When the idea for CANDDi first began to crystallise, we had a very specific type of customer in mind- companies selling lower volumes of high value goods, usually as part of a complex (rather than simple retail) sale. B2B examples might be consultancy services or financial products, B2C examples might be high-end consumer electronics or cars.
As we listened to mentors and prospective customers over the last twelve months, we realised we might be a little narrow minded. Unusually for a start-up we were perhaps a little too focused on a niche. Because in reality, CANDDi could be very attractive to the high volume retail players as well.
We initially targeted companies with a high value sale because we thought the value of CANDDi would be in allowing users to target specific prospects for an intervention to increase the chance of that prospect converting. There would have to be a reasonable margin to justify the time cost of a manual intervention, so hence we thought we would target those selling high value goods or services.
As CANDDi has developed we have realised that the rules that help you to identify one prospect with whom to intervene could just as easily identify a thousand. For example, searching your interactions to find all those who have not yet touched a particularly effective piece of content that is a common factor amongst many converted customers could turn up many targets. The campaign tools that we are building into CANDDi make it just as easy to intervene with a thousand prospects as with one (as long as you are doing it electronically).
So why couldn’t CANDDi Prospect Analytics be used for online retailers or anyone else delivering high volume goods? Surely the ability to intervene in every purchasing process must be highly attractive to companies used to the guesswork practices of A/B testing to improve their funnels? At least that’s our thinking now…