Expert Perspective: Deep Dive into CDPs

Speakers:

• Joan: Webinar Host
• Vijay Chittoor: Co-Founder & CEO, Blueshift
• David Raab: Founder, Customer Data Platform (CDP) Institute

Welcome and Introduction

Joan: Hello, everyone, and welcome! I see many of you joining, so we'll give everyone just another minute, and then we'll get started. Welcome to our expert panel, where we're taking a deep dive into CDPs. If you have questions, please put them in the Q&A section, and we will answer them at the end of the webinar.

Today, I'm super excited to introduce our speakers: Vijay Chittoor, Co-Founder and CEO of Blueshift, and David Raab, Founder of the Customer Data Platform Institute. Welcome!

Quick Introduction to Blueshift

Joan: For those who may not be familiar with Blueshift, I want to provide a quick two-minute introduction. We help you power customer engagement across every channel, focusing on three key areas:

1. Unify Customer Data: We unify and organize customer data from any source to deliver rich customer profiles and easily accessible segments that you can tap into in real time.
2. AI Decisioning: We help you automate and scale your marketing with AI. This enables you to engage customers with the right content, the right product, the right offers on the best channel, and at the right time. AI-driven recommendations and predictive scoring facilitate this.
3. Activate Across Any Channel: We help you orchestrate and activate your data across any channel where your customers are present, including email, SMS, web, paid media, and more.

That's us in a nutshell! Feel free to reach out if you'd like to learn more.

Webinar Series Overview

This is Part Two of our webinar series. If you missed Part One, which covered "CDP's Role in Intelligent Execution," "CDPs in the Modern Data Stack," and "CDPs as Enablers of AI," I encourage you to tune in. The high volume of questions from Part One inspired us to create this follow-up session.

Today, in Part Two, we'll cover:

• Selecting the Right CDP
• Secrets to Successful Implementations
• Realizing ROI from Your CDP

With that, I'll hand it over to Vijay and David.

Selecting the Right CDP

Vijay Chittoor: Thank you, Joan. David, I'm excited to speak with you again on this topic. Our last discussion on how CDPs fit into the modern data stack, enable AI, and drive intelligent execution generated a ton of questions. So, I'm eager to dive into what was on everyone's minds.

Let's start with selecting the right CDP. David, at the CDP Institute, you've seen countless CDPs and even coined the term. I'd like to share some of your research with the audience, specifically focusing on what selection criteria lead to satisfied buyers after implementation.

Research: Selection Criteria and Buyer Satisfaction

(Chart displayed: Satisfaction score vs. Buying Criteria)

Vijay Chittoor: The top chart, represented by the red line, shows satisfaction scores. We can see that higher satisfaction is correlated with buying criteria such as feature sophistication, internal integration, and ease of use. Conversely, lower satisfaction scores tend to correlate with criteria like initial cost, operating costs, and available workers (implying a status quo approach to staffing). David, how do you interpret this research, and what advice would you offer our audience today?

David Raab: Thanks, Vijay. This data is from the current year, but we've seen very similar, consistent results in previous years. While correlation doesn't always equal causation, it's a strong indicator.

This research tells us that people satisfied with their MarTech results (our actual satisfaction question) tend to select based on features. Nearly everyone prioritizes internal integration, and those who don't are likely unhappy. Other factors correlating with higher satisfaction include ease of use, external integration, and feature breadth. These are all core technological aspects of the CDP that buyers explore upfront. Anything above 3.5 on our scale indicates a positive correlation with satisfaction.

On the flip side, buyers who focus heavily on operating costs and initial costs, though common, tend to be less satisfied. The "available workers" criterion is interesting; it suggests a reluctance to invest in staff training, which usually leads to poorer MarTech outcomes. This set of correlations has remained very consistent over time.

Vijay Chittoor: Very insightful. The "available workers" point certainly suggests that successful MarTech initiatives often require embracing change management and tapping into new skill sets.

