.

How a CDP Drives Value

David Raab: So, we understand what a CDP physically does, but how does it drive value?

• For Marketers (Traditional Users):
  • Increased engagement and conversion rates.
  • Improved ad spend efficiency (ROAS).
  • Increased retention and lifetime value (LTV).
  • Increased visibility into omnichannel campaigns.
  • These are all things you do with that unified view, beyond just having the view itself.
• For IT and Data Departments (Increasingly Key Users):
  • Cleanliness and accuracy of data.
  • Efficiency of data processing.
  • Privacy, compliance, and governance.
  • Efficiency of connecting all systems to one central system.
  • These are benefits your technical staff gain simply by having, building, and maintaining a CDP and creating those profiles.
• Broader Enterprise Benefits: Customer service, sales, and operations teams also derive significant value from the CDP's output and customer profiles.

The Shift in CDP Responsibility

David Raab: We see a clear shift from marketing-focused to enterprise-focused CDP management. While primary responsibility for CDPs was once largely with marketing, it's now increasingly almost exclusively held by IT teams and data and analytic teams. Only a minor 12% of CDPs are now managed by marketing; almost all are managed by data and IT professionals.

This change adds some complexity. If you're a marketer, you might feel you've lost some control, but for the enterprise as a whole, it's very much a good thing.

Janet Jaiswal: Awesome. Great, David. Thank you so much for that overview. I think it's super helpful to frame up what a CDP is and how it's used.

Customer Spotlights: Real-World CDP Impact

Todd Illberg: My name is Todd Illberg, and I have the privilege of bringing the voice of the customer to today's call.

Customer Spotlight 1: Personal Finance (Card Issuer)

For our first customer spotlight, we'll discuss a client in the personal finance sector—a card issuer specializing in the hospitality industry, particularly dining experiences.

• Strategic Initiatives:
  • Enhancing brand visibility.
  • Acquiring net new customers by leveraging strategic partnerships and digital platforms.
  • Implementing sustainable practices.
  • Enhancing customer loyalty programs and personal experiences.
  • Harnessing vast amounts of data to achieve these goals.
• The Challenge:
  • They operated using a legacy DMP platform and had many data warehouses and siloed data sources.
  • Data was not actionable for customer insights.
  • Legacy DMPs were designed for paid media and performance marketing, requiring extensive IT resource-intensive middleware for integrations into marketing automation platforms.
• The Solution (CDP):
  • A CDP was a natural fit, providing a 360-degree view of the customer profile for enhancements and personalization.
  • It enabled two-way integration with their marketing automation platform via SFTP for real-time data imports and exports.
  • Provided analytics for better retargeting of first-party data.
• Data Sources & Functionality:
  • The CDP brought together data from diverse sources related to customer experience, transactional and behavioral data, and large-scale data from card management and risk, as well as content.
  • CDP functionality included: Data ingestion and integration, unified profile management (to avoid retargeting the same person with different promotions), real-time segmentation, and applying analytics and AI capabilities.
  • This approach, leveraging a CDP upfront to enable their MarTech solution, led to very positive customer outputs and interactions.

Janet Jaiswal: All right. So now it's time for our first poll question.

Poll: Primary Customer Data Sources

Janet Jaiswal: The question is: "What are your primary sources of customer data for marketing purposes?" Please select as many as apply to your companies.

Your options are: Data Warehouse, Data Management Platform, Marketing Automation Platform, Customer Data Platform, Customer Relationship Management, and Custom Built Solution.

(Poll results displayed)

Janet Jaiswal: All right. So now we have the results. Looks like CRM happens to be the most popular source for customer data, followed by Marketing Automation Platform and Custom Built Solution. David, Todd, any comments on that? Does this follow what you see in the industry, or is it a little different?

David Raab: It's pretty typical. The CRM system is most companies' primary repository of customer data, so it certainly feeds into the CDP. Marketing automation is common in both B2B and B2C. It's interesting that Data Warehouse is relatively low, but traditionally data warehouses were built more for financial analysis, not customer data. So, that's not a shock.

The presence of "Custom Built Solution" is a good reminder that many companies have these. They are often difficult to access for pushing data into a CDP, but they can be very critical to a company's business operations, often requiring special connectors to extract essential data. These legacy systems haven't gone away.

Todd Illberg: Janet, I just want to add that the big picture here is that the challenge still exists. Marketers are trying to get their hands on so many disparate data sources. Being able to figure out which ones are truly actionable without storing a bunch of unused data (which leads to inefficiency) or trying to find a "silver bullet" is key. We're going to have to test our way through to achieve better ROI and LTV.

