In a market where products are increasingly indistinguishable, customer experience is now the key differentiator. Power is with the customer – all the more so when experiences can be amplified and shared via social media.
Service industries are customer centric because they have to be. Web and mobile based interactions have put the customer at the heart of every interaction, alongside an instant broadcasting mechanism. Context, as well as content, is now relevant, adding to the complexity of customer experience management. Poor service has nowhere to hide and the customer is definitely king.
The large online players, such as Amazon, Google, Facebook and Apple, have set the standards very high, but this is only the start. Compared to more complex trading companies, their transactions are simple and potential gains limited. As customer experience management moves into corporate, B2B as well as B2C, the potential is huge and it is only just beginning to be realised by the early adopters.
The technology fraternity has responded with lots of hype… Big Data, Cloud, SaaS, In Memory, Advanced Analytics, Machine Learning, NoSql, Predictive, Data Science, real time, Internet of Things, OmniChannel, Personalisation. But as usual, technology is just a distraction from what is actually required.
So what is required?
As the physical and online trading worlds come together, we need a customer centric view that learns from customers’ interactions and other information sources, to intelligently guide the customer to the service they want, not the service we want to sell them. Ultimate Personalisation. But not ‘Big Brother’.
Our first experience of this is probably online advertising, where we are targeted using search terms we have previously applied. Many of us find this ‘creepy’, but this is too simplistic and obvious. Using more information we are able to better understand our customers’ needs and target offerings that are helpful and welcome rather than creepy. This is currently the world of the Data Scientist who has to analyse data to understand customer needs and help Marketers to determine how to communicate in a way that influences behaviour.
Marketers will always be required, as it needs a human to understand desires, emotions and perceptions. But a Data Scientist? Really? Isn’t this the techno-crowd creating jobs for the boys? If we can automate data collection, can’t we also automate the data science? Shouldn’t good data scientists drive themselves out of business? Maybe this is why it is not happening – turkeys don’t vote for Christmas!
Advances in Cloud computing enables us to collect and analyse customer data, process it in real time, and guide marketers with self-learning tools. With this platform Marketers rule the customer experience landscape – no geeks in sight.
I call this ‘Data Science as a Service (DSaaS)’, and within the next few years this elite process will become commoditised as part of the marketer’s toolkit. The next question will be, ‘Does this change the characteristics of a modern marketer?’
BrightTarget is one example of the new generation ‘Data Science as a Service (DSaaS)’, calculating Customer Lifetime Value and helping to drive loyalty and profitability. In itself this is nothing spectacular – large organisations such as telcos have been doing it for years. What is different is how they are doing it: an elite team of software developers using enterprise tools, rented via Cloud services and delivered via globally scalable architectures. This is the guerrilla app developer model, now being applied to corporate solutions.
Who will own the corporate market place for such apps? Amazon, Microsoft, IBM, Salesforce, Google, SAP? Maybe a new player that no one has heard of yet… Watch this space.