AI Case Study

First Book increases repeat sales by 331% and revenue by 35% by targeting customers who are more likely to do repeat business using machine learning

First Book, a non-profit firm which sells books at a discounted rate to low-income families, turned to machine learning to better segment and understand publishers and buyers. They could then identify organisations which are more likely to do repeat business using machine learning and target them effectively achieving 331% increase in repeat sales success rate.

Industry

Consumer Goods And Services

Entertainment And Sports

Project Overview

Using Persanalytix, First Book identified four personas based on demographics and psychographics. They could use response rates from customers to predict which customers are most likely to respond to different marketing channels. This insight enabled them to refine messaging to be more impactful and reduce unwanted email and 'unsubscribes'.

Reported Results

According to the company:

* 331% increase in repeat sales success rate
* 92.97% accuracy predicting individual customer spend
* 35% increase in sales

Technology

"Persanalytix® classifies your customers and prospects into Personas defined by their scientifically predicted propensity to respond favorably or unfavorably to your engagement efforts. "

Function

Marketing

Channel Marketing

Background

"First Book is a nonprofit organization which runs a book bank and retail bookstore. The First Book National Book Bank takes books donated by publishers and distributes them to churches, schools and organizations serving children with special needs. First Book Marketplace allows qualified subscribers from low-income families or disadvantaged schools to buy books at a discount."

Benefits

Data

"Marketing channels, offers, campaigns, CRM, email, direct mail, social media) to specific transactions or customer responses.
Integrates data from standard sources such as Salesforce, Constant Contact, Facebook, MailChimp, HubSpot, and Blackbaud"