“What gets measured gets managed.”
– Peter Drucker, management consultant and author
Sales Metrics
There are 2 main categories of metrics you should pay attention to in sales:
1. Customer Metrics
Conversion rate, sales cycle, customer acquisition cost (CAC), lifetime value (LTV), churn, etc. Clarity on these metrics helps you with further improving your messaging and activities to capture more customers, more quickly, and with fewer resources.
2. SDR Metrics/Key Performance Indicators (KPIs)
Sales target achievement, number of deals closed, an individual’s conversion rate, activity metrics (e.g. number of calls made, emails sent, meetings booked, etc.), customer satisfaction, etc. These metrics are necessary to effectively coach and support your SDRs.
I won’t go into the details or various formulas you can use for calculating them since there is already an abundance of information available online. I will instead focus more on how to effectively use your data. But before you jump into trying to capture as much data as possible, remember:
“Data is like garbage.
– Mark Twain, author
You’d better know what you are going to do with it before you collect it.”
Data is Only a Part of The Picture
If you ask, “How did you hear about us?” to try to better understand what led your prospects to you (a.k.a. source), the answer may not paint the full picture.
They may have originally heard your ad on the radio, seen a few Facebook ads, and then searched for a solution to their problem on Google. They happened to select you because they were already familiar with your brand and might answer “Google” due to the recency effect: the tendency for people to recall items or information they encountered most recently more easily and accurately than information encountered earlier. Or they might have deflected their response to the most obvious answer because they honestly don’t recall where they first heard about you.
Data is important, but make peace knowing it won’t be 100% accurate because you’re dealing with messy humans. Worst case, with bots, and predictability more so in the coming future, with AI. A lot of what you capture may not even be human, a study found approximately 20% of ad impressions served in the United States alone were fraudulent. It’s becoming increasingly difficult to distinguish humans from bots in ad clicks, web traffic, and even social media engagement.
Begin your data strategy with your goal and work back from there:
- What are you trying to improve?
- What do you need to learn to improve it?
- What data can you capture to help you better understand what you’re trying to learn or give you an indication if you’re trending in the right direction?
Some Things are Difficult or Impossible to Measure Accurately
While transactions are easy to measure, the quality of a relationship is a lot harder to quantify. Even with great referral tracking in place, you might still miss properly attributing a referral if they don’t remember who they heard about you from.
Step back to consider the bigger picture and long-term outcomes as well.
Account for Indirect Effects
Rarely will data depict a direct correlation between activity and outcomes. Even if it does, it’s still important to take a bigger picture perspective and be mindful of other less obvious effects. This story of Kinko’s from the Empire Builders podcast provides an excellent illustration:
Many of you may not be familiar with Kinko’s. For some context, they were a popular American photocopying and printing retail chain in the 1980s and 1990s. Kinko’s was acquired by FedEx in 2003 for $2.4 billion. There was a point in their operations where Paul, the founder, was evaluating with a partner for one of their locations in a convenience store, whether they should keep it open 24 hours.
They would do about $30 worth of business at night and $60,000 during the day. Based on this obvious observation, they decided to close at night; however, as soon as they did, daytime business also dropped by about 50%. This led Paul to get all the other stores to do the same, and it was monumental in helping them grow the business nationwide.
Why in the world would that happen?! They still barely sold anything at night. There are many opinions on possibilities, but here are some potential explanations:
- Perhaps that was when they acquired a new customer because they were the only store open?
- Maybe it made them more noticeable because they were the only store visibly lit up at night?
- Or because it helped anchor an impression of reliability that kept them top-of-mind for their customers?
Whatever the reason, and even if doing the same thing might not create similar results in your context, business, or location, the point here is to be attentive to indirect and less obvious effects that you may not be intentionally measuring or observing.
Some Things Take Time
Data is often captured in short windows. However, some campaigns may take a while to bear fruit. I don’t recall the specifics, but I heard an example along the lines of:
There was a restaurant (in Yukon, if I’m not mistaken) renowned as a high-end establishment, the kind you would take your partner for a fancy date night. In an attempt to grow revenue, they decided to adjust their marketing and branding to better capture casual diners.
In the short term, as they started to pull in both casual diners and fine diners, you could call their campaign a success. However, over time, this shift in positioning ended up sticking more than they anticipated and their establishment became better known as a location for casual dining. This eventually drove down average order value, and they even lost some of their loyal fine dining clientele, ultimately leading to a bigger loss in revenue.
It’s hard to predict the long-term outcome of a campaign like this, but before you jump the gun on defining success metrics, ensure
1. Your activities align with your organization’s values.
And
2. You not only measure the short-term results but also continue to analyze the long-term trends.
Many of us harbor common misconceptions and unconscious limitations regarding what we choose to measure and set as goals. Most goals, especially business goals, are set on Monthly, Quarterly, and Yearly targets. Paraphrasing Simon’s talk in this video:
These are unnatural limits because of pre-defined reporting, fiscal, or taxation cycles. We place similar limitations as well when we set personal goals: 30-day diets, resolutions for the new year, etc. While deadlines can be useful for driving urgency and challenging ourselves, we have to also remember life is a continuum, it’s not constrained by months or years. Let’s look at an example of 2 different sales teams working towards hitting their monthly revenue goals:
Team A:
- Morale is up and down. If the month starts slow and they feel like they won’t hit the target, they are not motivated.
- Poor retention, people are quitting all the time.
