The rising value of first-party data has created a bit of a “gold rush” mentality. Companies are hearing that first-party data represents unrealized marketing value, so they’re mistaking the goal as amassing as much first-party data as possible.
But first-party data is a lot more like crude oil than gold. It doesn’t have inherent value. First-party data needs to be refined and used effectively to create value.
Here are three common missteps companies are making that prevent them from fully realizing the value of their first-party data:
Mistake #1: Not collecting the right data
When companies default to the “more is more” mindset, they collect any first-party data they can think of. They end up storing massive amounts of data they have no planned use for — or data that looks interesting on the surface but they can’t attribute reliably.
On the flip side, some companies aren’t thinking big enough. We’ve seen companies dumping data they didn’t have a use case for today – only to realize a year later they could have used it.
Defining your data and getting specific about your use case(s) should be the starting point for any marketing transformation initiative. Think about ways you can action on data right now, and imagine how you might use other data in the future as you build momentum and sophistication in your data-driven marketing.
Mistake #2: Not building a solid first-party data structure
Often, business leaders tend to focus on the coolest data and the most complex/sophisticated use cases. In the process, they overlook the importance of building a solid first-party data structure.
Core data, like contact name, proper postal address, email, phone, mobile, etc., isn’t exciting, but it’s absolutely critical. Without a proper data foundation, it’s difficult to build a data-driven customer journey.
For example, when businesses want to use first-party purchase data to drive nurturing campaigns, they look at the “what” and the “how” of the purchase data — instead of starting with the “who” and making sure they have accurate email addresses to match to that purchase data. Incredible customer intelligence within companies’ own ecosystems, but you can’t go deep into that intelligence if the basic core customer data is riddled with errors.
Setting up that core first-party data structure is essential to making the rest of your first-party data usable.
CIOs, CMOs and chief data officers need to ask tough questions around that core data: How can we validate the integrity of this information? What are the fill rates we need to get higher-quality data? After those questions are answered, connect the core data to deeper data sets.
Mistake #3: Onboarding too slowly
Let’s say you’ve found a use case: using sales data to automatically trigger hyper-personalized offers in your customer loyalty program.
Now, you need to onboard that sales data by matching the core customer data (name, email, etc.) with the specific sales/purchase data. You need to accurately match the right purchase data to the right core customer data. You should also simultaneously validate (again) that the core data is accurate. Verify the customer hasn’t moved, the email address is still valid, etc.
All of these steps need to happen fast. The whole idea is “right customer, right time,” after all. Relevance of customer intelligence fades by the hour. And core customer data is also more dynamic than most realize. For example, one percent of customers move every month.
This data onboarding and validation is where a lot of companies get hung up. Some don’t do a good job matching data and filling gaps, so they’re working with inaccurate data and/or aren’t able to use a lot of their data. But the bigger problem is companies often take so long on the “match and patch” process – weeks or even months – their “data-driven marketing” efforts are fueled by dated data.
Without speed, companies are missing opportunities because they can’t act fast enough to be relevant. Just as bad, they’re wasting money on marketing for outdated targets.
Putting it all together: Three keys to activating first-party data
We’ve seen companies big and small – including sophisticated marketing organizations with big budgets and fancy tech stacks – making all three of these mistakes. But we’ve also had a front-row seat to how the most successful marketing transformations come to life.
The first key is focusing on the right data – not trying to do too much or starting with the most complex use cases.
With that tightened focus, the second key is building the data hygiene of your core customer data. Data integrity means creating processes to ensure you’re getting the fill rates you need to capture core data and using tools to help validate and fill gaps in that core data (like new mover databases) to improve attribution and match rates.
The third (and arguably most important) key is onboarding rapidly – ideally matching and re-validating in 24 hours or less. Because capturing the best data in the world doesn’t amount to much if you can’t use it while it’s still relevant.