Janet Jaiswal: Good point. And actually, Todd, to your point, the previous slide in your case history showed a dozen, maybe 15 or 20 sources. That's more like reality. Your survey here only listed a few, but most CDPs and companies have many different sources of customer data. That's something to bear in mind when you think about the effort involved in pulling one of these things together. Absolutely. That's right.

CDP Use Cases: Critical for Build or Buy

Janet Jaiswal: Now, let me turn things over to David, who's going to discuss CDP use cases, as they are critical to determining whether to build or buy. David, over to you.

David Raab: So use cases, they're my favorite things. We do love use cases! They are really important in making sense of what you need to do and what requirements your CDP (or other system) has to fulfill. We've listed quite a few here, based on real data from research.

You see personalization, targeting, ROI—these are all outputs, marketing programs, or projects designed to generate revenue. If you ask most marketers or users what they want from their CDP, they want it to make them money. But of course, the CDP does more than that. It has to build those profiles (unifying data to any resolution, maintaining them). That's not an output in itself, but it's crucial because the CDP can't do anything else without it.

The thing to bear in mind about use cases is that people consistently struggle to understand what the use cases are for their CDP before they buy it. That's one of the biggest questions we hear: "What do I do with this thing? What are my use cases?" Because that drives everything else. This is a good, detailed list, not necessarily your list, but a valuable one to consider as you think through: "What would I do if I had a CDP?"

Framework: Matching Use Cases to Functionality

(Chart displayed: Matrix of Use Cases vs. Functionalities)

David Raab: If you go to the next slide, you can look at a framework for how to match use cases to functionality. As I said earlier, use cases are the base—this is what I want to accomplish. But that doesn't tell you what your CDP needs to do; it only tells you what the desired outputs are. How do you transition from "here's what I want to do" to "here's what I need to have available to make that happen"?

This is a simplistic and oversimplified matrix. Down the side, we have our use cases (campaign, personalization, audience segmentation, measure marketing ROI). These are the outputs. Then, across the top, we have functionalities or capabilities. For example, "real-time listening" is required for two of those five use cases. "Social media advertising as a data source" is needed for three. "Schema-free data load," important for CDP function, might not be required by these specific use cases.

What we're doing here is looking across and identifying the different things I may or may not need. At the bottom, you ask: "Is it needed? Is it missing (a gap)? Or do I already have it available?" And finally, if it is missing, "Is it something the CDP can do?" Because it might be something that happens outside the CDP. This framework helps you input your use cases and capabilities to build your requirements list. It's crucial to realize that your requirements are driven by your use cases—that's the value of use cases at the start of these projects.

And the point here is it's more than just technology gaps, which is what the previous slide showed. We also have:

• Data gaps: Do I have the data I need? Can I get it?
• IT gaps / Skill gaps: In the IT department, data department, or among users. Can users take advantage of this wonderful tool?
• Measurement gaps.
• Organizational gaps: Around coordination across groups.
• Value gap: Maybe a particular use case isn't actually valuable to me.

These are all different kinds of gaps you need to look at. It's not just technology. Every one of these gaps must be filled; it's a chain, and any broken link means the chain doesn't work. You must fill all your gaps, or you simply can't complete the process.

Todd Illberg: No, this is for me. So, picking up the voice of the customer and translating it into another customer spotlight.

Customer Spotlight 2: Retail E-commerce (Automotive Parts)

Here, we're going to focus on a retail e-commerce customer operating in automotive parts and accessories. They have a large, diverse customer base and a big catalog of parts. They focus on their online presence and manufacturers to help build their presence, doing a lot of advertising and managing a lot of data.

• Growth Focus: Expanding product offerings, enhancing website functionality, and focusing on timely delivery (consumers expect Amazon-like speed).
• Visibility: Increasing brand visibility for market share.
• Acquisition & Retention: Attracting new customers while retaining existing ones.
• The Challenge:
  • Their current solution lacked the ability for a customer lifecycle journey orchestration.
  • They needed in-market event data and signals (e.g., browse signals) for near real-time recommendations.
  • Lacked informed data recommendations, especially for automotive "fitment" and other data-driven enhancements.
• The Solution (Full Engagement Platform):
  • A full "soup-to-nuts" engagement platform that included both the CDP side (customer view) and seamless activation and analysis.
  • They are experimenting with cross-channel at scale, which is their next maturity step.
• Solution Graph & Functionality:
  • It involved ingesting data from similar but also unique sources, including in-store and e-commerce signals.
  • This data was piped through the CDP for ingestion and profile management.
  • Identity resolution was crucial to avoid paying for the same person multiple times in performance marketing.
  • Analytics were applied for content and message optimization at the right time.
  • Ultimately, this created enhanced web experiences and cross-channel delivery.

This represents another great experience for a customer and how they organize and activate their data.

