Pricing is an historically data-centric discipline. And pricing consultants spend a lot of time crunching numbers and building models like price distribution graphs and pocket price waterfalls – useful approaches to answering some basic questions about pricing like:
- “How do we segment our customers by price?”
- “Are some of our customers getting exceptionally good (or bad) deals?”
- “What price are we really getting (the pocket price – the amount of money we put in our pocket)?”
- “How do discounts and off-invoice concessions impact our actual price?
Internal data, which you can harvest from sales and invoicing systems, can be used to answer the above questions. Putting all of this information into a pricing management system for analysis is a good start. But, in today’s world, it isn’t remotely sufficient. The move to cloud-based solutions, subscription pricing models and IoT (Internet of Things) have opened vast new realms of data that can and should be used to improve pricing.
So what does the new pricing data supply chain look like? It uses formal models for value, price and usage (or engagement) and draws the connections between these three sets of variables to create a dataset from which you can pinpoint your ideal price. Furthermore, it integrates data from inside and outside the company to get as complete a picture as possible of how value is being created.
There are some important feedback loops taking place in a sophisticated pricing data supply chain. First, value informs pricing. How you set prices depends not only on the value you create for your customer, but also on how much value you aim to capture. Second, price impacts use. How you price your offer will impact how and how much your customer uses your product. Third, use determines value. How and how much your customer uses your offer determines what value they get from it. So we travel from value to pricing to use and back to pricing.
This is why pricing is dynamic. You can’t just set a price and forget about it. The value you create for customers, your price and how your customers use your product all interact in often surprising ways. You need to understand these interactions and make regular adjustments to ensure that each component in your pricing system is reinforcing the other. Increasing the wrong pricing metric can reduce use, which can decrease value, setting off a negative spiral. On the other hand, a pricing metric that communicates and tracks value can set off a positive feedback loop. This is what has happened in online advertising, where pay-per-click is much closer to value than impressions or ‘eyeballs’.
The last step in the system is when your customer pays against your invoice. The actual invoice is created by taking the price from the pricing model and applying the usage data. Policies on discounting, volume adjustments and so on are then applied and the fee for the time is period set.
Let’s look at some of the concrete steps you can take right away to build your pricing data supply chain:
- Build a formal model of how your customer gets value from using your offer.
- Identify all of the variables in the model – these are the points for which you’ll be collecting data.
- Look at your usage and engagement model. Are there any variables that show up in both your value model and your usage model? These are going to be critical to your pricing model.
- Ask if there is additional usage data that you could collect that would inform your value model. If yes, start tracking that data.
- Go back to your value model. Are there any variables that are determined by data external to your system? Interest rates, energy prices, labor rates, basically anything that impacts your customer’s business model should be considered. You should also look at data that can be derived from other enterprise systems, like your CRM or project management systems. If there are variables that you can track then connect these to your model.
- The intersection of variables in your value model, your usage model and external variables that impact your customer’s business model are the ones you should consider for your pricing model.
Building a system that follows these six steps enables you to track changes in the value you provide to your customer based on the interaction of how they use your solution. In other words – build your pricing model from the data up. This way you can tie value, usage and price together into a meaningful bundle. By tracking the variables underneath each of these critical vectors of performance, you’ll get a better understanding of the value of your offer, how to price and how to adjust pricing in order to create positive feedback loops between value, customer, price and usage.
Steven Forth is a co-founder of the skill management platform TeamFit. He also provides consulting on revenue models and pricing strategies to companies in the B2B SaaS and Industrial Internet of Things space as a partner at Ibbaka collective.