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Looking back at pricing predictions for 2018


Back in January, I made some predictions for 2018 over on the OpenView blog.


1. The pace of commoditization will accelerate

2. Predictive analytics will get better at predicting

3. Performance-based pricing will become more common

OpenView’s Kyle Poyar had this to say at the beginning of the year.

“Companies Pay Attention to Pricing (Finally)

Kyle Poyar, Director of Market Strategy

2018 will be the year that companies finally pay attention to pricing. After all, it’s fundamental to how businesses make money and is a SaaS company’s most efficient profit lever. Yet, 53% of companies have no one on their team dedicated to pricing, even if it’s just one component of their job. Worse still, only 14% consider pricing before deciding whether to build a new product. This leads companies to miss revenue targets and waste precious product and engineering resources. But in 2018, this is destined to change. Investors and executives will wake up to the amount of money they’re leaving on the table by failing to focus on pricing, and finally take steps to address it.”

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So, how did we do? Forcing myself to answer this question reveals that these are not very good predictions as it is hard to test them. If they were bets on, they would have been rejected as being unverifiable. I will do better for next year predictions! Still, it is worth looking back and reflecting on the predictions.

1. The pace of commoditization will accelerate

Commoditization occurs when there are many acceptable substitutes for any offer. It is driven by standardization of offers, whether through technical, procurement or dissemination of best practices. Information sharing and transparency contributes to this standardization.

So is commoditization becoming more common and is the pace at which it occurs accelerating? Anecdotal observation suggests that this is indeed occurring. Our customers are certainly concerned with this. One of the main reasons they contact us is commoditization and its associated pricing pressures. Pure play offers, whether data or products or even conventional professional services, such as those offered by lawyers and accountants, are increasingly easy to copy.

It is more difficult to commoditize a solution than a simple product. This is especially true when the solution combines software, data, professional services and hardware (as in the typical Internet of Things application). Our larger clients are mostly moving towards solution centric growth. This brings its own pricing challenges.

2. Predictive analytics will get better at predicting

There has been a lot of buzz this year about deep learning and artificial intelligence. This has been building since 2007, when Geoffrey Hinton and his team published a series of astonishing papers that directed artificial intelligence research towards deep learning. 2018 was the year AI became a required part of every business strategy. Gartner put pricing near the top of the hype cycle.

Gartner Hype Cycle for Emerging Technologies 2018

Gartner is suggesting here that it will be another 2 to 5 years before deep learning and neural networks reach the plateau of productivity. In strategic terms, that is not long at all. How will this impact pricing?

Begin by asking how it will impact value creation, differentiation and commoditization. AI alone will be table stakes in any application or solution that can collect data. It is the data that is likely to drive value and differentiation and not AI. One of our customers claims to ‘touch more patients across more disease states than any other company in the world.’ If that company can reliably harvest that data, dealing with the data privacy and ownership issues, and find patterns within and across disease states it is likely to find itself in a dominant position. AI strategies need to be data strategies first.

For pricing itself, better prediction means reduced risk. We don’t always realize it, but prices, especially B2B prices, come with a risk discount. There is always a risk that the solution will not provide the anticipated value so the price has to be reduced to reflect this risk. More accurate predictions about value means that, in general, prices can go up. It may be that the downward pressure on prices from accelerated commodification will be countered by upward pressure from decreased risk.

3. Performance-based pricing will become more common

The risk discount can be completely eliminated by performance-based pricing. In this pricing model, the seller is paid based on actual performance. Risk is transferred from buyer to seller and prices go up. What will make this possible? Well, better predictability for one. One reason that sellers resist performance-based models is that there are too many factors beyond their sphere of control. The risk higher for the seller than the buyer, so rather than risk discount pricing, performance-based pricing comes with a risk premium. For this reason it has been most popular in areas where the seller (vendor or provider) is almost completely in control of the outcome. Many large outsourcing and managed services contracts have a large performance component in their pricing.

For performance-based pricing to become truly common we will have to get a lot better at teasing out the causes of performance differences and controlling for them. Fortunately, there is good work being done in the area of causal modelling by people like Judea Pearl. It will probably be ten years or so before this work starts to change how we price things, but it is worth exploring it now.

So, I would give myself the following grades on these predictions:

  • Accelerated Commoditization: A- (accurate but could use more data)

  • Better Predictions: B+ (probably accurate but a bit early)

  • Performance-Based Pricing: Incomplete (student has not yet completed course work)

For some thoughts on 2019, please go over to OpenView Labs and see our post on pricing resolutions for 2019.

We will make our pricing predictions for 2019 in January.

Have a happy holiday season.

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