Destination Arrival Prediction Drives Lower CPA
Net Conversion worked alongside our DMO client to generate interest and drive demand to partner hotels by prioritizing shifts in geo-targeting and messaging based on destination demand.
Net Conversion is partnered with a Destination Marketing Organization located here in Florida. The organization’s primary goal is to generate interest and drive demand to partner hotels. The DMO was faced with a challenge in 2022 in attempting to recover to pre-pandemic 2019 performance levels despite lingering pandemic effects and recent economic uncertainty.
As part of their growth plan, our DMO client was tasked with continuing to increase destination arrivals year over year with a distinct marketing strategy that would overcome external factors affecting the destination as well as the broader industry.
The organization’s primary goal is to generate interest and drive demand to partner hotels. Ideally, our DMO client would like to reach 150K partner referrals linkouts and 16k email sign-ups while maintaining website visitation volume year over year.
- 150K Partner Referral Link-Outs
- 16K Email Sign-Ups
To reach our clients goal, the team prioritized keeping a close eye on economic trends that were shifting the target areas’ destination demand on a daily basis. Based on our extensive experience with marketing for DMOs, our team quickly identified the biggest factors that affected destination arrivals.
We supported our DMO client in exceeding their partner referral goals by prioritizing shifts in geo-targeting and messaging based on destination demand. As of Sept. 15th, 2022 (not EOY), we’ve assisted them to hit 213K partner referral links, +42% higher than their initial goal, and 20k email sign-ups, +25 higher than their original goal.
Partner Referral Link-Outs
NC Next Steps
However in response to our secondary analysis and goal, the team has proposed a new strategic plan for 2023, with hyper-focus on quality LOS linkouts. After exceeding our client’s partner referral goal by more than 60%, the team is working on positioning itself to produce a greater quality of partner referrals using the model above. As a part of the normal targeting the team does, there will be campaigns devoted to these findings, targeting the regions identified to have the lowest CP LOS. This altered approach will result in an increase in bed tax collection through longer stays which ultimately fulfill the partners goal. Through discussions with the DMO’s team, we have identified KPIs for these campaigns and the lens in which we view success.
To reach our DMO client’s goal, the team prioritized keeping a close eye on economic trends that were shifting the locations’ destination demand on a daily basis. By analyzing demand shifts in each key feeder market, the team shaped their strategy around weekly geo and messaging optimizations to reach the audiences that were showing the most demand across all channels. Our nimble strategy allowed us to hit the partner referral goal earlier in the year than intended (month 8 vs month 12), and hit our email-sign up goal in 10 months time (vs 12 month expected. Our team was eager to level up the strategy and drive incremental destination growth aside from the client’s goal and external factors.
Based on our extensive experience with marketing for DMOs, our team quickly identified the biggest factors that affected destination arrivals. Using Arrivalist Arrivals data and our Google Analytics data, we found that there is a strong correlation between Website Linkouts to partner hotels & Arrivals to the location. Due to this correlation, we knew we needed to implement a data-driven optimization strategy that would result in increased website linkouts from the most qualified audiences.
Our current media optimization methodology for the DMO client assumes all partner linkouts are created equal. However, when analyzing the quality of linkouts, we were able to identify a secondary correlation where average length of stay increased, as distance traveled increases. Therefore, to further enhance the quality of linkouts driven from paid media, our analysts built a new methodology to leverage Arrivalist’s data to account for average length of stay, creating a blended metric – Cost Per Length of Stay.
Based on historical trends across Google Analytics, Arrivalist and official bed tax collections, Net Conversion is able to predict the number of arrivals to the destination.