First, we applied revenue engine diagnostic to ensure a granular understanding of the client’s business economics. Simultaneously, we ran thorough desk research to get the complete picture of the logistics SaaS products market, eventually letting us figure out how our client compared to the remaining players. We were also hunting for market trends that would enable us to make sound predictions that we could further implement into our final recommendations.
Afterward, we run a bunch of individual in-depth interviews (IDI) and Focus Groups in cooperation with our research partners from one of the most prestigious universities in Poland. We identified the target group, which we divided into three categories. Our first objective was to determine if a given SaaS functionality was attractive enough for the customers to pay for it. Such action allowed us to understand the overall sentiment for each functionality our client had to offer. We identified which functionalities were perceived as table stakes and differentiators by the customers.
As a continuation of IDI, we decided to run a few Gemba Walks - we visited the actual warehouses of clients' potential customers. This approach allowed for a deeper understanding of the final customer’s everyday challenges, fears, and priorities to tailor communication against shortlisted SaaS products. Consequently, we could judge if the functionalities offered by our client were reflecting customers’ needs.
Lastly, we run a CAWI research with 600 participants to set the prices for the client’s SaaS products. For that purpose, we used the Van Westendorp pricing tool to uncover optimal price ranges. CAWI also helped us precisely understand the preferred subscription models and how different customer cohorts diverged in their willingness to pay for various functionalities.