4 Ways Customer Data Platforms Will Change the Way You Look at Marketing
Imagine you’re a telemarketer working your way through a list of cold leads. Every time you reach a live human being, you go into your canned pitch:
“Good morning, Mrs. Smith! I’m calling because I’ve got a great opportunity for you! Did you know that four out of five people in your neighborhood are eligible–”
“–hello? Mrs. Smith? Mrs. Smith?”
This is what we internet marketers are like when we don’t understand our customers, which is why we collect data. But little bits of data, taken out of context, don’t really help us understand our customers very well.
Apparently it’s a big problem. Marketers recognize the need for a single, unified customer view, but it’s out of their reach. Why? According to an analysis by David Raab, at least part of the reason is lack of technical expertise:
Enter the Customer Data Platform (CDP). Identified by Raab in 2013 and added to Gartner’s hype cycle in 2016, CDPs provide a central, unified customer view, ideally in a tool that is manageable by a marketing person without advanced technical skills.
How exactly are CDPs different from other kinds of data collection platforms, and why are the differences important? Read on to find out the four key factors:
- The CDP is the Cure for the Customer Data Gap
- The CDP is the Connective Tissue Between Customer Data Sources
- Customers Expect What a CDP Enables You to Deliver
- Personalization at Scale is the Key to Data Differentiation
1. The CDP is the Cure for the Customer Data Gap
Econsultancy’s survey concludes that digital recognition is central to growth and retention strategies:
Why is this a challenge today? A large part of the reason has to be the fact that most customer data originates in systems that weren’t designed to share it with anything else. The difficulty of getting various systems to talk to each other leads to data silos. To achieve a unified customer view, marketers have a range of possible choices.
Let’s take a look at these options in turn.
- Data Hubs, like Boomi and Jitterbit, allow data to be moved between systems, which is helpful for achieving a unified customer view, but not adequate. Data hubs create redundancy and allow inconsistency. Furthermore, they do nothing to address identity resolution, and they don’t persist historical data. They are more useful for cross-system processes than a single customer view.
- Data Warehouses, which store all data in a central database, are a big step in the right direction. But EDWs are mostly for analysis and don’t support real-time updates or access. They are typically big corporate IT projects that take years if they ever get done.
- Marketing Clouds and Suites, like Adobe Marketing Cloud, combine customer-facing systems in a single system with a unified database. In theory, this sounds great, but the reality is that such systems are built from acquisitions and are very lightly unified, perhaps providing a table to link identifiers and some very skinny profiles, e.g. for personalization. They don’t allow easy analysis or real-time access across systems, and they don’t play well with external systems, which spells trouble for marketers who want to integrate data from multiple systems.
Marketers who are already using multiple systems to collect data, i.e. most marketers, need to unify the data they are already collecting into a single persistent and robust customer view. A system that is actually designed to do this is a CDP.
2. The CDP is the Connective Tissue Between Customer Data Sources
Of course, many systems that are not CDPs collect detailed tracking data on customer behavior. An example is the Data Management Platform, which tracks cookie data on the web in order to build up advertising profiles. The major difference between a DMP and a CDP is anonymous vs. identified profiles. Cookies are anonymous, and DMPs (unless they are a CDP by another name) store only anonymous data by design.
Without personal identifiers, there’s no way to link data from one source (e.g. the web) with data from other sources. Hence DMPs do not make it possible to obtain a single customer view.
More than this, customers expect you to be able to identify them.
3. Customers Expect What a CDP Enables You to Deliver
Consumers consistently say that they want more personalization in their online and offline shopping experiences, and 49% say they buy more from companies who provide personalized ads. This desire for personalized service is not confined to retail—it is a reflection of rising customer expectations for service across every industry. As Raab says, “today’s customers simply assume that your company knows – and remembers – who they are, what they’ve done, and what they want, at all times and across all channels.”
Of course there’s another side to this. Everyone nowadays has had the experience of “creepy retargeting”—the unwelcome sensation that either the ads popping up wherever you go are a little too perfect, or conversely, that an ad for a particular product keeps popping up everywhere long after you’ve already decided you’re not interested. But in can be argued that creepy retargeting is just dumb retargeting. A company that injects its ads intrusively into the customer experience is a company that doesn’t understand its customer well enough.
There’s no such thing as understanding your customers too well, or being too smart about personalization. And a company that employs a CDP is a company that can deliver smart personalization at scale. A recent Harvard Business Review article pegged CDPs as a key component of this long-anticipated goal:
4. Personalization at Scale is the Key to Data Differentiation
Mark Andreessen memorably said “software is eating the world,” but it might be more accurate to say that data is eating the world. As Stephen O’Grady pointed out and I discussed at more length in an earlier post, software is no longer a robust differentiator among technology companies, if it ever was. Software is cheap, readily available and easily duplicable, whereas data sets are hard to build, hard to get and virtually impossible to copy.
O’Grady’s example of data differentiation in action is Google Maps vs. Apple Maps on iOS. The thing that differentiates the experience of using Google Maps from the experience of using Apple Maps is not the software design per se. The software design is not what causes Google Maps to send you safely to your destination and Apple Maps to drive you into a lake. The difference is the gigantic, detailed body of data Google has to draw from in Google Maps, data they had been collecting from Maps users for years before Apple Maps ever came out. Since they will continue to collect data and refine their product based on user experience, forever, it will be very difficult for Apple Maps to ever catch up.
We call the Googles and AirBnBs Data Giants because of this differentiating factor, which O’Grady calls a Data Moat. But as the Maps example highlights, it’s not simply the sheer amount of data they own that differentiates the Data Giants, it’s what they do with it. The Data Giants use unified, rich data to provide a hyperpersonalized experience for their customers. And they do it at scale.
Customer data platform software can help differentiate your business by giving shape and meaning to the data you collect. Another way to put it is that connected data you use to improve customer experience, to automate and personalize marketing processes, and to align your teams on these goals, is Live Data. Data that is disconnected, stale, and inaccessible to your teams, is useless.
Fortunately, more Customer Data Platforms are becoming available each day. They all have different approaches to managing and accessing your customer data, so as always it’s worth doing your homework. A good place to start is the Customer Data Platform Institute. If you’d like to explore a CDP specifically designed for Live Data Management, by all means take a look at our platform Treasure Data CDP Solution.