Amazon has launched new metrics for brands advertising on the platform to better understand their audiences and who is buying on the platform. There are four new metrics that offer new-to-brand insights for advertisers. The metrics give an idea of what percent of purchasers and orders are new to brand versus returning customers coming from your ads. This level of insight is great for learning how much it costs to reach new users with your campaigns and products. It can also influence your keyword targeting in your campaigns.
As of now, the new metrics are for video and display ads on the Amazon DSP platform and for Sponsored Brands ads on the self-service platform on Campaign Manager for Seller central and the Advertising Console for Vendor Central merchants. The metrics are not currently available for the Sponsored Product Ads.
Let’s break down the new metrics and offer some ideas on how they can influence your advertising strategy.
New-to-Brand Orders and % Of Orders New-To-Brand
The New-to-Brand Orders metric informs you how many orders are from customers who have not interacted with your Brand on Amazon over the prior year. These are new customers you have likely not reached with your products previously.
The % Of Orders New-To-Brand gives a percentage of orders that are from new purchasers versus overall orders for that campaign from return purchasers. A campaign with a higher percentage is going to be one that has products that are more often found and purchased by new users and for a lower percentage, it means the products are purchased more often by returning users.
For the campaigns with a high number of new-to-brand orders and a higher percentage of new-to-brand purchasers, I would recommend using the products in those campaigns for competitor targeting. Create keywords around competitor products similar to the products that are bringing in new users. You know those products are often chosen by newer users, so they would likely be good products to steer shoppers away from competitors and toward your products.
With campaigns that have a higher number of return purchaser orders and lower new-user percentage, use those for brand searches to ensure the products most often bought over and over are showing up when people search your brand. You can assume if they are searching for your brand that they have likely purchased from you previously. Having the products they are most likely to purchase at top of page ensures your competitors have a harder time stealing those customers from you.
New-to-Brand Sales and % of Sales New-to-Brand
The New-to-Brand sales reports how much revenue you received from purchasers who have not interacted with your brand in the prior year, very similar to the New-to-Brand Orders metric. The % of Sales New-to-Brand shows how much revenue can be attributed to new-to-brand purchasers.
These metrics can also influence your keyword targeting. If, for example, you have niche or expensive products that you advertise versus products bought frequently, looking at sale revenue over order volume makes more sense since there would not be enough order volume to make a decision. You can look at overall new sale revenue and choose from the highest earners.
These are really cool metrics being introduced by Amazon. Being able to see how many purchasers are new versus returning is a great metric of data to have and can have a solid impact on strategy. Being able to know what products are being purchased frequently by return users and what are being purchased by new users can shape how you target people and what products you focus spend on. At this point, my only complaint is that I cannot use the metrics with Sponsored Product ads, which tend to be the most popular ad type and the one I normally recommend starting with. However, with the New-to-Brand metrics in the account now, I might soon be switching that recommendation to Sponsored Brand ads to get that data sooner.
Have you seen the New-to-Brand metrics in your account? Are you using them in your strategy? Let me know on Twitter!
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Author: Tanner Schroeder
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