Project realized for one of the most avant-garde school publishing players, with the aim of supporting teachers in the selection and adoption of the best textbooks for their students.
Description and Benefit
Officials of the sales network of a publisher specializing in school textbooks meet periodically with teachers and professors of schools in their area to update them on new publications of interest, and give them the opportunity to decide which texts to adopt for the following year. Each official is responsible for a very large territory, which can contain over a thousand schools.
To ease the work of the officials and help them focus their attention on the institutions with the greatest potential, we have developed an algorithm that takes into account several factors: the purchase history of the various schools, the previous interest of groups of teachers and the teachers’ level of interaction with the publisher’s online platforms.
From these data, Moxoff’s algorithm extracts an estimate of the interest level in the textbooks shown by teachers at various institutions for the upcoming school year. These predictions constitute a quantitative support that the publisher offers to its agents, in order to improve their work.
Data driven decision making
To realize this algorithm, Moxoff worked in close collaboration with the publisher’s sales network. Thanks to the suggestions collected, Moxoff has developed two functions able to satisfy both the needs of the sales department, related to the monitoring of sales, and those of the sales network itself to identify more quickly the teachers most engaged. This is a tool that integrates the commercial and human qualities of the agent: it helps him in orienting and planning his work better, like a faithful map to consult at any time.
- Decreased turnaround time, early identification of teachers most likely to adopt textbooks
- School support, the algorithm supports the replacement of books with outdated content with more up-to-date ones
- Greater efficiency in proporsals, qualitative improvement in formulating a supply that meets demand
