There is a range of operating styles among entrepreneurs in hardware and software companies. Some CEOs are “quants”; very numbers oriented. Others, especially in the early days, base most of their strategic decisions on experience, feel and “gut”. I believe that there is room for both of these approaches in strategy development; especially in the early days when data is lacking. And let’s face it, as Mark Twain (among others) so famously said “There are three kinds of lies: lies, damned lies, and statistics.” Sometimes the number do lie, especially in the very early days of a tech startup. As things mature, you can generally trust them more. So at times – ESPECIALLY very early on, it makes sense to ignore what some of these key performance indicators (KPI) are suggesting. But this uncertainly should NEVER be an excuse that prevents you from gathering and measuring KPI metrics from the very beginning. At some point, you will need them and will want to have exhaustive data to make your evaluations and strategic decisions optimal.
So let’s dive into some of the most important KPI metrics for software and hardware-based tech companies.
KPI metrics for ALL tech companies
Revenue growth rate (RGR)
A software or hardware company’s revenue growth rate, or RGR, is sort of self-evident in its importance. Revenue is the lifeblood of any company, of any type. Without it, none of the other metrics matter much. So above all, you want to avoid a negative RGR!
You can calculate your RGR over many periods, such as month over month, quarter over quarter or year over year. All can be important measures, depending upon the specifics of your business, it’s maturity and the volatility of your tech company’s market. For raw startups it might be month over month; for public companies quarter over quarter may be most important due to Wall Street influences. I find that year over year is most common, and most useful over the broadest range of situations.
Calculating your year over year RGR:
Subtract the previous year’s revenue from the revenue of the most current full year, then divide this value by previous year’s revenue and multiply by 100
For example, if you had revenue of $5M in your first year and $6M in your second year, your RGR is
6M – 5M/5M x 100 = 20%
- If your revenue growth rate continues to increase, you’re generally heading toward a nice growth in net profit
- Investors heavily rely on trends in revenue growth rate when evaluating a tech company’s potential as an investment
- Institutional investors, such as VCs in particular, are looking for VERY HIGH RGRs
- Revenue growth can be broken down granularly to reflect growth by product or service line items
Customer acquisition costs (CAC)
CAC is defined as follows:
Total marketing and sales expenses for a time period / number of customers acquired during that period
So for example, if you total marketing & sales expenses over one year is $4M and you acquired 10K customers, your CAC is:
$4,000,000/10,000 = $400
For both software and hardware technology startup companies, this is one of the KPI metrics that will be very inflated in the early days. In fact, you shouldn’t even worry about it early on (click here for more on very early stage tech sales & marketing tactics). But again, that doesn’t mean you shouldn’t track it from the very beginning. At startup, your CAC will often appear to be unsustainably high. That’s ok. But what you want to see is a decreasing CAC as you start to get some traction in the marketplace and figure out what a good marketing campaign looks like, are able to document a repeatable sales process, etc. If these acquisition costs stay high as you gain more customers, that’s usually a problem. A problem that you need to devote a lot of attention to. By tracking the trend line of your CAC costs, you get a very good idea in the long run of how efficient your sales and marketing process is, which is important to the ultimate profitability (and often survival) of any tech company.
- Use CAC trends to guide improvements to your marketing and sales processes
- CAC is often used in comparison to your Lifetime Value of your Customer (LTV) to provide a forecast of future profitability
- CAC should decrease with time and business maturity as you build your brand
- An unexpected increase in CAC is a warning sign that something has changed in the market: increase overall competition, a disruptive market entrant, a segment approaching saturation, a change (for the worse) in your marketing approach, etc.
THE key metric for startup tech businesses
For technology startups, your burn rate is by far the most critical KPI metric to track. It tells you how long of a leash you have before one of three things must occur: your performance improves, you need to raise additional capital, or you simply go out of business.
Burn rate is a very simple calculation: it’s the amount of cash used per month. For example, if a business has $200K in total operating expenses per month and a revenue of $50K, the company has a burn rate of $150K/month.
