Start at the end
As with any project you need to establish what you want to achieve. What are your aims? What do you want to do with your data? What does improved data quality mean to you and your organisation? Ensuring you have a clear view of your objectives from the offset will result in your data being fit for its intended use. Whether the use is for order taking, cross-selling, up-selling, knowing what you want to achieve will ensure you capture all the necessary fields from the start.
Consider the data elements
There is much more to a customer or prospect than simply a name and address. That’s merely just the starting block of a whole host of information that can enhance your customer relationships. So the questions you need to ask yourself are – what do I want to know about my customers and prospects? What information can I gather that will allow me to communicate to them better? Next, analyse your current data. Evaluate its relevance and look for gaps in the information you do have. Once you have determined all of this you can implement a way to ensure you capture key information from the start, enhancing communication between you and your customers and prospects.
Measure data quality
Did you know that every day in the UK 1,600 people die, 18,000 move house, 1800 register with the Mailing Preference Service and 18,000 register with the Telephone Preference Service? These are pretty hefty statistics and just as shockingly business data decays by 37% every year.* Cleaning your customer and prospect data on a regular basis and not just at the initial point of capture is vital. With suppression sets available to identify people that have moved house, deceased etc, cleaning your database is easy but it needs to be done on a regular basis.
How to get from here to there
A key aspect of any data quality programme is establishing where you are now and where you want to be. That way you can then assess the steps you need to take in order to get there. Set targets for yourself and evaluate your performance at every step to assess how much the quality of data has improved. Prioritise the processes which are in the poorest state or the one that is having the most negative effect on your business.
Whilst most businesses appreciate that data quality is fundamental, we all know that gaining that stakeholder buy-in often isn’t easy. If there is a lack of understanding on the benefits that data quality can bring then start by educating who you need to influence. Demonstrate the link between data quality and the businesses objectives and show how it can benefit them. The key is to make it relevant to each stakeholder by identifying their key drivers. If perhaps driving efficiency and cutting costs is one, explain how a structured data quality plan can help them achieve just this. Furthermore, identify areas of your business where there are potential gaps in data quality and where you’ll be able to achieve quick wins. Then communicate those quick wins in order to gain internal buy-in.
*Ten Top Tips, Experian Data Quality, 2013 Download here.