By Charlie Pope
One of the fastest ways to drive revenue growth and margin is by optimizing product bundling and pricing. Most B2B companies recognize this but sub-optimize their ability to grow profitably when they ask the wrong questions. When designing product bundles and setting prices, teams often ask:
If these are the questions that come to mind, you’re in good company. However, you’re likely leaving a lot of money on the table. The problem with relying on market scans is that current offerings may not reflect the evolving needs of various customer segments. Trying to determine the price that’s low enough to win the deal completely ignores what your competitive advantage is or could be. And pricing with a “cost plus” approach causes us to ignore the nuance related to customer willingness to pay (losing volume or upside that could otherwise have contributed incrementally to profits).
To maximize contribution dollars from your existing product portfolio, here’s what you should be asking:
Optimal customer targeting requires a deep understanding of your customer segments and their respective buying behaviors. Axiom uses powerful statistical methods such as clustering algorithms to identify demographic, geographic, psychographic, and other hidden dimensions that are the most powerful predictors of buying behaviors. The beauty of using machine learning tools for this process is that we often uncover hidden relationships between segmenting dimensions that would otherwise go unnoticed. The outcome is a refined customer segmentation model that will enable optimal bundling and pricing decisions.
The key here is to quantify the economic value “left on the table” by simulating the outcomes of pricing products and bundles at various levels. Axiom applies predictive algorithms to firmographic and transactional data to test large numbers of price/bundle combinations and score configurations by segment. Once these high-value configurations have been identified, additional interviews with customers and internal stakeholders are used to “gut-check” the analysis and ensure the findings stand up to real-world logic.
To answer these critical questions, Axiom leverages an advanced statistical method called conjoint analysis. Conjoint methodology yields unbiased insights into value perception by asking customers to signal their preferences between various products and packages. This approach generates a rich data set which we analyze to uncover optimal solution configurations (bundles). The analysis also provides guidance on price points by quantifying the relative amount of “utility,” or economic value, that customers associate with each product tested.
Axiom leverages expertise in go-to-market strategy as well as deep data science and behavioral science capabilities to unlock value for clients. If you would like to learn more, let’s chat today about your organization’s bundling and pricing strategy.