So if a business has $1.5M cash in the bank, at this burn rate it has 10 months to significantly improve it’s performance or raise cash. Otherwise, you’re out of business.
- This is usually the first KPI metric a potential investor (or anyone evaluating the company) will ask a startup software or hardware company about.
- It’s important to react relatively quickly if the burn rate is higher than forecast, hopefully by increasing revenue. If not, by reducing expenses.
- Sometimes a high burn rate is actually a good idea, if the money is being spent wisely to grow the business rapidly. VCs will often push this concept to their portfolio companies in fast growing or competitive markets. For most folks, however, it’s much better to keep the burn rate as low as possible. I always say that startup success is often as simple as “surviving long enough to get lucky”. If you believe this, it puts a premium on extending your runway as long as possible, which means minimizing your burn rate as much as possible.
KPI metrics for subscription-based businesses (such as SaaS)
Customer Retention Rate (CRR)
CRR measures how many of the customers that you’ve fought so hard to acquire remain with you during a specified period of time. While it can be argued this is important for ANY business, it is particularly important for subscription-based businesses such as SaaS. That’s because SaaS business rely on customers “re-upping” their commitment to their business on a regular basis to retain revenue. So CRR is often used as a measure of “stickiness” for SaaS and other subscription-based tech businesses.
CRR = ((E- N)/S) x 100
S = Number of customers at the beginning of a period
E= Number of customers at a period’s end
N = Number of new customers acquired during a period
For example, if you have 2000 customers at the beginning of a period and you lose 200 customers and gain 300. You have a total of 2100 customers at the end of that period and your customer retention rate is;
CRR = ((2100 – 300)/ 2000) x 100 = 90%
The inverse of CRR (1-CRR) is the Churn Rate, which in this case would be 10%
- CRR is first and foremost a measure of your customer service; but a low CRR can also represent a disruption occurring in the market, especially if there is a rapid change in the CRR.
- The old saw about it being more expensive to acquire a new customer than it is to keep a current one just happens to be true. So your profitability will usually follow the trendline of your CRR as your business matures.
- Strategies to increase your CRR go hand-in-hand with strengthening your brand reputation.
Life Time Value of Customers (LTV)
There are a number of ways of calculating the LTV for your business, some very complex. I’ll present one simple formula :
LTV = Average Annual Contract Value / Churn Rate
As an example, if you have an average annual contract value for a SaaS business of $5000 and your annual churn rate is 10%:
LTV = 5000/.1 or $50,000
To get a more accurate picture of LTV, multiply the Average Annual Contract Value by your Gross Profit Margin % in the calculation above.
Lifetime value of a customer is a very important in understanding how much you can spend on marketing, sales and overhead per customer and still turn a profit. It can also be useful as a lever for understand how increasing marketing expenses may affect your total profit. It’s a measure that doesn’t mean much in the early days of a SaaS startup, but as you begin to gather data over time it can become a very meaningful KPI metric to monitor your business. As discussed above, start collecting data immediately when you begin doing business; just don’t put too much credence in the data until you get a bit further down the road.
Annual Recurring Revenue (ARR) or Monthly Recurring Revenue (MRR)
ARR or MRR is conceptually a rather simple calculation. It is the summation of all recurring revenue that you realized over one year (or one month for MRR). So for a typical SaaS business you’d calculate this KPI metric by multiplying your average annual (or monthly) contract value by the total number of active user during that period.
ARR is most often used by enterprise SaaS companies primarily offering annual or multi-year subscription contracts, while MRR is generally more useful for consumer SaaS and low cost B2B SaaS companies with monthly subscription models.
While your ARR or MRR are useful KPI metrics to measure the overall size of a SaaS company, it’s probably most useful as a measurement over time. This ARR or MRR trend line will give you a good picture of the health of your subscription-based business, as it will include both new customer acquisition AND customer churn, both critical components of SaaS business performance.
Customer Experience via Net Promoter Score® (NPS®)
Here is another of the simpler KPI metrics, and not a perfect one in my opinion. It’s an attempt to measure something that is inherently “squishy”: the “goodness” of your customer experience. But I believe it is the type of thing that deserves measurement, as it is very important. There are many more complex ways of attempting to quantify this, but NPS is easy to put in place.
