This list is by no means an exhaustive list, but rather a core group of metrics and KPIs that should be tracked and made visible across the time at all times.
Other, more granular, metrics such as bounce rate, click through rate, and average time on page are not as critical to the business and are historical metrics. In other words, they don’t tell you very much and are near useless to make decisions on.
These metrics are all relevant, forward-looking metrics and KPIs that can be used to project for future performance and make decisions on.
Unique website visitors refers to the number of distinct people that visit your website over a particular period of time (commonly a month).
Visitors come in all shapes and sizes, from sales-ready buyers to sceptical researchers (and even a few people who’ve ended up on your site by mistake). In order to determine which visitors are which, and identify potential customers, it’s essential to learn more about them.
Month over month unique visitor growth is a key sign of increasing brand awareness, healthy website traffic growth, and just a sign that things are working.
If your monthly unique visitors are going down, it's a sign that things are slowing down and that you need to revisit your current tactics.
Many SaaS products use free trials and demos to engage prospective customers, and it’s important to understand where these fit into the sales funnel.
Free Trial users are usually counted as MQLs: signing-up for anything “free” requires relatively little commitment from users, and simply kicking the tires of your product provides no indication of sales intent.
Some SaaS products, namely in high-touch sales models, can be more complex, and require custom set-up before use. This often means that free trials aren’t viable, and instead, running product demos is a more effective way of proving out the value of your product.
Getting on the phone and sitting through a demo requires a greater commitment from your visitors, so demo requests are usually regarded as SQLs. Though the distinction isn’t always clear, it’s important to choose a simple, consistent rule for qualification, and stick to it.
Your number of free trials or demo requests will be a key growth metric. If your monthly unique visitors are growing or number of leads every month are growing but your number of free trials or demo requests are not growing, you know that you have a leak in your funnel.
Leads are visitors that have filled out a contact form on your website, usually in exchange for a download or free resource. In doing so, these visitors have parted with more than just their email address — often submitting their name, job title, business name or website address.
Leads do not necessarily mean anything because you don’t know who is qualified and who is not. But your number of leads will be a key number in other metrics. Essentially, you eventually want to figure out how many leads convert into customers as well as how long it takes to convert a lead into a customer.
These are leads that fit the appropriate demographics of a customer, and demonstrate interest in your solution, either by viewing several product-focused pages on your website (like case studies or pricing pages), or engaging with more product-focused content offers.
Marketing qualified leads are leads that you know could potentially buy your product. Simple as that.
These are leads that meet the MQL qualification criteria, and have demonstrated sales-readiness — usually by requesting a sales conversation or free demo.
Sales qualified leads are marketing qualified leads that have showed intent to purchase your product.
Opportunities are SQLs that have been handed over to your sales team, vetted, and deemed a genuine sales opportunity, kicking-off the sales process.
Opportunities are generally used in high-touch sales models and used to describe an open deal with a lead where the annual contract size can be estimated or projected.
Tomasz Tunguz, venture capitalist at Redpoint Ventures, defines PQLs as “potential customers who have used a product and reached pre-defined triggers that signify a strong likelihood to become a paying customer”.
For freemium business models, a PQL is the new MQL or marketing qualified lead. It helps SaaS businesses pre-qualify potential customers based on their product usage.
Product qualified leads are usually free trial users who have engaged with the product in some way that proves they are a good fit with the product.
Once you’ve documented your PQL (or MQL) definition, you need to calculate how many you need each month.
Knowing your qualified lead to close ratio (See Sales section below), work backwards from your revenue target to calculate the volume of leads needed. (Here’s a helpful revenue to lead calculator if you want some help running that math.)
All would be great in the world if you could snap your fingers and start generating the lead volume you need to exceed your revenue target. But, since that’s not realistic, plan to increase your lead volume every month, so that you’re comfortably hitting your annual revenue target by the end of the year. In fact, “there’s no reason leads can’t grow every single month like clockwork” says Jason Lemkin, the creator of the LVR ratio.
Why should you obsess over LVR? Since it is just a matter of time before some percentage of your qualified leads close to a customer, LVR is a great indicator of future sales attainment.
To calculate LVR, use the following formula:
[[(Qualified leads current month - qualified leads last month) / qualified leads last month]] x 100 = QLVR
The rate at which website visitors convert into leads. Tools like pop-ups, email subscriptions, free downloads and landing pages can all be used to convert anonymous visitors into identifiable leads, and it’s important to optimize this conversion rate over time.
This is an overarching conversion rate that looks at the rate at which leads convert into customers. Generating lots of poor-fit leads will lead to an extremely low conversion rate, and vice versa, so this can offer a very revealing insight into the quality of the leads you’re generating.
This is the rate at which free trial users become paying customers. Small improvements to this figure will generate big improvements in revenue, so it’s important to continually optimise your free trial onboarding process.
