In the rapidly evolving software industry, determining the right pricing strategy for adding new features is crucial to staying ahead of the competition and driving market success. Features such as advanced AI capabilities and enhanced cybersecurity tools improve user experience, streamline processes, and provide previously untapped insights from data. However, this introduces important questions about how to price these features effectively without alienating customers or overcomplicating the product offering.
Let’s examine this by looking at a software company that uses a Good-Better-Best pricing structure. After conducting an in-depth analysis, they determined that the financial value of integrating an AI feature into their software is $2 per license.
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Possible Pricing Approaches
Companies could consider selling this feature to customers in two ways. One approach is the “Patchwork Approach,” where the feature is offered as an add-on priced at $2 per user (see Figure A). Alternatively, the feature could be bundled into existing pricing tiers, as illustrated in Figure B.
As shown above, while maintaining the same customer base breakdown, bundling the AI feature into the “Better” and “Best” tiers would generate a 15.2% increase in overall revenue (from $755 to $870). However, if the company offered this AI feature as an add-on for $2 per user, it would need to cross-sell to at least 58% of users across its pricing tiers to generate the same level of financial benefit as bundling it into the packages.
This conversion would require a considerable amount of sales effort, including sales calls and marketing campaigns, increasing both time and cost. While this strategy might seem easier to implement and roll out, the fragmented approach can confuse customers by diminishing the clarity of the product offering and requiring greater effort from the sales team to generate immediate benefits.
By using the bundled feature approach, the company not only enhances revenue but also simplifies the product lineup, making it easier for sales teams to upsell customers in the ‘Good’ tier to upgraded options that include AI functionality.
Breakeven Scenarios: How Many Customers Would Need to Trade Down?
There is always the risk that some customers, not interested in the added AI functionality, will resist the price hike and trade down to the lower-priced tiers. This potential “trade-down” risk is particularly significant for customers in the ‘Best’ tier.
As shown in Figure C, bundling would only backfire if nearly 40% of ‘Best’ tier customers and 24% of ‘Better’ tier customers downgraded to the lowest offering. Any percentage of downgrades less than 40% in the ‘Best’ tier or 24% in the ‘Better’ tier would still result in a net benefit, further validating the strength of this bundling strategy.
Key Considerations
Timing is also crucial. Introducing new features alongside annual price increases helps justify them effectively. This strategy allows companies to present the added value during routine price adjustments, simplifying the sales process and making the price increase feel more justifiable to customers.
While bundling may seem like the most effective pricing strategy for introducing new features, it’s crucial to first build a solid foundation of customer segmentation within your existing tiers. Without this, bundling can result in misaligned pricing, customer confusion, and missed revenue opportunities, ultimately weakening the impact of your pricing strategy. However, when new features are bundled based on clear customer segmentation and paired with regular strategic price increases, the result is a streamlined pricing structure, improved customer satisfaction, and steady revenue growth.
