Like so much of the digital marketing space, social marketing is a data-driven process where ROI can be figured down to the penny and KPIs can be set based on black & white metrics like CPM (cost/thousand impressions), CTR (click-through-rate) and CvR (conversion rate)) versus AOV (average order value) and LTV (lifetime value).
When you know what your customer acquisition cost (CAC) thresholds are and you've set an ad budget, it's simple to understand what KPIs you need to hit to come in below that CAC. If you want 1000 new customers, we know we have to hit a combination of ( X impressions/reach * Y CTR * Z conversion rate ) / Ad Spend to stay within a CAC that's profitable.
In the other direction, we have (or will quickly establish) average CTR and average conversion rates, and almost all of the social platforms will provide a range of reach estimates within a given budget range. That gives us what we need to make some reasonably accurate estimates on anticipated ROI from any given campaign.
The data also gives insight into a host of "what if" scenarios. What if we could increase our conversions by .5%? What if we doubled our reach? What if we find ad set B gets a .6% better CTR than ad set A? By testing these what-if scenarios, we get a systematic approach to identifying areas of the funnel we can be improve and the ability to prioritize those improvements to meet and exceed our goals.
We know we have to hit a combination of ( X impressions * Y CTR * Z conversion rate ) / Ad Spend to stay within a CAC that's profitable.
As someone who loves the creative side AND the analytical side, paid social presents the opportunity to flex that creative muscle and then test that creative work to show whether it just looks cool or makes a measurable impact on campaign success.
This was a series of campaigns that started in early 2018. We were pretty clearly targeting women across the board, but had different personas within that female demographic. We started with a controlled collection of interest- and demographic-based targeting, and then began A/B testing variable segments of that audience profile along with the ad creative.
Interesting: All other variables equal, the simple ad creative switch from "3 years" to "11 years" resulted in a 68% CTR improvement.
Want additional insights? Reach out. Reach out. I'd be happy to walk you through some of the non-confidential details of our work in this space.
I began with some deep-dive, top-of-funnel content to help us build a warm lead audience. We executed that across a couple of different channels. We then built out a series of middle-of-funnel (MOF) approaches using retargeting. This wasn't a national market. In fact, we were pretty restricted to the SF East Bay, which meant our reach on this MOF content wasn't very high, but we worked with a high AOV and absolutely crushed the conversion rate — delivering an astronomical ROI on the ad spend. We were also able to build some strong lookalike audiences for subsequent campaigns and create some advanced lead scoring based on time-on-page, given the length of our cold lead content.