Situation
Our customer, a retail membership chain wanted to maximize ROI on spend in two ways:
- Optimize new member acquisition through online ad campaigns.
- Identify ideal sites for a new location, with minimal competition and a large target market.
We set out to answer a few questions for them:
- How can we predict if a member/prospect will join a location?
- What’s the best site to invest in a mew physical location?
- Where to spend marketing dollars to get most output?
Solution
We had data from our customer about the target member profile (including age, income, gender and cancellations/rejoin data). Using this we collaborated on a propensity model for a member and estimated cost per acquisition for new members.
By combining census data, location data (including competing chains) and target member model information, we were able to deliver an application that:
1. Segmented target areas
2. Enabled optimizing target member zones by location, number of prospects and cost per acquisition of new members
3. Identified target areas for new locations of the chain
Outcome
Overall, these outcomes improve prospect conversion accuracy, expand market reach, optimize marketing spend, identify ideal locations, elevate sales effectiveness, and drive sustainable growth and profitability. With the AO Platform and Easy Answers, businesses can achieve superior targeting and conversion rates, ensuring long-term loyalty and success.
Reduced Customer Acquisition Cost(CAC)
- Better customer targeting
- Visibility into new investments
In the future, we can:
- enrich the models to optimize for many other variables
- add more prospective member data from external sources such as Experian
- create event based insights based on news, weather, etc.
