One of the big distinction is that Business Intelligence and Customer Intelligence tend to focus on the past, so they put a lot of effort into understanding what’s happened in the past, and that’s useful. It’s a little bit like looking in the rearview mirror, you can’t drive looking in the rearview mirror forever, so you have to predict what’s going to happen next, and then organizing your business around that because that’s where the real value of analytics comes in.
When we see these sort of the BI focused projects, very often we find that they’re not driven by a particular business problem, so one of the things we tell our clients and customers is to start with something that they really trying to solve, like start with a metric that they’re very clear about, what are they trying to do? Is it a kind of improve annual rates? are they trying to improve upsell rates? Are they trying to improve cross sell rates? Are they trying to attract more prospects so you can improve conversion rates, Are they trying to improve retentions? because once they know you’re trying to andwer these questions, they don’t need that big BI project anymore. In fact you can do it with a smaller exercise, where you are very clinical about what data sets you use, and make sure you are keeping a good balance of internal versus external, because a lot of traditional BI systems tend to focus very much on internal side but they have no real way of mining all the external data that becoming available, so making sure you have a balance of internal and external, then make sure that when you have done those things you take it through the prediction phase meaning; building the systems to actually predict customer behavior.
