Today’s post is dedicated to the Ukrainian resistance. If you haven’t yet found a way to support the cause, please see this page from the Ukrainian government that might get you inspired.
Why does a business exist?
There are two ways to answer this question. The first involves purpose - solve a real need for a group of people through products and services you offer. The second involves profit - generate ROI for shareholders (investors and employees).
In today's post, we'll focus on the latter - profit. The concept of profit is relatively simple—revenue minus cost. However, there are a lot of nuances to be aware of when analyzing the quality of that revenue, cost, and the resulting profit and can make or break a sustainable business. This is why studying the seven metrics below is critical.
You must have a good understanding of basic financial metrics like revenue, costs, and profitability for your business before you can get to the advanced metrics below.
Most GTM operators falter when looking at retention. Without a high retention business, sales & marketing teams have an uphill battle every month or year trying to find new customers for their business because prior customers are either churning or not doing repeat business with them.
The first metric that can help you avoid this misery is Logo Retention. Let's say you acquire 100 customers in a month. Out of those 100 customers, what percentage stay as customers in the following month or a year from now? If this remains close to 100% over time, you have a solid business. If this drops precipitously over time, that's not a good sign. If it drops initially but plateaus to a stable state that continues for many months/years, that's a defensible business.
You should be looking at this metric for every monthly and yearly cohort of customers to understand if your GTM and Product efforts are improving or hurting Logo Retention.
Continuing with the example above, let's say that each of the 100 customers you acquire in a month pay you $100/mo. After a few months, 20% upgrade to a $500/mo plan and 20% churn. The net effect is that even while your Logo Retention is 80%, your Dollar Retention is 180% due to the higher revenue from the customers upgrading to the higher price plan. 100%+ Net Dollar Retention is usually a great place to be. This is fantastic!
Suppose you can grow the average revenue per user over time in this way through pricing/packaging or through cross-selling or through usage-based pricing. In that case, you can increase net dollar retention significantly.
These metrics aren't just for SaaS businesses. You can look at the same metrics for ecommerce, marketplace, or payments businesses by looking at every cohort of customers and the revenue contributions of that cohort from the GPV or GMV in subsequent months or years.
100%+ Logo Retention and Dollar Retention allows your initial upfront sales & marketing investment to grow without additional efforts, almost like a savings account or a financial investment. Err, that's what a great business is all about. That's what investors and shareholders ultimately want.
Don't get me wrong, lack of good performance in these two areas isn't necessarily a death sentence for the business. But, it means you've got hard work to do every month because the number of customers and dollars your business goes down over time, so you're depleting your bank balance in this regard.
Yes, there is a way to measure product/market fit!
Rahul Vohra, from SuperHuman fame, posted about this a few years ago. It got a lot of hype and attention back then, but I don't think it reached mainstream acceptance even though everyone loves talking about P/M fit these days! :)
So, how do you measure P/M fit? Ask your new customers about how disappointed they'd be if they couldn't use your product or service. If you get at least 40% saying "Very disappointed," you're on to something. The ideal time to collect this data is after they've experienced the core value of your product or offer. For some businesses, this could be within days of new customer signup, and for others, it could be weeks or months.
If you're going to measure P/M fit, make sure you can collect data for a high percentage of customers and ensure that the data collection method gets you a proper representative sample and doesn't ignore disengaged customers. If you're only measuring this for a small subset and extrapolating, you're making a dangerous assumption.
My strong recommendation is to collect product/market fit data often and consistently. Why? Because it's possible to lose product/market fit as you expand to new segments of customers, launch new products and services, refine your pricing and packaging, and change the user or buyer experience.
This one will be spicy! I think Pipeline is one of the most important and yet misunderstood topics in GTM.
Every sales & marketing team has a quota/plan to hit on a monthly, quarterly, and yearly basis - regardless of the sales motion - inbound, product-led, or outbound.
In each of those sales motions, there's a funnel to manage. The value in each stage of the funnel is the Pipeline at that stage. As a prospect progresses through the funnel stages, the probability of winning goes up, and the team feels more confident in the Pipeline. Pretty straightforward.
