Real time awareness cultivated from big data flowing in from the Web and then married to off-line brick and mortar data will bring retailers closer to their customers.
In another case, a call center agent in a bank advised a customer to pursue getting a home equity loan for a building project - when the customer had already been turned down for a similar loan by the bank's lending department.
Welcome to the world of "disconnects" that retailers face at the same time that their customers expect them to be fully cognizant of every interaction they have ever had with the company. Retailers have a word for understanding customer expectations. They call it "omnichannel" because it represent a 360-degree understanding of each customer, based on every single channel (e.g., e-commerce, brick and mortar, etc.) through which the customer has ever done business with the company.
The pursuit of "omnichannel" awareness of every customer is challenging retailers and the financial services industry - because most enterprises have disparate systems in their call centers, e-commerce, and brick and mortar channels that don't talk to each other. On top of this, there is little "big data" intelligence coming in from the Web on customers, their purchases and their buying habits - which retailers ideally want in real time.
X+1 is a cloud services company that entered into this space in 1999-2000, with an initial goal of focusing its solutions on what it calls "data-driven marketing decisions."
"What we focus on is a digital market hub,' said Leon Zemel, x+1's Chief Analytics Officer. In other words, we gather information from any channel that carries real time customer data."
Of course, Web-based data analytics in itself isn't enough to get companies to an "omnichannel" understanding of their customers - because these customers still also patronize brick and mortar stores.To include brick and mortar customer information, x+1 obtains offline files from its clients' systems, and then blends data from these files with what has been gathered about customers online. End goals for retailers are to not only get the traditional demographics about customers (e.g., where they live, what their ages are, etc.), but to also deduce psychographic information about customers that can tell a retailer more about what customers are likely to buy next. Omnichannel customer information can also be grouped through analytics into profiles of customers with similar buying patterns. This allows companies to better pinpoint products and promotions to more highly defined customer buying segments.
Retailers are building out their big data analytics staffs to include statisticians, programmers, and other skillsets, so they can better capitalize on big data analytics. In the meantime, they can lean on cloud services companies that already have the big data science teams and methods in place.
Equally important for retailers is being able to take action on big data as it flows in about consumers from the Web so they can anticipate what consumers are going to buy at any given moment. "We can tell a retailer that a client has just gone to its Website looking for information about a specific item, and this information can automatically trigger a process that pings the customer with an email about the item," said Zemel. "We can even ping the call center."
Real time awareness cultivated from big data flowing in from the Web and then married to off-line brick and mortar data will definitely bring retailers closer to their customers - and will avert embarrassing episodes like trying to pitch a loan in the call center to someone who's already been refused that loan at a brick and mortar branch.
Most importantly, we are now seeing solid use cases emerge for companies that are able to successfully merge big data with traditional data from their internal systems of record for new insights into consumer behavior.