Metrics should be a direct reflection of what is important to the business. In this blog post, we’ll outline how to think about Sales Metrics, given a specific sales motion. For early-stage companies, there are often multiple sales motions being run in parallel and your metrics should reflect that.
Many companies struggle to identify the best metrics to capture their success. There are, after all, many kinds of metrics that a company needs – north star metrics but also domain-specific metrics. Metrics should be a direct reflection of what is important to the business. In this blog post, we’ll outline how to think about Sales Metrics, given a specific sales motion. For early-stage companies, there are often multiple sales motions being run in parallel and your metrics should reflect that.
Measuring things is hard, but data helps enrich our understanding of what is going on. For growing organizations, your sales funnel metrics help you direct your focus, align understanding across your company, and drive impact. Using the right metrics specific to your sales motion helps break you out of generic numbers to user understanding and true process visibility.
As we move through this blog post, we will use Meroxa as an example. (Special thanks to CEO DeVaris Brown and the Meroxa team for allowing us to use them as an illustration in this blog post.) Meroxa is a real-time data platform as a service that gives data teams the data orchestration tools they need to build real-time streaming infrastructure in minutes, not months. It removes the time and overhead associated with configuring and managing brokers, connectors, transforms, functions, and streaming infrastructure. Companies using Meroxa add resources and set up connections to source data and targeted destinations and then schedule pipelines to move data in real time.
Meroxa has two kinds of sales motions, and they are defined by whether or not the customer needs to talk to someone before buying.
If a customer can purchase online, without talking to anyone, this is considered a self-serve sales motion. The vast majority of online shopping is a transactional sale. You would never think about having to talk to someone before you placed your next order from Amazon. Usually, customers who are engaging in a self-serve sales motion have already decided that they are going to trial and/or buy. Meroxa has a generous free-tier with the first 5 Million events each month being free with a pay-as-you-go option costing just $0.000006 per additional event. Meroxa’s free tier is in many ways a free trial. They grow with you as you, and your number of events, grow.
In this self-serve sales motion, we can think of the following points on our customers pre-conversion journey:
Some customers are looking for a consultative relationship with Meroxa. They are not interested in just buying the product, but talking to someone about their problems and envisioned use cases. They are looking to get value from the Meroxa team’s expertise. This may be as part of a bake-off where customers are considering multiple products or where the investment is significant. If a customer is targeting a consultative relationship, they know that that relationship will cost more- and we see this reflected in tiered pricing- but they are willing to pay the extra cost because they value their expertise.
This is especially visible in the post-sales journey, where customers are left with an account manager, account executive, technical account manager, or similar persona as a point of contact. These customers are not just buying your software but they are also buying a relationship. For most early-stage companies, all of your design partners and early customers are looking for consultative relationships.This sales motion requires slightly different metrics to best measure efficacy.
For the sales assisted part of the business, it’s similar but different:
Set up, activation, and aha are different and distinct moments in a user’s journey. When going through a definition exercise, oftentimes folks confuse these. It’s important to differentiate these in your metrics and in your mind. If people set up but don’t aha, they’re unlikely to convert. You can think of the Aha moment as the moment someone says “wow, I have to tell my coworker about this.” Every step between sign up and aha is crucial, and an opportunity for users to drop.
As you define these moments for your product, you will find that there is some trial and error to be had. The best thing you can do is make sure you’re collecting data as early as possible on your interactions, so that you can iterate on your model around these moments. For example, with Meroxa, one might hypothesize that setting up a pipeline is the Aha moment, but only after running correlation analyses and a regression do you realize that isn’t the best indicator of conversion and a successful pipeline is much better.
Over the life of a product, you may find that your set up and aha moments change. This is very normal in product development as the product evolves and the use cases for the product evolve alongside it.
When we think about setup, activation, and aha moments across our self-serve and sales-assisted funnels, whether these moments may be the same in both of these funnels is specific to your business. There may be a fundamental difference between the kind of customer who looks for a self-serve sales motion and the problems they’re looking to solve versus a sales-assisted customer looking for a solution to a similar but different problem, whether it’s large scope, additional complexity, or something else. For example, if someone is only buying one seat because they are a data team of 1, their product experience will be fundamentally different than someone who is helping their team of five run a bake-off of multiple products.
In this post, I’ve used terms like “users”, “customers”, and “accounts” interchangeably, but these are very distinct terms with very distinct meanings. “Users” are individuals who use your product independent of their financial relationship with your product. “Accounts” map to companies who are buying your product. If you sell to Acme Co with Maria, Jane, and Tyrone with logins, that is one account (Acme Co) with three users (Maria, Jane, and Tyrone). If Acme Co is paying you, that account is also a customer.
So what are teams? Some organizations sell into multiple teams within a company. In that case, teams are considered different groups within the same account. Don’t overcomplicate this sort of model until you need to.
Once customers adopt your product there is often the opportunity to help them better use it or solve additional use cases, resulting in expanding usage into additional tiers. These customers are Product Qualified Leads (PQLs). Some portion of users will do something that means they’re good targets for sales-assisted upsells. For Meroxa, monitoring usage, both data volume and number of resources, is a great way for them to understand that a customer is ready to get more serious, or define the relationship, as the kids say these days. Something about the user’s usage is an indicator that they’re going to want to expand usage with Meroxa, and you want to reach out to them before they reach out to you.
Different companies will use slightly different qualification contexts for different funnels for different customers. You may have heard about PQLs as a product qualification step in the sales process. The idea there is that you measure a propensity to convert based on product interaction. Your “aha” moment should capture this sentiment. PQLs should be based on post-purchase product usage.
When I talk to many companies, people feel that their metrics need to be specific to their business. And, they’re not wrong, but they’re not right either. These Sales Metrics should be a reflection of your customer’s journey, which will evolve over time as your customer evolves and matures, your product evolves and matures, and you understand product usage by customers. Even as your tracking becomes more granular, these funnel metrics can help serve as the pillars to track progress and growth over time.