Scaling product revenues is a challenge for all product managers and product marketers. Once a product graduates from the early adopter stage of the Technology Adoption Life Cycle, there are patterns in successful sales transactions. Product people should learn these patterns. The MoneyWheel is a tool you can use to discover and scale repeatable sales transactions to drive revenue growth.
In the 1990s I worked for an enterprise software firm that sold enterprise application development tools (CASE tools). A challenge we faced was that some sales regions and sales reps were much more successful than others. We started a project to learn why. The MoneyWheel was an analytical technique we built. What we discovered was that there were patterns to the sales transactions of the most successful sales reps.
Sales wins fell into specific ‘buckets’. These buckets represented common reasons why customers decided to purchase a new solution. The most successful reps recognized these patterns and used them to quickly qualify or disqualify specific opportunities. They invested their time in the most promising deals. We found that specific sales regions and sales reps were more skilled at exploiting these patterns than others. By sharing these best practices we were able to improve the performance of the lowest-performing sales reps. This drove an increase in revenues and profits.
The MoneyWheel is a tool you can use to understand the repeatable sales transactions that occur in your product’s market. This knowledge helps you make better decisions about feature prioritization. You can also use it to make better decisions about investments in demand generation programs.
A MoneyWheel has two components: categories and spokes. A MoneyWheel category is a broad type of sales transaction. There are five broad categories:
- Net New Customers. These are customers that have not bought any of your products before.
- Add on Sales. These are sales of add on products to customers who have already bought a base product from you.
- Expansion Sales. Customers buying more units of a product they own, like more authorized seats or more transactions.
- Competitive Migrations. A special type of new sale where the customer is migrating from a competitive solution to your product.
- Financial. Transactions that are specifically financially based and not on the features/functionality of your product. Enterprise-wide licenses are one example. Multi-year contracts are another.
Spokes are the specific types of repeatable sales transactions that occur within a MneyWheel Category. They are often triggered by an event that occurs at a customer or in a marketplace. Spokes help explain why a customer purchased something.
For example, here are four spokes for the Net New Customer category for a Marketing Automation SaaS provider:
- New Marketing Vice President. When a new VP is hired, they often replace existing marketing automation solutions with vendors they have had success and experience with.
- Merger/Divestiture. When a merger occurs, the acquirer often replaces an existing marketing automation solution with the one the acquirer has standardized on.
- Bad Quarter. If the customer has experienced a bad quarter from a financial perspective, they will often consider a new marketing automation solution to boost revenues.
- Competition. If a customer’s competitors start performing significantly better, companies will often consider upgrading their marketing automation solution to match or exceed a competitor’s performance.
Spokes are unique to your product and market. While MoneyWheek categories are common across most SaaS companies, most spokes are context-specific.
Here is a MoneyWheel example for a marketing automation provider:
As the table indicates, the majority of revenue is coming from net new customers, especially when a new VP is hired or the company experiences a bad quarter. Interestingly enough, improper use audits are only generating 2.6% of total ACV. A product manager or marketer might ask is the risk of losing customer goodwill enough to justify punitive improper use audits?
You can extend the MoneyWheel analysis by incorporating revenue tiring and Pareto analysis. Consider the following:
By classifying deals into revenue tiers, you can see that half of the revenue is coming from net new customers with an annual contract value of between $50K and $100K. Deals below $25K account for 37% of the transactions, but only 7.5% of the revenue. Clearly larger customers deserve high priority than smaller customers.
You can further refine the analysis by adding in sales regions:
You can see which regions are having success and which ones are struggling. For the regions that are struggling, it might be due to a market condition (No new VPs or M&A in the Central Region). Or it might be due to an execution issue.
You can further refine the analysis down to an individual sales rep:
This type of analysis helps you to understand which reps are struggling. You can leverage the experience of the successful reps to help the lower performing reps. This will drive more revenue and profits.
If you need to brush up on your Pareto and Tiering Analysis, check out Why Pareto Analysis is Important for Product Managers.
You can use the MoneyWheel to roughly estimate the demand generation required to hit a specific revenue target. To do this you need to complete a historical MoneyWheel for your product. Next, you need to estimate the historical conversion rates between stages in your sales funnel. Consider the following:
You could break this down further by looking at all the possible demand generation programs. Here is a chart for typical B2B sales funnel conversion rates by program type:
Using this data, you could estimate the demand generation program requirements for net new customers:
It is important to emphasize that this analysis can provide general guidance for demand generation. It is not an exact science, but it leverages the data you have available to make more informed decisions.
The first step is to assemble the base data you need. There are two types of required data. The first is sales transaction data. The second is marketing/sales funnel conversion data. Sales transaction data can be extracted from salesforce automation systems like Salesforce.com, Hubspot, and Keap. For each deal get customer id, product name, deal amount, sales region, and salesperson information. Sales funnel stats can come from marketing automation solutions like Saesforce.com, Marketo, and Hubspot.
Conduct qualitative interviews with members of the marketing and sales teams. The goal of these interviews is to get insights into demand generation program performance and MoneyWheel spokes. Target marketing operations personnel, product managers, product marketers, sales management, and sales reps.
The goal of these interviews is to discover and validate the spokes of the MoneyWheel which are relevant to your product. You want to explore what triggered a customer started the process of evaluating a new solution, what sources of information they considered to be credible in their research, and the factors they used to decide what solution they selected.
Next, enhance the base data you collected. Add revenue tier information to each sales transaction. Most salesforce automation solutions do not categorize sales transactions by MoneyWheel spoke so you will have to do that yourself. The insights you gained from your subject matter expert interviews will help. It is hard work, but it has a significant payoff.
Next build your MoneyWheel and analyze the information. Excel is a good tool to use. The goal of the analysis is to identify areas of success and opportunities for improvement. The MoneyWheel provides you with a fact-based way to talk to the organization about where you can invest to scale success.
Share the results of your analysis across the organization. USe it as a tool to support discussions about specific improvements that can be made in marketing, demand generation, and sales.
The MoneyWheel is a tool you can use to discover and scale repeatable sales transactions to drive revenue growth. By analyzing historical sales transactions and conducting qualitative interviews with marketing, product management, sales management, and sales personnel you can develop fact-based insights into product sales performance. You can leverage these insights in many ways, such as supporting estimating the demand generation requirements needed to achieve a product revenue growth goal.
You can download the Excel files used in this post here.
Also published on Medium.