Your Customer is Changing Their Buying Process. Your Pricing Process Needs to Change.
At the spring edition of the Professional Pricing Society (yes there is such a thing) pricing thought leader Craig Zawada challenged the audience with some provocative claims. Craig has been disrupting pricing for a couple of decades now. In 2004 he was a co-author of The Price Advantage. This book introduced some of the key frameworks for pricing strategy, value mapping (see this article for more on value mapping) and the pocket price waterfall. The pocket price waterfall is the standard tool pricing experts use when looking for profit leaks.
In 2010, Craig surprised the pricing community by moving from McKinsey to the revenue management and pricing platform PROS where he is now the Chief Visionary Officer (you can read more about this transition here). In his recent talk, he justified the ‘visionary’ part of his title with some important predictions.
His key insight was that changes to the B2B buying process plus our experiences as consumers are forcing us to change how we approach pricing. This provides a powerful lens to bring pricing processes into focus and make sure they are aligned with the buying process.
The key changes to the B2B buying process
- Most buyers are about 70% of the way through their buying process before they ever speak with a vendor, having done extensive research online.
- Procurement has gotten more sophisticated and powerful, and is generally better equipped to negotiate price than the vendor’s sales force.
- There has been a general acceleration in the speed of business, affecting everything from product development cycles to the speed of decision making, to willingness to change.
These three changes are having a big impact on how to price your products. Most B2B software is priced in one of two ways. The website provides some information on features and functions, maybe even a few case studies, and then potential buyers are asked to contact the vendor, sometimes after being asked to fill out a form.
The other option is a set of tiered pricing offers on the website, from which the buyer self provisions. Many companies use the second approach for smaller customers and the former for ‘enterprise’ customers. Both approaches have big problems in the new world.
Forcing people to contact you before providing critical price information, and then entering into a protracted sales process with lots of negotiation, slows down the customer buying process. As most salespeople have experienced, it can grind to a halt, and a slow decision often converts into no decision and no sale. Speed matters. Losing momentum kills deals.
The challenge with making your price public in a tiered pricing model is that you lose the opportunity to really understand your buyer and what is driving value. Web analytics will only get you so far. Even worse, a lot of value in modern ecosystems is driven by integrations and data sharing. In most cases, even with the help of applications like Zapier or Mulesoft, integrations require human intervention, generate costs and they should change your pricing (more on that in a future post).
Even the best-tiered pricing model is underpricing for some customers while scaring others away, who might have been won over with the chance of conversations. All of these challenges are getting worse.
Speed is the new currency
One of Craig’s key points at the Professional Pricing Society conference is that “speed is the new currency.”
One of PROS’ clients found that win rates went down 40% if a quote took more than 24 hours. Further analysis showed that price accounted for 67% of the time required to make a quote. The length of time it takes to generate a quote is emerging as a critical metric for pricing performance.
So how do we accelerate pricing? How do we get to a shared understanding of value quickly, without endless back and forth negotiations and pushback from procurement?
Craig’s answer to this question is that we have to make better use of pricing algorithms, that systematically connect price to value and demand. He went further than this to say that,
“People are beginning to trust algorithms more than they trust humans.”
This is a bold claim and as you can imagine many people in the audience pushed back. Media has been full of stories recently about the problems caused by content recommendation algorithms, the bias built into artificial intelligence and the impossibility of explaining how a deep neural network makes a prediction or recommendation. One of the hot trends in AI is XAI or eXplainable Artificial Intelligence. DARPA, the people who brought us the Internet, even have a project on this.
Before you dismiss Craig’s claim out of hand, think about the experience of buying a car. Some people like the negotiation process. But many of us, I am one, are a bit afraid of it. We know that the car salesman has a lot more experience with this than we do, is better trained and has more information (sort of like the procurement experts at a large company). Pricing transparency has become a value proposition in buying a new car.
There is an important lesson here. If the pricing algorithm is transparent (explainable) and makes sense, we are more likely to see it as fair than the outcomes of a high stakes negotiation. In many cases, a well-designed algorithm leads to a price that both parties see as being fair.
Ask yourself if there is an easy way to explain the algorithm behind your own pricing. The algorithm should have the following properties:
- Be easy to explain
- Connect price to value
- Calculate using easily available data
If your pricing algorithm has these properties, your pricing will be seen as transparent, consistent and fair. This is what today’s buyers are looking for. And by meeting these criteria it will also be a lot easier to meet Craig’s first challenge, the need for speed.
Mike Walsh, CMO at Reflektive, has gone through multiple pricing processes and has developed his own framework for assessing the situation and then developing pricing that is appropriate and effective. Learn more about his 4-step framework here.