From “Techno Message” to “Business Message”: Developing a Return-on-Investment Sales Tool Internally

by Andrea L. Heilman, 7 August 2002

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“We can't just state ‘our product will let you do more.’ Instead, we have to go the next step and say by doing X with our product, you can save/make more money. This is a difficult statement to substantiate, but it's what we get paid to do.” Tim Smith, PhD, "Selling Messages", March 22, 2002.

Tim’s statement reminded me of a challenge I faced last year. Feedback from our salespeople suggested that market research studies and customer success stories quantifying return on investment (ROI) and total cost of ownership weren’t providing enough information for potential customers to justify our product’s cost. While seeing how much money adopters had saved using the product was of interest, potential customers wanted to know how much money their own companies would save.

The solution I developed was an ROI model. In the end, a project that began as one ROI model for one product for use on salespeople’s laptops grew to include versions for other products in the portfolio, versions for use by customers on the external website, and even a version for use on salespeople’s handheld devices. Below, I summarize the process I used to develop the model and share some of my key findings. My hope is that this brief article will serve as a starting point for marketing professionals contemplating a shift from a “techno message” to a “business message” in their marketing and selling strategies.

Moving from Features to Benefits

The first step in developing an ROI model is to understand how your product’s features tie to quantifiable benefits. For me, this step meant gathering the latest marketing collateral, creating a list of all the features mentioned, and attempting to quantify benefits for each feature. I spent one day developing my initial list of features and benefits and another day talking to members of the sales and engineering teams to gain additional insights into how our product was currently being used and could potentially be used.

To begin the exercise, you might ask, “If a customer doesn’t have our product, how does he/she complete the task?” The answer to this question, however, is only the beginning. At this point, you want to decompose your product into a bundle of features and ask questions about each feature separately. One way to grasp the significance of a feature is to ask, “If our product didn’t have X feature, what would the customer do instead?” At the end of the exercise, you should have a comprehensive understanding of what a customer would do if you removed X feature, Y feature, or Z feature from your product.

Consider a product with a “Virtual X” feature that enables the customer to upgrade applications remotely. You might be tempted to say that the benefit is “remotely upgrading applications”. True, but how do you quantify that benefit? To begin, rephrase the benefit as “reduction in costs due to remote upgrades”. How exactly does the customer reduce costs by using the “Virtual X” feature? To answer this question, we need to answer “What would the customer do instead?” Let’s say, for example, without “Virtual X”, the customer would spend two hours in front of each machine manually upgrading the application. All we need is the customer’s cost per man hour to upgrade the application manually, and we have a quantifiable benefit for our “Virtual X” feature: “reduction in wages due to remote upgrades”. But wait, what if the customer has machines in several offices scattered across the city or across the country? We don’t want to forget to capture “reduction in travel/transportation costs” as a quantifiable benefit.

The key to this first step is finding quantifiable benefits by understanding exactly how each feature is used and what the alternatives to use are. Once you have a list of features and quantifiable benefits, you are ready to create your ROI spreadsheet model.

Developing Spreadsheet Models

If you’re relatively comfortable using Excel, creating your initial ROI spreadsheet shouldn’t be too time-consuming. I spent approximately four hours creating my initial model, which included more than 100 lines capturing product acquisition/deployment costs, quantifiable benefits tied to six features, and a net present value (NPV) calculation for the product’s lifetime as well as charts summarizing the calculations.

At a minimum, the model should include three columns: one for the item’s name, one for the number, and one for the explanation (is the number a required input, an assumption, or a calculation?). Using the example above, the first column would contain the following items: (1) number of machines you will remotely upgrade with Product X, (2) anticipated number of upgrades per year, (3) cost per man hour to upgrade machines, (4) average number of man hours per machine per upgrade eliminated due to remote upgrades, and (5) total savings realized from reduction in wages due to remote upgrades. The first four items are required inputs, while the fifth item is a calculation simply multiplying the first four. If you would like to see a sample Excel spreadsheet for the entire “reduction in costs due to remote upgrades” example, please contact me at andrea.heilman@duke.edu.

