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Case Study: Software Company: Pricing Optimization


Software Company: Pricing Optimization

An interview with Stefan Boedeker

The Company

A prominent financial software manufacturer.

The Challenge

The manufacturer had no real product-pricing scheme in place. It would launch individual products without a way of optimizing the cross-selling or bundling of these products with respect to pricing. The prices were not derived via any scientific pattern, but instead were created based on an ad hoc assessment of what individual teams responsible for each product thought the market would bear.

The Solution

BRG experts were retained first to do an economic analysis of the competitive landscape and identify key drivers for cost and revenue in this specialized software market. This market study, the economic analysis, also included an overall product-demand forecast that looked at the capacity this software manufacturer was able to deliver.

The next step was an econometric numbers-based analysis for which models were developed that assessed and quantified simultaneous impacts that identified key drivers in the case where products were bundled. That was put into an analytical decision tool that the company could use on a continuous basis to update its prices. The pricing updates were dependent on the competitive landscape and on actual consumer purchase decisions and elasticity, which was particularly important for identification of cross-selling and bundling opportunities for existing products.

The Result

The client now had a tool to bundle and price a completely new line.

These actions also centralized pricing decisions under finance, which had been a decentralized and somewhat politically loaded process. From a corporate management view, it was a huge improvement to move the control of pricing into the finance department, so they could control costs, know where the money was going, and tie it directly back to revenue generators.

The advantage of the modeling approach in this scenario is that users can measure the effectiveness of what they're doing by centralizing and automating a pricing function. This stands in contrast to an ad hoc or even siloed approach, where individual teams are responsible for certain products or aspects of products. Teams do their own thing, and at the end of the day, it's hard to measure how much that really costs the company and how much could be saved or reallocated.