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- This call doesn't obligate you to anything. As part of it, we will try to understand how we fit each other and whether we can give a significant result;
– minimal monthly budget to work with us – $3,000
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2X in ROAS and 4x in revenue for
4 months
case study
The client is an underdog in the furniture segment. In less than 2 years, he created the best UX in the market, turn call center operators into interior specialists and collect more than 20,000 SKUs of furniture, decor, home textiles. Before us, tree agencies were already working on campaigns, but they failed to achieve the desired ROAS and revenue.
310 000$
ads budget
gross profit
78 000$
case study
  1. We checked the correctness of the analytics. It turned out that e-commerce "doubled" real revenue, which killed the ability to make adequate management decisions and optimize campaigns.
  2. Turned off ineffective campaigns with high ad spend and ROAS below 300%.
  3. Tested new product photos. The use of photos of products that competitors do not have made shopping ads more attractive and increased CTR.
our growth hacking tool in Google Shopping
5. Segmented shopping by key categories on the site. We set up separate campaigns for best-selling products and brands, which made it possible to manage their sales and performance
launched campaigns performance
6. Optimization in Smart Shopping campaigns was carried out once every 2 weeks to adjust the target ROAS within + - 20-40%, which helped to achieve more than 700% ROAS in more campaigns.
brand smart shopping campaigns performacne
7. Created a custom report in Google Data Studio for each traffic source. In it, the client can analyze the effectiveness of campaigns in real-time in the context of a unit economy7.Created a custom report in Google Data Studio for each traffic source. In it, the client can analyze the effectiveness of campaigns in real time in the context of a unit economy
how does it looks
case study
  1. Analyzed running campaigns. It helps to avoid making the same mistakes twice;
  2. Checked the work of Facebook Pixel to get the correct data for analysis and optimization;
  3. Compiled a list of audiences that have not yet been tested;
  4. Launched advertising campaigns for interests and behavior: Furniture, Renovation, Interior Design, JYSK, IKEA, recently moved, LAL audiences.
  5. We tested adding cards manually and dynamically from the catalog. Catalog product ads performed better because they change the list of products regularly and users see the most relevant ones.
6. We tested the optimization strategy for the maximum ROAS with a budget for the entire duration of the test. This strategy did not give the desired result, so we abandoned it and returned to the optimization strategy for maximum conversions;
cases are not only about "victories". This result was shown by our strategy with optimization for ROAS
7. The site receives a lot of traffic every day from paid advertising and organic search results. In addition, Facebook users rarely buy expensive things directly. That's why the retargeting campaign showed better results than the cold audience campaign. We decided to turn off cold campaigns and set up a new retargeting split by events and timing.
in retargeting, we tested optimization for various events in order to determine the most profitable bundles
8. At the scaling stage, we change the optimization strategy from ABO to CBO to enable the algorithm to manage the budget more flexibly
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