What Are the Data and Analytics Requirements for a Quantified Value Proposition? Part One

The importance and practical value of a Quantified Value Proposition (QVP) has been well established over the last few weeks’ posts. Now it’s time to eliminate any mystery around the actual research that goes into creating a QVP, which we’ll cover in the next two articles.

Getting Started

The first step is to effectively gather and analyze all the information needed to develop a QVP by answering some basic questions up front. This will provide the structure to guide you through the QVP creation process.

First, make sure you are clear on the intent and purpose of the QVP. Some questions to consider are:

• What is the offering?
• What does it do for customers?
• What are the main features?
• Where do these features and/or the overall offering differ from the status quo and the competition?

Then, think about how your offering intersects with your customer needs and pain points:

• What are the customer’s pain points?
• What improvements would the customer like to see?
• What benefits will the customer derive from each feature of your product or service?
• What valuable benefits can you offer that the customer doesn’t even realize she needs?

Once you are comfortable about what you are offering, why you are offering it and how it benefits your customers, you are ready to determine what these benefits are worth.

Let me share an example for how to quantify value.  Suppose you are selling a new solution that enables customers to reduce maintenance costs. One of the features of your solution is a module that executes advanced instrument analytics in order to predict performance issues that could result in a failure. Let’s translate that feature in a customer benefit.  By having better visibility in an instrument’s performance customers told us they are making more informed and timely decision regarding maintenance. Specifically, they are opting out from performing routine maintenance unless it is really needed. 

Given this this insight, we can now create a simple model that would enable us to put a dollar number to the benefit we are calling improved maintenance analytics. To quantify value we need to define a few variables. 

• Routine maintenance events per instrument per year
• Average cost per routine maintenance event including parts and labor
• % reduction in routine maintenance events per year due to improved maintenance analytics.

With these 3 variables we can build a formula that would show the value of one of the key features of the solution which is advanced instrument analytics.  

Voila! We have quantified value for one of the features of a solution that enables customers to reduce maintenance costs! 

How to Frame the QVP

While the QVP you’re creating is exceptionally valuable on its own, it can be made even more compelling for individual customers with some additional effort. This is because the current situation a particular customer finds themselves in can determine how you frame the QVP so that it’s most attractive to them.

For example, if you’re offering a solution that changes the status quo for the customer - something they can either decide to try or to ignore - you’ll want to frame the QVP as a percentage increase in revenue or decrease in expenses compared to deciding to do nothing.

On the other hand, if you’re offering a solution that requires your customer to make a choice among different competitive options, you’ll want to frame the solution around how your product or service is superior to that of your competition.

Although the same basic value proposition is being described under both circumstances, the actual figures being used and the value drivers being highlighted may differ.

Where to Go for the Data

Lack of data should never be an excuse for not taking a shot at quantifying value.  These days, most companies have collected and stored far more data than they could ever effectively put to use. By diving into this data and searching for specific insights related to how their customers can benefit from your solutions, gems can be mined from a mountain of numbers.

It’s also possible to gather a lot of useful industry data from sources such as:

• Online discussion groups
• Industry publications
• Annual reports
• Google searches

More in-depth data can be gathered through granular research, including:

• Interviews with current and former employees
• Interviews with the sales team members and other internal stakeholders who have established relationships with their customers
• Interviews with customers (being open to both positive and negative feedback)
• Customer surveys (for broader insights)
• Analysis of the company’s data store

Now that we’ve laid the groundwork by introducing the concept of the QVP, how it can be framed to provide additional benefits, and where the data you’re going to use can be found, the next article will dive into how a QVP is created through strategic research and data analysis.

If you’d like further guidance in using data to create your own QVP, please contact EMM Group for assistance.

Roberto is a Manager at EMM Group and is a marketing and value based pricing expert with 15 + years of experience helping B2B enterprises drive profitable growth. You can connect via e-mail at robertorivera@emmgroup.net