How to Make Money in Software (No Matter What Company You Run) Software investments do pay off -- as long as you approach them the right way.
By Joel Basgall Edited by Dan Bova
Opinions expressed by Entrepreneur contributors are their own.
Industry standards are for often less than helpful -- especially when they're used to make strategic business decisions.
Granted some benchmarks are useful for purposes of comparison. If you run a chain of grocery stores and your profit margin is 4 percent, you're outperforming the average grocery store's 1 to 2 percent profit margin.
But others are simply shortsighted. Just yesterday I was asked, as I often am, how to determine what a company should invest in creating or growing a software product. Many people fall back on some sort of industry or internal standard, like mandating that R & D should be 15 percent of gross revenue.
The problem with making a strategic decision using a broad standard is the total lack of context. A product in a competitive, information-based industry that will generate $100 million in revenue and therefore net $50 million in profits is worthy of a significantly greater investment than an e-commerce product that generates $100 million in revenue but only nets $2 million in profits.
That's why what you should invest in software should be based not on an industry standard but on the value the investment in those features will generate, both tangible and intangible. The key is to not start with how much you're willing to spend and then determine if that amount makes sense -- the key is to determine the value and let that drive your investment decision. There's an added benefit to choosing not to look at the cost and decide whether you should spend it. Figuring out how to fit the work into a smaller bucket forces you and your team to find creative ways to get things done. I call that the Bigger House Syndrome: no matter how much larger your new house may be you will soon find ways to fill all the rooms with furniture… even if you don't ever use those rooms.
Related: Can a Software Development Company Be Your Co-Founder?
Here's a simple formula that will help you determine what you should invest in growing a software product:
Investment < (Revenue from NEW Customers + Additional Revenue from EXISTING Customers + Indirect Revenue - Indirect Cost) * Likelihood
Look complicated? It's not. Let's break it down.
Investment. Obviously you want to invest less than that investment will return. That's how you make money. You may think that is short-sighted, since sometimes the right approach is to ahead of return, but we'll cover that when we evaluate Indirect Revenue.
Revenue from new customers. This factor accounts for the revenue you will receive from new customers that will use your service, either because it is a new product or because you plan to add features to an existing product that will attract new customers. The math is straightforward. For example, 10 new customers at $1,000 per month equals $120,000 a year. Forgetting other factors for a moment, that means you could invest up to $120,000 in that product every year.
Additional revenue from existing customers. The same premise holds true: If you can charge more for your new features you'll generate additional revenue from current customers. While some existing customers will adopt a new product, this is most useful for determining the value of upselling customers to a new service level when you upgrade or enhance an existing product. LinkedIn's Sales Navigator is a good example of a product that generates additional revenue from existing customers.
Indirect revenue. Here's where it gets interesting. Sometimes a product facilitates or supports rather than directly generates revenue.
Related: How to Know When to Bring Software Development In House
For example, at Geneca we work with a number of professional services companies. Those firms generate revenue through their consulting work and their software enables and supports those consulting efforts. Say your software allows your consultants to be 20 percent more efficient. That means they can use that time to work with 20 percent more clients. If each consultant generates $200,000 per year in revenue, an additional 20 percent equals $40,000 per year per consultant. If you have 100 consultants that's a $4 million boost in annual revenue.
Plus, greater speed and efficiency typically results in happier customers which then results in greater customer loyalty -- an important, if often ignored, by-product of building effective software products.
Indirect costs. Capturing additional revenue may require more than simply investing in a new software product. You might need to expand your call center. You might need to beef up your IT infrastructure. Those costs must be factored into the equation.
Add up your projected revenues, subtract the indirect costs involved, and you have a great sense of the value of your new software features.
But you're not done. The last thing you need to do is apply sensitivities to determine the likelihood of capturing all that revenue.
Let's work through a few real-life examples.
Scenario 1: You Only Gain New Customers
- Revenue from new customers = $120,000 a year (10 customers * $1,000 per month * 12 months)
- Additional revenue from existing customers = $0
- Indirect revenue = $0
- Indirect cost = $100,000 (2 new customer service reps at $50,000 per, with benefits.)
- Likelihood = 50 percent (You think the odds are 50/50 you will generate the revenue projected)
The math is simple: ($120,000 + $0 + $0 - $100,000) * 50 percent = $10,000
That means you can spend $10,000 on the new product or feature and expect to make a profit. And keep in mind you won't need to spend the $100,000 on new customer service reps if the product isn't successful. In effect your net loss will only be the cost of product development.
Also keep in mind this is a first year results; if you don't need to invest additional money in the product in the second year, the additional revenue is all profit.
Scenario 2: You Can Upsell $100 in Revenue Per Year Per Customer
In this case we'll assume you're creating new features for a "premium" version of your product.
- Revenue from new customers = $0
- Additional revenue from existing customers = $100,000 ($100 / year * 1,000 existing customers)
- Indirect revenue = $0
- Indirect cost = $0
- Likelihood = 75 percent (You estimate 75 percent of existing customers will buy the "premium" package)
Again, the math is simple: ($0 + $100,000 + $0 - $0) * 75 percent = $75,000
That means you can can spend $75,000 on the new feature and expect to make a profit. Again, this is a year one calculation; if no additional investment is required the ROI going forward is much higher.
Scenario 3: You're Losing Customers... and $3 Million in Revenue
Say your software does not include key features that customers really want -- and that makes them go elsewhere. Instead of serving as a way to land new customers or upsell current customers, in this case developing new software is a customer retention strategy.
- Revenue from new customers = $0
- Additional revenue from existing customers = $0
- Indirect revenue = $60,000,000 ($300,000,000 * 20 percent. Why times 20 percent? You may actually lose 20 percent of your existing customers if you don't develop these features.)
- Indirect cost = $0
- Likelihood = 10 percent (You think the odds of not losing customers are only one in 10 if you don't add those features; in other words, you're almost certain you will lose them.)
Here's the math: ($0 + $0 + $60,000,000 - $0) * 10 percent = $6,000,000
That means you can spend $6 million on the new features and expect to make a profit. While $6 million may sound like a big number, over time this investment projects a total of $60 million in revenue.
Keep in mind all these examples are from actual client engagements.
In some cases, it is obvious that a particular client should create new software or add new features. In other cases, it's less obvious. One of the most important variables is determining the level of certainty that some of the assumptions used in a given scenario will become a reality. You may need big data and significant research to help applying different sensitivities to the Likelihood factor.
Related: 9 Essential Tools for Agile Product Development Teams
Or you may not. Sometimes the math makes the decision to develop a new software product extremely easy and a lot more accurate than simply applying an industry standard and hoping that everything turns out okay -- because in my experience, hope is rarely an effective business tool.
