What technologies were you using?
At the time, the primary technologies we were using were really on more on the statistical side, so none of the big data stuff- we were not using Hadoop. The primary database technologies were SQL-driven. Ford has a mix of a lot of different technologies from a lot of different companies- Microsoft, Teradata, Oracle… The database technologies allowed us to go to our IT partners and say “This is the data that is important, we need to be able to make a decision based on this analysis”- and we could do it. On the statistical side, we did a lot of stuff in R. We did some stuff with SAS. But it was much more focused on the statistical analysis stuff.
Já viu o que se usa, né? Outro trecho:
Ford use text mining and sentiment analysis to gauge public opinion of certain features and models; tell us more about that.
So a lot of the work that we’ve done to support the development of different features, and to figure out what feature should go on certain vehicles, is based on what we call very targeted social media. Our internal marketing customers will come to us and ask us, “We’re thinking about using this particular feature, and putting it on a vehicle”- the power liftgate of the Ford Escape is a good example, the three-blink turn signal on the Ford Fiesta is another one. In those circumstances, we will take a look at what most people think about the features on similar vehicles. What are they saying about what they would like to see? But we don’t pull in terabytes of Twitter and we don’t use Facebook- we go to other sources that we found to be good indicators what customers like. It’s not shotgun blasts, so to speak; it’s more like very specific rifle shots. This gives us not only quantitative understanding- this customer likes it and this customer doesn’t- but also stories that we can put against it.