Context: Customer Data's Secret Sauce
Big data and its natural companion -- smart analysis -- are great for understanding trends and general behaviors of customer segments. When it comes time to make the sale, though, you're back to dealing with people. They may be people who come from a specific, targeted segment, but they're people just the same.
01/31/13 5:00 AM PT
I had a call today from someone at a company that made a technology that helped inside sales people target the exact right prospects from a list of leads. She said she was using this technology to make the call, and assured me that this technology could make a big difference to the inside sales organization in my company.
Which is just swell. The problem is that I don't work in sales, let alone inside sales. I don't make decisions about the technology used by this department I don't work in.
Basically, this technology designed to target prospects picked me, an act which would be described by the kids these days as a "fail" (which is short for "failure," if I'm not mistaken).
The hapless caller lacked a couple of things -- the ability to check job titles, the sense to end a call when it was clearly starting to enter a death spiral, etc. The basic thing she lacked, though, was context.
Why was I in the system? (Answer: my name had been harvested from a list of people at a trade show.) What was my job title? What other information about me is available? And, most importantly, does any of this suggest that I'm in sales, or that I'm a decision-maker about sales technology?
Context Is King
Context is the framework on which all your customer data is assembled. It helps you understand the who and the why of that data, and thus provides the real picture of the customer. Context, though, is often poorly cared for in today's technology; we've become so concerned with collecting data that the circumstances in which it was collected can get lost, leading to uses of that information that confound and confuse potential customers.
Even in CRM applications, the context must often be inferred by the contents of the customer record. The beginning of the relationship is well documented, as are sales activities. Spotting events or changes in behavior, however, that alter how the customer views the relationship or which change their buying behavior is not that easy.
Unless you can identify those changes, it's likely you'll continue with the same tactics that have worked in the past. These can be ineffective and even infuriating; the customers expect you to know them and that means you know how information about them fits into their stories.
This one of the perils of the "big data" era. We can get so fixated on collecting and controlling data, and paying attention to the data as an aggregated whole, that it becomes easy to miss a key element that explains why customers are doing things, and which should determine what the company's response should be.
There's Data, and Then There's the Story
At that point, you're back to paying attention to the real story in the data. Doing that still requires a smart person. Technology can help only so much. We're getting closer to technologies that can identify those context-establishing data, but much of this process must be intuitive.
Without context, the data that you think may identify buying behaviors may mislead you and waste your sales staff's time.
I'm thinking about a time when I sent flowers to someone who worked for a sales analytics vendor. The vendor saw that I'd hit their website and clicked around, and it used that information as the impetus for a call from its inside sales team. Imagine the salesman's response when I told them I'd used their website to send flowers, not to research a purchase.
On a bigger scale, specific events that affect a market can change the context of your data. For example, a natural disaster or a market crash could dramatically affect your customers' ability to buy, or to even consider a purchase. Taking such market-changing events into consideration is not going to be done automatically by technology. It has to be done by managers, marketers and sales people.
We talk a lot about having a 360-degree view of the customer. This is a great aspiration, but if you don't know where data fits on the compass, the story you create to explain your customer is going to be incorrect.