Enhancing Sales Efficiency through AI
Helander, Elmeri (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025052616345
https://urn.fi/URN:NBN:fi:amk-2025052616345
Tiivistelmä
The objective of this thesis was to study and propose a practical AI implementation concept that reduces administrative burden and empowers Sales teams to focus on customer value. The case company is Saint-Gobain PAM Finland, a local sales branch of Saint-Gobain PAM, which is a subsidiary of the Saint-Gobain Group. PAM business specializes in solutions and products that manage the flow of water. AI needed to be researched, as it might potentially provide a competitive edge for the case company or, on the contrary, the competitors utilizing it.
The study was conducted as applied action research, and it stresses the development in co-creation with the stakeholders. The topics of efficiency and workload were examined by defining challenges in the current state by the 22-participant stakeholder survey, interviews with 6 key stakeholders and analysis of operational guidelines for Sales. The main challenge highlighted during the analysis was the customer request fulfillment time, which depends on multiple work processes in the sales workflow.
The theoretical framework focused on the challenges and possibilities of AI to tackle the identified challenges in sales. After theoretical knowledge was examined, a round-table discussion with 7 key stakeholders was held, collecting ideas and suggestions for the initial proposal. A validation session was held with the company CEO to validate and further develop the initial proposal into a final proposal.
The outcome of the study was a concept for AI implementation suggesting two possible places of investment for AI solutions: Pricing and Product recommendation to support investment planning. The concept value is to support strategic investment decisions in AI adoption. If implemented, the business impact should be faster customer request fulfillment time and less need for manual data handling.
The study was conducted as applied action research, and it stresses the development in co-creation with the stakeholders. The topics of efficiency and workload were examined by defining challenges in the current state by the 22-participant stakeholder survey, interviews with 6 key stakeholders and analysis of operational guidelines for Sales. The main challenge highlighted during the analysis was the customer request fulfillment time, which depends on multiple work processes in the sales workflow.
The theoretical framework focused on the challenges and possibilities of AI to tackle the identified challenges in sales. After theoretical knowledge was examined, a round-table discussion with 7 key stakeholders was held, collecting ideas and suggestions for the initial proposal. A validation session was held with the company CEO to validate and further develop the initial proposal into a final proposal.
The outcome of the study was a concept for AI implementation suggesting two possible places of investment for AI solutions: Pricing and Product recommendation to support investment planning. The concept value is to support strategic investment decisions in AI adoption. If implemented, the business impact should be faster customer request fulfillment time and less need for manual data handling.