Why Poor Data Quality Makes Marketing Automation a Chore

Why Poor Data Quality Makes Marketing Automation a Chore

Marketers have access to an unprecedented amount of data; far more than they’ve ever had before. IBM estimated that we generate 2.5 exabytes of data every single day; this infographic shows how quickly our data silos are growing.

All of this data has given marketers some serious efficiency gains, with marketing automation software removing a lot of manual administration. The CRM has been transformed from a database into a real-time communications hub, and marketers can tap into all of this data to get a better picture of their customers.

Yet here’s the problem. Data doesn’t stand still. The more you have, the more likely it is that some of it is out of date. The longer you allow that data to decay, the less reliable your data will be. And the more data you have, the more expensive it is to verify and store.

Practical Steps to Clean Data

If you’re a marketer, you might be wondering why I’m preaching to you about an IT problem. But that’s not necessarily an accurate interpretation of the facts. Data quality isn’t someone else’s problem, and it isn’t something you can hide away in the data centre. Data quality is everybody’s problem, and we all need to take steps to improve it.

Take the CRM as a perfect example. If a record won’t load because of a validation error, and a marketer fudges a workaround to make it save, that’s a data quality problem that could have been controlled. One practical step would be to confirm with the form validation and enter the correct data. If the validation is broken, the marketer could report the problem to a developer to fix.

Likewise, a fake phone number or a duplicate record could wreak havoc with future reports and marketing campaigns. And spelling someone’s address incorrectly is going to result in a lot of waste – not least in the amount of printed matter that gets redirected to the trash can. If marketers ensure they’re entering clean data in the first place – by spelling things properly and using existing records rather than creating copies – they can stop data quality problems from being introduced.

That’s not to say automation is a bad thing. Far from it. Some types of automation can actually help to solve data quality problems. But to avoid cluttering a database with invalid records, we all need to take responsibility and play our part.

The Consequences

When you use automation, you’re essentially putting your marketing on autopilot. That can leave you open to problems. We’ve all seen badly-timed Facebook posts that were scheduled days in advance of a tragedy. In the same way, automating the management of leads can result in poor targeting if the core data is allowed to go unchecked.

The best care in the world won’t solve data quality problems. Data still decays all by itself, and the only way to tackle that is to clean it on a regular basis. But if you’re serious about using automation, it’s critical to recognise that your data is the biggest asset you have. Treat it well, and you’ll be rewarded with marketing automation that delivers genuine results and reliable, accurate reporting.

Article written by Martin Doyle
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