Research: Buyer Priorities Over Time

(Chart displayed: Buyer attention to criteria, 2022 vs. 2023)

Vijay Chittoor: Now, let's look at how buyer priorities have trended over time. This chart compares 2023 (blue bars) to 2022 (red bars). A larger blue bar indicates increased buyer attention.

I notice an increase in focus on initial cost and operating costs in 2023, which might be understandable given economic turbulence. However, feature breadth, a key indicator for buyer satisfaction, shows a shorter blue bar, meaning less attention. Thankfully, internal integration remains consistent. David, what do you observe in this data? Are there trends that concern you or make you optimistic?

David Raab: This data is indeed very concerning—it's probably what gives me the most nightmares from our recent research. Why? Because focusing on cost correlates with lower satisfaction. To put it bluntly, more people are making the wrong choice. While we understand the increased budget pressures, this is a very short-term approach that will lead to poor long-term outcomes. We are quite upset to see this trend.

Conversely, it's upsetting to see fewer people focusing on features, which is critical to getting it right. Buying the wrong tool at half the price is still buying the wrong tool. The cost of the tool is a fraction of the value it should generate. We raise a red flag here and urge folks to carefully consider buying the right system. If it costs a little more, that's truly okay.

Vijay Chittoor: That's a very interesting point. From a vendor perspective, it perhaps places more responsibility on us to meet buyers where they are, by aiming for lower initial costs while still delivering a wide range of features that lead to long-term satisfaction. At Blueshift, when we see this data, it reinforces our commitment to delivering feature breadth and strong integration while striving to reduce the initial cost of deployment.

David Raab: That's a good point. People often select on cost when they perceive products as similar. It's up to vendors to clearly explain their differentiation and why their product is the best fit for a particular client, even if it costs more because it truly offers superior value. If the product differences aren't clear, cost will always be the deciding factor.

Product Differentiation and Value

Vijay Chittoor: Given that, let's discuss differentiation. In our last webinar, we touched on high-value use cases like orchestration and real-time interactions, which not all CDPs support. Gartner categorizes CDPs into buckets—some focus on "marketing data integration" for unification, while "smart hub CDPs" handle real-time interactions and orchestration. Marketing cloud CDPs might not excel at the data layer.

David, how do you guide buyers to think about different types of CDPs and true differentiation, especially when they're focused on cost? How should they consider product differentiation and value?

David Raab: We sound like a broken record on this, but it always comes down to use cases. You must understand how you plan to use the system and what your company specifically needs to achieve those goals. Companies differ, sometimes more than they realize.

• Data CDPs: If you only need data integration because you already have excellent delivery and analytical tools, then a CDP vendor focusing solely on building customer profiles (what we call "data CDPs," similar to Gartner's "marketing data integration CDPs") might be sufficient.
• Orchestration/Smart Hub CDPs: If you have significant gaps in your delivery, orchestration, or analytical systems that prevent you from executing your use cases, you'll need a CDP that provides those additional functions. Most CDPs offer some delivery capabilities.

Ultimately, you must match the type of CDP you buy with your company's specific needs. This brings us back to use case analysis, which drives feature analysis, highlighting why selecting on features is so crucial.

Research: Trustworthy Information Sources in CDP Selection

Vijay Chittoor: That makes perfect sense. When selecting on features, buyers also consider various information sources. Research from TrustRadius shows that when buyers evaluate information sources in their buying process, they rank them as follows:

(Chart displayed: Trustworthy Information Sources for Buyers)

Vijay Chittoor: A product experience (e.g., free account, ability to load their own data) is highly important. Referrals and product demos also rank high. This is good news, as many of these are product-centric. Conversations with analysts, presumably like yourself, about feature sets are also valued.

Furthermore, purchasing behavior is evolving. In 2021, a free trial account was ranked #5, but by 2022, it jumped to #2. Product demos are very capability and feature-centric, and free trials allow buyers to customize the experience to their environment, testing if it scales to their specific use cases. User reviews are also key. It seems buyers are gravitating more towards feature-centric evaluation.

