TACKLE THE PROBLEM…
We are online customers. And we make no exception: like all of them, we read reviews before purchasing.
WHY CUSTOMERS RELY ON REVIEWS:
It is pretty simple: customers are looking to build a trust link with sellers without being able to touch their products. As a result, online reviews become the main source of advices from peers.
HOWEVER SOME FACTS ARE WELL KNOWN
We think about reviews as an unbiased representative sample but, as a matter of fact, this is just an illusion. Some customers have a higher than normal likelihood of reporting their opinions.
IT’S NOT JUST ABOUT THE RATINGS
We got fascinated by how disagreement evolves in online reviews (check References). We realized that disagreement arises because negative reviews increase over time. But also, because negative reasons starts to permeate positive reviews.
…WITH AN ACTIONABLE SOLUTION
During our journey, we also realized that making sense of online reviews is a very complex endeavor. Of course, you cannot read all the reviews: there is too many of them. Sentiment analysis helps, maybe along with tag clouds of frequently cited words or the identification of influencers. But how can you turn this info into something actionable?
If you want to take real action, you need to unveil the reasons behind your customers’ opinions. For example, it is one thing to know that the positive sentiment on a product of yours is decreasing over time. It is a different matter to know that customers are complaining because the application that controls your tool is not connecting to WI-FI. Or that everybody expects your product to work with, say, Amazon Alexa.
With a unique combination of Machine Learning, NLP and Artificial Intelligence, we identify the hidden whys, and turn them into actionable insights for your business. There is a lot of actionable knowledge in what your customers say about you and your products.
Don’t miss out on the chance to use it!
A FEW REFERENCES
- Simone Gabbriellini,Francesco Santini: From Reviews to Arguments and from Arguments Back to Reviewers’ Behaviour. ICAART (Revised Selected Papers) 2016: 56-72
- Simone Gabbriellini,Francesco Santini: From Arguments and Reviewers to their Simulation – Reproducing a Case-Study. ICAART (1) 2016: 74-83