Last month was the customer service week, and as dictated by tradition, there has been a flurry of activities by various corporates towards endearing and reminding their customers that they do care. I have for instance received a couple of SMS messages from Airlines, supermarkets, Banks, Telcos, Restaurant’s name it.
What strikes me is how many of those entities have developed a customer engagement strategy that will ensure seamless customer experiences in the long run? Just very recently I missed a 5am flight on a regional airline just because I arrived at the check in desk at 5.05am only to find a remorseless check in staff telling me that the check-in desk closed 5 minutes earlier. What’s more surprising is my preferred way of online check-in wasn’t possible thanks to the airlines dysfunctional website. And there are many more such experiences every second, thanks to social media, customers are now able to keep brands accountable to dissatisfying experiences.
What remains consistent all through is the need to put in place a mechanism that first attenuates the chances of bad experiences and secondly mitigates whenever such an experience happens. One such mechanism can be found in deployment of Big Data tools. Its one area which can have direct, measurable and visible impact. Organizations, both large and small, need to use big data analytics to deliver superior customer service and build strong customer loyalties.
Big Data comes from your mobile phones, Facebook likes, emails etcetera. The insights gleaned by big data can create BIG opportunities deepening customer engagement, optimize operations, mitigate risks, and capitalize new sources of revenues. Penetration reached through analyzing transaction data, social sites, foot traffic and in-store checkout wait times have led to shifts in decision making and in-store tactics.
Telco companies for instance are increasingly analyzing their own Big Data to improve their revenue while improving customer service and reducing customer churn rates. To the extend that they have reached an inflection point that they no longer find it necessary to advertise on traditional channels thus making further savings. Think about it – telcos are flooded with Big Data each time someone simply makes a phone call, sends a text message or gets online. And now more than ever before, coming up with Big Data road-maps aimed at addressing 2 key success factors for increasing revenue: First, Creating a 360-degree view of their to provide better customer service secondly, obtaining near real-time/real-time analytics combined with current data to better understand customer-centric objectives.
Businesses have more data about their customers available to them than ever before. They have data about the demographics of their customers, they have data about the marketplace, they are competing in and they have plenty of other data available to them. The problem that businesses have is not that they do not have enough data to improve the customer service they provide, but that they almost have too much information available. If they try to look at all of the data they have available to them, it can become confusing. Trying to use the data in raw form requires more time and effort than a business has and may not provide them with the information they need.
The idea is to take all of the information that is available for a business, record it, collate in and put into a format that is something the business can use. Instead of seeing a bunch of numbers, the business can see the data in a format that relates to their business. It can give them specifics about the people that are utilizing what the business has to offer, or it can tell them what markets are the right ones for the business.
Its not only big businesses that are taking advantage of these tools anymore. Medium and small businesses can have access to the systems and the tools that allow them to utilize all that big data analytics has to offer. It is starting to level the field and give small businesses the chance to take on the big businesses.
Story By: Timothy Oriedo
Executive Coach and Data Scientist Strathmore Business School