Lower Costs, Better Reach, Higher Sales: Can Data Health be the Answer?
Trade-offs are part of life. You can eat a big cheesecake, or you can run a marathon, but you can’t do both. It’s no surprise that the most compelling stories at the Olympics this summer are stories of personal sacrifice. We all live on a budget and have learned to balance our expectations. Spend or save. Instant gratification or long-term happiness.
It’s the same if you’re running a company: reaching out to new consumers is great, but it’s expensive; cutting expenses is necessary, but it can hurt sales; and chasing revenues often cuts into margins. But if you’re a marketer at a retailer or other business with lots of customer data, there’s one move you can make right away that will help you win on all fronts: that’s investing in the health of that data.
After a thorough data health assessment, one of our clients fixed their most vexing data issues and the results in the first year were dramatic: $1M in direct mail cost savings, 2.4M more customers and prospects reached, and a $5M boost in sales. A success hat-trick.
You can do it too.
What’s wrong with customer data today?
Brands have been collecting customer data for decades. The tools to collect, store, analyze, and activate that data have been around for a long time, and marketers have built very successful businesses turning that data into repeat sales, outreach campaigns, and exciting new product lines.
But it’s one thing to collect data, and another thing entirely to keep it current and accurate.
In their eagerness to look ahead and capitalize on new data, many companies fail to keep up with old data. Considering that it takes less than two years for 60% of the data in your typical CRM database to become obsolete, you’re wasting your marketing budget if you’re not addressing the problem head on. Remember the adage: “Half the money I spend on advertising is wasted; the trouble is I don't know which half?” Now you do: you’re wasting it on bad data.
The COVID pandemic has made the problem even more acute: Consumer habits are changing much faster than in the past (with online shopping jumping five years into the future, according to IBM), and many people have relocated during the pandemic to get away from hot spots or get closer to family. It’s simply impossible to be sure that the key attributes you rely on to reach customers (like their address, phone number, or email) are still reliable if you don’t have systems in place to check the health of your data regularly.
It may be hard to believe, but obsolete data is not even the most crippling data issue today.
So many blanks to fill, so little time
The reality is, the vast majority of customer records, old and new, are missing key data to be fully activated. By some accounts, 90% of all customer records are incomplete, and 20-40% are duplicates.
Consider how you shop: If you’re using your phone to order a pizza, the shop will have your address and phone number, but probably not your email address. If you’re buying a new pair of shoes online, chances are they’ll have your email and mailing address, but not your phone number. And if you’re buying Cheerios at the local supermarket, General Mills won’t know anything about you. As for attempts to capture email addresses at checkout, they’re good for entertainment (look it up, it was a whole thing on TikTok last year) but are generally a bust.
New consumer channels (e.g., livestream shopping) are emerging all the time, and marketers simply don’t have time to fix the data they already have before more data comes piling up. Especially when that new data comes with its own separate identifiers.
Identity to the rescue
How do you get out from under that data avalanche?
The first step is to do a data health assessment. You need to know where you stand before anything else.
That client I mentioned earlier? We worked with them to understand their needs and help them find a way to reconcile their four primary consumer databases into a single, unified view of their customers and prospects. They wanted to eliminate duplicate records, fill in the gaps, and enrich their records for a better view of the consumer. They also wanted to be able to determine when prospects were actual customers, or not-yet customers but ready to be lured from the competition.
We were able to unify data across all of their databases (current customers, prospects, lapsed customers, and customer service claims). We cleaned it all up and filled in the gaps with reliable contact information: email coverage in their prospect file went from 18% to 68%, and phone coverage from 39% to 91%.
None of this would have been possible without a unified identity framework to bring all the pieces together. More importantly, the systems they now have in place will validate and enrich new records on the fly. It’s all onward and upward from here.
Data Health: lower costs, better reach, higher sales
What results were they able to achieve?
- Lower costs: With corrected and de-duplicated addresses, our client was able to reduce direct mail marketing spend by $1 million.
- Better reach: Our client was able to use new contact information to reach 2.4 million consumers who were present in their existing databases but were previously unreachable.
- Higher sales: Data improvements were directly responsible for more than $5 million in new revenues in the first year.
Today, only 28% of marketers feel confident that they can improve the health of their customer data. It’s easy to get discouraged: There’s no standard format for customer data, every marketing channel is different, and marketers and tech companies are in a tug of war over privacy concerns. But with the right partners and the right identity framework in place, it can be done, and it’s well worth the effort.
Ready for your own success hat-trick? We're confident we can help you improve your data. Let us show you how