What's interesting to me is that most GTM teams don't align around Pipeline holistically. Sales teams do because that's how they operate against their quota, which is tied to their compensation. However, most marketing teams don't do this due to convention. Most marketing teams are assigned goals around the "hand-off" to sales - MQLs, SQLs, SQOs. Ultimately, what matters is Pipeline since that's the metric directly upstream to revenue.
Creating goals in this manner makes it easy for sales & marketing to fall out of alignment. Marketing ends up optimizing the quantity of those MQLs, SQLs, SQOs. Yes, there will be checks and balances around quality, but those are hard to do well in practice. It's practically impossible to perfectly validate prospects' quality as a buyer with marketing data.
There is a better way. I learned about this from Chris Walker in this podcast episode. Total game changer.
HIRO stands for High Intent Revenue Opportunity. Chris defines this as a stage in the funnel where the probability to close won is 25% or higher. HIRO Pipeline, in turn, is the Pipeline at that stage and beyond. Setting goals for both marketing and sales teams around HIRO pipeline makes sure that everyone is thinking deeply enough about the bottom of the funnel and not just about getting traffic and leads at the top of the funnel.
If you have good attribution data (more on this another day), you can then split HIRO Pipeline by source and figure out source-specific contributions - website, social, outbound, etc.
Having worked in many self-serve environments, an interesting observation for me is that the same concept applies there. Marketing teams in self-serve motions need to look at the conversion rate to the buying step and do all types of analysis + experimentation based on activation/usage in the product to increase the conversion rate. Not just the upstream traffic metrics.
This is another one I learned from Chris Walker!
The metrics helps you figure out out how quickly Pipeline is being created and converted to revenue.
Pipeline Velocity =
[Win Rate] x [ACV] x [Number of qualified opportunities created]
[Sales cycle length]
Win rate is the number of closed-won deals divided by total closed deals in that period. Average ACV and sales cycle length are calculated for closed-won deals only.
The output of this calculation is a number that reflects the amount of revenue your GTM engine is on track to generate daily. I love this metric because it allows GTM teams to monitor performance holistically and optimize each part of the equation.
If you have attribution set up correctly, you can analyze Pipeline Velocity by source and get granular insights into what's working and what's not. More on attribution in a future post!
I love how this brings everything together in a simple-to-understand way.
One straightforward way to look at the efficiency of your GTM engine is to analyze and benchmark the Payback period. Payback period is the number of months it takes for a customer to generate enough profit to pay back its CAC (Customer Acquisition Cost).
To calculate this, you need to divide all your sales & marketing spend, which generally forms CAC, by your MRR (Monthly Recurring Revenue) multiplied by your Gross Margin. However, as you've seen in the points above, MRR can go up or down for customers over time. So, it's more important to look at this on a time continuum to understand when the cumulative monthly revenue x margin for a customer reaches the break-even point for CAC. That's your payback period.
Even better if you look at this for each cohort of customers to see if Payback is improving or worsening as you acquire more customers and scale your GTM engine.
Tomasz Tunguz has some excellent articles on Payback period that you should check out here, here, and here.
The final metric we'll talk about is LTV to CAC. LTV is Lifetime Value and is the cumulative value of a customer throughout their lifetime. To calculate it, you need to either have historical data on customers' cumulative revenue/profit or need a simple predictive model for future revenue/profit.
The simplest way to model LTV is to divide the revenue or gross profit by the dollar churn rate. You can do this with annual or monthly numbers, and you'll arrive at the same result. The conventional benchmark for LTV:CAC is 3:1. Anything higher, and you're doing well. Anything lower, and your business isn't attractive to shareholders.
Suppose your churn rate is negative (i.e., positive net dollar retention). It will lead you to believe that your LTV is infinite, obviously incorrect. For such businesses, we need a different way to model LTV. I highly recommend David Skok's new formula here. It uses the concept of DCF (discounted cash flow), which essentially means that the value of a dollar 10 years from now is lower than the value of a dollar now. Therefore, using a "discount" for future value can provide a more realistic view of LTV.
These six metrics aren’t the end all be all. Each business is unique in its model and stage, and you should identify the right metrics that help you drive growth and profitability. I hope that these seven metrics provide you with a foundation for building your GTM strategy.
If you need help identifying the right metrics, please reach out and let’s chat!
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