Attend any marketing conference today, and you’ll find entire tracks dedicated to data and how it can be used to improve customer experience. There are discussions about profile data and market data, about target data and financial data, about big data and metadata, and so on and so on.
In fact, many look at data as the “Glengarry Leads” of marketing.
Now, is data a helpful tool to run a better business or marketing campaign? Well, certainly. But there also are three common problems with data. Fortunately, though, there are also some simple hacks that you can use to break through the barriers that those problems cause. And here they are.
Problem #1: Silos Everywhere
Any organization, large or small, has useful data. The challenge is that many employees either don’t know how to access the data or how to interpret it. This is both common and problematic for marketers today.
As an example, pretend that you’re a marketer of a health system and tasked with promoting a particular service line. Wouldn’t it be helpful to know what are the most profitable procedures and who the patients are within that service line? You need data to understand their demographics, capacity, market size and more, but rarely does a marketer have access to that data. Is it billing data, patient data, claim data – and who owns the data? Can Bob in IT help me, or should I go to Jane in finance?
The Hack: Integrate, and then innovate
Create a customer journey map and identify every department that interacts with that customer experience. Bring all parties together and ask what underlying data they add to the process that can inform and improve strategy and who owns it.
Prioritize data together to build teamwork and avoid analysis paralysis. Next, overlay the customer map with a data map. This not only will identify areas of opportunity, but also barriers that can be broken through together.
Problem #2: Emotional Void
Having too much data also is problematic. Because, while data might produce a strong prospect or persona “profile,” it can never tell the actual human story. And no matter how many layers of demographic or behavioral data points that you might have access to, the data is still emotionally void.
Let’s say, for example, that your churn rate is showing brand loyalty slipping with a key customer audience. While it might seem wise to dive deep into that specific audience’s demographic data to design improved products or experiences, that is still a risky strategy. Why? Because most consumers make emotional decisions on the very same products and/or services that you seek to sell them.
The Hack: CoCreate with your customers
Move beyond the data and give your customers a seat at the design table. And no, that doesn’t mean relying on surveys, focus groups or other legacy tactics that claim to get at VOC either. If you really want to understand your customers, you should craft custom experiences together.
These CoCreation experiences provide opportunities for companies and consumers to work together beyond data. You’ll discover that the byproduct of CoCreation for your brand’s awareness, loyalty and performance is truly powerful.
Problem #3: Great Expectations
Since every company now has data, the bar is automatically set high today for tracking sales, service and marketing activity. However, while accountability in those regards is understandable, an expectation of instant success is not. Customer loyalty is the goal, but it’s not guaranteed.
For decades, many C-Suite executives have viewed marketing as an expense. Missed expectations do not help that mindset, especially with data now front and center. Similarly, consumers today have their own high expectations of the brands that they decide to do business with.
The Hack: Under-promise and Over-deliver
This is perhaps the easiest, yet most overlooked of our three hacks. It is simple and straightforward, but takes discipline. Why? Because it might require you saying “no” to your boss or customer. It also may force you to educate yourself or others on metrics outside of comfort zones.
C-Level executives may not understand marketing, but they understand a P&L. So use the right data show profitable services, customers and products. Also use data and CoCreation to demonstrate loss leaders that could drive downstream profit over time.
So what other data problems you have encountered and what hacks do you recommend?