Dynamic Audiences: Taking the Guesswork out of Campaign Optimizations


We talk a lot about unstructured data on here at Simpli.fi – specifically the benefits it offers over pre-packaged data segments. Hopefully you know the drill by now; segments group users together based on a previous action, even though that action may not always offer real value. You buy a segment for users searching for a pizza parlor, but you could be serving ads to someone who wanted to order a pizza last week or someone looking for a pizza delivery job.


Because – and this is the rub – you can’t see how each user got added to that segment. Did they visit a certain site? Search for a keyword? Did they do it 10 minutes ago or last month?

This lack of visibility of what’s under the hood of a segment – whether it’s recency data or search retargeting data or something else – creates a stumbling block when it comes to optimizing campaigns. Segments block the granular detail needed course correct your campaign, offering only a group level view of performance. Not only is it hard to know which campaign elements are working, it’s impossible to optimize at a finite level for specific users. In short, you can’t know which users are worth your time or adapt in real time to their responses.

And that’s creates a unique opportunity for Simpli.fi. You see, here we’ve moved beyond building custom audiences and focus on dynamic audiences. What’s the difference? It’s huge.

See, your audience is changing constantly. When you create only a custom audience, you define a fixed audience group that doesn’t evolve, which is like putting yourself in a retargeting straitjacket where you can’t respond nimbly to those changes. But if you create dynamic audiences, you supercharge your custom audience and allow it change throughout the life of the campaign based on what’s working. With dynamic audiences, you can pick the most relevant users that fit your criteria and let it evolve throughout the campaign. Instead of a group lumped together through a mix of actions and intentions, you can select by all kinds of data: contextual, location, site, search, demographic and other attributes. You’ll also have transparency into performance, and you’ll have the visibility and agility to keep optimizing your campaigns.

Audience of One, Please

Let’s say you’re advertising a national chain of sandwich shops. You run a campaign with pre-packaged data and audience pre-defined audience segment and… well, you get what you get. You won’t know exactly what worked or why. You won’t know how many wasted impressions were involved or how you can improve your next campaign.

But with a dynamic audience, that changes. You create your audience defined on the keywords, timeframe and other criteria important to the campaign. The first data rolling in during the campaign reveals that many of your users were looking for a fast meal on their lunch break – not specifically a sandwich shop. Now you can change the campaign levers and audience. With more data, you realize that there’s a regional difference in terminology. Users from the northeast might look for a grinder or hoagie, while California audiences respond more avidly to sub shop. So you optimize some more and find that you can actually localize your national budget to get the best results regionally. What a concept!

That’s the benefit of a dynamic audience – you can keep your strategy fluid and dial different campaign elements up or down as needed, on the fly. You’re no longer addressing a block of users, whose real intentions remain a mystery. Instead you’re achieving that most important of marketing goals: delivering the right message to the right person at the right time.

And best of all, you’re no longer guessing which elements drove the best performance. You’re collecting insights that fill in all the gaps missing with data segments, and learning about your audience. You’ll be that much more informed for your next campaign – and your next audience.