Marketers today have access to more data than ever before. Regardless of the systems you use, you likely have at least one dashboard in programmes like Hubspot and Salesforce that put a million different data points at your fingertips at the click of a button.
Now, I don’t know about you, but despite 15+ years in marketing, I still struggle to see the value of some of these numbers and to contextualise their meaning across so many different data points. The reality is that most of us are tracking too many things—not because the information is useful, but simply because we can.
Over time, I’ve refined my process to distill down the metrics and KPIs that are the most meaningful to me, and I’ve come to the conclusion that there are only three distinct buckets you need to look at. I’ve listed them below, along with a few things to keep in mind as you establish your own KPI monitoring cadence.
Simply put, engagement metrics measure how your prospects and engaged prospects respond to your campaigns and content. The specific engagement metrics you track should be influenced by your individual campaigns and should demonstrate some level of intent to be put into your marketing funnel or into your sales process through your SDRs. For example, if you’re trying to drive engagement through LinkedIn, you might measure likes, comments, and shares on your company profile or the personal profiles of your company’s leadership.
On the other hand, if your focus is on website engagement, you might measure website visits, average time on site, or pages per visit—basically, whatever the best leading indicator is for your specific company from an engagement perspective.
Now, you can go a lot deeper with this process, depending on how engagement is designed within your business. Imagine that you’re only marketing on LinkedIn. In this case, there are several different ways you could measure engagement. One would be to follow the growth of your personal page or company profile in terms of ICP accounts. If you’re publishing playbook-type content, engagement might be measured in terms of clicks, form fills, ‘reading time’, or any other metric that demonstrates how engaged your target audience is with your content.
Going even deeper, one way to measure engagement at different funnel stages is with multi-tiered lead designations. For instance, imagine you’re monitoring connection growth within your ICP accounts, but you still want to be able to separate out prospects who are higher up in the funnel from those who are more engaged. In that case, you might have several MQL designations—not just one.
However you decide to measure engagement, don’t be afraid to pivot your strategy. Establishing your metrics is a medium-to-long-term play. Pick somewhere to start, but learn as you go and make changes as needed to ensure your chosen metrics are as useful as possible.
Next up are your pipeline metrics, meaning the KPIs that measure the number of customers at each stage of the funnel, as well as their conversion rates from one stage to the next.
Establishing pipeline metrics is relatively more straightforward than setting engagement KPIs. To start, you’ll need to identify each stage of your unique funnel, as well as implement a tracking mechanism that shows you how many people pass through each stage within a set amount of time.
For example, imagine you use a basic funnel like the following, and you see that the corresponding number of people pass through each stage in a given month:
Prospects - 1000 -
MQLs- 200
SQLs - 15
Closed-won - 1
Using this data, you can establish your conversion rates between funnel stages:
You can also measure conversions between stages to understand your funnel’s overall performance. For instance, dividing 1000 prospects by 1 closed-won customer represents a 0.1% overall conversion rate.
Even better, you can use pipeline metrics to understand the velocity of your sales process. Tracking this data will enable you to plan effectively in terms of sales forecasting.
Finally, you have your revenue metrics, including KPIs like:
Tracking these metrics requires some upfront labour—to measure customer lifetime value, for example, you need to have some type of tracking system in place that reveals these costs. However, these metrics are especially important to the health of your business, since you don’t want to be signing a load of rubbish customers with no LTV.
Generally speaking, if you have a low CAC and a high LTV, you have a healthy business model. If you have a high CAC and a low LTV, you’re in trouble. There are exceptions to this. If you have upfront funding and can sustain high CACs, knowing that your business model is going to change in the future to bring your costs down, you may be able to get away with operating in the negative for a short time. But eventually, you have to have a transitionary period where your costs come down or your LTV improves—no business can run long-term with a high CAC and a low lifetime value.
Knowing your revenue numbers helps you work out whether you’re operating sustainably, but it can also help you understand the numbers you need to hit at each stage of your funnel to meet your goals.
For example, if you know that 0.1% of your prospects eventually become customers—and you know your CAC and LTV—you can work out how many prospects you need to reach to hit your goals, as well as whether your sales and marketing budgets are large enough to cover your potential costs. You can also determine whether these costs are justified, given your LTV. If not, you’ll know you need to make changes at some point in your funnel.
One final note here is the importance of brand building. If your funnel relies entirely on performance marketing, your revenue metrics might be ok when you first start out. But what happens if Google or LinkedIn raise their ad prices, which happens regularly? What happens if the board says you have to cut your performance spend? Unless you also invest in building your brand with a minimal viable audience, relying on ads is both highly risky and unlikely to be sustainable.
Now, one common concern I hear a lot is that “Oh, we don’t have data; we’re just a startup”. My advice there is that it’s better to move ahead in an imperfect way than it is to not move forward at all. Try to work out a few target metrics for each group as a starting point. You can always come back and change your metrics as your programme grows in sophistication. But if you continually wait for everything to be perfect before starting, there’s a good chance you’ll never get started to begin with.
A bespoke framework and capability model 'DEMAND KARMA' that delivers DD services to investors, VC firms and CEOs.
Retained advisory at funded scale-ups. A simple monthly fee. Helping CEOs build a scalable marketing machine. (Booked out until December)
Book time on my calendar to work through a standalone project or to get answers to your most pressing marketing strategy and execution questions.