Janet Jaiswal: All right. So now we'll cover the build versus buy framework. David, over to you.

Build Versus Buy Framework

David Raab: So there are really three core questions when you're trying to decide whether to build or buy (or honestly, any marketing technology decision):

1. What do I want to do? This refers to the programs you want to run, which are a function of your business strategy and resources. This drives your use cases.
2. What's stopping me? This involves comparing your needs to your current resources and identifying the gaps—things you don't have available.
3. What's the best solution to close the gaps? Here, you evaluate the features and costs of all your different system options and pick the best one.

In a build vs. buy decision, we primarily look at cost, but it's not just financial cost. There's a whole range of other costs. Janet, I know you have a very beautiful framework for discussing that. So let me hand it over to you.

Evaluating Needs: Eight Categories

Janet Jaiswal: Okay. Thank you. The next step is to evaluate your needs along these eight categories:

1. Strategic Alignment: How well is the CDP aligned with your marketing strategy? Do you have a clear long-term vision for customer data management?
2. Cost: What is the total cost of ownership? Consider initial investment, maintenance, and operational costs.
3. Time to Market: How soon do you need it to be operational?
4. Scalability and Flexibility: How well will the solution scale with your business growth, whether you build or buy?
5. Technical Expertise and Resources: Do you have the technical expertise and resources to build and maintain a CDP?
6. Opportunity Cost: What are you giving up by choosing one path over another?
7. Data Security and Compliance: Can you meet regulatory requirements and data security standards? This is especially crucial in regulated industries like financial services and healthcare.
8. Vendor Support and Innovation: Will you get the desired support, training, innovation, and, importantly, updates? If you build, can you continuously support innovation, or if you buy, can your vendor provide those updates as needs and use cases change?

For each criterion, we've listed the implications of build versus buy (pros and cons). You'll want to list more detailed criteria under each of these eight major categories, depending on your company's unique needs.

Example of a Completed Evaluation

(Chart displayed: Sample Rating for Build vs. Buy Criteria)

Janet Jaiswal: This chart shows each of those factors with a sample rating. Ratings are 1 to 5, with 1 being the lowest score (partially meets criteria) and 5 meaning it fully meets the criteria. The idea is to rate each criterion, then total the score for a more objective rating of which option makes sense for you: build versus buy.

Key Takeaways and Resources

Janet Jaiswal: Okay, we're almost done, and soon we're going to open it up for Q&A. Let's talk about the key takeaways and useful resources.

Key Takeaways

1. Meet Demanding Customers: We are in an era of increasing competition and demanding customers who want to be met on their terms. A CDP is critical here to meet customers where and when they want to engage.
2. CDPs for Complexity: There are many customer data management solutions. CDPs are ideal when you have large amounts of data and high customer relationship management complexity (e.g., customers with changing needs across many channels, requiring integrated, one-to-one engagement).
3. Build is a Serious Commitment: Building a CDP is a serious commitment and should be thoroughly evaluated. The frameworks shared today should help you make an informed decision.
4. Maturing CDP Market: The CDP market is soon entering its maturity phase, according to Gartner. This means functionality, usability, and innovation (especially in AI) are expanding the value delivered. It's an exciting time with significant innovations emerging.

Useful Resources

I promised resources at the end of the session, and we have a couple for those who attended this webinar:

1. Choosing the Right CDP: This resource outlines the 10 most critical factors to examine when choosing a CDP, ensuring you enter the selection process with open eyes and ask the right questions.
2. CDP Institute Self-Assessment: For anyone considering the acquisition, development, or enhancement of a CDP, this provides a comprehensive list of items to consider in your CDP project.

Q&A Session

Janet Jaiswal: It's now time to open things up for your questions. We've already had a few questions submitted during the webinar registration process, and I'll turn it over to David and Todd to answer. Feel free to submit more through the Q&A box.

Question 1: Data Warehouses vs. CDPs for Marketing Audience Member: Our company has several data warehouses. Why can't they just use that for their marketing efforts instead of a CDP?

David Raab: That's a question on many minds right now. The answer is, maybe you can. It really depends on your specific data warehouse. If your data warehouse does everything a CDP does—building proper customer profiles, providing real-time access, and real-time updates for managing real-time interactions—then sure, you can use it as your data source.

The problem is most data warehouses don't do that. You need to assess your specific data warehouse: Which data sources are feeding it? Which data is it keeping versus discarding? How is it formatting and analyzing that data? These are all critical questions, and they're part of what's covered in the 100-item self-assessment tool I mentioned. If your existing systems do everything you need, great, use them. If they don't, you must consider how to close those gaps—whether by extending your existing warehouse, building a new one, or buying a separate, standard CDP with built-in functionality.

