Every couple of years, a hot, new trend bursts its way into the collective lexicon of the B2B marketer. In recent years, predictive marketing and ABM took center stage as marketers looked to hone in on the data that underpins just about everything th
According to Experian, 91% of organisations have had problems with their contact data and 88% believe contact data errors affect their bottom line.
They’re pretty big stats and there’s plenty more research out that backs up these figures. So the first question you might ask is, why on earth is it that bad?
Well in the old days (pre-marketing cloud) it was simply a case of human error, lazy call centre or sales reps entering bare minimum information or quite often customers deliberately or inadvertently giving incorrect data. Of course, this was compounded by the lack of technology to check the details either at the point of entry or after the fact. It used to be very hard for marketers to keep contact data clean.
However, today is a different scenario altogether. Marketers have access to a vast array of realtime automated technology to help fix the problem.
The very well respected research specialists at Sirius Decisions have suggested a ‘cost of failure’ on this bad contact data. According to their metrics, it costs a marketer $1 to clean data on entry, $10 to clean the data after it’s entered a CRM or a whopping $100 per record if uncorrected. It does beg the question why marketers don’t get on top of the issue?
The answer is actually quite simple. Marketers are focused on the wrong metrics, or certainly too focused on one end of their marketing performance. For marketers with lead generation or acquisition roles, they are typically focused and more importantly KPI’d on the number of leads/acquisitions they make. These KPI’s may even have ‘quality’ elements to them, in the form of MQL or SQL targets. However, this has an adverse effect on how performance marketers assess the ‘success’ of their activity. They focus on how well their activity is driving ‘leads’ or even ‘higher value leads’, as such they focus on ‘success conversion’ rather than or as well as ‘failure to convert’. Of course it’s very useful to know that marketing activity is driving x% of MQL or SQL and how to increase the conversion. But this doesn’t look at why the remaining leads are failing to convert.
At Convertr we’ve analysed over 12 months of lead generation activity from multiple brands. From this analysis we know that on average over 30% of leads generated are invalid or have incorrect contact data. It’s a significant figure and probably the biggest unforeseen issue facing performance marketers today.
Marketers need to start looking at both ends of performance measurement and ask questions of why leads fail, as well as what it is driving success. If they did, they’d realise that vast amounts of budget are being wasted.
To find out more about how you can dramatically improve your lead or customer acquisition quality, read our whitepaper ‘The New Lead Generation Metric’ by clicking here.
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