In 3 months:
• Scaled to stable 6-figures in monthly revenue from $83k/month to $253k/month at a 305% growth rate.
• While maintaining a 5.21x ROAS from Facebook Ads.
• Sold out 2 times (in April).
Gone above & beyond our client’s expectations and managed to generate $570,922 revenue with a 5.71x ROI in our first month.
February
March
April
May
Maintain a ROAS above 3.3x and scale to stable 200k monthly revenue.
...branded ads and high-converting ones we had to do some rebranding and hire a professional copywriter who would write copy and scenarios in the exact cultural language our target audience spoke.
...an attractive offer that would help us scale more easily. So we had to prepare a special bundle with a back-up plan for how we could run its cheap-traffic ads, even though it was sold out.
...get more UGC content with a simpler method without hiring expensive influencers.
...bypass Facebook’s algorithm and handle performance instability.
Because of the COVID-19 situation in the U.S., we were faced with a unique opportunity.
Since we knew that there would be less competition = the CPM’s would be lower and we could spend 20% of our budget on tests with less risk. After all of this, we adapted the above strategy which we knew, if done right, would help us hit & exceed the goals faster than we first set out to accomplish.
To find a balance between a strict brand look and high-converting ads, we dug deep for more insights by doing lots of copy mining, collecting data from Ads Manager, and finally combining everything into one sheet. Then we did some rebranding with the client.
After our media buyer and creative teams did more research to better understand our target audience - we decided to invest in a professional copywriter who would write copy in the cultural language that our target audience spoke.
Through natural copy and branded creatives, we kept the client satisfied and slowly started scaling up.
When we were running ads with a special offer or a discount, the best-performing ones were GIFs displaying the total value of the bundle while putting them into a basket, then brushing it off and emphasizing the “xx% off” or “save $xx” (the offer).
These types of ads converted better than the traditional ones, even in cold audiences.
Together with the client, we created a brand ambassador campaign where we would offer micro-influencers, fans of the brand, and even cold audiences free products in exchange for taking some photos with them.
Later on, we offered them money but for more of an educational/testimonial based content. The plus side of getting brand ambassadors rather than asking content from influencers is that the temptation of becoming a brand ambassador made our audience put in more effort in the content they sent us. They were not in it only for the money or free products.
The high-quality UGC content we generated here will be used for years to come.
We handled the instability with a rotation strategy where we would use an ABO structure with the same ad sets, but we would keep restarting them after 2 days, because the results were always better in the first 2 days.
When using the ABO structure, Facebook will put your ad set in an audience pool which is tempted to buy more. In that same period, Facebook will predict if your ad set will reach the 50 events required to learn more about the ad set and your ads to see if they’re relevant for that audience pool, and then, optimizes for that pool. If Facebook predicts that they won’t, the ad set will be assigned a “Learning Limited” message and put it into a worse audience pool - which caused the before-mentioned instability.
Using the rotation strategy, we were able to bypass Facebook’s algorithm and gain more conversions.
Delay attribution was a harder nut to crack.
At the time, we handled it by looking at ads more holistically.
We checked if metrics like the AOV and CR% were realistic, compared to what we got on average, whether the traffic costs were cheap, and so on.
Eventually, we found a pattern - the biggest indicator for us was if there were a lot of people adding to cart but not converting - these types of ads had the most delay attribution.
We were also looking at unique metrics because they show real stats behind the metrics, the difference is - if a single prospect added to cart 5 times, there would be only 1 unique add to cart, while a non-unique add to cart metric would show 5 add to carts.
We did a test called “Super Ad'' which meant we would first find the best working video with the same copy, thumbnail, and even CTA button. Then with the best working video, we would test different copy then with the best working video and copy - we would test different thumbnails and you get the rest.
We tested a single variable for 3 days and after it had spent 2xCPA - we could decide if it was worth being a part of Super AD. In the end, the Super AD performed at an average ROAS of 4.74x.
After trying different retargeting campaign structures we decided to stick to ABO.
The problem with CBO is if you have different audiences with sizes that differ more than 50%, Facebook will spend on the one that is bigger, but not necessarily the most profitable one. And if you have minimums or maximums it damages the whole CBO optimization, what it was made for - giving freedom to Facebook. So while CBO is still not mandatory - we recommend leveraging ABO for retargeting.
We created a free personalized quiz that helped prospects figure outwhat type of products would help them. This brought us cheaper traffic and collected emails which converted greatly in the back-end through email marketing. After completing it they got discounts up to 33%.
To create a killer offer we did some research on our TA and briefed everything with the client - we created a bundle our prospects couldn’t resist, which also boosted our AOV by 10$ and gave us room to scale further since our CPA also got bigger.
With the bundle, we offered 4 bestsellers, a guided Facebook support group, and an email course on how to replenish damaged hair. The added digital products increased the value of the bundle and decreased the total value added of it by 50%. The bundle sold out within 2 weeks of launching.
After the best-selling offer had sold out - we started running ads directing to a landing page which offered alternatives - the personalized quiz and special discounts on bestsellers. The ad also had 2x cheaper traffic than the Evergreen ones because of the attractive offer, and in the end, that meant we would get cheaper conversion costs, despite the offer being non-existent.
