How sellers increased clicks with Sponsored Display
By: Rachel Fan, Senior Media and Analytics Manager, and Ashton Brown, Technical Writer
In this 2020 study, we analyzed over 13,000 brands selling from China to a global consumer base (8 locales: United States, United Kingdom, Germany, France, Japan, Canada, Italy, and Spain). We refer to this group as “China-based sellers” for the remainder of this article.
To perform our analysis, we grouped China-based sellers into four clusters, with Cluster One being the most successful and Cluster Four being the least successful in terms of total number of clicks. Specifically, cumulative clicks over the campaign duration and conversion rate (number of attributed units ordered in relation to Sponsored Display campaigns divided by the total number of clicks).
To provide advertisers with actionable insights, we used machine learning to analyze advertising and media attributes that contribute more, or, less to clicks and conversion rate. We then identified which attributes have the largest positive impact on conversion rate.
This article provides insights/best practices on the key attributes or strategies by quantifying the degree to which top-performing China-based sellers (Cluster One) and lower-performing China-based sellers (Cluster Four) have adopted each key attribute or strategy.
For more on how we performed this study, see the Methodology section at the end of this article.
When looking to increase campaign clicks for advertisements, campaign duration is essential. Put simply, the longer the campaign runs, the more opportunities ads have to reach customers. In the period observed, top performing advertisers ran Sponsored Display campaigns for a median of 329 days, while lower performers only ran them for a median of 92 days.
For best campaign performance, we recommend that China-based sellers use Sponsored Display year-round. Doing so helps to ensure that the brand is always present and allows more time for campaign optimization.
- China-based sellers should consider expanding product targeting to 30+ products/ASINs (serial numbers) and 3+ categories in their advertising campaigns.
- With products on deals or promotions, customers are more likely to click on the Sponsored Display ads, which can increase sales and improve the overall performance of Sponsored Display.
Finally, we found that increasing the quality and quantity of customer reviews could improve the number of clicks and could also improve the customer conversion rate. Top performing advertisers had a median of 2,200 customer reviews per unique ASIN or serial number, compared to a median of 1,100 customer reviews for lower-performing China-based sellers.
To improve customer trust, we recommend that advertisers strive to improve the quality of their customer reviews. For more on improving customer reviews, China-based sellers should consider:
- Using Amazon Brand Registry. Enrolling in Amazon Brand Registry unlocks a suite of tools designed to help you build and protect your brand, creating a better experience for customers.
As seen in our analysis, in combination with our supervised machine learning model, we identified four tactics China-based sellers using Amazon Ads can use to improve clicks and conversion rates year over year: (1) run Sponsored Display ads year-round; (2) use product targeting on multiple products in multiple categories to improve reach; (3) combine Sponsored Display with product deals; (4) improve the quality of customer reviews by using Amazon Brand Registry.
- Select brands: 13,272 brands with Sponsored Display Product targeting campaigns. Specifically, China-based advertisers selling worldwide (8 locales: US, UK, DE, FR, JP, CA, IT, ES).
- Create success metric: Calculated based on year-over-year growth of cumulative clicks over the entire campaign period, and conversion rate (the number of units ordered attributed by Sponsored Display campaigns / clicks delivered).
- Identify effective ad or retail actions: Once the success metrics were defined, we identified the top campaign actions to help increase the success metrics with machine learning algorithms. We leveraged a gradient-boosted decision trees model to identify the most important campaign actions that contribute to the success metrics. This method helps us understand which advertising actions are the most important to drive strong campaign success metrics.
- Group brands: Brands were grouped by composite score (clicks and conversions) into four clusters ranked from highest- to lowest-performing.
- Compare brand groups: We identified what strategies top-performing brands (Cluster One) use to increase clicks and conversions, compared to strategies that lower-performing brands (Cluster Four) are or are not using.