What Is Analytics?

Caption:​ Analytics begins when you compare metrics, examine their relationships, and ask questions that lead to better business decisions.

Is analytics the same thing as a metric?

The answer is “No”, analytics is not the same thing as a metric. Before we talk about analytics, let’s quickly review what a metric is. A metric is a defined measurement that you track because it measures something important to your business. If you’ve already read What Is a Metric?, this will be familiar. If not, don’t worry—you’ll have everything you need to follow along, and you can always read What Is a Metric? later for a more in-depth explanation

Analytics is the next step. It takes those metrics and helps you understand what they mean. Stated plainly: analytics is taking the numbers you’ve tracked and comparing them under specific conditions you choose — this month vs. last month, before vs. after a change, one stage vs. the next — so you can see what the comparison is actually telling you. Everything else in this article is really just that one idea, shown a few different ways.

You may also hear analytics called data analysis — and honestly, that’s the more accurate name for what’s happening: you’re looking at numbers and asking questions about them. Most people just call the whole thing “analytics” instead, so that’s the word this series uses too. But don’t let the two words confuse you — they’re pointing at the same thing you’re already doing.

The whole chain, from a raw number to a decision

Everything in this article fits together in one line:

Numbers → Measurements → Metrics → Analytics → Better Business Decisions

Here’s what each step means:

• Number — just a raw value, with no context. 50, by itself, means nothing.
• Measurement — the same number, once you give it context. “50 visitors” is a measurement — now it means something specific.
• Metric — a measurement you deliberately track on purpose, over time, because it tells you something you need to know. That’s the word the last article used all along.
• Analytics — asking questions about that metric: is it higher or lower than before, and why?
• Better business decisions — what you actually do once you understand the answer.

Each step builds on the one before it. You already do the first three without thinking about it — analytics and better decisions are simply what happens once you start looking back at what you’ve tracked. The rest of this article is about that last part: how to actually do it.

Analytics begins when you ask questions

A metric, by itself, is just a fact. Analytics starts the moment you look at that fact and ask something about it.

Take income. Say your notebook shows:

• Metric: Income this month: $42,000
• Metric: Number of sales this month: 13
• Metric: Income last month: $38,000
• Metric: Number of sales last month: 12

That’s just a fact — true, but not yet useful on its own.

Now, let’s take the next step by comparing the two metrics. This is the first step in analytics.

• Analytics: income this month is different from last month. The reason is one additional sale is associated with the extra income. You are now beginning to examine the relationship among the metrics within a particular context.

Analytics is what happens when you start asking about it:

• Is that more or less than last month?
• Why did it go up (or down)?
• Was it a few big sales, or a lot of small ones?
• Is that likely to happen again next month?

The numbers didn’t change. What changed is that you’re now understanding them in a relational context instead of just recording them.

The same thing works for expenses and savings

You don’t need new metrics to start doing analytics — the ones from the last article are enough.

• Expenses: Did they go up? Did they go up faster than income did? Is there anything in there you could cut?
• Savings/profit: Was it higher this month? Was that because sales went up, or because expenses went down? Is that level likely to hold, or was it a one-time thing?

Notice the pattern: the metric is a single number. The analytics is a handful of honest questions about that number.

Metrics Are the Gauges. Analytics Comes from Comparing Their Readings.

Think of the dashboard in a car. The speedometer, the fuel gauge, the temperature gauge — each one is a metric. It tells you one fact, right now.

Analytics is what a driver does with those gauges: noticing the fuel gauge is dropping faster than usual, wondering why, and deciding whether to pull over. The gauge doesn’t do that interpreting for you — you do, by paying attention to what it’s telling you and asking what it means. Another example is noticing that your average speed has been steadily increasing over the last several miles and deciding to slow down before you exceed the speed limit. If you go over, you know what the results could be.

Your business metrics work the same way. They’re the gauges. The readings tell you where you are today. Analytics comes from comparing those readings over time to understand what they mean.

Analytics gets stronger when you compare across time

So far, every question has been about one number at a time. Analytics gets more useful once you start comparing one point in time to another — that’s usually where real patterns show up.

Notice what all of these have in common: there’s always a comparison. That’s really the heart of analytics — metrics measure, analytics compare, and comparisons are what reveal a pattern worth acting on.

One thing to be clear about: this table is just showing you what a comparison looks like — it’s not a list of things you’re supposed to be tracking. You don’t need referrals, email, and seasonal sales data all at once. Use whatever metrics you actually have, and compare those.

Comparisons don’t have to be across time — they can be across stages, too

Time isn’t the only thing you can compare. You can also compare the different stages someone goes through on their way to becoming a customer — and ask why the numbers drop or hold steady from one stage to the next.

Remember the business-card story from an earlier post: some people took a card and walked away, some kept it, some scheduled a follow-up, and a few became customers. Each of those was a metric — a count at one stage of that journey.

Each column on its own is just a count. Reading across the row — asking why the number dropped or held steady from one stage to the next — is the analytics. Again, this is just one example of what stages might look like — your own business may have different, or fewer, stages worth watching.

When adding a website or social media, the same idea applies

You may not have these yet, and none of this is required right now — but it’s worth knowing the same “metric vs. analytics” idea carries over once you do.

A website, social media, and email each produce their own set of metrics — plain counts, same as anything else you’ve tracked so far: 

On their own, each of those is just a count — the same as “income this month” is just a count. Analytics is what happens when you start comparing them: did a social media post send people to your website? Did an email bring someone back in to buy? You don’t need to know any of this today — it’s simply the same idea, showing up again once you have an online presence to apply it to.

Do you need something fancy to do this?

No — analytics isn’t a tool, it’s a habit. If you’re already writing your metrics down on paper or in a simple spreadsheet, you already have everything you need. The only new step is occasionally looking back at what you’ve written and asking a few honest questions about it, instead of only glancing at today’s entry.

As your notes build up over months, spotting patterns by eye gets a little harder — that’s usually when a spreadsheet’s basic sorting or a simple chart starts to help. But that’s a later problem. Right now, the habit of looking back and asking “why” is the whole thing.

Where this fits with the layers from before

Analytics isn’t a new layer sitting on top of money, customers, and growth — it’s what ties those layers together.

Each layer — money, customers, growth — is made up of individual metrics. Analytics is simply the habit of looking across any of those layers, comparing one point in time to another, and asking what changed and why. It’s not a fourth layer to learn. It’s what you start doing once you already have layers worth looking back on.

The whole idea, in one paragraph

A metric is a single number you track on purpose because it tells you something. Analytics is what happens next — asking honest questions about that number, like whether it’s higher or lower than before, and why. The chain runs: numbers become measurements once you give them context; measurements you track on purpose become metrics; asking questions about those metrics is analytics; and the answers lead to better decisions. You don’t need new tools or new metrics to start; the income, expenses, savings, and customer numbers from the last article are already enough. Metrics are the gauges. Analytics is comparing readings and deciding what to do based on what you see.

What’s next

This article has used the metrics from the last one — income, expenses, customers — without asking where any of those numbers actually come from. That’s the natural next question, and it’s what we’ll cover next.

New here?

This article is part of an ongoing series on business metrics, written so each piece stands on its own — you don’t need to have read the others to follow this one. That said, if you’d like the full picture, it helps to start from the beginning: “What Is a Metric? A Business Metrics Guide for Beginners.” From there, each article builds on the last.

Next up: Where do metrics come from?

If any of this doesn’t quite click, or you’d like help applying it to your own business, feel free to send a message or schedule a call. No question is too basic — that’s exactly what this series is for.

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