Back when there were a handful of channels, interactions between customers and brands were relatively simple. Today, by contrast, more than half of all customers move through three or more channels to complete a single task.

“We have a treasure trove of data—it’s highly valuable.”

To open a bank account today, for instance, a typical customer embarks on a multichannel journey: researching online, downloading an application

speaking to a call center agent, linking brokerage accounts, visiting a branch, and installing the bank’s mobile app. Those steps leave a long and complex digital trail. That multi channel complexity, combined with the scale of the data, U.S. companies store at least 150 terabytes of it, makes divining insights into customer behaviors a serious challenge.

Parsing this data, however, is critical to improving the customer experience and growing your business. In our view, the most productive way to get there is not by fixing individual touch points but by improving the entire customer journey. So not just marketing to potential customers but using the data to improve the customer experience. Analysing the drop off points in the customer experience can lead to better retention and loyalty. When a customer can not find and answer or has too many blocks in the road these need to be removed, but first they have to be identified.

To put big data to work in improving the customer journeys, companies should keep three things in mind:

1. Focus on the top journeys.

Companies may feel they need to study all the bits and bytes available to them. Our analysis across industries shows, however, that three to five journeys matter most to customers and the bottom line. They generally include some combination of sales and onboarding; narrowing the focus to those journeys allows companies to cut through the data clutter and prioritize.

For instance, a cable television player used advanced data analysis of multichannel customer behaviors to focus on where drop offs in the journey occurred in two journeys—onboarding and problem resolution—to address nagging customer retention and loyalty issues. The data team helped them identify key service troublespots and ways to improve the onboarding process. Those insights

Companies often hesitate to take action for fear their data is missing or a mess. In our experience, however, successful organizations tend not to overthink all the details and instead just roll up sleeves and get to work. Most companies, in fact, already have the data they need. The challenge is pulling the data together.

“If we can unlock the value of all our data, we will have a wholly new revenue stream.”

2. Figure Out Where Data is Stored

Companies need to figure out where that data is stored, and what it takes to extract and aggregate it so they can understand the customer journey across multiple touch points. Since data often lives in systems managed by various functions, bring the necessary operations, IT, in-store sales, and marketing people together to identify the touchpoints. Track performance from the outset, mistakes and all, since that experience helps teams test, refine, and learn and ultimately accelerate the benefits.

“Hedge funds will love our data—they will buy practically any set of data that might give them a potential edge.”

3. Focus on analytics, not reporting.

Companies tend to focus on generating reports from their data about what has happened. Much greater value, however, comes from analyzing data to pinpoint cause and effect and make predictions.

Big data harbors big opportunities to improve customer journeys and value. What it requires is a commitment to focus on what really matters.

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