B2B Case Study – Adaptive Optimization and Revenue Modeling

Business Issue

A North American client with a global footprint was exploring options to deliver digital dashboards to a range of customers in the US and abroad.

The anticipated benefits to customers were that it would speed up management and maintenance of critical safety operations across verticals (especially during COVID shutdowns) and make communication more transparent.

The anticipated benefit to the producer was enhanced customer satisfaction, and at the same time increased sales/service productivity – reducing the time and frequency of client-site visits.

Dashboard configuration, pricing levels, additional  features, and new functionalities were all under consideration to determine the best mix from a customer point of view.

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Adaptive Conjoint Modeling (ACM) research was applied to identify customer’s optimal features, functional levels and pricing structures across companies in 4 core industry verticals.

ACM streamlines the response modeling task among time-starved professional respondents via a 2-stage approach. First, they eliminate items not relevant to their consideration set, and levels of benefit they would  never consider.

Then they are presented with a series their relevant options, varying levels of each option.

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The ACM model identified the relative importance of all features/levels to the selection decision (importantly, identifying unimportant things as well); identified optimal configurations per industry vertical; and predicted potential revenue along the price curves of industry segments.

Based on results, the client launched their “MVP” dashboard to the customer segments /industry verticals identified as the most viable and willing to pay the break-even price. 

An additional key deliverable  was a simulator the management team could employ to predict different outcomes, enabling data-driven decisions into the future.

competitive pricing
revenue per vertical