Improving clicks-through-rates based on insights from top FinServ advertisers
By: Eric Tutlys, Analytics and Media Manager
In a 2019 study of more than 50 brands in the financial services (FinServ) category (insurance, brokerage, credit cards, and banking) advertising with Amazon, we found that top-performing advertisers saw, on average, 2.9x higher click-through rates (CTR), 1.5x higher daily reach, and 1.6x higher six-month rolling reach than other advertisers. They also made more use of three key advertising strategies:
- Always-on campaigns
- Audience remarketing
- Diverse ad spend
This article provides insights on these strategies and recommendations for improving them.
Top-performing advertisers delivered 6% more impressions than other advertisers. Additionally, top-performing advertisers ran always-on campaigns for 25 weeks (for each six-month period), while other advertisers ran always-on campaigns for 14 weeks (for each six-month period).
Top-performing advertisers were 6x more likely to use audience remarketing than other advertisers.
FinServ advertisers should consider remarketing tactics because it can help drive CTRs, consideration, and conversion. Remarketing can also help build customer loyalty. To improve remarketing success, advertisers should consider:
Top-performing advertisers used a minimum of four ad products and inventory types across desktop display, mobile display, tablet display, Amazon DSP, Streaming TV ads, and audio, while other advertisers used only two products and inventory types.
We recommend FinServ advertisers consider diversifying their ads across multiple ad products and inventory types because it can help form a full-funnel strategy that helps you reach today’s omni-channel shoppers. To build awareness, try expanding reach via Streaming TV ads, audio ads, and display or online video ads through Amazon DSP. If done correctly, advertisers can increase reach across multiple channels.
We analyzed over 50 advertisers in the FinServ category in the United States in 2019. The FinServ category includes advertisers in insurance, brokerage, credit cards, and banking.
We created a composite score of CTR, daily reach rates, and six-month reach rates. The composite score includes CTR, average daily unique reach, and average six-month rolling unique reach. Daily reach is a measure of daily messaging strength, while six-month rolling reach is an approximation of total audience reached.
We then identified the top advertising strategies to help increase the composite score with machine learning algorithms (Stepwise Linear Regression and subject matter expert suggestions are used to assign features weights).
How does the clustering work?
We labeled advertisers that ranked in the top 50% across all three components as “one,” and otherwise as “zero,” We then applied an XGBoost classifier to identify which features and with which weights best predict these labels. In doing so, we considered Amazon Ads or retail actions as features such as ad product usage intensity and mix, timing of advertising support, tactics of targeting, creatives and placements.
Using the identified features and weights above, we then applied a k-medoid clustering algorithm to classify advertisers into clusters. Note that we classified advertisers by their actions rather than by the components of their composite score. Next, we ranked the final clusters by their composite scores from high to low. Cluster 1 is the most successful cluster with the highest composite score, and Cluster 5 is the least successful.