How to Choose The Right Metrics

A metric is not just a number. It's a signal. A well-chosen metric tells you something is working — or  something needs to change. A poorly-chosen metric is a distraction that keeps you busy without moving anything forward.

This guide will help you think about metrics the way high-performing teams do: with intention, clarity, and a focus on action. We'll use a grocery store as our running example — because good metric thinking applies everywhere, from mid-sized businesses to enterprise-level corporations.

The "What’s Next?" Test

Before you commit to tracking a metric, ask yourself this question: "What’s next?"

Meaningful metrics should give you something to think about and prompt you to take action. For example, imagine your dashboard shows that sales in your Vancouver location dropped 12% last week. Okay — What do you do next? Do you know why it dropped? Which products? Which customer segments? And, most importantly, what action does that number lead you to take?

If a metric doesn't point you toward a decision or action, it may be measuring the wrong thing — or measuring the right thing but in the wrong way.

Here’s an example using a grocery store:

Your grocery store sells fruit. You track a metric called “Fruit Sales”.

One Monday, the number is down. But is it Apples? Oranges? Bananas?
Is it a Toronto problem or a Vancouver problem?

The “Fruit Sales” metric doesn’t answer any of these questions — and so it can't tell you whether to reorder stock, run a promotion, or call your supplier.

It fails the “What’s next?” test.

Metrics that pass the "What’s next?" test are actionable. They point to a specific response or responses. Here's a simple way to apply it:

• What decision could I make if this number goes up?
• What decision could I make if this number goes down?
• Who on my team would act on this number?

If you can't answer at least two of these three questions, the metric needs to be redefined, or replaced with a different one.

Does This Metric Align With Your Goals?

Every team has a purpose. Sales teams want to grow revenue. Operations teams want to reduce waste and costs. Marketing teams want to find and attract the right customers. A good metric reflects that purpose directly.

When you're evaluating a metric, ask: "Does tracking this help my team get better at what we're supposed to be doing?"

Let’s go back to the grocery store:

The produce manager's goal is to minimize spoilage and maximize sales. The right metrics for them could be:

• Sell-Through Rate by Fruit Type — what % of what we stocked actually sold
• Days to Spoilage by Product — how long until we have to discount or discard
• Revenue per Square Foot of Display — are Oranges earning their shelf space?

Total Revenue alone? Not aligned. Useful somewhere, but not for the produce manager trying to decide whether to order more Oranges or put Bananas on sale.

Leading Vs Lagging Indicators: Cause And Effect

Here's something that trips up a lot of teams: technically, all metrics are historical. By the time a number appears on your dashboard, it's already measuring something that happened. The thing to understand here is it’s not really about “past vs future”- It’s about cause and effect, from the perspective of your team and its goals.

A leading indicator is a metric that reliably precedes and influences a desired outcome. To qualify, it needs to meet three conditions:

• It must be causally connected (or at least strongly correlated) to the outcome you care about
• It must move before the outcome moves
• It must be something you can actually act on — if you can't influence it, it's not truly leading, it's just earlier

A lagging indicator is a metric that shows results from earlier actions. It tells you whether your efforts worked, but by the time you see the results, the window to intervene has usually passed.

Here’s the tricky bit: The same metric can be leading for one team and lagging for another.  
Let’s use the “Marketing Qualified Leads (MQLs)” metric as an example:

Meanwhile at the grocery store:

For the produce manager, last week’s flyer spend is a leading indicator. It predicts how many customers might come looking for bananas this weekend.

For the store's advertising team, the same flyer spend is a lagging result of their campaign budget decisions.

Same number, two different perspectives.

The essential principle is always cause → effect.

When you're choosing metrics, ask: for my team's goals, does this metric tell me something happened, or does it help me predict and shape what's going to happen next?

The best dashboards include both — lagging metrics to confirm results, and leading metrics to give you time to act.

Raw Numbers vs Ratios

Raw or absolute numbers lack context. For example, a raw value of "1,000 customers" might sound great, but, is it? Compared to what? Your competitor? Your target?

Ratios and percentages include context. They naturally allow you to make comparisons — across time, across teams, across regions.

What ratios reveal – let’s go back to the grocery store for an example:

Suppose that last week, the Toronto store sold 800 oranges and the Vancouver store sold 500 oranges.

The Toronto location wins, right? Not so fast.

Toronto stocked 1,200 oranges. Vancouver stocked 520. Toronto's sell-through rate was 67%. Vancouver's was 96%.

Suddenly the story flips. Vancouver is running a tighter, more efficient operation. The ratio shows you something you wouldn’t otherwise have seen. 

Ratios are one of the reasons calculated metrics — like “Sell-Through Rate”, “Revenue per Customer”, and “Average Order Value” — are often more valuable than raw counts. We'll dive deeper into calculated metrics in Article 3: Building Block Thinking.

There is an important note here though. Ratios and rates can be volatile and misleading if the underlying numbers are too small. If your sales in Vancouver increased by 100%, you might be inclined to celebrate — unless that number was achieved by selling just one additional banana! While ratios do offer more context, it's important to always know what sample size you're working with.

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The Golden Rule of Good Metrics

Across all these considerations — actionability, alignment, leading vs. lagging, ratios over raw numbers — three qualities show up again and again in the best metrics. We call this the Golden Rule:

A Golden Rule Metric in Action

"Revenue per Customer Visit by City" checks all three boxes.

• Understandable and Comparable - It’s a simple concept that everyone can understand. It compares one location to another (Toronto vs Vancouver).
• Ratio-based - Because it's “revenue divided by visits”, it’s an accurate, fair way to measure results for stores of different sizes.
• Bonus - It also passes the “What’s next?” test - If Vancouver’s number drops, you know to look at either average spend or foot traffic for that location.

Don't Track Everything. Track What Matters.

One of the most common mistakes teams make is tracking too much. Every additional metric on a dashboard competes for attention. The more you track, the harder it is to notice what actually matters.

A focused set of well-chosen metrics is more powerful than a sprawling collection of data points. Here's a practical framework for deciding what makes the cut:

If a proposed metric doesn’t meet at least two of these criteria, reconsider whether it belongs on your dashboard or in your metric catalog — or whether it needs to be defined more clearly before you start tracking it.

Quick Recap

• The "What’s next?" test: If a metric doesn't lead to a decision or action, reconsider it.
• Goal alignment: Track what moves your team's needle, not just what's easy to count.
• Leading vs. lagging indicators: It's not past vs. future — it's cause vs. effect.
• Ratios vs raw numbers: Ratios provide the context needed to make fair, meaningful comparisons.
• The Golden Rule: good metrics are understandable, comparable, and ratio-based.
• Track what matters: Only track the metrics that make a difference to your business.

Next Steps

Now that you know how to choose good metrics, it’s time to learn what a metric actually is. In our next article, we'll get into the core vocabulary of data: metrics, measures, and dimensions.

From there, we’ll move on to a third article that introduces “Building Block Thinking”. You’ll discover how well-defined base metrics can be combined into powerful, calculated metrics. We’ll conclude our introductory series with an article on “Graph Thinking”, the approach that makes your data truly AI-ready.

Continue Learning

• Metrics: The Building Blocks of Modern Self-Serve BI — a deep dive into how metrics are structured, stored, and shared across your organization.
• MetricHQ — an expert-contributed library of metrics and KPIs across every business function, so you're never starting from a blank slate.

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