Don Peppers: “Big Data” – Coming to a Customer Experience Near You

In thinking about how to assess the customer experience, it’s important to keep two different…

In thinking about how to assess the customer experience, it’s important to keep two different kinds of data in mind: observational data and interactive data.

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The Voice of Customer surveys you do, whether you use NPS or some other customer satisfaction metric, represent interactive data. And there’s no better judge of the quality of a customer experience than the customer herself, so interactive feedback is vital. This kind of feedback has proven particularly handy for immediately revealing mistakes, errors, or missteps in the experience delivered to a customer during a transaction or some other event.


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Whenever a customer buys something, or calls in to talk to someone, or selects something on your website – absolutely every time a customer engages with your business in any way you have an opportunity to outperform or underperform, relative to that customer’s expectations. So capturing transactional VOC feedback with respect to that interaction is a highly important “complaint discovery” tool. Still, as useful as interactive VOC feedback is for a business, every business has only so many customers, and no customer wants to be asked repeatedly to spare a minute and to give feedback. Again. In other words, the volume of VOC feedback you can acquire is limited by a precious, finite resource: your customer’s attention span.

However, observational data is proliferating willy nilly, as technology creates more and more of it. It’s everywhere and anywhere: in the continually updated geolocation of your delivery vehicle, in the customer’s clickstream and browsing behavior, in the data collected by your product while the customer is using it, and even in the words, speech patterns and emotions encoded in a customer’s voice over the phone. Moreover, as the Internet of Things inevitably expands, observational data will increasingly come from the products around us and their interactions and communications with each other.

In short, this is one big mess of data. This is “Big Data,” but for individual companies. And it presents a Big Problem, because most companies aren’t equipped to handle this kind of data – massive flows of both structured and unstructured data, capable of providing deep insight into the quality of the customer experiences they deliver to individual customers. It’s one thing if a company is in the “Big Data” business itself – using terabytes of data, for instance, to predict crop yields, price changes, or securities trading. But most companies are just trying to use the increasing data available to do a better job of running their non-data businesses. 

Consider an ordinary automotive manufacturer – Subaru, for instance. By paying extremely close attention to the customer experience over the years, Subaru can now make the astonishing claim that 97% of the cars it has sold in the last 10 years are still on the road! But staying ahead of customer expectations takes increasing amounts of data – volumes and volumes of marketing data. Not just surveys and VOC feedback, but data from service records, marketing campaigns for all the different Subaru vehicles, advertising logs, response and clickthrough rates, social media, dealer WiFi logs, proprietary “first party” customer data, second-party media-sourced data, and anonymous third-party data. 

And of course around the corner soon the company will have to digest a tidal wave of car performance and telematics data, by individual customer. According to Ogawa Hideki, chief engineer of Digital innovation at Subaru, with the advent of 5G wireless technology Subaru expects soon to “collect a significant amount of connected-car data, likely at a volume and frequency comparable to log-data collection.” And the executive added that Treasure Data offers “the only platform we’ve found that will handle that scale of data collection as quickly and flexibly.”

It’s no small task for any Customer Data Platform today to accommodate the immense volume and variety of observational customer data, and to make it immediately and efficiently accessible to an ordinary business simply trying to provide a smooth, frictionless and engaging experience to customers. It’s already a difficult task, but it’s destined to become even more challenging at an exponential rate.


Don Peppers is an Advisor for Treasure Data.

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