Three Pricing Predictions for 2018 (and How to Use Them to Your Advantage)

January 2018 already! Your inboxes are no doubt full of predictions for the New Year, so let me suggest why you should care about pricing predictions. Pricing is where all the different aspects of your offering (be it product or service), your marketing plan, your sales process and your customer, converge. If you can’t agree on a price with a customer, well, then you do not have a customer. Long a rather geeky sub discipline of marketing, changes in business models and technology have made pricing a locus of innovation. Pricing will be the critical marketing discipline over the next five years, and what was once the domain of experts is becoming of general interest. So how will pricing change in the coming year, and how will those changes impact your business? Here are three predictions.

1. The pace of commoditization will accelerate

Commoditization is often seen as a bad
by pricing experts. We like to see lots of meaningful differentiation so that we can apply value-based pricing and win our clients’ higher revenues, or profits, or market share. One cannot apply value-based pricing to commoditized offers. What does commoditization mean? Basically, that there is widespread understanding of an offer, how to deliver it, and market acceptance of the value proposition. It means that the innovation has been a success. Think of some typical commodities – electricity, audited financial statements, bank accounts, Internet access, dish soap. We all know what these are, how to buy them, and what to expect. Commoditized markets take three forms. If you are in a commoditizing market (and you will be at some point) you need to understand which one your own company will fall into.
  1. Captured by regulators (or their proxies, the standards bodies)
  2. Priced by markets (there is an exchange where the commodity is bought and sold)
  3. Brand driven (widely divergent prices for the same commodity based on the brand power)
There are a number of strategic options based on which paradigm captures your category. We will explore these in a future post.

2. Predictive analytics will get better at predicting

Predictive analytics is getting better and better at predicting. There are several reasons for this: the rapid advances in machine learning, the wider availability of data and the integration of value and usage models. I suspect this will lead to the emergence of two new parameters: predictive engagement (your engagement metric will be an equation that predicts future engagement) and predictive value (you will have a set of equations that predicts the value of a solution for a specific customer). As predictive engagement and predictive value are difficult to calculate, we will be using the generic machine learning services (from IBM, Google, Microsoft, Amazon, HP, Opentext, etc.) to build models. What will be most interesting is the relations between predictive engagement and predictive value! The ability to predict use (engagement) and value will open up many new pricing models. This will be exciting to watch.

3. Performance-based pricing will become more common

There are some very smart people who have come out against performance-based pricing for B2B SaaS companies. See for example Tomasz Tunguz on The Challenge Of Performance Pricing For SaaS Companies. I think he got this one wrong. The main argument against performance based pricing is not that SaaS companies will have less predictable revenues (some investors believe that subscription models have made revenue more predictable, although there is little actual evidence for this). The problem is that buyers need predictability and are cautious about committing to open ended contracts. In many procurement and financially driven organizations budgeting trumps any notion of value. Increasingly, we can address this objection by applying predictive analytics to tell buyers how much of a service they are likely to consume and how much value they will get from it. Companies that invest in predictive engagement and predictive value will have a major competitive advantage. They will be able to reduce uncertainty and take on more risk, shrinking the risk discount that holds down SaaS prices. As performance-based pricing supplants fixed pricing we will enter into a more dynamic environment where prices are constantly being adjusted to reflect business conditions. The winners will be the companies that make best use of data and machine learning to reduce risk for their customers.

Trends to Watch

There will be several topics that get a lot of attention this year, but will likely not have that much immediate impact on actual pricing work. Two that come to mind are behavioral pricing and FairPay pricing. This does not mean you should ignore them. It is important to begin studying their applications to your business and finding places to experiment. Behavioral pricing is the application of prospect theory and its extensions to pricing. If you have not already done so, read Thinking Fast and Slow by Daniel Kahneman. If you have already read it, read it again and think about how to apply the insights to pricing. FairPay pricing is a radical innovation in pricing where instead of setting prices you invite buyers to set the price based on their notion of fair pay for fair value. There is a book on this too, FairPay by Richard Reisman. Before you dismiss this out of hand, see where you could test it in your own business. If you want to build your own pricing expertise the must read book is The Strategy and Tactics of Pricing. The Sixth Edition, by Tom Nagle and Georg Müller, came out late last year. The new edition adds material on behavioral economics, offers a more robust process for price setting and has a greatly revised chapter on Creating a Strategic Pricing Capability. This book commands a high price, which reflects its value! Make 2018 the year in which pricing becomes a strategic lever that helps you drive up your own performance while delivering more value to your customers.
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