Personalization can mean different things to different people. This can start with marketing messages and end with the follow up email from a purchase made. There are several things brands can do to make the user experience more personalized but it needs to feel natural and not automated. Over the coming weeks, we will discuss various personalization tactics and how you can navigate them in a world where privacy and data regulation rule. Before you can personalize anything, you need to know who your customers are with a 360 degree perspective, beyond just what they bought from you, where you shipped an item, or their click stream behavior.
The problem we are really solving for is data loss. Over the last 10 years or so, it has been quite easy to build a profile of your customers and find more people that look like them. Click stream data was helpful but that is gone due to IDFA and cookie loss. Facebook may have been the best source of data because not only do they have more behavioral data on their users than anyone else but they also have tons of declared data. Did you know that Facebook has over 1.3 Million data points on their users. On an individual user basis, they have over 35k data points. They used to make all of this available to advertisers because it encouraged them to spend more on advertising. But this isn’t the case anymore. Between Cambridge Analytica and Apple (and soon to be Google), Facebook has made the business decision not to share this information with advertisers anymore. This doesn’t mean they don’t have it. It just means that they have it and they want to control it. They are still happy for brands to advertise but they want advertisers to trust them on the targeting and optimization. Last year “SEOClarity” ran a study that found Facebook was the least trustworthy tech company in the U.S. with only TikTok being .4% worse. So how does a brand start to understand it’s customers more deeply so they can connect with them and find more people like them under these challenging circumstances?
Enter ProfitWheel, a new kind of customer insights tool that provides a deterministic understanding of your best and worst customers, your window shoppers, and the ones most likely to return product. Their data output can be used in a variety of ways to meet most business use cases. At a high level, they tap into the look-a-like audiences that Facebook creates for your customer data. They then unpack the users in the look-a-like audiences at a cohort (1,000 people) level. The output in their dashboard will show you what a brands users like, post, read, share, etc… This is in addition to all the declared data that users share with Facebook. One must remember that Facebook has data on us from the thousands of websites that have a Facebook pixel, in addition to what we do on Facebook, Instagram, and likely Oculus/Meta.
Once advertisers have this 360 degree view of their users, ProfitWheel can build adsets within Facebook to be bought against. This allows for unique creative and optimization at an asset and interest level. It’s really all the same things that you used to be able to do but cannot anymore. ProfitWheel can then push the adsets to Snap, TikTok, and DV360. You can also take it with you to any DSP. There is immense power in knowledge.
ProfitWheel also has a contextual tool that will save you from the DSP CPM mark-up but we will save this tech for another post. In the meantime, check out this video on their insights platform and this video on their contextualization platform. If you are interested in learning more, you can contact me at firstname.lastname@example.org.