Ideally, you will create different versions of the model to address the needs of different types of customers such as IT professionals, purchasing managers, and CIOs. I’ve found it easiest to create a comprehensive model first and then remove the aspects that might not be relevant to a specific audience. For example, my comprehensive model might include an NPV calculation, a graphical representation of how each calculation contributes to the final number (such as a tornado chart), and 90-50-10 likelihoods for each input number for use in sensitivity analysis. If the model will be used with a customer who is certain of his/her costs and must justify the expenditure in the first year, I would then remove the 90-50-10 likelihoods and the NPV calculation.

Once the spreadsheet model is complete, the next step is to develop a presentation that not only explains how to use the model but also ties it to current marketing and sales strategies.

Creating a Complementary Presentation

For your ROI model to be useful (and used), a "how to" presentation is absolutely necessary, particularly if your salespeople are accustomed to selling with a "techno message". In general, the presentation should reinforce the connections between your features and benefits as well as provide a step-by-step guide to using the model. I like using an example from a current customer if possible, entering the numbers into the ROI model and pasting screenshots of each step into the presentation.

The presentation also provides an opportunity to explain the nuances of using the ROI model with different types of customers. While the ROI model (ideally) captures all the potential customer benefits of your product, chances are that not every customer will receive every benefit. You might find, for example, that each vertical market uses different features, which means that certain steps in your model should be skipped. One way of highlighting the need to skip some of the steps in the model is to develop selling scenarios based on customer type or vertical market. I've found Geoffrey Moore's elevator pitch template in "Crossing the Chasm" very helpful in developing separate pitches for each type of customer versus a general pitch explaining everything the product does.

Now that you’ve finalized the model and presentation, you have one last step: QA testing.

Asking for Feedback

You should plan to test the model prior to sending it out to the entire sales force. Send what you consider your final versions of the model and presentation to a few salespeople (or even trusted customers) for feedback. Don’t be afraid to ask how to make your model more user-friendly. You may have to spend time reworking portions of the model, but in doing so, you’ll increase the likelihood of your sales force using the model on a regular basis.

Finally, after you've made changes based on feedback, send the next iteration to a larger set of salespeople and go on a few sales calls to see how customers react to the model. Once you’ve armed your entire sales force with your ROI model and presentation, develop a process to capture additional feedback and to gather insights into how customers are using your product.

Integrating with Future Strategies

Customers’ responses to the model may provide insights useful for your strategic planning. You may find, for example, that 90% of customers have no interest in X feature, but the 10% who do plan to use it realize an additional $1,000 per license. In such a situation, you may want to consider a new usage-based segmentation strategy and spend more marketing dollars targeting potential customers similar to that 10%. Alternatively, you may want to consider a versioning strategy in which you remove the X feature from the base product (because 90% of your customers don’t care if it’s there anyway) and charge a little more for adding on the X feature for the 10% who do care about it.

Although I can’t tell you the ROI on my ROI model, I can say that it created an opportunity for salespeople to move from a “techno message” to a “business message”. For potential customers, the model provided a believable justification for the expenditure. Although the calculations were “back of the envelope”, the dynamic nature of the Excel-based model enabled customers to use (and later update) their own numbers and reinforced the validity of our marketing research studies and customer success stories.

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A Note on the Author:

Andrea L. Heilman recently completed her MBA at Duke University’s Fuqua School of Business and is in the process of moving to Chicago. Her business school experiences include a three-month internship as a product marketing manager for a high-tech manufacturer and a three-month marketing strategy project for a wireless carrier. She also served as co-chair of e-vision 2002, the Duke Business Technology Forum (www.dukevision.org). Andrea is currently seeking an opportunity to use her quantitative and creative skills to contribute to an innovative company’s marketing efforts. She can be reached via email at: andrea.heilman@duke.edu.

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