How to ensure the success of your CDP initiative
Before you engage with a CDP vendor, performing some due diligence upfront will make the evaluation process less painful.
Vendors, analysts, and industry trades have heralded the Customer Data Platform (CDP) as a panacea for the seemingly impossible task of collecting and unifying data from disparate, unconnected online and offline data sources to form a comprehensive 360-degree view of the customer across devices and channels.
And marketers are jumping in with their pocketbooks. Statista research from March of this year indicates that CDP industry revenue worldwide for 2021 was approximately $1.6 billion, reflecting a 23% increase over the previous year. And that doesn’t include the costs for building and maintaining in-house bespoke solutions.
While the pandemic has accelerated digital adoption and activation in many organizations (for example, according to Statista, in 2021, e-commerce accounted for about 20% of global retail sales), before jumping into the CDP pool feet first, step away from the checkbook, and consider some things.
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The omnipresent consumer
We’ve all been told that omnichannel experiences are the epitome of modern marketing. If you’re not creating omnichannel experiences — using as many channels as you can to reach and connect with your customers — your business is going the way of the dinosaur.
While it’s true that consumers are rather ubiquitous in their use of devices and channels to conduct their day-to-day, trying to simultaneously use as many channels as possible to connect and convert isn’t realistic, as many marketing organizations have realized. The proven approach is more convergent in its practicality; it’s about creating integrated experiences across your prospects and customers’ preferred channels, a seamless experience encompassing online and offline touchpoints.
CDPs are purpose-built for the structured and unstructured data aggregation required for these integrated experiences to come to life. They provide a way to consume (and enrich) channel-specific data from websites, point-of-sale systems, social platforms, CRMs, mobile and myriad other first through third-party data sources.
I’m sure we agree that collecting and unifying all of that data provides a compelling and potent method of harnessing the power and value of data and using it as a force for good to create integrated experiences. The benefits include, but are not limited to, keeping up with customers moving (and changing) faster than your brand, developing more profound and meaningful relationships with prospects and customers and predicting future behaviors.
However, despite the hype surrounding CDPs, it’s not as simple as signing up for Gmail. I recently spoke with a CMO who wanted to add a CDP to the upcoming budget cycle. “Just tell me when you think we should slot it into our ’22-’23 roadmap and how much it’ll cost.” I wish it were that easy.
Like any marketing technology initiative, adding a CDP to your digital ecosystem will require time, money, people, and a considerable amount of (before, during and after) work. One of the most critical areas of focus before you sign on the dotted line and engage with a CDP vendor or start building your own is understanding your data from every possible angle.
Data quality is your friend
Garbage in, garbage out is an adage with a lot of truth. My uncle was a sanitation worker, and he used the phrase a lot, but we’re talking about data quality in this case. “Data quality” can have many meanings. For our discussion, let’s define data quality as “…the state of qualitative or quantitative values and its fitness for intended uses in operations, decision making and planning.”
IBM research indicated that bad data costs the U.S. economy around $3.1 trillion yearly. Experian also found that bad data directly impacts the bottom line of almost 90% of American companies, with the average company losing over 10% of total revenue. Let’s face it. The chances of your data being grungy or downright junk in its present state are pretty good. And I’m not judging — I promise. We’re all pretty much in the same boat at one point or another.
That’s why part of your CDP implementation budget will focus on proactively cleaning and standardizing your data mess and making the data fit for purpose to enable CDP integration, use cases, automation, machine learning, analytics, privacy and so much more.
It’s not about you
The CDP is a marketing tool. But the monetization of data – and there’s no shortage of it – through employing it to understand your customer’s attitudes, needs, buying preferences, behaviors and more is everyone’s obligation.
The consolidation of data silos from across the enterprise into a single source is one of the primary goals of the CDP. But getting the plethora of marketing and other data into the hopper is just one part of the equation. It’s also about democratizing the data and turning it into information and insights that everyone in the business can use to reach their intended business, marketing, and, yes, even technology goals. According to Splunk, some 55% of an organization’s data is “dark,” meaning they have no idea it exists – and if they don’t know it exists, it stands to reason they can’t use it.
Empowering the enterprise, not just marketing, to utilize this powerful “magic” through robust data governance and syndication is critical to your CDP investments’ successful activation and realization.
But wait, there’s more
Depending on the goals and scope of your CDP initiative, the care and feeding of your CDP will require more than a positive attitude, unbridled excitement, innovative technology, and clean data. Three specific areas where you’ll need to invest in skilled, experienced people to make your CDP implementation and operation a success are marketing operations (MOps), data operations (DataOps) and development operations (DevOps).
Gartner defines MOps as “…the function of overseeing an organization’s marketing program, campaign planning and annual strategic planning activities. Other responsibilities include technology and performance measurement and reporting and data analytics.”
CIO.com defines DataOps as “…an emerging discipline that brings together DevOps teams with data engineer and data scientist roles to provide the tools, processes and organizational structures to support the data-focused enterprise.”
AWS defines DevOps as “…the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organizations using traditional software development and infrastructure management processes. This speed enables organizations to better serve their customers and compete more effectively in the market.”
The point is there are substantial human costs beyond just the licensing of a commercial CDP or the development of an in-house bespoke platform. As Tony Byrne of Real Story Group says, “The other piece on the cost side is that implementing a CDP often requires collateral work around data availability, cleaning, stewardship, quality control, and identity resolution. We see licensees constantly adding new pipelines, new events, new activations, and new customer interactions. All these needs marketing, data and IT ops to work together.”
Know before you go
Regular reviews are essential to help you unlock the power and ROI of your marketing technology investments. If you haven’t already, perform a detailed assessment of your digital ecosystem, specifically your martech stack. Before you engage with a CDP vendor, performing some due diligence upfront will make the CDP evaluation process less painful, more efficient and significantly improve your chances of success.
One other thing to consider is hiring a guide to help you navigate the growing CDP landscape and choose wisely. The upfront investment in the success of your CDP initiative will more than pay for itself through faster time to market, enhanced time to value and a reduced total cost of ownership.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.