In this article, the author presents a detailed process for developing compelling quantified value propositions. Stephan M. Liozu, Ph.D. (sliozu@gmail.com), is the Founder of Value Innoruption Advisors, a consulting boutique specialized in value-based pricing, industrial pricing, digital and subscription-based pricing. He is also an Adjunct Professor & Research Fellow at the Case Western Research University Weatherhead School of Management. He is a Certified Pricing Professional (CPP), a Prosci^® certified Change Manager, a certified Price-to- Win instructor, and a Strategyzer Business Model Innovation Coach. He has authored seven books: The Industrial Subscription Economy (2022), Pricing: The New CEO Imperative (2021), B2G Pricing (2020), Monetizing Data (2018), Value Mindset (2017), Dollarizing Differentiation Value (2016), The Pricing Journey (2015), and Pricing and Human Capital (2015). Stephan sits on the Advisory Board of the Professional Pricing Society. He is a Strategic Advisor at DecisionLink and Monetize360 and a Senior Advisor at BCG.

The Journal of Professional Pricing, December 2021

Over the past decade, I have built hundreds of customer value models. I have helped small, medium, and large companies across many sectors develop value propositions, economic value estimation models, and value stories. The hard part of the process is getting in the trenches and calculating the economic value we aim to deliver to the customer versus the competition. The science of customer value quantification is not overly complicated. In general, I work with incredibly talented teams, and they can identify value drivers, assemble the right formula to calculate economic value, and calculate the value pool. However, the art of the value quantification process is in general the most complex step of the value-based pricing approach.

Assuming you have built your customer value model (EVE®) with a multi-functional team and your exercise led to a particularly good outcome, there are some questions that come to mind:

1. What do we do with the outcome? You might have some good analysis and lots of calculations in a spreadsheet or on a flip chart. What comes next? Who manages the next step and what happens to the first draft? Too many times, once the training or the workshop is done, the energy level goes down, the adrenaline also disappears, and we end up with a semi-finished EVE® model that needs lots of refinement and validation.
2. How confident are we in the value numbers? During the EVE® exercise, I push the teams to go through the process from A to Z and to develop a first draft of a value model that will move to the refinement phase. Lots of times though, the first question is about confidence in the value measurements and the actual value numbers. This is often the case when creating value models against no alternative or with software solutions that can generate lots of savings. Boosting the level of confidence in the numbers can only be done through refinements and validation with customers.
3. How comfortable are we in showing this to customers? Your first draft is a very rough estimation of differentiation value versus alternatives or direct competitors. It is not a best practice to share this version with customers or prospects. I usually recommend two or three rounds of internal refinement work and some basic external validation before engaging in external discussions.
4. How credible are our sources of data? This is always a key question I ask teams to think about. Most times, I will ask working teams to find additional and more robust external data to increase the backing of their value story. It is amazing what value nuggets and sources of credible data you can find through web searches. I would dare to say that most organizations do not have the DNA of proactively collecting these types of sources. Better sources of data mean more credibility for your customer value models.
5. Do we have a credible and crisp story or not? Finally, when all is said and done, is your quantified value story credible, crisp, and compelling? Again, your first draft is not going to be the best work. More validation needs to be done and storytellers need to add finishing touches to be able to use the final model in marketing and communications.

Building EVE® models of quantified customer value propositions is a muscle that takes time to develop. It takes lots of practice in multi-functional mode as well as great data to feed your value quantification process. The bottom line is that you cannot finalize a terrific value model without proper refinement and validation exercises. I usually recommend a 45 to 60 days process of back and forth between validation and refinement to be able to produce a quantified value proposition that can be used in marketing and selling. You never have enough value data, and you need time to craft the right value story. As you increasingly create more of these, this period gets shorter. You might consider hiring full-time value engineers and value consultants that can accelerate the value modeling process. This is the specialization route that works well but requires headcount and budget.

What do you Need to Validate?

There are a lot of moving parts in an EVE® model (as shown below). Assuming you get the segmentation and selection of the reference value right, here are several areas that need validation:

