.jpg)
Net Conversion and client achieve a 42% increase in ROAS by redefining geo-targeting based on sales trends.
As an analytics-first company, Net Conversion is persistent in trying to answer your most complex and strategic questions using our in-depth data analysis. By doing so, we are able to go beyond the basics with business intelligence insights with cluster, propensity, sentiment and root cause analysis, among others. Particularly for our local entertainment water park client, we wanted to experiment expanding their geo-targeting strategy to push high conversion rates and reach a more qualified audience with the same budget currently in place. The question was, could we pinpoint higher saturated geo locations that could in turn have a higher conversion rate for our strategy?
Objective
- Optimize client’s geo-targeting within Orlando to increase ROAS.
- Implement advanced geo-targeting across our other location specific accounts.
Implementation
For our entertainment water park client, our media dollars have been spread across the Orlando, Lakeland and Tampa areas. After deep analysis of performance per region we’ve gradually allocated more funds towards the general Orlando area as a result of strong performance across our omni-channel strategy and overall, website conversion rate.
With Orlando making up such a high percentage of spend, we advised the client to provide our team with a zip code report of their sales, to better refine geo-targeting within the top areas of Orlando, as opposed to just targeting the Orlando DMA as a whole.
After receiving the zip code report of their sales, the team uncovered some interesting trends. 55% of the sales were from people living within 30 miles of the park. The closer someone lived to the park, the higher the penetration of sales to the population, which in this case was households with children.
Based on this we decided to do a cluster analysis to ensure there was a correlation between geolocation and conversion rate. Once we rolled up all of the zip codes to their respective city, we found a strong correlation between that city’s distance from the park and conversion rate. The closer you are to the park, the more likely you are to purchase tickets.
Results
Post cluster analysis, the team adjusted our omni-channel strategy based on the correlation found in their analysis. After making adjustments to focus on the closer areas, our Facebook ROAS increased +42%. Not only did this strategy shift boost ROAS, but it also increased click-through rate to the website by +13%. Overall our goal is to continue to find ways we can strategically analyze data we already have access to, to further increase the efficiency of our strategies for our clients.
Net Conversion has the resources to run a similar type of analysis across a variety of our accounts. If you’d like for our team to run a similar test with your account, let us know!
.png)
.png)
.png)
.png)
