Last updated: CDP use cases: From marketing and CRM to the enterprise

CDP use cases: From marketing and CRM to the enterprise

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The popular Gartner Hype Cycle map tracks emerging technologies from introduction (“wow, look at this cool new thing”), their most hyped peak of inflated expectations (“this is going to solve everything!”), to their ultimate reality check –- the trough of disillusionment (“this technology is cool, but doesn’t solve all of my problems”) —  and beyond. 

Customer data platforms reached the peak of expectations in 2017, crested in 2018, and have been slowly sledding down the steep slope of the trough of disillusionment ever since. This happens to every new technology. Some survive, but many don’t. Basically, the tech either evolves and scales with the companies that use it, or fades away because it’s too expensive, hard to use, or some new law or technical change makes it less useful.

So, what about CDPs? Will they break out of the trough and be useful, or will they be another flash-in-the-pan technology? Rather than looking at the CDP against Gartner’s hype cycle, let’s look at the evolution of CDP use cases.

CDP use cases: All for the CMO

Many big software innovations happen in marketing and advertising, mostly due to large budgets held by CMOs.

Marketing remains a focus for CDP uses cases with two primary types:

  • “Systems of insights” focus on data management – data ingestion, transformation, segmentation, and analysis – to make understanding customers easier and more effective.
  • “Systems of engagement” use a real-time profile store to do things like personalize websites and apps, and triggering experiences across channels and systems.

Consumers today are extremely fickle, move at the speed of light, and engage with brands across countless systems that are never seamlessly integrated. To date, no system has effectively combined both marketing CDP types well. Most are aimed at making e-mail campaigns better, customer journeys smarter, or doing better cross-channel measurement.  

There’s reason to believe that many marketing-oriented CDPs will thrive and survive, despite their narrow focus on the CMO.  

Single source of truth: CDPs and CRM use cases

Today, there’s a lot of discussion about delivering personalization beyond marketing into all the touchpoints customers have with a brand. What if CDP use cases could extend into:

  1. Service (make call center and field service more personalized)
  2. Sales (give salespeople a deep view of their contacts and accounts)
  3. Commerce (connect in-store and e-commerce experiences to drive more personalization, leading to more upsell/cross-sell opportunities)

We associate these touchpoints with CRM, of which marketing is a single element. The enlightened view, especially among companies who own a portfolio of CRM-type solutions, is that we’re entering a more advanced era of CDP focused on collection and activation of data from and to every connected endpoint. 

We’re seeing this couched as a “customer golden record,” “single source of truth” or “360-degree view” of the customer, made available to the entire enterprise. This is indeed valuable.

While a diverse set of data coming into the CDP informs a richer understanding of customers, the ability to act across digital touchpoints at scale drives CX success. More personalization keeps customers happy, reducing churn, and helps drive increased loyalty, which increases revenue and overall lifetime value.

CRM is perhaps the old way of thinking about customer experience delivery, and CDP is the technology helping it make the leap into modern times. Every major software player will provision its version of a “customer 360” that aligns with their unique capabilities across the massive CRM category. 

This trend aligns the CMO and their budget with the CIO/CTO, who owns the technology stack. The extent to which they can innovate together to drive revenue through experience delivery at scale will determine the success of this exciting wave of CDP use cases. 

CDPs in the enterprise: Piecing it altogether

So, how does the CRM-oriented data platform evolve? Analysts will tell you that there are two big areas for CDPs to focus on: intelligence and automation.

Although there’s no shortage of clever ML algorithms and AI tools to help companies wring insights from their data, the challenge remains mired in the “garbage in, garbage out” paradigm – clean, unified data is needed to power intelligent insights. What we’re seeing in the CDP use cases for CRM is an amalgamation of highly valuable, yet surface level, data.

An example is the lifetime value score, or LTV. Does this score account for how much this customer buys – and then subsequently returns – products? There are a lot of high LTV customers out there who shop for sport, and may be returning 75% what they purchase, creating a net loss for the business.

Clearly, the missing element is deep, enterprise-level data from financial ledger systems and the supply chain to round out a customer profile. Without populating profiles with truly valuable attributes, you’re stuck at a surface-level understanding of customers, unable to fully leverage machine learning to drive actionable intelligence at scale

Automation is the other piece of the puzzle. Today, we think about automation as a CDP’s ability to trigger customer engagement events: offers at an ATM screen, showing the right product SKU in e-commerce, or moving a customer in real time from one journey to another based on a behavioral or contextual signal. Incredible when it works, but stuck at superficial levels today.

What’s more valuable is when automations start to inform the actual manufacturing process, the delivery of proactive field service, or when a global enterprise uses real-time signals to change prices dynamically. Only ERP can deliver on that.  

C-level alignment, real results

The evolution of CDP from marketing to CRM applications and finally into enterprise systems is not only about what the data connects. It’s also significant because it starts to align people.

Namely, it brings together the CMO and CIO with the CFO, who has a deep interest in understanding how massive technology investments in data management impact the bottom line and produce tangible ROI.  

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