- One campaign with all products
- Split by brand and non-brand
- Split by margin groups
- Split by gender
- Split by best and worst sellers
- A mix of 2 to 5
- Conclusion on the campaign setup
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There is no single right setup for Performance Max campaigns in fashion e-commerce. We compare six strategies – from one campaign with all products to splits by brand, margin, gender or best and worst sellers, through to a mix – each with its pros and cons. What matters is that your campaign structure follows business goals, not collections or seasons.
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Google's PMax campaigns are an innovative way to optimise your online advertising. With Performance Max campaigns you can tailor your ads to different audiences and increase your conversion rate.
For fashion e-commerce, PMax campaigns are particularly relevant because they let you showcase your products across platforms such as YouTube, Gmail, Discover and the Display Network. That way you can reach potential customers in many different ways and make your fashion items irresistible.
PMax campaigns also let you segment your audiences by criteria such as age, gender, interests or purchase intent, so you can tailor and personalise your ads to strengthen customer loyalty.
But PMax campaigns are not without pitfalls. In this post you'll learn about six campaign setups, their pros and cons, and how to get the most out of PMax despite its challenges.
Pro: Very simple to manage with little room for error. Works well for beginners, too.
Con: Different margins aren't reflected. Brand traffic within the campaign leads to heterogeneous results the algorithm can't handle well. Individual audiences and product groups easily get lost and receive too little reach.
Pro: With a lot of brand traffic, different tROAS targets can be set, which ultimately increases reach and revenue. The non-brand campaign can be used more specifically for new customer acquisition. This makes it easier to align tROAS with your CAC and CLV goals.
Con: Splitting the data across two campaigns only makes sense above a certain traffic volume – otherwise both campaigns will struggle to hit the target ROAS. Management and monitoring become more complex.
Pro: It's easier to find the sweet spot between sales volume and profitability. If margins differ a lot, the algorithm can steer products more effectively. Sale products can be separated out.
Con: If margin differences are too small, splitting the data across several campaigns tends to have a negative effect. Accounts quickly become too complex. Product margins have to be updated continuously.
Pro: If a brand gets a lot of traffic from one gender, the algorithm may disadvantage the other. A separate campaign can increase traffic volume.
Con: A gender split is only possible via the assortment, by including only womenswear or menswear in the feed. Unisex clothing or cross-gender customers make this approach difficult. Generally a rather messy strategy.
Pro: Best sellers can be pushed in a targeted way.
Con: With Smart Bidding, splitting products across several campaigns is no longer recommended. Potential best sellers may be identified too late. A split only makes sense if there are different economic goals, i.e. different tROAS targets.
Pro: The chance of finding the best setup increases. Greatest potential for revenue and profitability.
Con: Management requires professional and technical know-how. With sloppy hypotheses, money can be burned quickly. The account risks becoming too granular and therefore inefficient.
For all strategies:
➡ Performance Max campaigns should primarily follow economic interests – not collections, tastes or seasons.
➡ Testing leads to success.
➡ PMax is and remains partly a black box.
➡ Bad feed = bad performance.
