image image 29th August 2014


…data definitions are tough… but you can’t live without them. They are probably the single biggest problem we come up against time and time again. It’s also the main complication when publishing numbers to ensure that everyone is (as my old director used to say) comparing apples with apples…

For example: Unique visits. A definition very much dependent on a timeline – a person who visited your website in January and then again in March is a unique visitor in both of those months, but a repeat visitor in Q1. If they purchase in March then your conversion rate in March will be higher than in January or Q1 (assuming only one purchase). It doesn’t really matter which way you measure it (although I’d recommend you look at a rolling average); what matters is that everyone agrees how you measure it and use the same formula across the business.

When does a prospect become a customer (or, in other words, when does the bloke in Sales get paid)? How do you know if a sale has gone to a New customer (+1 to your acquisition marketing team’s tally) or to an existing customer (Points awarded to your retention team)?

It can be as simple as agreeing the format for dates to complicated definitions of channel attribution. Agreeing what constitutes a sale, a customer, an application, a visit, an enquiry, a booking, a cold lead, warm lead, hot prospect… is key to providing clear KPIs and is fundamental in understanding your MI. Your sales & marketing team might have a very different approach to this to your finance team (see comment above re bust-ups). How can you understand a business plan/marketing proposal/product review if you don’t have consistent numbers and data definitions to base them on?

It’s the first thing we do once we get our hands on your data – sift through all the fields and potential numbers and agree definitions with you. So we’re always reflecting how your business operates and when you’re looking at your dashboards and analysis tools you can be confident that you understand exactly what those numbers mean.

We Love Data

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