David Raab: This is interesting data, though not from my research. We know that free trials and product-led growth have become more popular. There's been some debate about when this is appropriate. For a complex product like a CDP, a 30-day free trial is tricky; you need to devote resources to loading and testing your data, otherwise the trial expires unused.

While this data applies to all kinds of products, including simpler ones like email systems where a 30-day trial offers a good sense of the product, CDPs are more challenging. However, many buyers are now more sophisticated in their understanding of CDPs. So, even if they don't do a full deployment in a free trial, they understand what they're looking at and can sufficiently "poke around" to grasp what it might be like to work with the product.

Vijay Chittoor: You've hit on some key points. First, it's been nearly 10 years since you coined the term CDP, so market understanding has matured, and buyers are more sophisticated. Second, with the emergence of the modern data stack, data infrastructure is becoming more standardized, making data ingestion more streamlined. This is a great opportunity for CDPs to scale, as my perception is that most brands don't yet have a true CDP deployed as we define it. For widespread adoption, CDPs need to become simpler, with clear guidance on common data sources and quick starts. I believe CDP simplicity and hands-on experiences will become increasingly important for buyers.

Successful Implementations

Vijay Chittoor: We've discussed selecting the right CDP. Now, let's turn to implementation. Many brands find limited success, while others thrive. The CDP Institute has researched what leads to successful implementations, particularly in achieving high-value use cases like orchestration and real-time interactions.

Research: Obstacles to Successful CDP Deployment

(Chart displayed: Obstacles to Successful CDP Deployment, showing "Organizational Problems" as the largest bar)

Vijay Chittoor: David, what jumps out at you when you look at these criteria, and how do you advise CMOs and other CDP buyers based on this data?

David Raab: What immediately stands out is the "Other" bar on the right, which represents organizational problems. By far, the most common problem is getting cooperation throughout the organization. Honestly, we didn't need a survey to confirm that; we knew it in advance, and I'm sure you have too.

Buyers often blame the vendor or the technology, which isn't always the full picture. If you look at the orange/red bars, these are more technical issues like "bad requirements," "CDP failed," or "couldn't build a common ID." Some of these "bad requirements" are actually evidence of poor organization—we didn't define our needs properly. Issues like "activation systems that couldn't handle the output" should have been known before purchase; it's not a surprise. Input data is always a challenge, as no one's data is perfect.

While some individuals overcome organizational obstacles, it's clear that organization matters to everyone. The core message here is to engage your people from the very start of the project. Ensure requirements are accurate and that everyone understands the CDP's purpose. We've seen situations where a small team buys a CDP, then presents it to unengaged users who resist changing their workflows, leading to slow deployments.

Vijay Chittoor: Based on what you've said and this data, my thesis is that brands succeeding with CDPs embrace a shift from a channel-centric mindset to a customer-centric mindset, with the CDP as the enabling tool. A unified ID is crucial because disparate IDs across channels won't work. The organization must also be ready to embrace changes in roles and decision-making towards a customer-centric approach. My thesis suggests this is why organizational gaps frequently appear. Technology is key, but many issues boil down to unifying for a customer-centric experience. Does that broadly resonate with you, and how would you characterize this big-picture organizational change?

David Raab: Yes, very much so. This is fundamentally a change management problem. Unified customer data should transform how you interact with customers, enabling consistent orchestration across the entire lifecycle, shifting to a customer-focused (not product- or channel-focused) approach. Unfortunately, most organizations are structured around product or channel, rarely around the customer.

The CDP is both a catalyst and an obstacle here. It makes change possible and often forces it, but it also creates resistance. If the organization successfully resists, the CDP may not be fully or properly utilized. We certainly hope that doesn't happen.

Vijay Chittoor: That's super interesting. For anyone on this webinar considering a CDP, while we discuss technical aspects and buying criteria, this idea of change management—moving from channel-centric to customer-centric processes—is paramount. The CDP is a powerful technological tool for this, but the organization must be ready to embrace and make those changes.

