Three Data Onboarding Tips

Whether we’re combating churn through retention campaigns, or utilizing our first party data for Look-a-Like models to target the most likely prospects, onboarding is a core component of any digital audience strategy.

It seems simple enough – load our emails, MAIDs and other personal identifiers into an onboarding tool, check the match rates, and then push the matched audiences into our target ad platforms. While you’re probably familiar with the major players (see logos to the right), you’ll quickly find hiccups and caveats that need to be worked around to do exactly what you want. 

Here’s three quick tips to help you get the most out of your 1st party data efforts:

Use a Match Table to Avoid Delays

Depending on your business use cases, this may not be relevant. But for those looking for real-time activation against internal data triggers, most onboarding partners have a two delays. The first being on the initial onboarding of your data, and the second being when they push matched audiences into platform. For example, in my world our onboarder takes 3-5 days to do initial matching on our 1st Party data, and then another day delay when activating into respective platforms. That means it could potentially take 6 days for us to act on our data. 

We got around this by getting our onboarding partner to host a match table on their end. So when we push our 1st Party data, we attach an ID to our emails and MAIDs, and those that are matched are stored in a table on the onboarding partners side against their proprietary internal ID. For simplicity, it looks like this:

Now we never see the onboarder ID, but we don’t need to. We run routine jobs (weekly for example) to keep our match table updated with the most matched customers, but when we cut audience segments based on behavioral changes in our data lake – we don’t push emails and MAIDs to activate against, we push our IDs. Because those IDs are already matched on the onboarder side – we’ve cut down that initial 3-5 day match delay. 

This allows us to activate against churn triggers more quickly in our media campaigns.

Use Multiple Onboarders for Incremental Matching

Typical match rates for your onboarded data is going to be anywhere from 40%-60%. If you’re lucky you might get into the 70% range. Even then you’re still leaving a substantial portion of your 1st party data unmatched and un-targetable. 

Which is why we use multiple onboarders. Based on our match-back files from our primary onboarder, we take the unmatched customers and onboard them through a secondary onboarder – allowing us to increase our overall addressable first party data.

One thing to be careful of when doing this – it creates more line items in the ad platforms, and increases complexity within them. 

Plan Against Matched Audience Size, Not Your 1st Party Audience

Let’s say you have a customer list of 1.5 million emails and MAIDs which you want to serve retention ads to. Often media teams will plan out reach and frequency against an addressable audience of 1.5 million. But when they are pushed into the onboarder for matching, that 1.5 million might only translate (after match drop offs) to 800k actually addressable people in the ad platform. Even then, depending on how long your flight is, reaching all 800k is highly unlikely. 

It’s important to push customer lists into platform first, to understand how much of your targeted customer list you can actually identify within your ad platforms. That dramatically helps media planning. By further analyzing your match-back reports you can understand if there are clumps of specific customer types that didn’t match as high and are not possible to reach. 

By planning against your actual addressable audience, your plans will be much more efficient and net out much more predictable results. 

These three tips will certainly help you get more out of your first party data efforts, but this is of course just scratching the surface. I’ll cover more advanced (and granular) data onboarding strategies in future posts. In the meantime, any tips to share? Would love to hear in the comments below.