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Road to $596,800/month
Our cooperation with this client began at the end of October 2021. The home electronics niche is quite competitive, but with the proper strategy, we were able to scale the account. In the past, the client had worked with another advertising agency that handled Google campaigns with Shopping Ads and Google Display Network. The idea of working with us was to continue to grow, as the previous advertisers were stuck and had no clue how to scale up.
The main goals set at the beginning of the cooperation were:
- Launching more advanced shopping campaigns
- Creating Search Network ads with RLSA (Remarketing Lists for Search Ads) with complementary DSA (Dynamic Search Ads) campaigns
- Launching multi-level remarketing campaigns.
The results were satisfying, but we were looking for a solution that would allow us to scale shopping campaigns consistanly . We faced optimization limitations and a lack of control over keywords we were displaying for. We wanted to scale them up but couldn’t afford to pay high rates for displaying products on the wrong or overly general keywords.
Smart vs Standard Shopping Campaigns
We decided to segment the most expensive products into the Standard Shopping campaigns, dividing them into SPAGs – Single Product Ad Groups. This allowed us to control the search terms triggering the display of a particular product in search results.
By using proper campaign priorities and negative keyword lists, we were able to divide the campaign structure in such a way as to filter out the most valuable keywords and set the highest CPC rates for them.
In addition, some campaigns were divided by devices to have even more control. Some search terms used by mobile users were quite different from desktop users. That’s why it made sense to filter them separately and exclude them independently of each other, as one phrase that sells on mobile devices may not necessarily sell on computers.
Lower ticket products were launched with separate, Smart Shopping Campaigns based on product margins.
Performance Max Campaigns
During the scaling process, we also tested Performance Max campaigns containing different asset groups with and without listing groups. The results were average at the beginning, but after switching to assets groups containing only products without additional headlines or images, we started seeing some improvements in performance and ROAS. At that time, Smart and Standard Shopping were responsible for the most revenue, but some additional Performance Max campaigns could help us hit the KPIs, although lack of optimization features prevented us from utilizing this campaign type more.
Search Campaigns
We use RLSA (Remarketing Lists for Search Ads) in our campaigns, which allows us to increase the exposure of ads to users who have already been to the client’s website.
In Search, we also relied on a DSA (Dynamic Search Ads) campaign, which we treat as search terms „digger”, which is our standard procedure. At a later stage, we created a separate Search campaign for the most effective phrases, with headlines and descriptions perfectly matching the keywords and landing page.
In addition, an advanced brand campaign was also set up.
Google Display Network
We focused heavily on remarketing activities in the Google Display Network with many visuals, such as static banners, HTML5 creatives, and short videos. Different remarketing lists were created based on the users’ website behavior. We used dynamic remarketing with a multi-level approach – ads displayed products that users were interested in and had previously browsed on the website.
Results
After 7 months:
- 246% increase in the number of clicks
- CPC increased by 13% but
- With a 187% increase in ad cost, we generated 243% more transactions and 373% more revenue by focusing on high-ticket products (ROAS increased by 19% to 4,51x)
With campaigns structured in this way, not only did Google Ads revenue increase, but the store as a whole recorded a significant month-to-month improvement. Google Ads had an undeniable impact here, building brand awareness among customers.
The share of the revenue from Google Ads compared to other sources increased from 20% to 33% during this period!
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- For e-commerce businesses looking to maximize their conversion rates & average order value.