How We Scaled The Pony Jet To £50k / month
Oct 30, 2024
Context
Toby, the founder of pony jet and now a great friend of mine, came on as a client in late October. To be honest, it actually took months of following up on my end to get him on a call. But thank God I did! Toby was working with a freelancer who was taking him for a ride. This freelancer was running only a low-scale branded search campaign. There was no cold traffic and no new customers, resulting in a gross profit of only £600 per month. Toby was clearly losing money on this deal. For reference, here’s what Toby’s account looked like when he first approached us:
Results at a Glance
In just 30 days (mid-September to mid-October), we achieved:
Took spend from £0 to £7.5k/m.
Produced £48,370 in revenue in one month.
Achieved a ROAS of 6.45x
Strategy Deep Dive
Firstly, we decided to move away from performance-backed automation and machine learning, opting for a more manual setup. This shift allowed us to have better control over the ad spend and outcomes.
Secondly, we launched a series of standard shopping campaigns, segmented by location. We created three distinct campaigns, each tailored to a specific geographical area to maximise reach and relevance, allowing us to spend more effectively.
Next, we focused on optimising all products in the Google Merchant Center to ensure maximum visibility and relevance. This crucial step improved the performance of our shopping campaigns. By using feed rules, we provided the algorithms with high-quality data, benefiting from lower Cost Per Click (CPC).
Next, we used the search terms identified from the shopping campaigns to create targeted search campaigns. These non-branded campaigns were designed to attract new customers by leveraging the insights gained from the shopping data. We continuously grew these non-branded campaigns, increasing budgets month on month.
Additionally, we reduced the CPC for branded ads while maintaining their importance through manual bidding. This approach allowed us to control costs effectively and ensure that the brand's ads consistently appeared in top positions.
Finally, by implementing manual bidding for branded campaigns, we managed the impression share to always show ads in the number one spot.
This strategy enabled us to control costs and avoid relying on Google's smart bidding system.
For non-branded campaigns, we leveraged smart bidding to grow profitably, ensuring optimal performance and cost efficiency.
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