Making Big Data Personal
In today’s world of the connected customer, most business-to-business organizations have advanced contact centers. The goal is to ensure that they are ready to handle any inquiry, concern or opportunity to acquire, grow and retain customers. They also understand that with every client-facing interaction, there is the opportunity to deepen the relationship… or drastically harm it.
People call into contact centers for a wide variety of reasons – to buy a product, to inquire on an order, to file a complaint, to ask a question, to get technical support, etc. Of course, the primary goal is to handle the question, but once you have the customer on the phone or in a chat, there is always an opportunity to take additional actions.
The trick is to ensure that any additional action is timely, relevant and appropriate.
For example, if somebody calls in with a complaint, it’s probably not the best time to try to sell them something else. Also, if they haven’t paid their bills for a few months, you probably don’t want to use this as opportunity to upsell their contract, product, service or subscription.
One company that IBM is currently working with has an initiative they call “One More Question.”
The program uses all available data that can be unified and utilized about an individual customer and their status to serve up the best follow-up question for that customer at the point of contact. It might be something along the lines of:
- “Did you know we have a new version of the product you have?”
- or “did you know we have a new product that works with the product you have?”
- or “we have a new pricing plan that could save you money?”
- or “did you realize your bills are 60 days overdue?” etc.
By combining all the possible information – not just from the customer support system, but the order processing system, product catalog, website clickstreams, on and offline transactions, loyalty programs, and more, they can finely tune the right question to enhance the customer experience and make their data a point of personal connection.
Let’s take a look at some examples of what else is possible as marketers work to create personalized experiences throughout the customer journey:
Digital billboards are hot trends in advertising – they generate 3 to 5 times more money than traditional billboards. As the cost of digital billboards drops, they are being installed at subways, bus-stations, shopping malls, office buildings, elevators, and airports. The idea is to make digital billboards more effective by driving the choice of advertisement with real-time analysis of consumers who happen to be nearing a billboard … a new revenue source for Mobile Network Operators.
Based on real-time location data readings from cell phones, combined with the profile data of each device user, digital billboards can change to promote, for example, tonight’s concert as a group of college students approach a subway station.
This kind of dynamic, data-driven, real-time engagement is where we are headed.
MNOs have unparalleled reach into the location of their customers – spatiotemporal data on hundreds of millions of devices in real time in conjunction with demographics information of their customers. This can all be done while safeguarding the privacy of individual customers.
Finally, if there is one example we can all relate to, it’s customer satisfaction in airline travel.
In years past when you had a miserable travel experience, you probably said to yourself “I need to send an email to customer service” or “that’s the last time I fly with them.” And that was that.
Today, the consumer is in control. You can simply go to the airline’s Facebook page or tweet at them and share the good, the bad and the ugly for everyone to see. While this provides you with immediate relief and gratification, it creates a complex opportunity for marketers that calls for an equal balance of reactive response and predictive offers.
By integrating data from social media and operational systems, in real time, they can gather a variety of information that builds a complete profile of you as a customer. They know you are a detractor, they know your frequent flyer number, and if you occasionally purchase on-board snacks, drinks, movies and more. With that 360-degree view, they can apply predictive analytics to get a better picture of what you are likely to do and want today and tomorrow.
Now, they can properly react to your needs and serve you better.
For example, let’s say I’m traveling today and my layover flight was delayed at the last minute due to mechanical problems. The airline knows my status and now their system sends a text, push or email message to my smartphone inviting me to use the club lounge during the delay or offers a coupon for an in-flight snack or drink once we finally get underway. By taking this seemingly simple yet multifaceted data-driven action in real time, this airline has shown that they are both listening to their customers’ needs and reacting to them before the customer has to take the time to ask.
How would you feel had you received this “personalized” service?
I’m betting you’d feel pretty good about it.