Realizing Full Vision: Initial vs. Eventual Value

Vijay Chittoor: Along with this, there's another lens on successful implementations: initial proof points of value versus realizing the full vision.

(Chart displayed: Use Case Classification: Data Assembly vs. Customer Touch Points)

Vijay Chittoor: David, help the audience understand this data. How do you interpret it, and what do you emphasize when discussing it?

David Raab: This data comes from our use case generator, a tool that helps formulate use cases—which, as we discussed, are incredibly important. We classify submitted use cases, providing real data on what's top of mind for CDP buyers.

We find two main clusters of use cases based on their purpose:

1. Data Assembly Use Cases: These are foundational and aim to produce customer profiles. Many people start here, seeing profile building as their primary use case, which is necessary before anything else can happen.
2. Customer Touch Point Use Cases: These are on the right side of the chart (outbound campaigns, real-time interaction, orchestration). These are the actions that truly create value because they directly interact with customers. Until you touch a customer, you don't generate value or ROI.

Both clusters are important. However, only the "customer touch point" uses cases have an ROI attached to them. Data assembly is foundational—like asking about the ROI of your phone system; it's simply a necessity for operations.

Vijay Chittoor: That's right. For successful implementations, time to value is key. The high-value use cases are indeed in real-time interaction and orchestration, driving customer experience changes.

If someone takes a sequential view, data assembly is a significant project itself. Successful customers, however, understand the full picture: where to start and where to end. They compress the time to initial value. Even if data assembly isn't 100% complete, they establish a solid foundation and then iteratively build upon it, starting with about 80% of the data and some real-time or orchestration use cases. This only works with a holistic vision; without it, you risk tripping up.

Do you have any thoughts on getting started and achieving that initial time to value, especially as we move into discussing ROI?

David Raab: I'll use a cliché: "crawl, walk, run." Start simple, then add complexity, and finally, do the really fancy stuff. Even very simple use cases can provide value. For example, selecting lists for outbound campaigns or email retargeting is a classic, simple use case. If someone drops a shopping cart, you can push that data to your email system and send a reminder. Without a CDP, this might take days with manual work. With a CDP, it can happen in seconds or minutes.

This is a crawl use case: one data source connected to one system, simple to set up with standard connectors, and it yields a measurable outcome. If you want to be systematic, start here. Then, leverage existing connections. Instead of making your second use case involve connecting to a call center and your third to website personalization (each plowing new ground and involving new departments), cluster your use cases. Invest in a given data source or channel connector, and then find three or four use cases that can leverage that existing configuration.

This also applies to departments. It's easier to train one or two departments on four or five different use cases than to train four or five different departments on four or five different use cases.

Vijay Chittoor: That's a great insight! It ties back to avoiding organizational pitfalls in successful implementations. The insight that it's easier to train fewer departments on multiple use cases is key. Starting with two or three data sources for bare-minimum data unification is also crucial. Companies often find their customer journey siloed across in-product experiences, anonymous marketing, and in-store transactions. Connecting just a few of these, establishing a unified profile, and then starting with three or four use cases within one department are keys to that "crawl, walk, run" success. This creates the foundation for running. It's interesting how selection criteria and implementation success are intertwined.

Realizing ROI from Your CDP

Vijay Chittoor: Implementation success is ultimately measured by value and ROI. Let's discuss specific areas where CDP customers realize value, drawing on research from the CDP Institute.

Sources of Value from CDPs

(Chart displayed: Benefits Realized from CDP Adoption)

Vijay Chittoor: We've discussed these benefits previously, but they bear repeating: achieving a unified view, analyzing segments and audience insights, and enabling orchestration and message selection (determining the right offer, channel, and time for each customer). These consistently bubble to the top as key value drivers. Are these the primary sources of value you emphasize?

