Most SaaS companies have more or less done away with monolithic pricing models, and instead, focus on value when packaging and pricing for impact. This is where Good-Better-Best packaging comes in.
Essentially, this is a tiered model that provides (a) a basic/pared-down offering at a competitive price (Good) to attract a new customer, (b) essential/curated features to keep the existing customer satisfied (Better) and, (c) a feature-laden premium version to increase spending by customers who want more (Best), as highlighted in this HBR article.
But choosing a tiered approach isn’t everything. This McKinsey article suggests that for a GBB system to work effectively for both price differentiation and sales velocity, GBB packages must be designed with well-defined customer segments. Each package must provide the target segment with a product it will be happy with, at a price it is amenable to pay.
But will GBB work for you? Here are some insights from Pricing Experts, drawing from their experiences:
Joshua Bloom, Managing Partner (North America) at Simon-Kucher & Partners has this to say, “There are different structures, like use case packages and so on, and there are lots of different ways to think about the traditional concept of packaging or bundling functionality that isn’t necessarily Good-Better-Best. To boil it down pretty specifically, Good-Better-Best means that there was one land-and-expand path for a customer to go through with it. It basically assumes that there is a natural level of sophistication that you can stratify your customers into, and they get there in one direction. It assumes that they start quite simple, and it is easy to say what’s next with their needs.
But that is not the case with every product portfolio. Some have multiple entry points for people to start at. Others have multiple point places where they can achieve a different level of sophistication needed to go in directions B versus C - which essentially breaks the Good-Better-Best model. We’ve seen often that the model works, but not for every company because all of them don’t have one land-and-expand path.
Good-Better-Best also implies that the answer is in having three tiers of packaging. Again, that is not always the optimal outcome. In some companies we’ve worked with, a simplified two package lineup makes sense. There are others where there’s one upsell path, but they need four or five tiers to cover all of the different segments of customers that they’re reaching. It is useful as a tool in the toolkit to be able to say that we have a playbook for how to think about good-better-best and set limits and fences between the packages — but it’s not the only packaging decision.
Our research shows that less than half of all SaaS companies have public pricing pages. If the optimal structure is not a Good-Better-Best lineup because your product portfolio has more complexity, you’re more likely to put that behind the firewall or have a salesperson walk you through it — because it’s more complex. I would say that the majority of companies that do not have published pricing are doing something other than Good-Better-Best.”
Johnny Cheng, a pricing veteran illustrates how Good-Better-Best didn’t work for Gainsight, during his time as Director, Product Marketing for the company, “In the mid-market space (at the time), Gainsight used a feature-based pricing model where it was just a Good-Better-Best offering — that’s it. You got a Good-Better-Best package for a set price of say $1,000-$2,000-$3,000.
They also had an Enterprise model, where it was just completely discrete pricing. Sales would basically make up a price. The top of the Enterprise deals worked fine with that approach because they were value selling, and they didn’t need much guidance.
But Gainsight was stuck in the mid-market segment, where they didn’t have the luxury of doing a return on investment (ROI) analysis of a five-year launch and building a discrete pricing model, all while wanting to sell on value and not leave money on the table. The Good-Better-Best model wasn’t even working because they were always selling the middle-tier package each time. Even when they sold the larger tier, it was at the same Average Selling Price (ASP) as the middle tier. Not only that, but the packages created a lot of shelfware, and there were constant down sells.
Gaisight’s software was extremely custom. Every company does CS differently, and every client needs their platform to be something different. It’s not cookie-cutter or like Marketing Automation, with very defined for-use cases. Everyone knew how to do that. With CS, no one knew how to do it! Everyone had their own view, their own brain. The Good-Better-Best approach didn’t really work.
For larger Enterprise companies — the top ones — if you did an analysis based on their price points, it was all over the place. They were selling stuff for like $5 a user or then $1,000 a user. It was just like the Wild West. Whatever money they could get, they just went for it!”
Natalie Louie, Senior Director of Product Marketing Strategy at Zuora (Former Head of Oracle Marketing Cloud’s Pricing Strategy and Operations), ties it all up with a consolidated view on key considerations on packaging and pricing well, “Companies often start with one offering, then start creating add-ons. Then you start bundling your add-ons and new features to create different packages to serve different market segments - eventually to get to a version of Good-Better-Best packaging.
Within packaging, we see the companies that are growing the fastest also package in usage SKUs, which are based on consumption or event data you are collecting. Usage-based pricing is very fair, and your customers only pay for what they use.
Depending on what type of product you have or if you are B2B, B2C or B2Every, you have to test and iterate to find the right balance of usage pricing to introduce. On average though, the benchmarks show that having 25% of your revenue come from usage-based pricing is a healthy mix to maximize your growth. And there can sometimes be too much usage pricing which can also lead to slower growth. Many companies start with looking at their existing data, products and services and can simply start out with a ‘good’ package.
At one of the smaller start-ups, I was with, we just had one package, which we started with. Later, we introduced a more robust package because customers started growing with us. They were outgrowing what they were habituated to using and we created a bigger package to increase our Average Selling Price (ASP).
Over time, as we moved upmarket, we decided we wanted to go back to our roots and service the start-ups that we used to work with. And then, we created a smaller package. When your package keeps growing, you create a bigger one, and then sometimes you go backwards and create a smaller package again. I have seen this motion a lot, when I was at Responsys, Hired and now at Zuora with all our customers.
While all of this is a good problem, you also have to think about whether you as a business want to go after those smaller companies again or keep it Enterprise. You have got to figure out what your target segment is and where to put your resources. But one thing is for sure — each market segment you’re serving needs to have the right packaging, pricing metrics and price points (including discount strategy) that delivers value to them.
My own take on which packaging model will work is based on certain considerations. A Good-Better-Best model is better suited for when there is a large number of customers/accounts available in the market to be sold, that is somewhat homogenous in their needs. For example, direct to consumer, digital-first companies in the eCommerce vertical. On the other hand, a modular approach would be better if the market was more heterogeneous. For example, when the same product is sold to insurance, telco, retail, and/or hospitality where all these industries have varying needs.
At the end of the day, there are no rules to be followed, but once you understand the approaches and your own value proposition, you can always arrive at the right framework by mixing and matching for the best effect.
Views as originally published in author Ajit Ghuman's book, "Price to Scale" (Available on Amazon.com).
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