# Every Self-Respecting Professional Should Know These 4 Business-Critical Calculations

Passion and mindset are important but never more important than cold, hard numbers.

By John Boitnott

Opinions expressed by Entrepreneur contributors are their own.

In its simplest form, business is math. If the unit economics work in a business's favor, then the business will succeed; otherwise, the business will fail (unless leadership is able to inject a fistful of venture capital into the operation).

Even if you're math-phobic, there are a few essential calculations you should know to better serve your organization. Though you might be able to use analytics tools to do the calculations for you, you should understand the underlying meaning of the metrics provided.

Here's a look at five equations, some simple, others less so, that you should know.

Related: How Doing the Simple Startup Math Helps Avoid Overwhelm

## 1. Independent t-test

The independent t-test is perhaps a bit more complicated. It's used to determine if two sample means are statistically significant, or if the difference in means is simply the result of random error. The equation provides a score, called the "t value." Once you have calculated t, you must compare it to a "critical t value." If t is larger than critical t, then you can conclude that the observed difference in means is statistically significant.

It's worth noting that you select the critical t value based on the level of confidence you'd like to have and on the size of the sample, which is called degrees of freedom. A common confidence level is 95 percent, meaning that there will only be a 5 percent chance that the variation between means is due to random error if t is larger than the critical t.

Independent t-tests have a number of useful real-world applications. For example, let's say you want to test two web pages to see which one converts better. In this case, the two page variants are your independent variables, and the conversion rates of the pages are your dependent variables (the means you wish to compare).

You can use an independent t-test to determine if the difference in conversion rates is statistically meaningful. This free tool will do all the math for you, or you can learn more about doing the calculations yourself here.

Related: Elements of a Business Plan

## 2. Net promoter score

The net promoter score is derived from a one question survey presented to customers: "On a scale of 1-10, 10 being very likely, how likely are you to recommend this business to your friends or colleagues?"

As detailed in a Harvard Business Review case study, Enterprise Rent-A-Car administered the NPS survey to their customers. Thanks to the insights generated, they found success against their competitors.

Here's how you can calculate an NPS score: Detractors (0 - 6 scores) - Promoters (9 - 10) / Total Number of Respondents x 100.

Track your organization's NPS score over time to learn how customers perceive your organization. You can even take a page out of the Enterprise playbook and start compensating customer-facing representatives based on the NPS scores associated with the customers they interact with.

Related: How to Measure Your Customers' Happiness Score (and Why That Matters)

## 3. Pearson Product-Moment Correlation

To what degree are two variables correlated? You can answer this question by calculating r, also known as Pearson Product-Moment Correlation. An r score is a score from -1 to 1. The closer the score is to either -1 or 1, the more correlated the two variables are.

For example, the relationship between IQ and GPA has an r score of above .5, meaning the two measures are more than moderately correlated. Whereas the relationship between watching violent television and committing a violent act has an r score of .2, meaning the correlation is weak. If r is a negative number, it simply implies that the correlation is negative, for example, income and number of years spent in prison is probably negatively correlated. The fewer years you spend in prison, the higher your income.

Calculating r can be done with the help of Excel or similar spreadsheet tools, or it can be done by hand. In either case, calculating r can help to break through office conjecture by providing colleagues or managers with a statistical explanation of relevant relationships.

Related: Customer Loyalty Is Spelled N-P-S

## 4. Customer acquisition cost

How long does it take your business to break even once a new customer is acquired? To do this calculation, you first need to know your customer acquisition cost. This calculation should take into account the expenses related to all customer facing roles involved in winning a new customer.

For example, if you have an in-house sales and marketing team, the salary of everyone on the sales and marketing team, plus the cost of software, advertising, and employee benefits should be factored into the equation.

Once you've collected all of these numbers you can calculate CAC: (Total Marketing Costs + Total Sales Costs) / Number of Customers Acquired.

CAC is a simple, but powerful calculation. Marketers can calculate CAC per marketing channel to understand if particular channels acquire customers more cost effectively. Alternatively, senior managers can better understand how changing the composition or compensation of a team can alter CAC, and therefore the profitability of the business.

Related: How Much Did That New Customer Cost You?

## Conclusion

You don't have to tell me that math isn't fun. It can be an uphill climb to understand these useful calculations. But now that you know these formulas, surely you'll admit that math can be useful.

The next time you're faced with an important business decision, don't just rely on your gut. Try to put some of the formulas you've learned into play to better anticipate how various decisions could impact your bottom line.

John Boitnott

Journalist, Digital Media Consultant and Investor

John Boitnott is a longtime digital media consultant and journalist living in San Francisco. He's written for Venturebeat, USA Today and FastCompany.

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