David Raab: I believe these are indeed the primary value generators. What's interesting is that the less commonly cited benefits on the right, like less time/reaction, less IT reliance, and greater efficiency, are actually quite important. If you look deeper into who reports these, the more satisfied users often stress these "quick wins." They free up resources for future initiatives. While you might not buy a CDP solely to save IT effort, you will gain IT efficiency and faster reaction times. You'll get practical benefits that don't always generate ROI as directly as an email campaign, but the organization benefits from both cost savings and increased agility.

Going back to the right side of the chart, the more common goals: the unified view is clearly understood. People who took this survey grasped that "CDP generated unified view." Once you have unified data, the first step is analysis, which then leads to orchestration, message selection, and predictive modeling. The sequencing makes complete sense.

Orchestration is intriguing because it's the most sophisticated application. Some might dream that the CDP will magically enable super sophisticated cross-channel orchestration. While the CDP will enable that, organizational coordination issues might delay it. In contrast, message selection and predictive modeling are often out-of-the-box capabilities where you can expect the CDP to deliver substantial, measurable improvements that create ROI.

Vijay Chittoor: That's a very important point. And it's interesting how you highlighted the smaller bars on the right, the efficiency aspects. They might be discussed less, but they are equally crucial, especially given buyers' focus on operating costs. If you want to scale use cases without scaling your team, the right technology, faster data access, and reduced IT reliance become paramount.

CDP Benefits Across Teams

Vijay Chittoor: When we talk about "less IT reliance," it sounds like a benefit primarily for marketers. However, CDPs also offer significant benefits for IT and data teams. How do you position these CDP benefits differently for these two distinct teams? While their goals are ultimately aligned, how does your messaging vary?

David Raab: This chart lays it out quite well. They have different concerns.

• Marketers: Their primary interest is running marketing programs to achieve better outcomes. They care about costs, their own time, quicker reaction times, and agility. But most importantly, they focus on engagement rates, return on ad spend (ROAS), lifetime value (LTV), and potentially visibility (measurement). While measurement is important, the urgency of daily tasks often pushes it down the priority list.
• IT and Data Teams: They have a distinct set of concerns. IT teams prioritize security, reliability, efficiency, and data processing. Their goals boil down to keeping the lights on and company data safe. Customer experience sometimes appears on their radar, but it's usually lower than priorities like accounting, finance, or operations, which are arguably more critical in the short run. Data teams are the guardians of data; they focus on data quality, data access, privacy, compliance, and governance. These are critical for company safety and operational integrity.

The CDP must support both sets of goals. When selling or planning, you should present different aspects to different teams to ensure everyone in the organization is pulling in the same direction post-purchase.

Advice on CDP Buying Committee & Integration

Vijay Chittoor: On that note, we've covered selecting the right CDP and its buying process. What's your advice on how buyers should form their buying committee and how they can integrate both IT/data teams and marketers? How do you ensure both perspectives are met in the buying process?

David Raab: You obviously need to ensure all relevant parties are represented and, crucially, engaged on the buying team. It's easy to hand it over to IT, thinking they're the software experts, or to procurement. Marketers might write down requirements for an analyst, who then interviews them and gets it perhaps 80% right. The IT people might understand 80% of what the analyst compiled. So, if you're lucky, the resulting requirements will be only about 50% accurate.

You absolutely must have marketers and other business users involved to ensure the requirements genuinely reflect their short- and long-term priorities. Everyone is busy, especially marketers. If they don't believe they need to be involved, they'll happily skip meetings. This leads to situations where they're disengaged, and you end up with either the wrong tool due to inaccurate requirements, or even the right tool, but users are left confused about its purpose or benefits. Users should be eager to get their hands on the CDP, not dragged into a kickoff meeting where it's the first time they've heard about it.

Vijay Chittoor: That's spot on. In my experience, the most successful buying processes and happiest customers involve both marketers and IT teams truly touching and feeling the product during the buying process. IT teams focus on data loading, API integrations, and identity stitching. Marketers need to ensure it's a tool they can actually work with and build segments without constant IT intervention, supporting the "less IT reliance" value proposition. They also need to validate if the CDP can enable high-value use cases like real-time orchestration. Getting both teams to understand the product at a feature, usability, and functionality level is key.

