Understanding customers

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Content Copyright © 2006 Bloor. All Rights Reserved.

One of the most commonly used metrics in call centres is what is known as “first call resolution”. That is, you call in with some sort of a problem, you speak to someone and they sort out whatever your issue is. Now, what does that first call resolution tell you? Well, it tells you what it says on the tin. What it doesn’t tell you is that the customer is, in any way, satisfied. She may be really furious that the thing broke down in the first place, that it took so long to answer the call, that she couldn’t understand the call centre representative’s accent or that the actual process of fixing the problem was so complicated. On the other hand, she may be absolutely delighted with your service. There is absolutely no way to tell, based on this evidence, one way or the other. But yet, all too often, measures such as these are used to attempt to establish customer satisfaction ratings.

So, how do you establish customer satisfaction? The answer is that you have to talk to customers. And you need to do so soon. The reason for this is that attitudinal change precedes behavioural change. Suppose you have an accident while driving your car (not, of course, your fault). If the process of sorting out the insurance claim is a pain then your attitude will change, or start to change, but your behaviour won’t change until your insurance policy is up for renewal. So you need to capture that attitudinal change as early as possible so that you can either reinforce it, if the change was positive, or rectify things if it was negative. To take this a step further, one would ideally build this sort of follow-up action into the insurance claim process itself as a part of the workflow that describes the claim process.

Now, the most well-known company providing IT-based market research is SPSS and it has enjoyed an almost monopolistic position in the marketplace. However, one product that is challenging that hegemony is Confirmit from Future Information Research Management (FIRM).

Confirmit is sold both directly to market research companies and to end users and it sees its key differentiators from SPSS being its support for panel moderation and, in particular, its business intelligence and dashboard capabilities. To return to our earlier discussion about the difference between behaviour and attitude: KPIs (key performance indicators) measure behaviour but KAIs (key attitude indicator) can measure attitude based on event-driven feedback, which in turn leads to the ability to integrate with back-office systems (both for driving personalised feedback and to incorporate transactional data for reporting purposes) and drive alert systems (with built-in escalation) as well as supporting dashboards.

Of course, FIRM would concede that SPSS offers better analytics than Confirmit, which is hardly surprising from the vendor of Clementine (for data mining) and LexiQuest (for text mining). However, FIRM has customers that use Confirmit for capturing attitudinal data and presenting dashboard-level and then use SPSS for deep analysis.

Given that SPSS has customers that use Clementine for its ease of use and who then transfer models into SAS Enterprise Miner this raises the mind-boggling scenario of using Confirmit to feed Clementine to feed Enterprise Miner! Whoa!

Leaving that hastily aside, the key points here are that you need to look deeper than simple call centre metrics and that SPSS is not the only kid on the block when it comes to collecting the necessary attitudinal data in the first place.