Customers today produce a huge volume of data throughout all the touchpoints that occur as they interact with a brand’s various channels and many brands are working to corral and use that data. Gartner’s 2019 Marketing Technology Survey indicated that 43% of businesses polled currently have a fully-deployed customer data platform (CDP) and 31% are working to implement one. The CDP Institute defines a CDP as “packaged software that creates a persistent, unified customer database that is accessible to other systems,” but it’s actually much more than that.
As Gartner’s recent report, the Market Guide for Customer Data Platforms defines it, a CDP should be effective at “centralizing data collection, unifying customer profiles from disparate sources, creating and managing segments, and activating those segments in priority channels.” For those brands who seek to create an exceptional customer experience across all channels, a CDP is a must-have addition to its martech stack. This article will look at the ways a CDP can be used to gain a better understanding of the customer, and will provide a close look at the functionality and benefits that a CDP provides.
A CDP Creates More Precise Customer Segmentation
A CDP not only facilitates the creation of customer segments, it goes further than that and enables the hyper-segmentation of customers. It allows a brand to target specific groups of customers, and also enables the brand to exclude or suppress specific groups of customers who, for instance, are not likely to be interested in what the brand is offering.
Cory Munchbach, COO at BlueConic, a CDP provider, shared her thoughts on how a CDP provides value to brands through segmentation. “Segmentation is a great example of how marketing technology could be evaluated and used much more effectively. When marketers lack access to unified and actionable first-party customer data, it creates barriers in the form of time delays, inflexibility, and/or cost. For instance, marketers often have to wait on IT, analytics, or data science teams — or pay a hefty price to an external agency — to query data for segmentation. Moreover, they often end up sacrificing the sophistication of segmentation requests in favor of speed of delivery, cost savings, both, or, even worse, they just don’t do it at all. CDPs reduce these dependencies by enabling marketers to build their own multi-dimensional segments.”
A report from Adobe on the consumer demand for personalized content indicated that 67% of those polled said it’s important for brands to automatically adjust content based on their current context, and 66% of those polled said that if a brand annoys them with irrelevant content, they will cease to do business with the brand. Not only is it important to provide personalized content, it must be presented based on the customers’ current state. A CDP enables a brand to adjust its marketing efforts to the current context of its customers through customer segmentation and real-time decisioning.
Related Article: When Customers Control Their Data
The CDP Eases the Burden of Omnichannel Data
The customer today typically interacts with a brand in a variety of channels, including the brand’s website, app, social presence, email, text, chat and brick-and-mortar storefront, as well as via their mobile device, customer service interactions, surveys, feedback and reviews. This creates an exponentially growing amount of data. By aggregating, unifying and analyzing this data, a CDP is able to provide actionable insights that can be passed on to another part of the martech stack, which is then able to create the next best step in the customer journey, all in real-time. The “single person profile” that is crafted by the CDP facilitates the creation of a hyper-personalized, emotionally positive connection with a customer.
David Raab, founder of the CDP Institute, told CMSWire that a CDP would produce a single person profile that is omnichannel. “In theory, the complete profile would include all ad impressions, web behaviors, purchases, customer service interactions, product uses, demographics, and other static attributes. Details depend on the industry — e.g. travel collects different information from health insurance or a restaurant.”
Other details that are often included in a single person profile include customer demographics such as name, address, email, phone number, date of birth and gender, transactional data such as purchases and returns, campaign metrics such as engagement, reach, impressions, behavioral data that comes from a customer’s actions on a website, app, or mobile browser, and customer service data such as live chats, number and length of interactions, frequency, Net Promoter Score and other voice of the customer data.
Raab’s CDP Institute states that “the CDP creates a comprehensive view of each customer by capturing data from multiple systems, linking information related to the same customer, and storing the information to track behavior over time. The CDP contains personal identifiers used to target marketing messages and track individual-level marketing results.” This is what is meant by a “single person profile,” meaning that a profile is created for each customer based on data that is collected from across all channels and touchpoints in the customer journey.
The Adobe report also indicated that customers are becoming used to interacting with a brand across multiple channels. According to the report, 48% of customers will visit a brand’s website to research a product, and 37% of teens and 27% of millennials will use video channels to do their research. Of those polled, 59% use online marketplaces and 49% will visit a brick-and-mortar store. After making a purchase, 51% will go back to the brand’s website to engage and 58% will use a smartphone while they are in a store to research their purchases. A consistently positive experience across all channels is vital for customer engagement, emotional connection and loyalty to a brand.
Munchbach explained why a CDP is extremely useful for marketing due to the difficulty of unifying data from multiple channels. “One of the long-standing technology challenges that marketers face is that they have a lot of different tools — particularly in digital marketing — that store data and recognize their customers and prospects in ways that are unique to each system. Marketers have an extremely difficult time stitching the data in those systems together to gain that elusive single person customer profile (often referred to as a single customer view) for activation across the customer lifecycle. With CDP profiles, marketers gain a mechanism to maintain a single repository of information about an individual person,” she said.
A CDP Works in Conjunction With the Martech Stack
A CDP has four primary purposes that make it a must-have addition to the typical martech stack. “All true pure-play CDPs offer four core capabilities, including unified, persistent customer profiles, multi-dimensional segmentation, customer lifecycle orchestration, and predictive modeling and analytics. But a best-in-class CDP stands out for its ability to flex in all the ways a modern, growth-focused organization needs it to — namely in its speed, adaptability, value and utility to business users,” said Munchbach.
Many marketing teams consider the CDP to be the core of the martech stack, rather than an addition to it. Since much of the data in the martech stack’s databases is siloed, a CDP is used to unify all the data in one database. This data is all linked by the CDP to a unique identifier for each customer.