Blueshift's ROI and New Free CDP Starter Pack

Vijay Chittoor: I see questions coming in, but we have a couple more slides before we open up the Q&A. Please continue posting your questions for David and myself in the Q&A section.

We've discussed how to select a CDP, ensuring successful implementation, and now let's talk more specifically about ROI and value.

Blueshift's Value Proposition and ROI

(Forrester Research data on Blueshift's ROI displayed)

Vijay Chittoor: This is research from Forrester, highlighting Blueshift's value through incremental revenue and cost savings from efficient workflows—both points David mentioned.

The drivers of incremental revenue include:

• AI-based targeting: Smarter targeting leverages AI to determine optimal offers, content, and channels for each customer.
• Real-time interactions: This is a key ROI driver, so I encourage everyone to prioritize it.
• Streamlined work and automation: Provides clear, tangible ROI through cost savings.
• Better cross-channel customer engagement: Also adds significant value.

Blueshift is very proud to deliver such high ROI to our customers. Understanding the levers and drivers of that ROI is crucial.

David Raab: To comment on the streamlined work, automation, and avoided costs: these are efficiency and cost-saving aspects that often more than pay for the system. They are also often easier to estimate than the more abstract "better marketing results." Sometimes, you can build your entire business case purely on these efficiency gains, especially if your organization doesn't fully trust marketing's future revenue estimates from new solutions.

Vijay Chittoor: That's right. Much of the efficiency comes from orchestrating multi-channel campaigns, which traditionally require heavy IT intervention. Reducing IT reliance for building basic elements like dynamic audience segments means non-technical marketers can build segments and targeting directly in the CDP without learning SQL or complex data warehouse operations. This direct access to data is critical for workflow efficiency.

Announcing the Free CDP Starter Pack

Vijay Chittoor: Based on everything we've discussed, it's clear that CDPs are foundational for the transition to cross-channel customer-centricity. It's also clear that buyers often perceive the buying process and technical implementation as complex.

That's why I'm excited to announce today our Free CDP Starter Pack!

This pack enables you to:

• Load data from cloud data warehouses.
• Ingest event data streams.
• Unify this data into single customer profiles (supporting up to 10,000 unified profiles in the free version).
• Start realizing value immediately through audience activation and one-to-one journeys.
• Orchestrate across various marketing, advertising, and customer experience destinations.
• All of this can be done by non-technical marketers using a self-serve interface to create segments and orchestrate campaigns without needing to learn SQL.

This Free CDP Starter Pack is available starting today. I encourage everyone in the audience to try it out and experience it for yourselves.

Q&A Session

Vijay Chittoor: With that, I'll stop sharing the presentation, and we'll take some questions from the audience.

Question 1: CDP Positioning and Use Cases Audience Member: Organizations mostly approach CDPs with just one or two use cases in mind, and cost is an important selection factor. Against those limited use cases, the perceived value is limited, hence cost becomes very important. As consultants/advisors, it's important to provoke more mature use cases and help organizations choose a more value-rich CDP. How does Blueshift position itself in this ever-growing pool, and how do you advise on use cases?

Vijay Chittoor: I'll address the Blueshift piece first. From day one, we've focused on high-value use cases around real-time interactions and cross-channel orchestration. As our ROI analysis shows, this drives significant incremental revenue and workflow efficiency, all measurable within the platform.

Our differentiation stems from:

1. True Data Unification: We unify relational data with event stream data in a self-serve manner, a challenge for many CDPs. This rich data modeling is foundational.
2. AI-Powered Decisioning: Our AI accelerates decision-making, which is an efficiency benefit and significantly boosts ROI (AI-powered targeting was our biggest ROI driver).
3. Comprehensive Channel Connectivity: We connect to every channel, not just for audience activation (like paid media), but also by supporting real-time APIs and triggered workflows in a marketer-friendly way.

