Customer Data


Wrangling Big Data: When in Doubt, Think Like a Customer

As businesses gain a new appreciation of the power of data, they’re discovering new tactics for sales and marketing that go far beyond what was possible in the past. It’s not just big data and a technology-driven revolution — it’s also a shift in attitudes about data’s place in the selling process, its role as a guide or as a reality check, and its ability to fuel new processes that drive greater sales performance.

However, it’s important to keep in mind the customer’s perception of how data is being used. Otherwise, all the data-based changes you make could be worse for your business than distracting shiny objects — they could be genuine customer turnoffs.

Those turnoffs result from a failure to think like a customer. They’re usually not based on privacy issues; they’re more often the result of how businesses use data. Businesses are getting creative about how they use data types in conjunction with each other, and that’s a good thing. Still, focusing too much on customer data, strangely enough, can cause businesses to lose sight of the customer.

Babies and Lawnmowers

A highly publicized example of this occurred when a pregnant teen was inadvertently outed to her family by Target’s data analysis.

Target’s data scientists were allowed a fleeting moment to speak to reporters about their methodologies.

The company had done an outstanding job of drawing conclusions about customers based on their recent purchases — for pregnant women, unscented lotions, cotton balls and vitamin supplements, primarily.

Then Target stopped thinking like a customer. Some women are not overjoyed to be pregnant, or they have chosen not to make their pregnancy common knowledge. Marketing directly to them with baby-related offers can result in unexpected blowback.

Target got smart and began filling its target mailers to expectant moms with baby-related ads intermingled with ads for lawnmowers, food, DVDs and other non-baby products. The company would reach the right audience with targeted promotions, but its mailers would be less likely to arouse customers’ suspicions that Target was spying on them.

Target started thinking like a customer — and not just its idea of the ideal customer, who was happy and enthusiastic about spending money, but on customers in different emotional states. It also helped keep Target’s customers focused on the products it was selling, instead of thinking about how they were being monitored by Target’s analytics.

Every Online Step You Take

Another tool businesses can use to do exactly the right thing from a sales and marketing perspective — and exactly the wrong thing from a customer perspective — is website visitor tracking.

Contacting a visitor quickly after a website visit is critical to turning them into a lead, statistics have shown.

Firms that tried to contact potential customers within an hour of receiving a query were nearly seven times more likely to qualify the lead as those that tried to contact the customer even an hour later, according to a study that first appeared in the Harvard Business Review. The firms that struck within an hour were more than 60 times more likely to qualify a lead than companies that waited 24 hours or longer.

Making a rapid response is great if the potential lead has filled out and submitted a form. However, with the growing use of anonymous visitor tracking and alerting, it’s possible for a business to send a speedy response in the absence of a cue from the prospect. Prospects who receive that kind of phone call or email often get the uncomfortable feeling that someone has been looking over their shoulder during their website visit.

You can see how this might play out in the context of a lead-scoring system. A lead nearing the qualification threshold tips past the qualifying score during a Web visit; an alert is sent to sales pointing out a new qualified lead; a sales rep calls while the prospect is still looking at the website. Some prospects may be OK with this — others may be creeped out.

Try to See It Their Way

I’ve long argued for the careful use of insights gleaned from analysis, and thinking like a customer should illustrate why: It’s one thing to offer a business information about yourself and then see that business use the information in the selling process.

It’s another thing to have the business use information you have not volunteered — and can’t even guess how it was obtained. That can be somewhat unsettling, and in a world where trust is becoming a critical part of how buyers evaluate sellers, it’s a terrible emotional ingredient to add to the relationship you’re trying to build.

You don’t have to tip off buyers to all the information you discover or infer about them, especially when it could be discomfiting or distracting.

Instead, look at that information from the point of view of the customer: How can your newfound knowledge benefit them, help tailor your marketing and sales approach directly to them, and make your interactions more valuable?

If you stop to consider these things, and take a genuinely customer-centric view of how you employ data, you can avoid the trap of using data in ways that ultimately are counterproductive.

CRM Buyer columnist Chris Bucholtz is content marketing manager for CallidusCloud and a speaker, writer and consultant on topics surrounding buyer-seller relationships. He has been a technology journalist for 17 years, focusing on CRM since 2006. When he's not wearing his business and technology geek hat, he's wearing his airplane geek hat; he's written three books on World War II aviation.

1 Comment

  • Well, I believe that thinking like a customer also requires focus on prices. Because, in these days, if we consider that the vast majority of e-commerce traffic is coming from price comparison engines, consumers are taking a look at multiple retailers in different tabs in their browsers. So, as one of those retailers, companies should be also aware of what their consumers might be seeing at competitors. This can be done by using tools like Prisync that delivers the massive competitive pricing data from the market in an automated and actionable way.

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