Data Quality – An opportunity or a cost?

a pair of scales weighing 'opportunity' and 'cost'

By Chris Turner, Head of REaDConnect at REaD Group

We can all attest to being bombarded with articles and advice on that overly (and at times incorrectly) discussed data protection regulation – to the point where it has almost taken on a Voldemort-like status. The mere mention of it might inadvertently summon the ICO. However, GDPR has, from its inception, presented a change for the better and a huge opportunity for businesses.

It’s important to remember that the legislation wasn’t primarily designed for organisations; it was designed with the consumer in mind and to champion their interests. Nevertheless, we can’t forget the consequences of failing to adhere.

Prior to GDPR’s implementation the primary focus for data quality and data cleansing centred around wasted mail being sent to people who wouldn’t receive it. Over a 6-year period from 2005-2011 Royal Mail had over 158 million undeliverable items of mail (it would be interesting to know what this figure is now!). It’s easy to understand how this can be the case given that, every year:

  • over six million people move home
  • more than 600,000 people die
  • at least 500,000 addresses change for reasons such as postcode boundary updates

Data cleansing has too often been seen as a cumbersome expense, however, in a post-GDPR world we should be viewing it as an opportunity. It’s not just about the money – at a time when consumers are increasingly conscious of their impact on the planet, being seen to be wasteful in terms of thousands of undelivered mailpacks bound with single-use plastic is sure to cause reputational damage.

And the distress caused by mailing the deceased has the potential to be even more damaging to a brand. Consider the social fallout for a major bank trying to promote a re-mortgage offer to a couple who are no longer together… and now imagine the reason they are not together is that the husband is now a widower with three children.

If we consider this scenario from another angle: Imagine a major bank sending a re-mortgage offer to a widower with three children promoting its ability to support families with ease of the switch process, payment breaks, vouchers for a major high street toy store and a donation to a charity of their choice. So really – is data quality an opportunity or a cost?

Many organisations feel it’s enough to have robust processes for dealing with complainants and returned mail by removing these records from their database. However, most people simply bin incorrect mailings rather than making the effort to return them. Brands need to ensure their data is clean and accurate before contact is made because, by the time a complaint or goneaway is received, it’s already too late: money has been wasted and damage done.

Data cleansing has always been a relatively simple process but has traditionally relied on batch processes and manual interaction. Essentially, prior to an organisation contacting their customers with an offer or promotion they will provide this data to a 3rd party who process against industry leading suppression files like GAS and TBR. Data is returned with incorrect records flagged or removed and the contact continues.

In the age of technology, it seems strange that we are still reliant on people to run these processes. Why do we not simply schedule tasks and pat ourselves on the back? Part of the reason for this is the pure size of data assets (GAS contains over 98 million names and addresses) and complexity of data matching algorithms.

Recently Royal Mail commissioned a report into Dynamic Customer Data in a Digital World which for me hit the nail on the head. It’s time to change the conversation.

Are Data Quality and Data Cleansing an opportunity or a cost?

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