Driving cross-sell conversion rates with AI
Download the 23-page whitepaper today, for free
What you'll learn in the whitepaper
The methodology, data, and technology used to reach a 33% lift in conversion rates for Mass Save's outreach campaigns.
The customer latency problem
If you’re a company selling a considered consumer purchase, generating more revenue from your existing customer base is crucial. The biggest challenge is identifying and targeting customers who are actually likely to engage with your cross-selling initiatives.
Netflix and Amazon use AI to make shopping suggestions and movie recommendations based on past behavior. Similarly, you can use the same type of machine learning predictions to identify latent opportunity within your customer base.
Demographic, psycho-graphic, financial, and property data on ~250MM US individuals and ~125MM US households that Faraday compiles from a range of public and private sources. Using name and address, we match this massive database with your customer data, which forms the basis for the training set used to train machine learning models.
Random decision forests are a technique in machine learning. Understand the process involved in training and validating the predictive models used to optimize conversion rates on every outreach campaign.
33% increase in conversion rates. This boost put Mass Save on track to save $13,000 in outreach costs and $311,000 in projected sales costs.