NPS attempts to measure your customer experience and can help predict future business growth. I am actually not usually very trusting of survey-based data. People lie in surveys! And converting something so subjective as customer experience into hard numbers can make them appear more accurate and objective than they deserve. So use this KPI metric “with a grain of salt”. But again, it’s easy to put into place and well worth attempting to measure and track over time.
You institute your NPS by asking your customers to answer a key question, using a 0-10 scale:
How likely is it that you would recommend [brand] to a friend or colleague?
Then group the responses as follows:
- Promoters (score 9-10): loyal enthusiasts who will keep buying and refer others, fueling growth.
- Passives (score 7-8): satisfied but unenthusiastic customers who are vulnerable to competitive offerings.
- Detractors (score 0-6): unhappy customers who can damage your brand and impede growth through negative word-of-mouth.
The final step is to Subtract the percentage of Detractors from the percentage of Promoters; this yields the Net Promoter Score, which can range from a low of -100 (if every customer is a Detractor) to a high of 100 (if every customer is a Promoter).
Again, I believe that this KPI metric is most useful to track changes in your customer experience over time, rather than being accurately representative of some absolute value. An increasing NPS may for example reinforce a recent customer service process change as a positive; a decreasing score may alert you to take a look at all processes and products involved in your overall customer experience. This could potentially enable you to uncover issues and correct them before they turn into a full-blown crisis.
KPI metrics specific to hardware companies
Many of the overall business KPI metrics apply equally well to hardware companies as they do to their software-based counterparts, such as revenue growth, customer acquisition costs and burn rate for hardware startups. But the manufacturing and warranty aspects of hardware companies add a layer of complexity that requires an additional set of metrics to ensure that the company doesn’t “go off the rails” in those areas. A hardware company can have high revenue growth rates and low customer acquisition costs. But if it has super thin gross margins, a high product failure rate and mismanaged inventory the company will likely under-perform or even fail.
Manufacturing cost per unit
I won’t go into great detail here; I expect most everyone in a hardware technology business is familiar with and can calculate this KPI metric. Also known as direct cost, It is simply the summation of the costs of all components, labor and allocated direct costs to produce a single unit. I list it here because it is the single biggest constraint of a hardware business that makes their strategy formulation different from software-based businesses. Because of this, it is one of the most important KPI metrics to track in a hardware business. Your manufacturing direct cost has a significant impact on gross profit, inventory carrying costs and overall need for capital. Obviously you want it to be a low as possible in an absolute sense. But I believe it may again be even more important to track your direct cost trend than this number at any point in time, as well as how you stack up with your direct competitors. These relative measures can greatly affect your strategic decisions moving forward.
Gross Profit Margin
Gross profit is defined as the revenue remaining after deducting your cost of production (COGS). COGS includes all direct costs required to produce a product such as of raw material, electricity and labor. This number is much more important to a hardware-based business than a software-based one. Unless you’ve architected your software product or SaaS very poorly, a software-based business should have very high gross profit margins
A tech hardware business’s gross margin is an indicator of the effectiveness of your design and production processes. It can also be an important KPI metric to highlight areas of potential improvements and guide strategic decision-making. For example, if your gross profit margin is too low, you may decide to kill an offending product line. For product’s with high gross profit margins, it may make sense to increase the amount of money spent on promoting that product.
Gross Profit Calculation:
Gross Profit = Revenue – COGS
Gross profit margin goes a step further, and is defined as gross profit as a percentage of the total revenue. Gross profit provides an absolute profit value; while gross profit margin provides a relative comparison between profits and overall revenue.
Gross Profit Margin = (Gross Profit/ Revenue) x 100
Gross profit margin is a KPI metrics that therefore highlights the proportion of profits generated by hardware product sales, prior to accounting for sales, administrative, and other overhead expenses.