This combination of intelligence and orchestration drives real value.

David Raab: This is an excellent question because it highlights that there are "use cases" and then there are value-driving "use cases." The use cases you deploy first in the "crawl" stage are simple. However, these are not the use cases you should use to select your system. You must ensure the system can support the advanced use cases you'll pursue in the "run" stage.

During your planning and requirements definition, look at the broad scope of sophisticated, cross-department, cross-channel use cases that will generate the most long-term ROI, even if you won't implement them immediately. Document these. While you'll start with simpler deployments, you cannot lose sight of the bigger picture. For example, build a data model that supports future needs. We often see companies redesign their data models post-deployment because they initially only supported limited use cases. It's crucial for consultants or project leads to take this broad view of mature use cases, even if they aren't deployed first.

Question 2: CDP Differences: Financial Services/B2B vs. Retail/B2C Audience Member: What should you consider if you're in a financial services/B2B environment versus retail/B2C when selecting a CDP?

David Raab: This is a great question because these environments are very different.

• Financial Services & B2B: You have diverse user types beyond just marketers, including sales teams, field forces, branches, and agents. These groups use different subsets of system functions. Data models are typically more complicated for various reasons.
• Retail: This was one of the first industries to adopt CDPs wholeheartedly, partly because data models are relatively simpler. Products might be numerous, but their structure is consistent. While you deal with physical stores, you lack the complexity of, say, a branch network of agents. Retail often has higher transaction volumes, introducing other complexities.

Ultimately, it comes down to understanding your specific requirements and ensuring the system meets your needs. Look for vendors with experience in your industry, whether specialists or those with a broad portfolio including your sector. This familiarity can provide a head start.

Vijay Chittoor: To add to David's points, let's start with what's similar across financial services/B2B and retail/B2C. Today, the customer journey is fragmented into many touchpoints across all business types. For a bank, you have in-person interactions, call centers (data going to different stores), mobile apps, and marketing websites—all generating siloed data. The same applies to B2C, with non-logged-in digital, logged-in digital, and physical store interactions.

Where they differ might be transaction velocity. Retail/B2C often sees high-velocity transactions for smaller items. Financial institutions typically have a more considered purchase cycle, but there are many valuable micro-transactions. For instance, opening a deposit account isn't the end; increasing net new assets monthly is another journey. This perspective reveals more similarities with retail.

Nuances exist: B2B/financial institutions might have fewer SKUs and place more importance on data modeling around accounts or households (though retail is also starting to group profiles into smaller households). But the commonalities are extensive. We encourage you to check out our case studies for both retail and financial institutions on blueshift.com.

Question 3: Testing Free Tier CDP Value for E-commerce PMs Audience Member: As a product manager in e-commerce, how can they test the value of the free tier CDP given data silos and needing IT for data connection?

Vijay Chittoor: The good news is that our free tier CDP provides access to multiple ways of ingesting data, including APIs and relational databases like Snowflake. You can set up recurring data ingestion. This makes it easier to break down data silos. Equally important, you can break down experience silos by unifying audience destinations and one-to-one destinations. It should be viable to easily validate all of this. We have several compelling use cases that demonstrate value very quickly, often within 15 minutes. I'm also happy to be available as a resource if anyone wants more information. My email is vijaybj@blueshift.com.

Conclusion and Farewell

Vijay Chittoor: We've run out of time for more questions, but I encourage everyone to reach out to myself or David on a one-to-one basis. We'd love to continue this important dialogue. Every brand needs to transition from a channel-centric to a customer-centric mindset, and it's great to see such engagement around CDPs. David, thank you for sharing your insights and the CDP Institute's perspective with our audience.

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

Joan: Thank you, everyone. That's a wrap. We will send the on-demand version of the webinar for you to share with friends and colleagues, along with a PDF of the deck, which will include David and Vijay's contact information for follow-up questions. Thanks everyone for joining. Bye-bye!