Chris Mele is the managing partner of Software Pricing Partners.
In marketing, segmentation has traditionally been the name of the game, with marketers slicing and dicing their prospective customers by demographic, geographic, psychographic and behavioral criteria to form detailed buyer personas.
Buyer personas have important functions for marketing and sales teams. In software, I’ve observed that some leaders opt to use content marketing frameworks for pricing. But content marketing frameworks just don’t work for software pricing, because fundamentally, pricing is about quantifying and expressing value. Content marketing frameworks lead software companies down the wrong path, leaving them with complicated pricing that can cause sales and operational friction, tarnished brand reputations and irked prospects.
The Fundamental Flaw Of Applying Content Marketing Frameworks To Software Pricing
Marketing teams create buyer personas to hone in on the qualities of the various participants in the buying process, including their pain points. That way, marketing teams can communicate the value their companies’ products or services bring to those various participants in the buying process—and create appropriate messaging and content that feeds the top, middle and bottom of the marketing funnel. As for sales teams, buyer personas enable them to better understand who they are selling to and the problems that these personas are trying to solve.
Buyer personas are useful for marketing and sales teams. But when software executives try to use buyer personas to guide them with pricing, that’s when problems emerge. Buyer personas are simply the wrong tool for the job of pricing. Why? A key goal of buyer personas is to tailor messaging to effectively communicate the benefits of a product or service to target customers. By contrast, the goal of a monetization framework is to quantify and capture monetary value to achieve a company’s market adoption and financial goals.
Using buyer personas to set pricing creates unnecessary complexity in a software company’s packaging and pricing. It’s a bit like that friend who keeps interrupting your story with all sorts of unnecessary details that are important to them but that largely miss the main plot of the story.
The role of a monetization framework is not just to define value and quantify it, but also to sacrifice some aspects of the minutiae to achieve simplicity—while simultaneously accelerating revenue generation and profitability. When you use the wrong framework for the job of pricing, you can’t achieve simplicity. You can see the results for yourself. Just hop onto your favorite software company’s feature comparison page, and chances are, you’ll be able to count the number of features, such as dashboards and lists, that are limited in usage.
What does monetization gone wrong look like? Let’s take an example from the security space. One thing dominates the minds of CISOs: avoiding a security breach that can harm their companies. Say there are two companies seeking to buy new security software to get access to analytics dashboards. At company A, each person on the team needs extra dashboards to drive insights—and they are empowered to say so. The team concludes that company A needs a lot of dashboards, specifically 22. But company B is organized differently. There’s no democratic vote: The all-powerful CISO decides what solution the firm will go with. The CISO has a standardized set of dashboards the team heavily relies on. The CISO is convinced that the team can perform just fine with those standardized dashboards and that no extra ones are needed.
Marketing-Based Content Frameworks Can Spur Nonsensical Packaging
These dynamics may be important to marketing—but when applied to pricing, they can focus too heavily on minute differences between prospects, adding unnecessary complexity to packaging. Differences are important to account for, but only to an extent. Take it too far, and you could end up with packaging that seems arbitrary at best and unfair at worst.
If a software team takes its inspiration from buyer personas and gets stuck on every small detail of packaging, everyone will get mired in the muck, missing the forest for the trees. Going back to the example above, buyer personas focused on what the people working under the CISO needed might have yielded packaging that limited the number of dashboards. Software leaders and their teams would have likely spent days debating the cut-off of how many dashboards each type of customer should get, how they might upgrade, etc. Employees would have pulled reports and analyzed dashboard usage, running all sorts of analyses to support their numbers. In the midst of all of that, it would have been difficult for someone to step back and ask, “But why are we limiting dashboards for our users?”
Segmentation can get convoluted to the point where there are, say, 10 buyer personas. It might make sense to create content targeting those 10 personas, but it doesn’t make sense to have 10 different packages for all of those potential buyers. Nor does it make sense to take your existing packages and add numerous variables on top of them with the hope of setting up each of these groups for an upgrade down the line (the false assumption being that the nuances will pay off later, that the pennies will add up to millions). Why? It complicates sales operations and supporting systems, creates complexity in the company’s price book and SKU structure, infuses confusion into the company’s sales dialogue and demos and gives customers too many choices.
Consider a hypothetical SaaS solution with packaging as follows:
• Package (A) at $20,000 offers access to 15 analytics dashboards and 50 user licenses.
• Package (B) at $40,000 offers access to 20 analytics dashboards and 80 user licenses.
• Repeat for another eight packages with varying features.
Now, playing out the two different customers from earlier, say company A needs 22 dashboards but only wants 45 user licenses. Are they likely to go with package A or package B? Current dogma would propose they’ll opt for package B because they need those extra dashboards. However, our research shows the contrary—they’ll overwhelmingly go with package A instead, demanding discounts and special treatment. Customers do not wish to pay for things they feel they don’t need, especially when the transaction devolves into minute differences like a few dashboards.
Customers know the marginal cost of a few extra dashboards is minimal, so they tend to get irritated at the game software companies often play here. Worse yet, this is the point at which the software provider usually ends up paying the price. Salespeople, instead of focusing on solving prospects’ business problems, are forced into the weeds. They start picking apart needs like whether or not prospects require a certain number of dashboards, what exactly those extra dashboards will be used for and more. The result: elongated sales processes and poorer closing rates. Inevitably, sales dialogues sour, with prospects pushing back.
Complexity Can Make Customers More Willing To Walk Away
If salespeople are savvy enough to get over this hurdle, all it really means is that the customer is more likely to go without the additional analytics dashboards and purchase package A while looking for a solution that could give them those extra dashboards to fill the gap (which is likely an internal workaround of some sort). And therein lies the problem. Nonsensical packaging spurred by content marketing frameworks can actually discourage prospects from upgrading—and push them toward using alternatives in their workflows. That makes the original software solutions less sticky and creates complicated customer retention problems.
Moreover, overly complicated packaging causes SKUs (product codes) to skyrocket, leading to even more confusion about packaging and pricing internally. In an attempt to wade through that confusion and survive under a dysfunctional system, salespeople will start giving discretionary discounts. Discretionary discounts will further create friction in the sales process and erode transparency. When customers or prospects learn that others with similar use cases are paying less than they are or were offered, then they won’t feel like they are being treated fairly—and will be more likely to argue for a lower bill or walk away, both of which jeopardize a software company’s ability to maximize profitable growth.
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