- There is no trust amongst the team as people compete with each other to steal sales.
- Toxic leadership.
Team B:
- Slow and steady growth, trending towards hitting the goal.
- Good and strong team.
- Good morale, has a capable leader.
We set a monthly revenue target and incentivize both teams to hit that target to obtain their bonus.
Team A aggressively closes customers, scrambles with last-minute discounts, and meets the target.
Team B falls slightly shy of the target but displays all the right behaviors.
If we incentivize Team A with the bonus, this is the message we’re sending: “We don’t care how you get there. We don’t care if you step on your co-workers. We don’t care if you are unethical. If you hit your number, you’ll do well in our organization.”
Of course, this is a theoretical example. Team B could also be highly motivated by the bonus and scrambled to meet it. But the point is: HOW you get there matters as much, if not more, than WHEN you get there.
As Simon says:
“When you have an infinite mindset, absolutely, have the goals, but the trend matters more. How you get there matters as much, if not more, and we pay attention to that. So even if I hit my fitness goal, I’m eating better, I’m sleeping better, my relationships are great, I’m going to the gym. Yes, I miss my goal, but I know if I just keep going, I’ll hit it. I’m getting healthier and healthier. I just got the timing wrong.
This is what we need to build into business: that infinite mindset. Yes, have the goals; yes, have the ambitions; yes, have the annual targets. If we miss them, as long as we’re doing the right things, we have the right lifestyle to take us there. That’s a much healthier way to live a life and a much healthier way to build an organization.”
Avoid accidentally encouraging bad behavior by incorrectly incentivizing the achievement of metrics (lagging) without accounting for how we achieve (leading) the desired results and the long-term trends. Recognize and reward the appropriate behaviors that contribute positively to your objectives.
Turn Data Collection into Customer Value
Say you run a restaurant and you’re trying to learn more about your customers: How many times does a customer return? How frequently? How much do they typically spend on a meal or drinks? What’s their average order size?
You could obtain this information by collecting their phone number or email. This would allow you to associate an individual with their behaviors during each visit and even potentially market promotions or specials to them.
To capture it, you may decide to train your servers to request a customer’s contact information before seating them. Don’t penalize them for failing to capture this information. Perhaps customers are not willing to readily disclose their contact information without context, as they do not want to receive spam. Instead, create an opportunity to improve the customer experience and add value with this information exchange.
This can be done if you make the benefit of the exchange clear. Perhaps you want their phone number so you can notify them when their table is ready, or they can unlock and track points with their phone number to exchange for discounts or free meals.
Lagging vs. Leading Metrics
| Lagging Metrics | Leading Metrics |
|---|---|
| • Outcome/Results • Which you don’t control • Usually business-centric | • Output, Behaviors, Activities, or Initiatives • Which you can control • Usually customer-centric |
| • Monthly revenue • # of conversions • Customers closed | • # of sales calls or outreach emails sent • # of events you organize • # of customers followed up with. |
Although the word “lagging” has a negative connotation, BOTH are important. What you choose to display and reward will also greatly affect the culture of your organization. Read this Inc. article “Jeff Bezos on Why Eliminating Daily Dashboards Can Make You More Focused, Productive, and Successful, Backed by Science” for more detailed insights. To summarize:
Lagging Metrics are easy to define and track. They help assess if your activities are effective and should regularly be reflected upon to determine if your initiatives are yielding the intended results.
Leading Metrics, on the other hand, help you predict where you will go. They’re indicators of the processes that you predict will produce certain results. If you’re looking to cultivate and encourage certain behaviors, it’s better to focus on leading rather than lagging metrics, since lagging metrics are only indicative of the outcome, regardless of what was done to achieve them.
For instance, if you’re trying to improve customer satisfaction:
| Lagging Metric | Leading Metrics |
|---|---|
| Net Promoter Score (NPS) | • How long till calls are answered (wait time) • ?% of resolved cases. |
| If you want to improve it, you need to look upstream to determine what initiatives you can put in place to improve this outcome. | • If it’s taking too long to answer calls you may need to hire more Customer Service Representatives (CSRs). • If too many cases are left unresolved, you may need to change something about your offering or possibly empower your CSRs so that they have more options or authority to resolve without needing to escalate. |
You may also enjoy reading: Don’t Just Trust The Numbers.
ASSIGNMENT
Define specific Lagging and Leading Sales metrics. If you need a framework to categorize them to ensure you’re accounting for all stages of the customer’s journey, the Pirate Metrics framework introduced by Dave McClure, founder of 500 Startups, is a pretty good place to start.
Pirate Metrics = AARRR (like a pirate, get it?)
| Stage | Example Metrics | Your metrics (no more than 3 per stage) |
|---|---|---|
| Acquisition | Website visits, Ad clicks, Prospects who walk into the store, New leads generated, Downloads | |
| Activation | Activation rate (% of users completing an essential action – e.g. using a feature, completing their 1st transaction), Onboarding completion rate | |
| Retention | Churn rate, Customer LTV, Repeat purchase rate, Engagement metrics (e.g. time spent on site/app, frequency of visits) | |
| Revenue | Average revenue per user (ARPU), Average order value (AOV), Conversion from free to paid, Monthly/annual recurring revenue (M/ARR), Sales cycle | |
| Referral | Net Promoter Score (NPS), Number of referrals made by customers, Referral conversion rate, Social media shares and mentions |