Big Data for Multiple Touches, Multiple Sales
Customer interactions today are no longer relegated to one-touch passes. Companies have numerous touch-points and are constantly looking for add-on sale opportunities. Car dealerships don’t stop at selling a car–they sell additional warranty, service contracts, insurance and accessories. Customers too expect one-stop shopping. In times past if you sold someone telephone service, you sold them telephone service. If you sold someone a bed, you sold them a bed. Those days are gone.
Nowadays, if you’re selling someone telephone service, you’re probably trying to sell them Internet access and entertainment services as well. And those entertainment services may include everything from on-demand movies to multiple sports subscription packages. And if you’re selling someone a bed, you may also be selling them an armoire, a chest of drawers and two lamps.
The fact is that engagements with customers are expanding. This is because:
1) Customers are an extremely valuable business asset—so businesses have learned that they can grow revenue and profits by selling additional goods to their existing customer base.
2) Customers are looking to deal with fewer vendors who know them better—and can deliver a better experience at a lower price—than a higher number of vendors who don’t know them very well at all.
This helps explain why big data is becoming such a critical discipline. Companies need a broader, deeper understanding of their customers, their markets, and the wider world in which those customers and markets exist because both companies and customers desire broader, deeper engagements with each other. And this broader, deeper understanding is exactly what big data offers.
IT leaders involved in the adoption of big data disciplines need to be especially clear on this point. It’s easy to make the mistake of thinking that we need to capture and analyze big data simply “because it’s there.” There is, after all, more data available to us than ever—from public sources, from social media, from device telemetry, etc. And somewhere in all that noise there are certainly signals that will be useful for our businesses.
But if big data is driven as a technology exercise, it is much more likely to fail—if it even gets off the ground very far at all. Instead, we need to understand the business case for big data and focus our efforts on concrete objectives that have clear potential to move the needle on some specific aspect of business performance—such as sales efficiency, market-driven product development, or competitively differentiated customer satisfaction.
In other words, it’s not enough to ask, “What technologies are we going to use to capture, store, rationalize, analyze and distribute big data?” It’s also essential to ask, “What positive transformations do we want to achieve in our engagements with our customers?” Or, better yet, “What do we want to discover about the positive transformations our customers want in our engagements with them?”
To truly transform customer engagements, businesses must invest in applications that manage and extract insights from their large volumes of highly heterogeneous data—including their unstructured text. Big data enables companies to dive deeper into customer needs for multiple touches and multiple sales. Before venturing off on big data initiatives, however, companies must have a clear vision of how big data relates to their business, their processes and their customers. How are you transforming your customer engagements with big data?