Predictive purchasing and cross-sell/up-selling (Schneider Electric)
Schneider Electric Norway AS has proposed master projects that will be co-supervised by them and will involve real and challenging ICT problems in their organisation. Part of the work will be done at their offices at Ryen.
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Predictive purchasing and cross-sell/up-selling
- Today, we are very reactive when it comes to project offers (what we sell to our customers). Typically, the customer will send us a list of product they need for their project and we will make an offer accordingly.
- When the customer does not know what they need or want, they use specialist (consultants) before they come to us, or they interact with our Sales representatives to define the scope of their work.
- Considering the enormous amount of information, we sit on, why aren’t we able to predict better what our customer should buy more proactively?
Scope of project
- Identify all existing sources of information, both internal and external
- Identify ways to structure the information so that it can be used to predict and automatize the “shopping list” of our customers
- Identify ways to optimize our pricing and discount strategy
- Identify ways to predict what should be proposed to customers, both in the same product family but also covering other offer types
- Identify ways to eliminate wrong purchasing or wrong scoping of projects
- Identify ways to speed up the quoting process but automatizing the selection of products required based on defined specifications
- Recommender system / statistical => Semantic model
This project is in the promising area of interaction between semantic technologies and data science. A student with an interest in either of these subject areas would be suitable for this project. Depending on interests, the project would consist of the design and implementation of a semantically-aware recommender system for a chosen set of data from Schneider Electric.