Case study | Facebook and Google Ads for Insurance company
One of our clients, insurance company, made a request to increase the sales and make Google health check and UX/UI audit.
Project: Digital advertising for the insurance company.
Ads duration: 1 month (March 2018).
Task: Increase the number of online applications for travel policies, make UX/UI audit.
Tools and channels:
✓ Google Search ads and Google Display Network
✓ Targeted ads on Facebook
✓ Remarketing for Facebook and Google Ads
- The technical task for eCommerce was written;
- Customized eCommerce in Google Tag Manager and Google Analytics, UX/UI audit;
- A sales funnel was configured to detect the weaknesses of the site on which users left it;
- Based on historical data from Google Analytics, the target audience was identified, customized lists of remarketing were set up (cart abandoned, session duration);
- Customized Hotjar to track user behavior on the site.
- Launched search and remarketing campaign in Google Ads
- Launched retargeting campaign on Facebook.
- Comparing to the similar past period, the number of online applications has risen from 30 policies to 100.
- During the two weeks, our digital marketing agency made a daily optimization (minus-keywords, keywords, testing of different ad formats, which led to the improvement of ad quality metrics).
- The cost-per-click (CPC) was higher than average, which resulted in a 20% increase in CTR compared to the original metric, and also increased the frequency and position of the ad.
- With a well-targeted target audience, CTR for Google Display Network was 5%, which is higher than the average for this niche.
You can double your sales
without increasing the budget on ads
ROCKET CRO LAB is a full cycle ecommerce CRO agency.
Our works include health checkup of analytics setup, heuristic analysis, user experience research, competitive analysis to understand your position against competitors, develop Heatmap and Scrollmap reports to find where your customer is finding the interest and develop insights based on the data. After that, we do data backtesting. Then our team develops well-structured hypotheses, which are based on user behavior and start A/B testing based upon data and insights gathered in the research phase.