The data you need to collect to inform pricing actions
Steven Forth is a Managing Partner at Ibbaka. See his Skill Profile on Ibbaka Talent.
Good pricing decisions require data. That data has to come from multiple sources inside and outside your company and the time to start collecting it is now.
The best practice in pricing is to build a portfolio of potential pricing actions that you could take. These actions will have different risk and reward profiles, will require different levels of data, and need different data to inform decisions.
If you are interested in how to build a pricing action portfolio, Karen Chiang and Steven Forth will be giving a workshop at the Professional Pricing Society Spring Conference in Chicago. The workshop is Wednesday April 29, the conference runs from April 28 to May 1.
What data do you need to collect to take effective pricing actions? You need a blend of internal and external data, collected from many different systems. And once you have collected the data, you need a set of models to inform decision making.
Tactical pricing actions
There are many different pricing actions you could consider taking. You need to be ready for different scenarios and prepared to take the different actions in your portfolio. Preparation means gathering the data in advance.
Some of the tactical pricing actions you should be considering are listed below.
Change Unit Prices (Increase or Decrease]
Change Discounting (the percent discount or the commitments needed to get the discount)
Change Pricing Corridors or Guide Rails (the minimum and maximum prices that can be charged)
Enforce Contract Terms (many contracts have price concession that depend on the customer meeting certain performance requirements (and vice versa), but in many cases these terms are not monitored or enforced)
Change Offer (the value included at each price point for each segment, this can include products, services, data and access to unique capabilities)
Change Bundle (the combination of products, consumables, data and services sold together; this will often include products from multiple businesses
As you build your portfolio of pricing actions, identify the data you will need that would cause you to execute and that you will need in order to execute.
Internal data to inform pricing decisions
Beginning inside the organization, there are four main systems that may have data relevant to pricing decisions.
CRM (Customer Relationship Management)
Financial
Customer Success
Pricing Management
In most cases though, these systems are poorly implemented and maintained and lack the data you are looking for. What data will you be looking for? Let’s begin with the CRM.
Configuring your CRM properly
On the CRM, you are most interested in what led the customers to buy. Most CRMs are configured to support your sales process. The most important data will be about the customer’s buying process. Check your CRM now to see if it is capturing the following data.
Why the customer bought
What alternatives they considered
Who was part of the decision making unit, who was the champion, who were the opposers
What value promises were made
If tools like value calculators, price calculators or ROI calculators were used, make sure that you are saving copies of these, or the data used in presentations to the customer. Data provided by the customer is especially valuable.
A good CRM configuration will capture information about the emotional and economic value drivers and how customers responded to them. Do a value survey as part of your sales process and capture the data in the CRM.
We regularly ask for this data, and we generally get something, which we run through our data clustering platform. Unfortunately, there is seldom enough relevant data to really inform pricing decisions. That is something you can fix.
Getting granular with financial data
Financial data is usually more robust and accurate than CRM data. It has to be. But it is often aggregated up into general categories that are not useful for informing pricing decisions.
One of the main things you want to do with financial data is to calculate the Sales Price Index and build pricing dispersion plots. You can do this so long as you can get detailed information on price and the pricing metrics that were used to define the price. If there are a lot of discounts that are captured in the financial systems (which is not always the case) then you can do additional analysis to understand which customers are getting discounts. You will often have to dig further to find out why.
These are one of the most important analytical tools and your financial or invoicing data often has the data you need to construct these.
Basically you want to do two things with these plots. Find the line with the best fit (one is interested in the shape of the line and how well it fits the data) and look for clusters of customers above and below the line. All of these can suggest opportunities for pricing actions.
Customer success, not just customer support
As businesses move to subscription models, they are shifting from customer support to customer success. Churn (customers that fail to renew) bleeds the profit out of subscription models and one of the best ways to reduce churn is to deliver on customer success. This has led to a new category of software, customer success management systems, such as Gainsight or Totango.
These systems can also have data that is useful to pricing. They will help you to understand which customers are likely to churn, the role of price in churn and they collect a lot of other data that can be clustered and fed into market segmentation. Remember, good pricing begins with a solid, value-based, market segmentation.
External data to inform pricing decisions
Market surveys are another important source of pricing data. Most companies do regular surveys of their market and customers. Adding a few strategic questions about emotional and economic value and tracking them over time can be of enormous value in plotting pricing strategy.
One also wants to be collecting information on competitors. Not just information on prices, pricing and value are joined at the hip, so you need to collect information on pricing and value.
Loon Lee Speilmann at Philips has a good piece Competitive Pricing Intelligence, that looks at how to gather competitive pricing information for B2B. The below graphic from his article is a good summary of both data sources and how to evaluate the data.
Instrumenting your own software
Now we get to the most important source of pricing data, your own solutions. With the spread of cloud software and Internet of Things (IoT) applications, there are more and more opportunities to collect data about how your systems are being used.
What data do you want to collect?
There are two key ways to think about this. First, brainstorm the value metrics for your software. A value metric is the unit of consumption that correlates with value. There will often be many different value drivers and some of them will be unique to your solution. If there are no value drivers unique to your solution, then you may lack differentiation, and that is a different problem.
Once you have brainstormed the value drivers, figure out all the ways that your software can collect data that help to measure V2C (value to customer). You may need to enhance some of this data with information culled from the customer success team. Collect that as data, not just as anecdotes. Create a data lake that combines all of the different measures of value.
Next you will need to build a value model that captures how you are creating value for customers. You may already have this model from a value, pricing, or ROI calculator. Most companies only use these tools in the sales process. That is a shame, They have an important role to play in both customer success and in pricing.
The value data you are collecting and the value models you are evolving will be the foundation of your future pricing actions.
If you have enough data, start to use machine learning and predictive analytics to start predicting value from other usage data (we call this PredictiveV at Ibbaka). Once you can do that, you are near the promised land. Eventually, you will be able to use the ability to predict value to customer to move to performance-based pricing. Ibbaka is predicting that, over the next decade, performance-based (or outcomes-based) pricing will replace value-based pricing.
Mapping pricing actions to data
Let’s go back and consider your Pricing Action Portfolio. As you build up this portfolio, you should also begin to identify the data you will need for each of the possible pricing actions. Part of building a portfolio of pricing actions is to invest in gathering the data you will need to decide if you should commit to the action and how to execute.
Collecting data can be expensive. So before over investing in any one area of data collection and analysis, build an initial portfolio of pricing actions and work out the timelines (some pricing actions can be planned, communicated and executed in days, others take months, some can take years) and the investments needed. Then workout the range of ROIs for each action and make choices.
Act now to stem the data loss
Everyday that goes by you are losing data you may need for pricing decisions. Much of this data can be multi purposed to product and marketing. Act now to stem the data loss. The order of operations is as follows.
Make sure your surveys capture economic and emotional value drivers
Update your CRM configuration to capture price and value information gathered during the buying process
Add value and price calculators to your customer’s buying process and use them across customer support process
Capture SKU level gross profit
Start calculating the Sales Price Index and mapping price dispersions every month
