The optimism of #Purpose & science of #design in forging #digital customer experiences! Opinions my own!

‎”When judging others it’s the intangibles that we often miss.”” Tom Baker aka The Pondering Man

I think it’s all about the “softer” metrics and the (formerly) intangibles.

I’m quite sure bad customer experience eventually bites us in the back – sending our customers directly into the hands of our competitors and them announcing it to their circle of influence on social media. If we tried to estimate the revenue potential loss, I’m sure the numbers would stack up.

Somehow, I don’t think we fully fathom these repercussions – the ripple effect. We simply have not assimilated these parameters into our decision making process, say when optimising contacts.

Perhaps one way would be to bake in and solve for (as an optimization objective) qualitative metrics such as customer satisfaction (CSAT), net promoter score (NPS) and customer effort score (CES). We read before in my previous post (…), that maximising the yield is not always customer-centric, so perhaps if we tried to solve for a longer-term metric (such as NPS?) we would be better off…

Since we’re talking softer metrics, I’d argue we require quantification of social inputs as well e.g. engagement metrics such as the volume of re-tweets and mentions etc. One problem though, we would only be able to tag a small fraction of our known customer base with their social media alter egos. I dare say not too many of us would want to expose our social vigilantism?

For retail banking and most other sectors, social media provides a peek into the consumer psyche. Useful for product development among other things (customer service is another popular use case); so perhaps we may want to retain social data at the product level, and glean what we can.

Using an example: if one of our products, say unsecured loans is a perceived market (aka loss?) leader vs. competitor A and B. It’s not that difficult to tease out concepts, why consumers rate our product superior. Tapping on to social data, we would be able to see most commonly used phrases to describe our product – whether it’s “lowest rates”, “accessibility”, “customer service”, “convenience” etc. Here’s where it gets interesting – since social data is by inference, public, we could be benchmarking ourselves vs our competitors, in real-time.

Now to sew it all up and integrate our new found social insights with our (existing) offline lead management processes. Some common sense may apply here.

For example, matching call center agent skill sets with a customer’s characteristics. What’s currently hot in the market – in social media parlance – should take precedence in customer dialogues, and telesales agents should be armed with a list of USPs in their scripts. With social insights, we take an outside-in perspective, eavesdropping on consumer conversations and incorporating those to foster more customer-centric dialogues.

Oh and guess what, revenue increase is a by product of being more customer-centric…