I’m not a statistician or data scientist, but I’m finding that social data more and more is reflective of what’s going on for your ‘connected customers’: your customers who are digitally inclined or digital natives. I began to experiment first to find a content calendar that worked, a content calendar that produced likes, engagement and reach that lent itself to a larger social media footprint. The result of a larger social media footprint of course, increases your chances of your social media posts and channels appearing on page one of your social channels. What we learned after a few short months and for a fraction of what they spent on their consultants and other agencies was amazing and helped us not only spend our budget better, but also ensured our ads were being delivered to the customers most interested in us and our products. In the end, we ended up with booming social channels and a better understanding of our audience. Here’s what we learned:
Why Facebook? | Facebook is the most established social media channel, it has only a very small discrepancy between men and women users, straddles generations, and it’s the only channel currently that can represent the larger world around us at the moment, mostly because we’re looking at eighteen plus, I’d like to note that we wouldn’t be able to use the same ideology when working on a product for teens etc. as they aren’t as robustly represented on Facebook any longer, hopefully Yahoo gets Tumblr up to speed soon!
Where to begin? | When you don’t know anything, or know the wrong thing much like this situation, you start from the beginning. Of course we had some hunches, but they’d need to be tested and ensured before they became our baseline. Because of Facebook’s data partnerships, their targeting is only going to get more granular; this is an amazing tool, if you know who to target! If you don’t you’re absolutely going to struggle, not spend your budget correctly, and disappoint your client with your ‘findings’. In the beginning, the tests were one variable and as basic as can be; we then moved outward to look at variables like ethnicity, education and interests to add to our baseline. I’ve detailed some examples below.
Note* All tests were completed using one variable. Identical creative, copy, age range, gender etc. were used unless otherwise noted.
Gen X v. Gen Y | Defined as Gen X=29-38 and Gen Y= 18-28. This test was a great example of what happens when you do a broad test— many KPIs didn’t perform that differently. Our average Gen Y v. Gen X CTR was only six points differentiated and our average CPC was identical at $0.44. Gen X and Gen Y did differentiate however when it came to reach and clicks.
Reach is defined on Facebook as the number of people the ad was served to; in this case, our generational targeting led to reaching Gen Y twice as much as Gen X.
It was clear that Gen Y was clicking the majority of the time, indicating not only interest, but idea we had, Gen X may be growing on Facebook, but they’re likely to not be interested in a need-based, bargain product as they are often homeowners and at their ages have better salaries. Gen Y clicked 2,103 times v. Gen X who clicked 1,035 times.
Conclusion | When advertising on Facebook, interest and reach is piqued by Gen Y and currently we can point the majority of our budget Gen Y’s way, however, this is a living demographic and as Gen Y ages into more comfortable, established adults; we’ll need to make the appropriate generational changes to our targeting.
Men v. Women | This test was important for us because we know from the data that’s collected year over year that women often make purchasing decisions for their households. Rug Doctor was given contradictory information due to their placement in hardware and home improvement stores likes Home Depot and Lowe’s. What we found through Facebook insights was clear; women were are primary fans and engagers and so we applied that to this test in order to further define our scope. We also began to tailor our content to Women and the results were very promising despite Facebook’s decreased organic reach.
From this ad we learned a few things about Rug Doctor advertising to women:
- Rug Doctor ads were clicked by women 3x than they were by men
- From an engagement standpoint, we received post likes from women at a rate of 2x the men
- We also received 2x the page likes as a direct result of the post
- Advertising to women on Facebook for Rug Doctor is cheaper than advertising to men
*Our most engaging for both genders was the ad above— women liked this post and Rug Doctor’s Facebook page, at 2x the rate men did.
This is a good example of a test that involved a media partnership, this particular one with The ASPCA. We did this test to determine whether Rug Doctor’s customers identified with The ASPCA or with being pet owners/enthusiasts in general.
Women between the ages of 18-28, who were fans of The ASPCA in the United States:
- We received 1,467 site clicks (web traffic)
- We reached 154,393 women
- The average CPC was $1.69
- We received 2,228 engagements as a result of the ad
- Our average CTR was 0.607%
Women between the ages of 18-28, who are pet lovers in the United States:
- We received 3,522 site clicks (web traffic)
- We reached 519,744 women
- The average CPC was $0.71
- We received 5,361 engagements as the result of the ad
- Our average CTR was 0.954%
Conclusion | A focus on pet owners is definitely a warranted focus, in fact, it’s cheaper to target generic pet owners than it is to target fans of The ASPCA. Our audience is more concerned with the value of the product than with the CSR of Rug Doctor when it comes to Facebook ads. It would certainly be worth considering a new partnership or cause that is more mutually beneficial or that opens doors to other audiences.