The CDP can also enhance the effectiveness of a CRM, facilitating a more informed relationship with the customer by providing a comprehensive view of customers and prospects, and their specific interests and preferred channels.
“Interoperable and system-agnostic by design, a CDP can work in the context of almost any martech stack,” Munchbach stated. “Instead of spending 300 request for proposal (RFP) questions across 6 vendors to assess feature parity, marketers should be describing what they are trying to accomplish, why it’s challenging today, and why it matters, so that vendors can then explain how their solution (features) will deliver the desired outcome (benefit). This kind of approach will also make answering the question, ‘Should I replace my digital management platform (DMP)/CRM/master data management (MDM)/data lake/campaign management/analytics/reporting solution with a CDP?’ much easier — both in terms of making a case for the replacement or simply explaining why you may choose to keep two systems with ostensibly similar features, which also will set the foundation for how the CDP will fit into the stack. Indeed, this is less of a technical question and more of a workflow and process question.”
As Munchbach suggests, it’s vital to understand why a brand would need a CDP vs. just using the DMP or CRM that has been working in the past. She provided an example that clearly illustrates such a question. If a publisher has a data science environment and they want to use profile data that is largely collected by the CDP on the website, to create an engagement score, how should they go about it. Should they do that work in their data warehouse or within in their CDP? “Typically, the team would assess technical features relative to this problem: which platform has more processing power, for instance, or can store more data types? But the assessment should be about why this score needs to be calculated at all. Is it for analytics or for activation? How long does it take for the calculation, given the exchange of the data back and forth? The data that originates in the CDP also needs to get back to the CDP in order to change the web personalization that the score is applied to, which means it’s 24 hours old by the time it’s used and the reader has long since departed — or visited the site half a dozen more times. Suddenly, it’s a huge benefit to do the scoring in the CDP and collapse the time between data collection, score calculation and onsite activation — from a day or more to milliseconds.”
A Data Strategy and Use Cases Determine CDP Requirements
Loosely defined, a data strategy is a plan for how a brand will collect, store, manage, share and utilize the data that is generated through the customer journey. An effective data strategy provides details on what data is collected, how it is captured and converted into a form that can be used, how it is shared across the business, and how actionable insights can be obtained from it.
A data strategy should be created with the overall goal of enabling the CDP to effectively access and use the data that is produced through the various channels from which it is collected. This is accomplished by integrating data as much as possible, eliminating data silos, streamlining data collection, making the data consistent through all channels, and having a clear data governance policy.
While a data strategy can help brands understand the way its data is managed, Munchbach believes that case uses are even more important. “Data collection can introduce new information, but it won’t result in smarter engagement or better outcomes if it’s not managed correctly. More important than a data strategy, arguably, is the development of thorough use cases,” Muchbach said. She goes on to warn that before implementing a CDP, business users should consider what answers they need from the data, what use cases are driving the need, what capacity their data resources have, and if it can be managed in a risk-mitigating way.
Raab added that use cases can be a valuable method of gaining a better understanding of goals. He points out that goal definition is critical to understand the requirements for your systems, so you can build or buy the right pieces. “Most companies are not very good at this, especially in marketing, where it’s hard to know in advance what kinds of programs you will need to execute or which programs will be most effective. The particular things companies need to do better are to come up with example “use cases” that they want to execute, define the specific requirements implied by those use cases, and determine which systems can actually meet those requirements,” he said.
A CDP Facilitates Real-Time Personalization and Decisioning
Personalization is not just a nice extra feature for today’s customers, it’s something that customers expect when they interact with a brand. A report from Epsilon indicated that 80% of customers are more likely to make a purchase when businesses provide a personalized experience. The customer journey is vastly improved when it is personalized specifically for each customer, and that is precisely what a CDP enables.
Experiences with tech giants such as Amazon, Netflix and Starbucks have raised expectations to the point where customers demand to be treated as individuals, with relevant content and offers that appeal to them personally, based on their past interactions with a brand. For those brands that fail to deliver, they stand to lose customers. A Gartner survey on marketing personalization indicated that brands can lose 38% of customers that have experienced poor personalization practices.
Raab told CMSWire that a CDP is able to create a hyper-personalized experience by “assembling detailed data and making it accessible in real-time. Depending on the system, it could simply provide profile data for a personalization system to process, or run models and algorithms to pick the personalized messages themselves.”
Because a CDP uses first-party data — that is, data that comes from customers that have purchased from or opted-in to a brand, a holistic view of each customer is created based on their preferences, past history and current real-time behavior. It is through the use of such holistic customer profiles and real-time data activation that Adobe’s RealTime CDP provides prebuilt APIs that enable brands to deliver personalized experiences to customers.
Additionally, there are tools that work in conjunction with CDPs to provide the real-time data activation that delivers omnichannel hyper-personalization. According to Oz Etzioni, CEO at Clinch, as first-party data becomes the norm, brands will struggle with activating the data. “As the industry moves closer to a cookieless reality, first-party data is more valuable than ever, as are platforms like CDPs whose job is to collect, manage and optimize that data. Yet most marketers are still scratching their heads when it comes to actually activating their data. Brands know they need more of it, but for many, there is a massive knowledge gap regarding how to put their first party data to work to deliver insights that drive positive business outcomes,” he said.
A CDP is a must-have tool in the martech stack. The CDP creates much more precise segmentation, eases the burden of omnichannel data, facilitates real-time personalization and decisioning, while creating single person profiles for each customer throughout their journey, including real-time data from the customer’s current session. By assessing a brand’s needs and goals, creating a data strategy and case uses, a brand can determine the features of a CDP that will suit its needs and increase its ROI.