Metrics are bullshit, you say, and you will be right. In something.
Indeed, when it comes to metrics, the very first metric that comes to mind is attendance.
Many people like to meditate for hours looking at the traffic graph of their site.
How cool it is to watch how the line jumps back and forth, back and forth ... And even cooler when site traffic is growing continuously.
Then blissful warmth spreads throughout the body and the mind soars to heaven in anticipation of manna from heaven.
Oh, what joy, what bliss!
And even if the picture is sad ...
You can't take your eyes off the schedule anyway, it's addictive.
It seems that there is a hidden meaning in the graphics. A little more, and the picture will reveal its secrets and tell you an incredibly simple and effective way to attract a huge number of customers. And then the money will definitely flow like a river.
But in fact, attendance is a typical “sweet (conceited) metric” that does not carry a useful meaning.
And most of these metrics. Basically, all the metrics that you will see are sugary. And that is why behind the metrics there was a bad reputation for a senseless waste of time and effort.
But in fact, this is not at all the case. The right metrics provide extremely important, and sometimes invaluable information for a business and a project.
The main bonus and purpose of metrics is that they make it possible to manage your business or project.
How to determine that the metric is bad?
Let's take a very simple example - the speed of a car.
Can you tell me what speed means...
100 km/h?
Hmm ...
Hmm ...
So what does it mean?
I think you probably guessed it yourself that ... does not mean anything!
OK. Now the second question:
Is 100 km/h good or bad?
Hmm ...
Neither one nor the other?
Right!
Speed is a completely useless and stupid metric. Unless, of course, it is used by itself. Together with other metrics, of course, it can say something, but on its own it definitely doesn’t.
Site traffic is exactly the same speed.
That is why there is absolutely no point in hanging in front of the site traffic schedule. He will not reveal to you the secret of life. Do you understand now?
What are good metrics then?
For example, Churn rate. This metric tells how many customers have left the company/website permanently over time.
Churn rate = 1% says that we are losing only 1% of customers. Those. we lose almost no one.
If Churn rate = 90%, then this means that we are losing almost all of our customers. It's horrible!
See the difference between this metric and speed?
Churn rate is a meaningful metric that answers the question of whether it is good or bad. And you don't have to guess what it means.
This is a metric that speaks for itself!
And now we are ready to take urgent action to reduce customer churn.
That is why such metrics are called effective. Because they motivate you to take action.
Criterion of “sweetness” of metrics
There is a very simple way to determine that the metric is “sweet / vanity” (English vanity).
Most absolute metrics, such as traffic, number of downloads, number of retweets, number of emails/subscribers, number of likes, etc. are sugary.
Relative, weighted, metrics are often powerful. But not all!
As for qualitative metrics, there is no unambiguity here, because a qualitative assessment in itself cannot be accurate and unambiguous.
But on the other hand, it is possible and necessary to evaluate the convenience of a program precisely by the level of perception of end users and nothing else.
How to approach metrics in general?
The first step is to turn the brain around.
No kidding.
Everyone (!) who encounters metrics, first of all, begins to look for the reason for being in them. But they won't show it, unfortunately.
Metrics are just like a regular ruler with which we measure everything we want.
You are not looking for the reason for being in an ordinary wooden ruler, right?
Finding the meaning of life in the line is what is called the bottom-up approach.
To work properly with metrics, you need to change the paradigm and start working the other way around, from top to bottom.
Those. first do some action, and then use metrics to measure the resulting effect.
Metrics should be used as a normal subject for measurement and nothing more.
Think about these words.
Use metrics to measure the effect of your actions, rather than invent actions based on the readings of a wooden ruler.
This approach is also called “Hypothesis->Measurement”.
Ok, this is understandable.
Question number 2: “What exactly to measure? How to find the right metrics?
How to create your own set of metrics?
Having climbed the Internet, you will surely find dozens or even hundreds of different metrics on the same topic.
For example, you can find about a hundred software quality metrics. These are GOSTR-ISO standards, and metrics calculated in SonarQube, and some self-written options, and even “high-quality” metrics based on user reviews.
So which are worth using and which are not?
The best approach is to be guided by the “core value”.
OMTM (One Metric That Matters)
Let's take an example.
It is clear that if you want to improve the quality of your software product, then you can measure this quality in different ways.
Quality is not only the number of errors. If you look at the quality in general, then this:
the number of incidents in the prom,
ease of use and ease of perception,
work speed,
completeness and timeliness of the implementation of the planned functionality,
security.
