A Customer Data Platform Picks Up Where CRM Leaves Off
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I don’t think there's a single good marketer who doesn’t want to know his or her customers. Most successful marketers strive to understand their customers so they can pick the right channels and the right messages to reach them.
These days, the best way to understand your customers is through data. And through the magic of big data, we no longer need to look at our customers at the aggregate or the segment level. We finally have access to data on individual customers and prospects that we can use to understand them as unique people.
The challenge is that this data is scattered across the organization. It’s in customer relationship management (CRM) systems, email and marketing automation platforms, analytics tools, ecommerce platforms, data management platforms (DMPs), point of service (POS) systems, data warehouses, call center solutions and much more.
Marketers dream of being able to bring all of this data together to create a single picture of each of their customers and prospects. That’s where a customer data platform (CDP) comes in.
Isn’t that the CRM’s job?
You may be thinking, “if I want to create a single record of each person, isn’t that what my CRM is for?” And you wouldn’t be wrong. This is what the CRM system was originally created to do. But today’s CRMs were not built for the requirements of today’s data. They were built in a different era when database structures were simplistic and data volumes much lower. They were not built with the ability to take in, store and interpret behavioral data.
What’s so special about behavioral data? Behavioral data is big data. Behavioral data is complex and messy. And you can collect behavioral data not just for visitors that you recognize, but anonymous visitors as well. Consider how you go through an ecommerce website as a consumer. You may come to the site from a Google search or an online ad and arrive on a product detail page (PDP). You spend some time scrolling through the PDP, looking at reviews, scrolling up and down the page, hovering over certain sections and clicking on particular product images or links. You visit other PDPs. You go to the homepage. You view another category or two. This visit alone generates a massive volume of data -- and each subsequent visit you make generates even more.
Then there are all the attributes associated with your visit. The source of the visit. Your physical location when you visited. The time of day and day of the week of your visit. The duration of the visit. What type of device and browser you used.
Most of this information on its own isn’t too valuable, but together it can create an important and valuable picture of the type of visitor you are and your interests -- products, categories, colors, price ranges, etc. It just needs a system that can capture and interpret all of it.
CRMs were simply not built to store all of this information and interpret what it means about a person, plus they can’t store anything on an anonymous visitor. But a CDP can.
What is a CDP?
You could consider a CDP like a CRM for the digital world. It is a central store of customer and prospect data. It unifies data from disparate systems into one record for each person -- whether anonymous or named -- adds in the deep behavioral data I just described and makes that data actionable.
This last piece about actionability is absolutely essential. It may sound obvious, but consider the reason we want to bring all this data together in the first place -- to do something with it. You want to bring all of your data together in one place so that you can truly understand each person who engages with your company. But all of that data is effectively useless if you aren’t going to actually use it.
To use it, a CDP needs to be able to send that data to other systems. Your marketing automation system, your CRM, or any other system you use should have access to this data.
A CDP should also be able to take certain actions on the data on its own -- and do so in real time -- whether that means triggering a message or personalizing an experience on the web, inside a mobile app, in emails, in digital advertising or through any other channel. A CDP that’s not only a system of record, but also a system of action, can deliver a unique and relevant experience to a person based on all of the data it has amassed.
Customer data platforms and personalization.
Let’s walk through an example. Consider a B2B software company with a long sales cycle and multiple opportunities for cross-selling and upselling. This company has a CRM system that tells the sales team which products a client has purchased as well as details on its interactions with the sales team. The email system tracks which emails have been sent to the client and how each recipient has engaged with those emails. The support system says which tickets the customer has submitted and how they have been resolved.
A CDP can bring all of the data from these systems together, combine it with deep behavioral data on how the prospect or client has engaged with the company’s website and other digital properties over time and how it has engaged with the software application itself. It can also interpret what all of this information means about the customer -- at the personal level and, ideally, at the account level. This information can be used in any number of ways. The sales team can use it to reach out to the right customers for upsells at the most appropriate time. The site experience can be personalized to include tailored content recommendations. The application user experience can be personalized to feature appropriately timed tips or tailored onboarding for new users. The emails that are sent to users can contain relevant content, engaging messaging and offers. The applications of this data are essentially limitless.
The concept of bringing disparate customer data together in one place can seem paralyzing to many businesses. So how do you get to this ideal state I’ve described? There are two main ways to go about it. First, you could solve the immediate problem in front of you: bringing all of your data together. I’ve seen many companies opt to do it this way.
The challenge is that once they have the data, they find that they can’t actually use it. They didn’t build it with action in mind, so they solve half the problem and get stuck there. So the second way -- and the better way -- is to start with the end in mind. Think through how you would use all of this individual customer data if you had access to it and then build or buy a solution that will allow you to accomplish that.
If you’re planning to deliver personalized experiences to any of your customers or prospects, you need to truly understand each person deeply and respond in real-time across channels with tailored customer experiences.