Social Media Case Study.
In 2017, prior to working with Visiture, Bagsy was running several campaigns that were being optimized exclusively for post engagement, with the goal of expanding their audience and delivering ads which resonated with their customers and prospects. However, there were no audience or demographic targeting in the earlier managed Facebook campaigns except for a handful of campaigns with lookalike targeting. All prior campaigns were effective at delivering an efficient cost per engagement, however, this approach did not support sales and scaling new customers.
Goals and Tactics.
We started by segmenting our audience into 5 categories (e.g., Purchasers, Email List, Social Engagers, Lookalikes, and Site Visitors). Once we reached statistical significance with the most engaging ad copy, we determined it was now time to optimize ads for conversions. We then used the post engagement data to create multiple ads each for the 5 conversion campaigns to see which ad copy variations resonated best with the various targeted customer segments. After publishing the conversion optimized campaigns with the best ads, we saw an immediate increase in our conversion metrics. Other key optimizations included testing and refining geotargeting, regular budget optimization, and testing various ad placements and formats. Our main KPI, ROAS, improved by 246%, while our CPM decreased by 11%, and prospecting campaigns (users who have never engaged with Bagsy) saw a 430% increase in ROAS vs prior acquisition campaigns.
With the drastic improvement in ROAS, we expected decreases in post engagement performance. As a general rule, optimizing towards ROAS decreases engagement-based metrics because we are simply only targeting the audience that is most likely to make a purchase as opposed to the audience that will engage with our ads based on their historical behavior. For example, at comparable spend levels our CTR decreased by 78% and CPC’s increased by approximately 3x as a result of a higher frequency. Frequency is the average number of times your ad was delivered to each person and generally, as it increases, generally, so do CPC’s whereas CTR will decrease.
Also, we noticed that the total number of clicks decreased by 78% which is also consistent with having a higher frequency and a lower CTR. Although you’re thinking, ‘these changes sound bad’, keep in mind these metrics are the result of scaling add to cart actions, purchases and improving ROAS by triple digits. Despite those decreases in engagement metrics, purchase-related efficiency metrics showed other improvements. Including Frequency which increased 248%, adds to cart increased by 103% increase, and the number of purchases increased 168%.
As a result of these actions, Bagsy saw tremendous gains in the last year, including:
Increase in Total ROAS
Increase in New Customer ROAS
Increase in Add To Cart
Increase in Purchases
Increase in Frequency
Decrease in CPM
The right optimization strategy, budget optimization, ad and audience testing, and targeting strategy may help produce smaller, incremental improvements in a silo, however, when combined and thoughtfully implemented can drive performance at scale. And don’t forget to create a campaign structure where you can control the budget allocation among your best performing audiences to maximize your performance gains.
And whether you are looking to scale ROAS, Engagement, Leads, etc. be sure to treat those as separate initiatives and not aggregate that data when evaluating social performance as optimizing towards one KPI will negatively impact another KPI at a macro level. We encourage looking at budgets and KPI’s separately to gain the clearest and most accurate picture of how social media is supporting your business.
Data Driven Marketing + Creative Commerce = Results.
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