Marketers aren’t shy about their love of data – which makes more than a bit of sense. We all build (or should build) our marketing strategies on insights gleaned from the data we collect. It reveals our successes and failures. It also provides direction for future strategic decisions. Which begs the question, if data quality is so important, why do so many marketers settle for less than excellent data on their current customers and leads?
Rather than spend an inordinate amount of time delving into this conflicted psychology, I’ll let you know why data quality is essential to your business, and cover the objectives that accurate data can help you accomplish.
Personas and Targeting
Personas are essential to modern marketing strategy. This is especially true in content marketing and inbound marketing, but personas also have a place in the world of outbound marketing. Accurate customer data helps you better develop personas – essentially a compound of demographics and behaviors – that you can use to target your content, website, and marketing campaigns.
You can then go out and rent or purchase prospecting data that aligns with these personas to better target your outbound marketing program. Not only will this strategy lead to better budgeting of your marketing spend, but it will also lead to better campaign performance along the way. But you can’t reach this better performance if data quality doesn’t play into your overall strategy. Accurate data is going to help you first develop these personas, and then verify the efficacy of your personas as you begin to work them into your marketing strategy.
Sending Reputation and Deliverability
If you’re reading this post, there’s a good chance that email is a tool you use to contact current customers, prospects, and leads. If you don’t keep accurate records (name, postal address, email address, other demographics, purchase history, etc.) on your leads and customers, you’re going to run into all kinds of issues. You might personalize a message with the wrong first name, or, if the name is ambiguous, you might send men a message that’s targeted towards women. Both of these scenarios are going to limit the success of your marketing.
Worse still, if you aren’t keeping your eye on data quality, and running hygiene and validation programs on your list(s), you’re going to hurt your sending reputation and deliverability. If you’re trying to run a profitable email marketing program, that’s essentially a deathblow. At the very least, you’re going to lose money, and at the worst, if you’ve violated CAN-SPAM (even unintentionally), you could face legal action. So, it’s in your best interest to keep accurate records and continually verify your data quality.
Reengaging, Retargeting, Upselling
Good data is going to make it much easier to do things like reengage old or inactive leads/subscribers, retarget your campaigns to the most engaged audience, and upsell your current customers on new products. These are all very valuable actions that allow you to make the best use of your data, and continually work towards the ROI you want to see from your data and your marketing activities.
For example, if you track engagement with your email newsletter, and you see that a certain group of subscribers hasn’t opened or clicked-through your newsletter in several months, it might be in your best interest to start these subscribers on a reactivation campaign. You can further target these campaigns on attributes like time since last open, last offer acted upon, or some other combination of both demographic and behavioral attributes. By tracking engagement, and using all the data available, you can potentially win back some of these lapsed subscribers and see better ROI from your marketing and your data.
You can use this same approach to spearhead the other activities I mentioned. In its simplest form, the idea is to continually collect the most accurate data possible, determine how you can use that data to accomplish a business objective, and then execute, making sure to track the performance of your activities along the way.
Hopefully this post gave you at least a cursory idea of the importance of data quality. Remain ever vigilant with your data collection, validation, and cleansing programs. Then, develop a strategy that makes the best possible use of your data and watch your hard work pay off.