Our client is the CEO of a popular online retailer. His site’s operations are impeccable and he and his team are smartly dressed, with immaculate manners… but he knew this wasn’t the case with some of the delivery drivers employed by the various courier firms they used.
He also knew how much it would cost to change to a better courier firm. So, he asked us a simple question: could we use text analytics to find out how much bad courier service was costing him in lost customers?
Using text analytics software, we analysed the customer comments at on an online review site.
We discovered that almost half (45%) of the comments talked about delivery. Some were good, but our analysis of the structured data showed that there was one delivery company which correlated with a ‘terrible’ service rating.
And that’s about as far as structured data could take us on the customer comments.
But we were able to use text analysis to investigate the 7500 reviews. The unstructured data, where the customers were given space to vent their love or fury, clearly revealed the cause of the dissatisfaction.
And digging even deeper, we were able to use the techniques of linguistic analysis to have a very good idea of who wouldn’t ever shop with our client, as a direct result of the courier company.
Since we also knew the Life Time Value of those customers, we were able to calculate that one unsatisfactory courier company was losing our client almost 7% of their turnover.
(And imagine if these disappointed customers were actually shout-out-loud fans of the brand.)
Fortunately, because we identified the precise cause of the problem, and provided a reliable cost-benefit analysis, our client is now able to look at other couriers, knowing exactly how much more it’s worth spending on better delivery.