It’s important to remember that your gross profit margin doesn’t represent the overall profitability of a business, as by definition it excludes operating expenses such as overhead costs. It’s therefore most useful as a measure of your product design and manufacturing functions.
- Gross profit margin is a very useful strategic measure when compared to competitors and industry benchmarks.
- Low gross profit margins suggest that a) manufacturing costs are too high or b) the product isn’t valued adequately in the market (which often points to design issues) or c) the competitive situation is very difficult.
- If your gross profit is too low, your business may be in danger of being unable to meet its operating expenses.
Hardware failure rates
What’s often utilized in the area of failure rates is the mean time between failures (MTBF). Among failure rate KPI metrics, I prefer a simpler measure. Divide the number of failures by the total population put into service over a particular time period, such as the warranty period or the expected useful life of the product:
total # of device failures / total population of devices shipped and in service for the period of interest.
For example, If you shipped 10,000 units and after the assumed 3 years of useful life then 1000 of them had failed, your failure rate would be 10%. Obviously, in all cases the lower the better. But tracking your failure rate can give you early insight into a number of important trends of a hardware business: How reliable your brand will be viewed (with it’s obvious broad implications), impact of repeat business, and the raw financial implications of having to repair/replace devices during a guarantee or warranty period. All three of these aspects are important. But while most would focus on the last aspect listed, in my opinion it is by far the least important of the three.
So why take the time and effort to measure and analyze all of these KPI metrics? I believe there are many good reasons, but here are a few key strategic reasons.
- Understanding when your business is in good enough shape to “hit the accelerator”. Sometimes you see opportunity, but your company is too fragile to undertake the required investment to greatly accelerate growth – an inherently risky move. If your KPI metrics say that it’s warranted and there is enough business stability to survive if things don’t go well, you can move forward with more confidence.
- Choosing between market segments for investment. A good handle on these KPI metrics on a comparative basis allow you to make, sound, dispassionate choices between investments in different market segments, product lines, geographies, etc.
- Identifying problem areas within specific functional areas of company that you can then target for improvement. All companies have strengths and weaknesses, and nothing is ever perfect. But management at it’s root is based on continuous improvement of operations; only if you know where you’re falling short can you most effectively make improvements.
There are many more KPI metrics other than the ones listed above that may be very valuable in managing your software or hardware business. In the interest of keeping an already long article from getting longer, I’ve limited the list above. For example, one notable metric that I left out of the hardware-specific section is “Days of Inventory”. Inventory management is a very important skill in a hardware business, and involves many factors such as purchasing, forecasting, etc.
In addition, how exactly that you use KPI metrics to analyze your business is a more in-dept discussion. For example, typically the LTV and CAC calculations are utilized as the LTV/CAC ratio; a rough rule of thumb generally recommends this ratio be 3 or higher for a successful tech business. If you’re LTV/CAC ratio is very low, it likely means that you’re going to struggle to make enough money off each customer to generate the cash required to grow the business. Worst case if it is low enough (or even less than 1), it may represent a going out of business trend. This is just one example of the myriad ways the metrics above and many more can be utilized to analyze a tech business, in support of important decision making.
This article is an introduction; I wanted to suggest some of the most most important KPI metrics that you almost certainly should be tracking, subject to the specifics of your business. The most important point to glean from this article is that at every stage of business it’s important to measure and consider quantitative aspects when managing and making key decisions. There many be points in time when these metrics may not make much sense, such as right at startup or during periods of transition. But that shouldn’t be an excuse not to track them; soon enough they will yield really important insights into your business. Even the least quantitative-oriented among us, those who manage by “feel” – you know who you are! – need to track these basic measures. Otherwise you risk missing some basic trends that could limit success or even jeopardize the survival of the business.
Please suggest some other key metrics that you’ve found particularly useful for your type of business. We’d love to hear either your questions or personal experiences with this topic, so please post in the comment field below!
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Wouldn’t churn rate be (1-CRR) instead of (1/CRR)?
Cheers from Kampala!
Phil Morettini says
Matthias, you read completely and closely! Nice catch, it’s now fixed. -Phil