5 Powerful Strategies for Scaling your Facebook and Instagram Ad Spend
by Andrew Krebs-Smith | October 19
Over the last few years, we’ve audited a ton of Facebook ad accounts and we typically see the same errors being made that prevent media scale and increased ROI.
We find that In-house operations have typically “hit a wall” and don’t know why. Each time they try to ramp up media spend, in hopes of increased sales, ROI plummets.
Agencies that have hit the same wall just have better excuses…”the algorithm changed”, “competition is increasing”, “we need better creative”, “it’s just seasonality”, and “other channels are getting credit for our conversions”.
If you’re working with an agency, our guess is that you’ve probably heard some, if not all of these excuses.
Lift testing is a technique that allows you to see incremental conversions driven by your Facebook ads. That is, conversions that took place as a direct result of your ads.
You measure lift by comparing conversion rates between an “exposed group” and a “control group” within a given audience. The exposed group sees your branded ads and the control group is served a PSA ad.
In the following example, we have observed that branded ads claim 10 purchases per 1,000 people, whereas the PSA ads claim 3 purchasers per 1,000 people. By taking the difference, we then conclude that the branded ads are actually driving 7 incremental purchases per 1,000 people.
This allows you to gain insight into the true value of your ads and their impact on your business. Awareness of incrementality will help drive smarter decisions and optimize your ad campaigns in new ways.
Lack of lift testing leads to misunderstanding of ad performance and the value that your Facebook ads are actually having. Disregarding incrementality may cause you to credit Facebook for conversions that would have happened regardless of your ads.
Conversely, it may cause you to ignore conversions that occur much further into the attribution window. As such, lift testing correctly awards credit to Facebook ads over longer periods of time. This is especially helpful for delayed purchases (e.g. a customer is shown an ad Monday morning at 9am and decides to make the purchase 8 days after seeing the original ad). Normally, facebook would not assign any credit to this ad. However, lift testing results would allow you to correctly assign partial credit to these types of conversions.
Insights from lift testing allow you to identify incremental conversions and make decisions to improve effectiveness, driving true value to your business. For example, you may find you are optimizing creative and or audiences that Facebook was previously discounting. This translates into increased performance of your campaigns (i.e. more revenue, better ROI, and the ability to very likely increase your and spend).
The Facebook algorithm allocates spend on ads based on performance. Older ads are often favored because the algorithm is familiar with how they perform. Younger ads make riskier decisions with impressions while learning to optimize, and receive less spend as a result.
Having a variety of ads is important for a healthy account. When spend isn’t allocated properly among ads, your campaigns are not reaching their full potential which will impact performance.
When one ad gets the bulk of spend, you are not able to see how your audiences respond to different ad types. Performance will likely decline as this ad begins to fatigue and viewers are consistently shown the same visual.
There are various methods that allow you to designate spend to neglected ads. For example, Facebook allows you to set spend limits on ad sets, forcing more of the budget towards ones that are being ignored. Ads can also be paused temporarily, allowing others to receive spend and complete the learning phase so the algorithm is comfortable pushing budget towards them in the future.
Frequent testing of creative concepts allows you to understand the specific themes and messages that resonate with audiences as well as the types of creative formats that perform best within each overarching theme.
Lack of or infrequent creative testing leads to misinformed creative production and a lack of insight into the types of creative themes and formats that are most effective for your audiences.
Continuous structured testing of creative allows you to see recent data on the types of ads that perform best. This insight will enable future data-backed optimization towards high performing creative.
Lots of “hard resets” are really bad and unfortunately, we see them all the time.
A hard reset occurs when large changes are made in an ad account, such as drastic budget changes or changes in optimization events. These will reset the Facebook algorithm which uses data and past learnings to optimize campaigns.
The Facebook algorithm is very sensitive to drastic changes. The algorithm goes through a learning phase when it is determining how to optimize and drive the best results for your campaigns. During the learning phase, Facebook will show your ads to different people within your target audience to determine who is most likely to convert.
It’s important that you don’t assess ad performance during the learning phase. If you do, you’ll be tempted to “hard reset”, thereby resetting the algorithm and preventing it from truly learning.
Drastic changes in account settings should happen infrequently and only when absolutely necessary. This ensures that the algorithm has sufficient time to do its job and achieve a state of optimization. Once the active learning phase is complete, only then can you accurately assess campaign results.
—This strategy only applies to advertisers that have brick and mortar stores—
Store Visit Ads is a Facebook campaign objective that allows you to optimize delivery of your campaigns for the outcome of visits to your physical stores. Facebook measures visits to your stores via both mobile phone GPS and data that’s collected at the point of purchase.
Store Visit Ads are highly effective for retailers and are an important tool allowing you to see the impact of your ads on offline activity.
Failing to take advantage of Store Visit Ads may lead to missed opportunities in driving store traffic and recognizing offline activity and conversion that resulted from your ads. This also creates an inaccurate perception of overall ad performance.
Optimizing for store visits allows you to drive and track user activity that is crucial to your business. It also provides greater insights on ad performance and the strategies that are most effective for meeting your business goals.