October 29, 2021 0 1241

$104 000 with a 7.3x Return on Ad Spend on Facebook

Today we are sharing a Facebook marketing case study from Max Berezovskiy, the CEO of ScaleX agency.  In this case, he was able to generate total revenue of $104 339 for a client while spending only $14 743 on ads in just 30 days.

Read along to understand the strategies and approaches he used to achieve the results of this campaign.

Brief Campaign Details

  • Niche: Clothes shop for women
  • Market: USA 
  • Revenue: $104 339
  • Ad spend: $14 743
  • ROAS: 7.3
  • Period: 1st December – 31st December 2020

Client’s Problems

  • Unprofitable prospecting campaign;
  • Illogical and horrible retargeting system;
  • Didn't change communications on retargeting in time (action drawdowns when compared with frequency);
  • The massive overlap between the active audience (sometimes it gets to 55-65%);
  • Every scaling trial went wrong (drawdown on ROAS and increased CPA).

Main Client’s Aims

  • To increase sales;
  • To increase the site’s profitability;
  • To scale and reach a minimum ROAS 3.0.

The first thing Max did was to create the right retargeting structure and lookalike audiences of 1% and 1-3%. These audiences were based on purchasers for the last 60 days (they were more than 1 500).

Next, he created a competent retargeting structure for the campaigns.

Competent Retargeting Structure

In order not to let go of customers who almost bought, Max built a complete funnel, which consisted of the following stages:

  • Those who interacted with the brand’s Instagram/ FB page in the last 0-7 and 0-14 days;
  • Then viewed the product card in the previous 0-7 and 0-14 days;
  • Then added the  to the cart in last 0-7 and 0-14 days;
  • Then added their payment info in the last 0-7 and 0-14 days.

The retargeting principle is to set up and build a separate communication for each step of the funnel.

Do not forget to change the optimization, depending on the funnel's step — the lower the stage, the lower the optimization.

Max then allocated 25-30% of the main budget for retargeting.

He took the data on the time frame for retargeting from the Cohorts analysis, which is found on Facebook analytics. The Cohorts analysis principle is to understand how many days the user needs from the moment of the first interaction to the purchase.

This project's early seven days was the most significant percentage of users’ return, and 7-14 was two times lower. So, cohort analysis gives you full information about the time period.

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Creatives Used

Max tested campaigns with a regular catalog, carousels, and videos. He made it in a way that each slide showed the product from 3-4 sides on the models (collage) for the carousel.

Videos were 10-15 seconds and filmed each in a different location and models.

The best performing combinations were catalogs with videos ads on prospecting campaigns. Collages performed well on the engaged audience's retargeting (MOF).

In the carousel, Max promoted the bestsellers, novelty products, and products from different categories. He tested up to 4-5 ads with different copies, collages, and videos with products in 1 ad group. For MOF (VC) and BOF, he used DPA.

Ad Copies

Max used short copies for the ads because people don't like reading a lot in general. That's why he didn't do massive texts. He preferred using ad copies of 3-5 sentences. He also utilized very personalized copies and sometimes funny copies, especially for the BOF.

Max put special offers for the BOF (discounts the most) and test simultaneously without offers. With a special offer, BOF works better.

Selecting Objectives and Testing

The first thing to start setting up is the objective. For testing, Max chose the target: Catalog Sales for retargeting and Conversions for prospecting.

He then tested different audiences, which include: broad audience, lookalike audiences 1%, 1-3%, interests with discounts and with clothes, dresses and etc.

Lookalike audiences 1%, and 1-3% were based on buyers. Max took buyers for the last 60 days. He does not recommend taking buyers from a longer time interval because, most likely, those people have already changed their interests and could have a similar audience of lower quality.

For this to work, the following tips from Max must be put into consideration:

  • The main thing is that there must be more than 1 000 buyers for each lookalike audience.
  • Do not forget to check the overlap between audiences before launching your ad. Otherwise, there is a risk of a higher cost of the result, biased testing, and higher CPM costs due to overlap in impressions.
  • Always make mutual exclusion or group together similar audiences. And also, exclude the audience source on which lookalike audience is based and exclude active lookalike audience from prospecting ad sets for reducing overlap.

On this project, the best performing campaign was lookalike audience 1%, 1-3%, and interest: clothes and dresses.

He then started to scale them using the approaches that are discussed below.

Structure of the Advertising Campaign 

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In this project, Max used CBO, except for the retargeting campaign. Before working with CBO, he tried to put everything in a proper structure.

Max separated the interest, behavior, broad audience, and lookalike audience campaigns and ran them individually.

This principle works hand-in-hand with CBO campaigns. Without it, you will not objectively test anything, and the result will also most likely not be the best.

Working with FB Analytics Data 

Facebook analytics’ data helped him to create very accurate custom audiences for retargeting. For example, audiences of people that:

  • Added to the cart more than 2 times;
  • Viewed the product card 7+ times;
  • Added billing information 2 times;
  • Viewed the sales page more than 20 times.

These audiences gave a good return on this project's advertising investment and squeezed out the maximum from retargeting.

Smooth Scaling

In this project, Max left 30% of the budget for testing and 70% for scaling.

As soon as he saw the audiences that generated the most sales and revenue, he raised the budget to 30-40% per day from the original figures.

Mark scaled the campaigns smoothly because the Facebook algorithm takes time to learn the audience. It does not already know who to show ads to (because learning phase), and it does it to everyone, and then the price for the result will be sky-high. Therefore, it is necessary to leave the learning phase and scale slowly. Otherwise, everything might break down.

Monetizing Previous Customers

The funnel will not be complete if it’s not made cyclical. You can use an uploaded list of buyers from the last two years or one year, and launch on them a catalog with season goods or with the top 20 products from the previous two months.

The audience is precious, especially if there is a lot of traffic to the site. Use optimization for reach because the audience is already from buyers.

In a catalog for cross-selling and up-selling, you can utilize all products, create custom catalogs with new products or best sellers.

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Summary of What Was Done

In this case study, we see Max turning an unprofitable ad account of his client into a profitable one, on a huge scale. To achieve the revenue of $104 339 with a 7.3 ROAS, Max applied the following key changes:

  • Right retargeting structure;
  • Separate communication on every step;
  • Competent scaling;
  • Hyper segmentation;
  • Correct prospecting structure with CBO;
  • Utilizing recycle customer journey;
  • Squeeze out the maximum from retargeting and made focus on it;
  • Nice creatives and right testing approaches.
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