There are many criteria and it is impossible to work with all at once. They act very simply: they choose one, the most important criterion at the current moment, and work only with it.
This approach is called OMTM (One Metric That Matters) - One (Only) Important Metric.
It is logical to select the number of serious (important and critical) incidents in the industrial environment as the software quality OMTM.
For online stores, you don’t need to think about OMTM at all - it’s sales or profit (depending on your decision).
This One Important Metric will be the core value for your set of metrics. And it is from her that their final set will depend.
Inside Value
They often start compiling a set of metrics “from scratch”, rummaging through the Internet and choosing the best options from the found ones according to the principle: “Oh! This will suit us!”
As you understand, this is not the best way, right?
But how to decide which metric to take and which not?
For example, various kinds of user conversions are often measured.
But why are users being measured and not something else? Have you thought about this question?
Naturally, there is an answer.
Let's take an online store as the easiest example to understand.
Let's say you want to increase your sales. What metrics do you need for this? How to approach this?
There is one simple, logical and working way. Everything falls into place when you answer the question:
WHO PRODUCES THE VALUE?
We're working on sales volume, right? We want to increase it, right?
Who and what should be influenced to increase sales?
Of course,
need to influence the cause -
who "produces" value.
Who makes money in an online store? Where does money come from?
Very simple: from customers.
Where exactly in the online store can you influence customers?
Yes, anywhere!
Right. At every stage of the customer life cycle.
To represent the life cycle, it is convenient to build the so-called. "funnel" of the client's movement through the process.
An example of an online store funnel:
Why exactly? Because customers are lost precisely when they move from one funnel step to another.
By increasing the number of customers at any level of the funnel, we automatically increase the resulting sales volume.
A simple example.
The metric “Percentage of abandoned carts” essentially shows the conversion when moving from a shopping cart to a checkout.
Suppose, at the first measurement, you found that 90% of the baskets are lost, i.e. out of 10 baskets, only 1 order is made.
There's clearly something wrong with the shopping cart, right?
For simplicity, we will assume that the amount of one order is 100 rubles. That. the total sales volume will be only 100 rubles.
As a result of cart refinement, the percentage of abandoned carts decreased by 10%, to 80%. How does it look in numbers?
Out of 10 baskets, 2 orders began to be placed. 100 rubles * 2 = 200 rubles.
But that's a 100% increase in sales! Bingo!
By increasing the step conversion by only 10%, you increased your sales volume by 100%.
Fantastic!
But that's exactly how it works.
Do you understand now what is the beauty of correctly constructed metrics?
They can have a fantastic impact on your processes.
With an online store, everything is quite simple, but how to shift it all, for example, to the quality of a software product? Yes, exactly the same:
- We choose the main value we are working on. For example, we reduce the number of incidents in the industry.
- We understand who and what produces this value. For example, source code.
- We build a funnel of the life cycle of the source code and place metrics at each step of the funnel. All.
Here, for example, what quality metrics could be obtained (at a glance) ...
Value indicator:
- prom defect density per 1000 lines of code
Metrics based on the life cycle of the source code:
- share of unsuccessful compilations,
- autotest coverage,
- percentage of failed autotests,
- proportion of failed deployments.
Metrics based on the life cycle of defects:
- defect detection dynamics,
- correction dynamics,
- reopening dynamics,
- dynamics of deviations of defects,
- average waiting time for a fix,
- average fix time.
Results
As you can see, the topic of metrics is really very important, necessary and interesting.
How to choose the right metrics:
Choose an OMTM, think about its core value, and measure the producers of that value.
Build metrics based on the manufacturer's life cycle funnel.
Try not to use absolute metrics.
What else to read on this topic
The topic of metrics has become popular in the wake of the Lean Startup movement, so it is best to start reading from the primary sources - the books "Lean Startup" (translated into Russian - "Business from scratch. The Lean Startup method" on Ozon) and "Lean Analytics" (no translation, but book in English is sold on Ozon).
Some information can be found on the Internet even in Russian, but, unfortunately, a comprehensive textbook has not yet been found even in the Western segment.
By the way, now even individual “productologists” have appeared, whose task is to build the right system of metrics for their product and suggest ways to improve them.
That's all.
If the article helped you better understand the essence of the issue, the author will be grateful for the “like” and repost.
Source: habr.com