Solver’s Kitchen—Installation and Service for Restaurants

Let’s assume Solver’s Kitchen (SK) is a B2B business serving restaurants throughout the United States. SK sells, installs, and maintains kitchen furniture and technology. It has several teams working in the field and is organized into sales and technical support units. Customers can choose from the following three main product lines:

• Material: Direct orders of materials without any service agreement.

• Project: Install projects for planning, supplying, and installing restaurant kitchens.

• Service: Contract with scheduled maintenance visits and on-call repairs.

SK grew a lot in its first years. Nowadays, sales teams face challenges in acquiring new customers as the market becomes more competitive and saturated. The management decided to switch the focus on cross- and upsell opportunities within the existing customer base. They hire us to support them in making more sense of SK’s data.

The business wants us to answer the following questions:

• How many of our past installation projects converted to service contracts? How many of those are still active? Which ones should we target first to grow revenue from monthly fees?

• What are promising cross-sell opportunities across product lines?

About the data

The restaurants dataset we use below is open data. See the Glossary in the “Appendix” section of this course for attribution. We faked all other tables using the mimesis Python package.