While customer data platforms, or CDPs, have been around for a few years, they have recently risen to the top of marketers’ technology wish lists. That’s because of the increasing prominence of the marketing problem CDPs address: As consumers interact with brands across a variety of channels, customer data passes through more channels with lightning frequency and becomes so fragmented that it doesn’t yield the kind of insights one would expect.
The result of this has been an explosion of new CDP vendors entering the market. This growth is good for marketers: it gives them a greater chance of finding a CDP that meets their particular needs. But it also means that marketers must develop an understanding of the options that exist, and of the differences between them, to find the right CDP.
Let’s look at the basic categories of CDPs and the pain points they are best equipped to address to help set your brand on the right path.
All CDPs are equipped to build and share a unified customer database — this is their baseline objective. Some CDPs are simple data-only systems. You might want one of those if your company is primarily dealing with any of the following challenges:
Did you know the average enterprise marketing department uses nearly 100 cloud services? That can lead to data ingestion overload. If you are dealing with ingestion overload, then you should seek out a CDP that specializes in connecting as many systems as possible. This will reduce the need for your company to build connectors of its own.
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The need to handle unexpected or novel data
When it comes to handling streams of customer data, it is usually a good rule of thumb to expect the unexpected. It is fairly common for new kinds of data — new event types or product attributes — to appear without warning in your regular customer data streams.
CDPs that focus on building and connecting data are equipped to capture this data, regardless of format, and later allow marketers to define and extract relevant portions. Data-focused CDPs help ensure that important, relevant data isn’t lost, even if it wasn’t necessarily flagged as important when it initially entered the system.
The need for reusable data transformations
Some CDPs specialize in converting raw data into complex derived values, such as lifetime value calculations or predictive model scores. They provide features to let users trace the origins of each element so they know how to apply it properly. This data is then exposed to analytical and marketing applications, saving users the effort of re-creating it while ensuring that everyone is working with consistent and complete information.
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Some CDPs not only build a unified database but also provide integrated analytics, such as segmentation and predictive modeling. You should consider investing in a CDP that offers analytics functionality if the following features would be useful to your organization:
Sharing made easy
Many companies need to share customer data among a variety of internal departments, including marketing, advertising, data science and customer service. This can get complicated, because each department may each have its own unique requirements for formatting, scheduling and transfer mechanisms.
If that sounds familiar, look for CDPs that have features that allow you to define how sharing is handled — from managing delivery to monitoring quality and alerting users in various departments of any problems.
Predictive models for everyone
Predictive models can be incredibly helpful for marketers looking to get ahead of potential customer churn, or to craft personalized customer communications based on customers’ anticipated preferences. Some CDPs that specialize in data and analytics will include standard predictive models that look at things like churn prediction, and offer automated features to tune those models to your brand’s specific needs.
Others will go beyond standard models and will allow marketers to define specific objectives, and then automatically build the models required to meet them, without any additional user input. Consider the complexity of your brand’s data streams to determine what level of sophistication you might need.
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Data, Analytics and Engagement/Targeting CDPs
The most powerful CDPs go beyond building databases and providing analytics tools; they are capable of actually driving and automating targeted customer engagement — they can select the ideal personalized communications for individual customers. Look for this type of CDP if you want to prioritize activities such as these:
Targeted online engagement
If you are looking for a CDP to beef up your ability to send hypertargeted messages to your customer base, look for one with features that allow you to build unified customer profiles, define campaigns, and manage and deliver personalized content. These CDPs can use tags embedded in your brand’s web pages that push real-time visitor information back to the CDP, identifying that visitor and enabling you to send marketing messages based on active campaigns, eligibility rules, current context, model scores and more.
Customer lifecycle management
CDPs that incorporate customer engagement capabilities can provide a framework for tracking customers as they move through different lifecycle stages, and to select messages at each stage that are proven to maximize progress toward desired goals. This requires data from operational and marketing systems to support persistent customer identity, segmentation to define lifecycle stages, tracking of sent messages and analysis of long-term results. Some CDPs can even identify opportunities for improvement and recommend ways to optimize campaigns.
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The First Step Toward Finding Your CDP Match
Of course, knowing which CDPs meet the general criteria to address your specific needs is only the beginning of the process. The broad categories of data, analytics and engagement don’t reveal important differences among vendor offerings that fall within those categories. But identifying which broad category of CDP will be most beneficial to your business is an important first step to take before diving into deeper research.