The Analytika is a dekadal newsletter that is delivered directly to your email. It focuses specifically on the topics of data and business analytical techniques for product managers.
Nowadays, businesses are slowly realizing the real potential of data-driven decisions and adopting numerous methods. If you are on the business side of the organization, you must be familiar with these tools — Analytics, Metrics, KPIs, and OKRs. They are part of daily conversations and meetings. Some people use them interchangeably thinking they all convey the same meaning and leaving an element of confusion to others. In fact, there are clear differences between them which many people overlook and use ineffectively. In this article, my aim is to give you that clarity and highlight the differences between them. Let’s start with Analytics.
Analytics
In my previous post, “The Anatomy of Data and Data Analytics,” I briefly touched on how the term analytics came into existence. With analytics, you perform a group of analyses to answer a set of questions to make the right decisions.
It’s like performing a scientific study with a question in mind to get the answer. That’s “Analytics.”
From a product management perspective, you cannot build an awesome product if you do not know what the word “awesome” means for your users or business. You may understand the “awesome” analyzing the data. Performing analytics can certainly help you make data-driven decisions that eventually lead to building awesome products.
There are 4 main types of analytics:
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
While performing analytics, you begin with basic descriptive analytics to understand the current state of the data and then move into the next dimensions of analytics such as diagnostic, predictive, and prescriptive analytics to get more precise answers. As you progress to the next, the complexity of analysis increases. See the popular infographics below representing the complexity.
Overall, carrying out analytics on products enables product managers to justify how impactful their decisions are and their direct effect on revenue, retention, churn, and other growth-related measures. That gives a great overlook of where the business or product is heading.
Typical questions the Analytics can answer:
What’s the most used feature in the product?
Which market should we focus on for higher growth?
What’s the best way to acquire new customers?
How long do users stay in the product?
Which customers are most likely to buy?
Who are the power users of the product?
How many users may we lose by the end of the year?
Now, let’s get to the Metrics.
Metrics
On the other hand, Metrics are simply the measurements of activities, output, or operations of a business or product. They are based on historic events representing the past and present. They tell you what has happened and what’s happening now. They do not look forward. Depending on what you want to measure, you can design your own metrics. However, to quickly get started, there are numerous metrics are available and ready to be used. Many of them, I have discussed in my previous post, “16 Key Metrics for Product Managers”. Please have a look at it.
Another interesting thing about metrics is that they are numeric and easy to analyze. Although they reflect past and present, they reveal patterns and trends that help to predict the future. In my view, they are crucial health indicators for the business and play an important role in decision making—for example, actionable and exploratory metrics. Check my previous post, “How to Pick the Right Metrics?” to know more about them.
Here is a good example of Facebook Daily Active Users (DAU) metrics.
Let’s move to the world of KPIs.
KPIs (Key Performance Indicators)
Key Performance Indicators, popularly known as KPIs, are used almost in every business. They are in fact just Metrics. However, Metrics are not necessarily KPIs. Out of all the standard metrics, these metrics are designated as “Key” metrics to evaluate the performance of an organization, individual, program, project, product, goal or action, etc., over time. KPIs are generally linked to:
strategic objectives
manage resources
measure against targets
Another way to look at KPIs is that they are naturally born metrics. They are primitive in nature, being originated with the organization’s objectives and goals. For example, if a company introduces a new product, the first metrics they may track could be the revenue to reach the target of ‘$X.’ The rest of the metrics come next.
So far, we have looked at Analytics and Metrics. Analytics answers questions and the Metrics measure and help you in answering those questions you asked in Analytics. Using KPIs, you can see how much progress you made to achieve the goal by answering your questions with continuous measurements using metrics. This is how all these elements—Analytics, Metrics, and KPIs are linked and distinguished by their use.
Here is the list of KPIs of popular social network website LinkedIn:
Followers’ Demographics
Number of Followers
Impressions & Reach
Engagement Rate
Company Update Stats
Viewer Information
Contact & Network Growth
Profile Views by Job Title
Post Views & Engagements
If you are interested in digging deep into the world of KPIs, this website provides a comprehensive list of KPIs. Take a look. Remember! For KPIs, their effectiveness comes from tracking only a handful of top key metrics.
Now, let’s dig into OKRs.
OKRs (Objective and Key Results)
OKR simply represents a set of key results tied to an objective. It is a strategic framework encapsulating KPIs to measure the key results. KPIs focus on measuring the performance of tactical items. They just report the progress. Whereas OKRs focus on setting up strategic objectives with associated KPIs to measure their success. Here, OKRs not only report the progress but also track the achievement of an objective or goal. They evaluate the performance of an objective.
OKRs provide a simple and very effective way to accomplish organizational goals. They are powerful tools especially at the higher level of the organization, as the key results mostly represent the business results. Typically, an organization will have 3-5 high-level objectives with 3-5 key results for each objective.
On OKRs, Morty Cagan in his book “Inspired” clearly emphasizes that:
“Key results should be a measure of business results, not outputs or tasks.”
So, while tracking the key results, you will have to wisely pick the KPIs that track business results.
To clearly evaluate an objective, it’s recommended the key results are graded numerically. As a general rule of thumb, make sure the key results are:
quantifiable
scored on a numeric scale (e.g., 0-10 or 0-100)
timelined
ambitious
S.M.A.R.T (Specific, Measurable, Attainable, Relevant, Time-bound)
Once the key results are established properly, decide what threshold makes the objective successful or a failure. For example, achieving 80% can be assumed as success. For quantifiable objectives, this could be straight 100%.
Filipe Castro writes a lot about OKRs and offers some tools as well. Check out his website here to learn more.
Here is one great example of OKR:
Objective: Increase revenue by 30 percent.
Key Result #1: Acquire 50 new customers. (scale 0 - 10)
Key Result #2: Increase marketing leads by 20 percent. (scale 0 - 10)
Key Result #3: Increase customer retention to 85 percent. (scale 0 - 10)
Threshold: Getting a score of 10. Because the objective is quantifiable. You can keep the threshold <10 if it is acceptable.
That’s it for this post. I hope you found this article useful especially to demystify the definition and application of these tools.
End Notes
Analytics, Metrics, KPIs, and OKRs are used in a very close context. As a result, there is no surprise why they are interchangeably used by many people adding an element of confusion to the discussions. Keep in mind—they have their own place and significance when it comes to what you are trying to evaluate and how. The best way to use these tools is by establishing OKRs first and then forming various questions around the key results figuring out ways to achieve them. This will trigger performing analytics which in turn requires us to look at metrics and the KPIs. It’s all done to keep track of those business results in the end.
References
I couldn’t have written this post without reading the following resources. I highly recommend you to visit the below link to get more information about this topic.
The Essential Guide to Product Analytics - by Gainsight
OKRs Vs. KPIs: Breaking Down The Difference - by Pierre Leconte
Metrics Versus Analytics from Scorekeeping to Scoring - by Joe Perino
The Analytika is a dekadal newsletter that is delivered directly to your email. It focuses specifically on the topics of data and business analytical techniques for product managers.
Thanks for reading! I hope you enjoyed this post. Connect with me on Twitter.
-Arjun