Question 2: Coexistence of Data Warehouse, MAP, CRM, and CDP Audience Member: Can we use a data warehouse and push data directly to a CDP, or have a data warehouse, marketing automation platform, CRM, and a CDP all together?

Todd Illberg: It's a great question. When you think about where a CDP sits as a marketer-friendly solution, it's really the aggregate of all that data. It's not saying it replaces these other systems, nor does it have to replace them; it can live right alongside them. It truly depends on the data you want to use to inform your campaigns and customer journeys.

The best marketers today, when considering the constant question of "how many messages can I send or campaigns," if you have a really robust data set, you're creating relevant messages that enable one-to-one experience at scale. There isn't a one-size-fits-all answer. We see customers who have data warehouses but struggle, as David mentioned, with long IT queues to get data or make improvements. The CDP puts data directly into the hands of the marketer, allowing them to be flexible and nimble without being stuck on an IT prioritization list or reprioritized due to rebrands or catalog refreshes. Marketers often don't get priority in the IT queue, and a CDP helps alleviate that.

David Raab: To add to that, if there's data in your warehouse that you want in your CDP, it makes a lot of sense to copy it from the warehouse into the CDP, rather than collecting it a second time from the source system. So, by all means, if the data warehouse is there, use it. There's no reason not to. As Todd just said, you might need both—a data warehouse for some purposes and the CDP for others. Your marketing automation and CRM systems all do different things, so chances are you'll have all of them anyway. The question then becomes the most efficient way to link them together to minimize duplicate processing while still getting the data you need in the right format and places.

The problem is that data warehouses, and certainly marketing automation platforms and CRM systems, weren't built to share their data widely with other systems. That's simply not what they were designed for, and most of them would admit they don't do a very good job of it. That sharing function of the CDP is a very important capability that many other systems lack. So, even if you had all these other systems with the right data, you might still want to run it through a CDP just to use it as the central access point for all other systems that want to use that data.

Question 3: Why Replace an Existing CDP? Audience Member: Why would someone want to replace their CDP if they already have one?

Todd Illberg: That's a good question, rooted in the idea that often, the current system of record for data activation may not have been originally set up to solve the challenges marketers face today. So, whether it's moving from one CDP to another or conducting a hygiene effort within a current data setup, we often see optimization projects with our customers. Marketers aren't always data-organized; we create scrappy lists and processes not meant to scale.

A reason to move CDPs is if your current one doesn't provide the functionality you need. However, as we often say in customer success at Blueshift: "Garbage in leads to garbage out." The platform and solution doesn't matter if you're not willing to take a hard look at the data you're using and the organizational strategy for bringing it in and reporting on it. You'd just be moving spaghetti from one system to another. But if you're looking to move up the maturity curve, to market to your customers smarter, better, and faster, using the right data to create informed experiences, that's where you'll see efficiencies. You can achieve this in your current CDP, or you might gain more efficiency from a clean slate in a new CDP.

Question 4: Reconsidering Enterprise Data Warehouses Audience Member: Todd, you work with many companies that are reconsidering their enterprise-level data warehouses. Can you share insights into their thinking and why they might want to do that?

Todd Illberg: When we look across our customer base, we see compliance becoming a major factor in data organization. Not just being on brand, but when we think about data privacy laws like GDPR and California Privacy Protection, these are changing really fast. So, being in control of your data and having an authentic single source of truth is incredibly important. That's a key driver for how customers are thinking about and using their data now.

Question 5: Best Solution for Multiple Channels and Changing Tastes Audience Member: Our customers are on multiple channels and have changing tastes. Which customer data management solution makes the most sense?

David Raab: You won't have a hard time guessing my answer here! When customers are on multiple channels, no one channel system will have all the data. You are essentially forced to pull data from all these different channels and then put it into a unified customer profile, which is precisely what a CDP does. Your CRM isn't built to handle web logs, and your website personalization isn't built to handle CRM data. You need a central place. It could be a data warehouse, but it's more likely to be a CDP because that's exactly what a CDP is built to do: take data from all those different sources, pull it together, clean it, unify it, build a unified profile, and then make those profiles shareable. It's almost a no-brainer to say that the minute you get into multi-channel operations and want to orchestrate across channels, you're forced to have some sort of central system that, whatever label you give it, will look a lot like a CDP.

Conclusion and Farewell

Janet Jaiswal: Those are all the questions we have time for. I wanted to thank David and Todd for sharing their insights. With that, we will call it a wrap. Thank you everyone for attending.

David Raab: Thank you, Janet. It's been a very good, very interesting discussion indeed.

Janet Jaiswal: Thanks everyone. Thanks, David. Bye-bye!