AI Case Study

HMH, the publishing house, forecasts demand to optimise pricing quotes and define salesforce KPIs using machine learning

Houghton Mifflin Harcourt uses machine learning to identify new sales leads and create personalised KPIs for sales associates and adjust prices and quotes in real-time from historic data.

Industry

Consumer Goods And Services

Media And Publishing

Project Overview

"HMH publishes at a speed which their legacy sales tools and performance software couldn’t keep up. To solve this, they brought in Salesforce-Einstein along with Wave Analytics to analyze the data, compare performance to forecasts and find new deals.

Sales reps found they could use it create their own KPI monitors and build price quotes on the fly during sales meetings. "

Reported Results

According to the company:

* Demand accuracy increase through not quantified
* ROI predicted to be 200% in 5 years
* Break-even point reached in less than a year

Technology

Function

Sales

Sales Management

Background

HMH is a publishing house in the US whose content is consumed by more than 50 million pre-K to 12th-grade students in more than 150 countries

Benefits

Data