1. The performance of your solutions versus that of alternatives or competitors: This is an area that requires a bit more research and validation. Some of your competitors might publish data sheets or technical reports. That makes it easy to validate. Others do not and you will have to be doing some investigation to validate what performance level you have used in your value models. Your competitive intelligence team can help. Product Managers might have detailed comparative benchmarks.
2. The unit and time of analysis in the mind of the customers: The context of your value models is an important framing mechanism for the entire process. Understanding how your customers operate and what drives their P&L is important. You might select a value model based on per product unit per year, for example. You will need to validate if these match the customer critical metrics. This information can be identified during discovery interviews or as part of a routine customer visit.
3. The selection of the right value drivers: Value drivers are connected to customer benefits, which in turn are connected to true differentiators. I usually recommend using two prioritization steps to get to the three to five key value drivers. Once these are identified, it is important to have a conversation with prospects and customers to validate them. These will vary by segment and against specific competitors or alternatives, so the process needs to be repeated accordingly.
4. The order of the selected value drivers: The second prioritization process involves the use of the 4C rating process (customer-pain centric, credible, commensurable, compelling). Each customer benefit is rated based on the 4Cs and the top value drivers are selected. I always recommend starting your value story with the most compelling and pain-centric value driver. It is the one that must be remembered. Validating the ranking of the value drivers can also be done informally during customer interactions. No need to make it a formal interview. That validation can also be done using existing market research reports you might have on hand.
5. The method to calculate value and the formula to be used: Once you get into calculation mode for your value drivers, you are living in the customer’s world. You need to think like them and put yourself in the shoes of a production manager or a maintenance manager, for example. Application engineers are the best resource for validating the way customers calculate costs or derive total cost of ownership. They might be the first line of validation. Spending time in the customer process might help validate your formula as well. Once and a while you might have to design a new calculation method. At that time, spending time with your technical peers might help refine your calculation method.
6. The assumptions you make when studying the customer operational process: During the design of a customer value model, you will make different assumptions. You must be able to think of usage scenarios of average utilization of the product or service, for example. If you are designing a generic value model for a segment, you might be able to use average ranges. For a customer-specific value model, you will need to validate the operational assumptions with the customer directly by asking simple questions: What is your average reject rate? How long do you use this product per day? What is the speed of the production line? This is what formal value-in-use analysis does. For innovative products and services, a formal analysis might be required.
7. The credibility of the sources of data: Your teams will use various sources of data. Are these credible in the eyes of the customer? Can they be trusted? Sources must be industry relevant and have a perceived reputation for your audience. Avoid having most of your sources designated as “internal company analysis.” That may not fly. Ask customers what they read, what sources they use, and what internal reports they receive.
8. The validity and relevance of data used in the calculations: The first types of objections you will get from customers and prospects concern the validity of the value data you are using. If you are citing research studies or industry reports, customers might challenge you on the validity of the data and the relevance to their industry. You must be ready to answer. One way to do this is to evaluate that validity upfront during the design of your value models.

I could list another eight parameters for validating, but these are the ones I most frequently recommend to teams to focus on. Some of them are easier to validate than others. If you need to validate parameters for a disruptive innovation, you might need to do more work as the reference value potentially does not exist. So, there is a lot of work. Remember the famous saying “garbage in, garbage out!” If you are serious about applying value-based pricing principles and truly quantifying customer value, you will have to do through this process of validation. Of course, companies that are insight-rich or extremely customer-centric might already have all relevant data and documented customer operational maps. They can accomplish these steps in a matter of days. Once you know what to validate, the next question is when and with whom do you validate?

What is the Right Sequence for Validation?

I posit that there is a proper sequence for validation, as shown in the visual below:

You might read this and think that eight steps are overkill. You are right! But the more value models you complete, the faster you can skip through the steps and get in front of customers. I am presenting this sequence for organizations and business professionals who might be new to the value modeling process and the EVE® framework.

Of course, it all starts with having the right secondary data in-house. Most of the time, marketing teams, competitive intelligence teams, and strategy teams have dozens of industry or technical reports readily available. These are full of nuggets that can be used to sustain your value claims and support your numbers. The first step is to gather these and extract relevant nuggets. I also use internet searches to create alerts on relevant topics. These alerts make you aware every day of what is published on a specific topic. You will be amazed by what is published. Finally, you can do specific searches to find sources and nuggets for your value models. What is important here is being curious and inquisitive. Next time you schedule a value modeling session, have all the teams spend one-hour conducting internet searches on the value drivers on which you are working. That will open their eyes to what is available out there.

The first line of validation is internal. Find experts who know the customer process and the application, industry, or segment on which you are working. Have them review your work and challenge your assumptions, data sources, and numbers. Ideally, they would be invited into your value modeling session. It is not always possible to have all the right people at a specific time. Spend some time reviewing your value models with quality managers, application engineers, program managers, customer service managers, etc. They might have information you do not have. Once this is done, you can refine the value model and spend time validating with a wider group of salespeople. Your sales team might have a different level of experience and customer intimacy. It is worth sharing your work with them. You will first gauge reactions to the credibility of your value story. They might challenge you again and force you to go back to the drawing board. The goal of this internal validation process is to have the best possible value model that is ready for a roadshow. This first step can be done in a couple of weeks.

The second line of validation is to go outside and work with friends and family customers, consultants, and channel partners. Because they are friendly to you, you might be able to be transparent and show the hidden part of the value model. They may review your calculations, the formula, and the assumptions. I would recommend 3 to 5 interviews or working sessions to get a sense of the robustness and credibility of your value work. They may share additional sources of information you might need to improve the credibility of your story. Or they may send you back to the drawing board with frank and direct feedback. This is the first real test for your value work, and it needs to be done. Think intentionally about what needs to be assessed and validated. Use these sessions strategically. This second line of validation might be enough for you to move forward and use your value model in marketing and selling.

