Three tactics to help grow your brand on Amazon.fr

By: Alice Deguilhem, Senior Analytics and Media Manager, and Ashton Brown, Technical Writer

In this 2020 study of over 100 brands in the PC Hardware category on Amazon.fr, we compare advertising strategies of top- and lower-performing advertisers. We then use this comparison to derive actionable insights advertisers can use to improve detail page view growth rate and new-to-brand customer growth rate year-over-year.

Story highlights:

In this study, we analyzed over 100 brands in the PC Hardware category on Amazon.fr (France) in 2020. The PC Hardware category includes brands selling products such as air PC screws, spacers, cooling accessories, etc. To perform our analysis, we grouped PC Hardware brands into four clusters, with Cluster 1 being the most successful in terms of detail page view year-over-year growth rate (DPVGR)/new-to-brand customer year-over-year growth rate (NTBGR) and Cluster 4 being the least successful.

Our analysis finds that top-performing PC Hardware advertisers (Cluster 1) had a 16.0X higher detail page view growth rate and a 13.3X higher new-to-brand growth rate in comparison to lower-performing advertisers (Cluster 4).

Top-performers

16X

Higher DPVGR

13.3X

Higher NTBGR

To provide advertisers with actionable insights, we used machine learning to analyze over 100 advertising attributes that contribute more or less to DPVGR/NTBGR. We then identified which attributes have the largest positive impact on the year-over-year growth rate of detail page views and new-to-brand growth rates. This article provides insights and best practices on the key attributes or strategies by quantifying the degree to which top-performing PC Hardware brands (Cluster 1) and lower-performing PC Hardware advertisers (Cluster 4) 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.

Top-performing PC Hardware advertisers ran Sponsored Products always-on campaigns throughout the year on Amazon.fr

In 2020, top-performing PC Hardware advertisers ran Sponsored Products always-on campaigns for an average of 46 weeks, compared to lower-performing PC Hardware advertisers who only ran Sponsored Products always-on campaigns for 22 weeks.

Number of Sponsored Products always-on weeks

46

Top-performers

22

Lower-performers

Learnings and best practices when using Sponsored Products

  • Keyword coverage: Use category keywords to help reach new audiences, and then use branded keywords to drive conversion.
  • Sponsored Products seasonal budgets: Shoppers’ browse and purchase behaviours have peaks and dips throughout the year, and synchronizing budgets to reflect this helps maximize return on investment (ROI).
  • Do not change promoted products too frequently: To support discovery and relevance, allow sufficient time for support to take effect and do not change promoted ASINs too frequently, such as daily or weekly.

Top-performing PC Hardware advertisers were 1.3X more likely to adopt Sponsored Brands and 8% more likely to use Sponsored Display on Amazon.fr

A second strategy from top-performing PC Hardware advertisers is adopting both Sponsored Brands and Sponsored Display more than lower-performing PC Hardware advertisers. Our analysis found that 31% of top-performing PC Hardware advertisers used Sponsored Brands in their campaigns compared to 23% of lower-performing PC Hardware advertisers.

Percentage of campaigns that used Sponsored Display

31%

Top-performers

23%

Lower-performers

Similar to Sponsored Brands, Sponsored Display was adopted 8% by top-performers and 0% by lower-performers.

Number of Sponsored Products always-on weeks

8%

Top-performers

0%

Lower-performers

Why use Sponsored Display?

  • Quick implementation: Sponsored Display is a simple, easy-to-use option that doesn't require a large budget or the ability to design your own ad creatives.
  • Efficient spend opportunity: Sponsored Display ads only show when your products are in stock and are the Featured Offer, and you only pay when customers click on your ads. Control how much you spend by setting your budget and bid per click.
  • Amplification possible when combined with retail deals: During events such as Prime Day and Cyber Monday, use Sponsored Display campaigns to highlight your product deals on product detail pages of similar products so customers won’t miss important promotions.

Top-performing PC Hardware advertisers have 2.1X more product reviews Amazon.fr

Customer reviews on Amazon serve many purposes, but in terms of increasing DPVGR and NTBGR year over year, we have identified two key reasons why customer reviews matter, and why top-performing PC Hardware advertisers are benefiting from 2.1X more customer reviews (19 reviews per unique ASIN vs. 9 reviews per unique ASIN of lower performers).

Top-performers

2.1X

More customer reviews per unique serial number

Why customer reviews matter

  • Customer reviews help inform customer shopping decisions: Customer reviews can help brands to stand out. If a product has more customer reviews, shoppers are able to gain insights that will help them make informed purchase decisions.
  • Customer reviews help create customer-centric products: Customer reviews help advertisers better understand their customers. Use customer reactions to improve products.

Learnings and best practices for customer reviews

  • If you’re a vendor: Use the Amazon Vine program. Based on a select group of Amazon shoppers helping fellow shoppers make educated purchases, this program can help boost review numbers.
  • If you’re a seller: 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.

Conclusion

As seen in our analysis, top-performing PC Hardware advertisers have been able to growth their detail page views and new-to-brand customers through (1) running always-on campaigns; (2) mixing investments between Sponsored Display and Sponsored Brands; (3) increasing and customer reviews and using customer feedback to improve products.

Methodology

We first used a supervised model to identify a list of attributes that help improve the composite score among 100+ media and retail advertising attributes. Specifically, we followed a five-step process to create a success metrics of detail page views and new-to-brand customers, and then identified the top advertising and retail strategies to help increase the success metrics with machine learning algorithms.

  • Select brands: 100+ brands in the PC Hardware category between in 2020 on Amazon.fr.
  • Create success metric: Calculated based on year-over-year growth of new-to-brand customers and detail page views.
  • Identify effective ad or retail actions: identified top actions to help increase composite score (actions that lead to higher year-over-year growth of detail page views and new-to-brand customers).
  • Group brands: Brands grouped by composite score (DPVGR/NTBGR) into four clusters ranked from highest to lowest performing.
  • Compare brand groups: Identified what strategies they used and quantify by how much top-performing brands (Cluster 1) increased year-over-year growth of detail page views and new-to-brand customers that lower-performing brands (Cluster 4) use.