Though revenue is typically the more important of the SaaS metrics than new customers, tracking how many new customers sign up to use your service is still helpful. This metric allows you to see how often you are able to close the sale and just how addressable your market is.
You can track new customers for the month, quarter, and year. Then compare new customer acquisition across periods of time to determine if your team is improving month over month, quarter over quarter, and year over year. This metric is also vital to understanding seasonal or cyclical trends.
Organic traffic comes from your organic rankings in the search engines, whereas paid traffic comes from Pay-Per-Click (PPC) ads, sponsored links, or purchased ads. But which one drives better results?
This can be calculated simply by dividing monthly organic volume by paid traffic volume and you’ll get a ratio like X:X
To measure virality, calculate your viral coefficient. The formula is simple:
Referral invites x conversion percentage = viral coefficient.
Referral Invites = Number of invitations the average user sends.
Conversion percent = The percentage of invitees that convert to customers
As an example, a virality coefficient of 1.5 means that every signup brings 0.5 additional sign ups, so for 100 signups, you actually get 150. The greater your viral coefficient, the faster and faster your company will grow.
Average Revenue per Account (ARPA), also known as Average Revenue per User or per Unit (ARPU), is a measure of the revenue generated per account, usually per month as most subscription businesses operate monthly. But you can always calculate it yearly or quarterly according to your plans and billing options.
A simple way to calculate this is to divide the total MRR you have at the end of a month and divide it by the number of active customers at that time, like so:
MRR / Total number of customers = ARPA
One way to tell if you have a good CAC is how many months it takes to recover the CAC. If it takes 12 months or more to recover your CAC, it’s too high. Ideally, you want to be able to recover your CAC in 1-2 months. If you have a short sales cycle and some cash in reserve, your CAC will be healthy if you can recover it in 3-4 months.
The basic formula for MRR is pretty simple: for any given month (period t), simply sum up the recurring revenue generated by that month’s customers to arrive at your MRR figure.
MRR is essential for understanding the growth of your business, and with a good handle on customer acquisition and churn rates (which I’ll cover below), we can even use it to extrapolate to the future, and predict future revenue.
You can measure customer satisfaction using customer surveys, and in particular, the Net Promoter Score. NPS is the most popular metric to measure customer satisfaction and loyalty.
But don’t just use NPS to measure your customers’ happiness with your products. Customer ratings are also necessary to evaluate your support team’s effectiveness. Also, it’s smart to measure your NPS after product updates to see which changes triggered a positive or negative response.
The NPS tells us the likelihood of a person to recommend a company or its product to someone else. NPS typically uses the 0-10 scale, where 0 means they won’t ever recommend the product and 10 means they definitely would. The higher your NPS the better, as it indicates satisfied users, who will likely stay with you over time.
Three categories of people can be distinguished: Detractors (a 0 to 6 score), Passives (a 7 or 8 score) and Promoters (respondents giving a 9 or 10 score). Calculating NPS isn’t as simple as averaging the ratings. So, use software to do it.
There are many tools that help you for measure and calculate your NPS: Drift, Delighted and Promoter.io.
As a subscription-based business, your growth depends on new customer acquisition, and crucially, minimizing the loss of your existing customers. Customer churn (often referred to as “Logo Churn”) measures the rate at which your existing customers cancel their subscription to your service.
Revenue churn (also referred to as “MRR churn rate”) is used to look at the rate at which monthly recurring revenue (MRR) is lost, as a result of lost customers and downgraded subscriptions.
Customer Lifetime Value is one of the most important metrics for understanding your customers. For some, it’s the only one that matters. It helps you make business decisions about Sales, Marketing, Product Development, and Customer Support. It’s actually pretty simple.
First, we need to calculate out Customer Lifetime which is:
1 / Customer churn rate = CLTV
The LTV is also important in discovering if a business model for a SaaS company is viable or not. In an out-of-balance business model CAC exceeds LTV, whereas in a balanced model CAC is significantly less than LTV.
This needs to be above 3.0 to be healthy and for you to have a viable customer acquisition strategy. If your CLTV is too low, you need to reduce churn. If your CAC is too high, you need to find less expensive ways to acquire customers.
CPL is calculated by taking the total amount spent in a campaign in a certain channel and dividing it by the number of leads that campaign generated.
Total spent in campaign / total leads from campaign = CPL
CPL is important to calculate and keep track of to find and compare your most profitable acquisition channels.
Email subscribers are visitors who’ve signed up for your newsletter, mailing list or blog updates. Though they’ve parted with their contact details, they haven’t shown any indication of sales intent, or interest in your SaaS product, making them distinct from leads.
Tracking these numbers will give you great context into how your marketing efforts are going. Identifying discrepancies in metrics and being able to compare one to another is crucial to marking a strategy as a success or failure.
In the next chapter, we’ll talk about how to use some of these metrics to inform optimizing marketing efforts.