3 tips for spring cleaning your data
There are those moments in the year that smell of opportunities and chances. Think of the good intentions in January, the new life in May, the start on September 1 after a blissful summer... Yet no moment can spark more energy in us than the first rays of spring sunshine.
That (renewable solar) energy gives us the zest every year to wash away that long, dark winter and make plenty of plans for the months ahead. Have you also started spring cleaning yet?
The spring cleaning of your data we mean, of course.
If you're thinking, say what, don't worry. Not everyone gets wildly excited when hearing terms like data quality, profile unification, segmentation, analytics, GDPR and the like. But with these 3 tips from the cleanup gurus, you can definitely get started during your data cleaning:
Are you still using it
Don't be a "data hoarder." Collecting and keeping data you don't use may seem useful at some point, but under GDPR, personal data must not be kept longer than necessary for the purposes of processing. Moreover, some data has an expiration date. Purchases, offers, clicks, participation in contests or events ... they all have a fadeout effect on your customers' engagement. Preferences and interests also change over time. Or are you still buying the same clothes as 20 years ago? 😉 Donating or recycling can be recommended in the case of unused stuff at home, but for data, obviously different rules apply: delete or anonymize the data that are no longer needed. If keeping this type of data is part of your data strategy (more on that later), you can keep some or all of it. Just keep thinking about it consciously and critically at all times.
Give everything a fixed place
Keeping data structured and standardized makes for an orderly data house. For example, keep address data in separate fields for street, house number, bus, zip code, city and country. Do the same for first and last names. Bringing together is always easier than pulling apart. Provide a uniform way to store data and use reference lists whenever possible. It seems obvious, but how often do we face data sources where customers (from the same source) live in Belgium, BE, BEL, B, Belgium, Belgium, Belgium, Belgium...? Prevention is always better (and easier!) than cure. On forms, you can implement (autocomplete) web services and uniform drop-down lists to help users fill in their data in a structured way.
Work in categories
Look for similarities in data by entity: people, companies, touchpoints... Which ones do you find duplicate and need to unify? In doing so, be sure not to underestimate the importance of the previous tip! Look for patterns that point to duplicates, analyze, check and implement automated processes to do deduplication. Because that way you contribute to a complete 360° overview of your contacts.
We hear you thinking ... Are these three tips going to solve all my data problems now? Yes and no... When cleaning up, consistency and regularity are key. You don't get a tidy house by cleaning up once a year, but by having good habits in your daily life, you keep things under control. It's the same with data. If you ensure good (automated) processes and tackle problems at the source as much as possible, the result is always better.
Does addressing your data quality feel like too big a challenge? Or don't know how or where to start? Then consider the words of Amelia Earheart: "The most difficult thing is the decision to act, the rest is merely tenacity." Or also, "done is better than perfect". Every step forward is one closer to your goal.
Still struggling to get started and would like the help of a data clearing coach? Contact one of our experts for a no-obligation consultation and we'll be happy to help you get started.