Data can tell you who to sell to, it can tell you when to sell a certain product, it can tell you whether you should launch a product, and when to bail out of a business. Data can answer the questions: who, what, when and where. However, data cannot tell you how or why. That’s on you.
Like unit tests in the software world, it is not just the quantity of the tests or the amount of code that gets covered, it is how the tests are approached and their quality. A unit test for a payments class could cover every single possible error code (of which there are hundreds), and every single possible combination of input. It doesn’t do any good if all the tests were for one payment provider. In data world, you can collect every aspect of a transaction, but if the data was created under different conditions, then it doesn’t matter what the data says. Why? Let me put it like this: because I put a water collector under a tree and another in an open field 100 feet away, they will collect different amounts of water. It doesn’t mean it rained less where the tree was.
In data collection, it is near impossible to collect data on website usage. Different people will get subjected to slightly different versions of a site, and at the end of the day, they are different people. The aggregate results may lead you to better things, sure. But collecting different people, in different areas of the world, in completely different demographics, on completely different sites? (sigh) What are you trying to measure here?
You have to think outside the box to kill the competition. Apple doesn’t own the smartphone market because Steve Jobs said it was cool, or because they got there first. They own it because they invest heavily in creating value. If you want leads, tell the leads why they should give you their information and don’t require it. If you want likes, create engaging tweets/statuses/boards/etc so that they want to read the crap that comes out of your keyboard. If you want customers, show them something that brings utility to them. The data will tell you who those people should be, when they should see it, where they should go, and what they should do. Its up to you to figure out how.
One of the best tricks I’ve ever seen with SaaS, was a few years ago. AnonymousProvider.com wanted their clients to keep their contracts. They had a great service that people had to learn to use. They had great support and sales. The first thing they tried was a free trial for their service. It worked great, people were signing up left and right … but they weren’t using the software. Since they weren’t using it, their customers would come to their site and bounce. Since the clients were paying so much for the software, they’d quickly cancel after two or three months, even if it cost money to cancel.
What AnonymousProvider.com decided to do, was make the second month free, instead of the first. Retention shot through the roof. Since the client had to pay for the SaaS platform, they figured they may as well learn it. By the end of the first month, leads were trickling in, but not pouring in like the sales team had told them. It was very easy for the support staff to keep them on board since the second month was free. By the end of the second month, they knew how to use the software and leads were coming in pretty steady. It was easy to convince them that it would only get better, and that next check would come right to AnonymousProvider’s bank account.
Another trick I saw once, was with SomeSearch.com. They discovered there were quite a few search terms that resulted in ten results or fewer. They made it a point to use that as an opportunity to engage them and convert them to a lead by telling them they could get notified of more results in the future.
The point I’m trying to make here, is that solutions to problems are not intuitive. Use the data as a map instead of a GPS. Figure out the answer to how, be bold and, experiment with the unintuitive.
Until next time,