‘Bad data’ perhaps sounds a little melodramatic to some, an example of anthropomorphism. But the fact is that customer data is indeed about people, and if that data is incorrect, your business cannot even hope for success.

‘Data is the new oil’, as we keeping hearing, and in a phrase I am taking complete credit for here, ‘oil needs to cleaned before it becomes petrol or kerosene’. (Strictly speaking, oil is fractionally distilled, but you get the point).

New research from Experian Data Quality shows that inaccurate data has a direct impact on the bottom line of 88% of companies, with the average company losing 12% of its revenue.

This loss of revenue comes from wasted marketing spend, wasted resources, and wasted staff time. In this post I’ll highlight some more surprising stats from the study.

The context

The hidden cost of bad data may be even greater than that 12% lost revenue. 28% of those who have had problems delivering email say that customer service has suffered as a result, while 21% experienced reputational damage.

The question here is not just one of increasing conversion at source, but one of protecting a company from the risk that comes from sending communications with incorrect contact information. In the US, this risk is high as ISPs increasingly crack down on email senders.

All of this forms the background to a key trend in marketing. Customer data (and in turn, CRM systems, marketing automation, customer experience management and analytics packages) remains a priority for improvement.

The EDQ survey was taken by more than 1,200 organisations in the UK, US and Europe, across a range of sectors and company sizes. Questions regarded how companies collect their contact data, how they manage it, and what impact bad data has on their business.

Why does data quality matter?

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reasons for maintaining high quality records

Where do companies collect data?

On average, respondents use 3.4 sources to collect customer contact data.

  • 73% of companies collect data from their website.
  • 60% collect data from face-to-face sales teams (60%).
  • 54% collect data from call centres.
  • 47% of organisations collect contact data via mobile websites or apps.

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channels used to collect data

Data checking: Excel spreadsheets?

  • Only 38% use software to check data at the point of capture.
  • 34% use software to clean data after it has been collected.

Meanwhile, 38% continue to carry out regular manual checks on Excel spreadsheets, while 26% say they use one-off manual checks for seasonal campaigns.

Startlingly, 23% of companies rely solely on manual checks to check their contact records.

How endemic is the problem?

The average organisation estimates that 22% of all its contact data is inaccurate in some way.

This figure is up from 17% a year ago. Estimates of inaccuracy are higher among marketing and sales professionals, who believe more than 30% of their records are incorrect in some way.

This problem manifests itself often as a barrier to marketing across multiple channels. 42% say inaccurate contact data is the biggest barrier to multichannel marketing.

Email bounce back and loyalty lapse

The survey asked organisations about email campaigns and bounce back. 67% reported problems delivering email.

Similarly, a high proportion of loyalty programmes have suffered through bad contact data. More than 70% of organisations running these programmes reported problems, with inaccurate customer information (34%) the chief cause. 

For more stats, see the full report