The third line of validation is to engage your market research or customer insights team to conduct a formal validation research program. It might include qualitative (focus groups, expert interviews, customer interviews, concept testing) or quantitative (conjoint, willingness-to-pay, customer positioning surveys) research methods. This is particularly useful when you are designing a value model for a new product or service. They might also give you expert advice on when and what to validate. If you do not have an internal team, you might have to use external consultants to do the work. Conducting formal market research is amazingly fast and affordable these days. It can be done with minimal budget and in a matter of two to three weeks.

Although I present this sequence in steps, the reality is that all steps might be happening at once, in parallel, or semi-sequentially. It depends on what value models you are building and how you are going to use them. It also depends on your maturity level in marketing and customer insights. The key is to have the mindset of validation so that you can have more confidence in your value modeling outcome and the salespeople have the confidence to use your quantified value propositions during the value selling process. If you can demonstrate that your work was evaluated and refined with inputs from the best internal experts and from customer interviews, chances are they will be more easily adopted.

Who Does the Validation?

The simple answer is everyone! Collecting value nuggets and speaking to customers about value is a team sport. It must also be part of the value mindset and of the DNA of the organization. It changes the game when you have dozens of people asking questions, collecting customer insights, asking the right questions, validating customer information, researching competitors, gathering market pricing insights, etc. The chief conductor of all these activities is the Chief Value Officer (if you have one). The second best is your Chief Marketing Officer and their team. To be realistic, it falls on your marketing research or customer insights leader. If you are blessed with research and customer insights teams, you will delegate the more formal part of the validation sequence to them (i.e., steps four to eight). They will design a validation program for some key value models at the segment level which might be applicable to lots of customers and prospects. They also have budgets to conduct formal market research studies. If you have no resources to go to, you will have to rely on your marketing and sales teams. You will prepare a customer insight program to validate your value models over a 45-to-60-day period and ask favors from everyone. That includes asking questions, conducting searches, buying research reports, and asking distributors for help.

Best Practices in Customer Value Validation

Here are eight best practices for customer value validation:

1. Make it a habit, not a one-time shot: Design your customer value modeling process with some validation activities for timing and scope. It needs to be part of the process for teams to do the required work.
2. Be intentional and strategic in choosing customers and/or prospects to validate with: Ask teams to think about who will be involved in the validation process, at what stage, and for what. Think of this upfront so that it is part of your action plan. Select the right customers or prospects to evaluate with. Do not test your value model only with procurement or with price buyers. Select friends and family accounts who understand value and embrace the TCO methodology.
3. Make it part of a fun customer insight program: Finding relevant customer value nuggets is essential to building customer intimacy and outstanding value models. Develop a program that is simple, fun, and rewarding for people to collect value nuggets and share them with the team. That includes reports, blogs, screenshots at conferences, nuggets exchanged during informal customer interactions, etc. The key is to document the source well and to share the nugget in a fun way.
4. Do not forget to use multiple sources and to triangulate the outcome: The more information the better. If you can have access to multiple sources, it will be better to use ranges or averages between the sources. Customers might be less willing to push back if you have done your homework. It also helps you validate the source by triangulating the information.
5. Use best practices in discovery and customer insights (direct questions, indirect questions, formal discussion, casual questions, quick bites, etc.): Asking good questions is an art. Not everyone is well equipped to do so. Learn the way to ask indirect questions to get to the answer you need. Drop a casual question during a formal conversation. These are techniques to avoid being too obvious about what you are looking for.
6. If you are using salespeople, train them and give them the script: Not all salespeople are trained in the art of asking excellent value discovery questions. Create a script for them and ask them to use it with specific accounts. Sometimes you might need to be surgical with your approach. Pick one question per week and ask your entire salesforce to ask the question during their sales calls. Give them a form or a way to send you the answer (voice mail, email, Slack, etc.). Imagine one question per week times the number of salespeople!
7. Make sure you capture the information and nuggets that are collected for re-use: Of course, the goal is to build a database of value nuggets that can be documented, connected, and re-used for other value models. Someone needs to oversee managing this information and incorporating the feedback into the value models.
8. Leverage technology as best as possible (WhatsApp, Slack, etc.): Find a way to make the gathering and sharing process fast and easy. Use technology to share and document the value nuggets and validation data. Remember that everyone is busy. Simple is better.

Concluding Thoughts

Validation and refinement are critical activities in the customer value modeling process. Validation needs to be completed one way or the other. I see too many teams building their first value model and not moving to the validation phase. If you are serious about doing value-based work, you need to spend time outside the building and in front of accounts validating your work. Hopefully, you are already rich in customer insights and value nuggets, and you can run a quick test on the critical part of your value model. If not, I recommend you take the time to do so and adopt some of the key recommendations and tips listed in this paper. Build customer validation into the overall process and timeline of your work. Do not make it optional (even if it adds three to four weeks to the process). Being value-oriented means being customer-centric. By spending time in front of the right people validating your work, asking value discovery questions, and listening to customer feedback, you are becoming more customer intimate. This is the overall goal of customer value modeling. You must put yourself in the life of your customers, think like them, and experience their pains. Only then, you can build compelling quantified value propositions.