September 24, 2020 | 5min read
6 Product Analytics Terms You Must Know
When you want to build a new digital product, publish a website, or open an e-commerce store, you need to put a lot of effort to ensure that there is a chance of it becoming successful. After all, according to an exemplary product process, you need to first do the research, prepare the strategy, design mockups, and visualize the product before you decide on publishing it. Moreover, in the meantime, you prepare and run usability tests to make sure that what was created meets the users’ requirements. It often takes months, if not years.
However, you will never be 100% sure that your product will be successful on the market and liked by the users. Nowadays, product teams are under extreme pressure to deliver amazing solutions and out-of-the-box experiences, which will meet the criteria of even the most demanding of users. That is why developing products and introducing changes should be done with the help of data.
Product analytics is skipped during the product development process and not really taken seriously.. Everyone knows that you should connect Google Analytics to your website, but do you know which metrics you should monitor? By following the users’ actions, you can quickly find places where they have problems, run tests, and check if everything is going in the right direction .That is, if GA is configured well. Additional, specialized tools such as HotJar, Amplitude, or MixPanel come in handy.
In this article, I will tell you more about the basic metrics you might have heard of. Keep in mind that different data should be collected for different business types. What is suitable for an e-commerce store will not work on a blog.
There are a few terms that you must know to correctly interpret the collected data. Often, people don’t pay close attention to the definition of, for instance, the Active User. Later, they have problems with a good definition and analysis of the data.
It’s a user who performs a specific action on a website or an app. Usually, in the basic configurations, an active user is someone who simply visits the site. There is a catch, though. Those are often not unique users (it is an additional term)—if someone visits the website twice in one day, he/she will be counted as two active users. It’s not the only catch. Depending on the business, an active user may have a different definition. It should be defined at the very beginning of devising the strategy. For a social media channel, a definition of an active user might be, for instance:
An active user is a registered person who entered the profile, liked it, or wrote at least one post. When the term is specified, you receive data that will help you make product decisions.
Or simply—Daily Active Users, Weekly Active Users, and Monthly Active Users. These metrics indicate how many active users were counted in a given period, day, week, or month. They don’t give us much information without the right context. What are the active users in a day if, for instance, we don’t know the number of all the registered users or what was the total number of website visitors? More advanced metrics come to the rescue.
It’s the comparison of Daily Active Users with Monthly Active Users. That way, we can determine your product’s “stickiness,” meaning how often active users come back during a month and how engaged they are. This metric is presented in percentages. For instance, if the DAU/MAU ratio is 50%, it means that an average user of your application or a website performed an action/visited the site 15 times out of 30 in a month.
It’s the share of visits, during which the user saw only one site on your website and left. However, if a person performed an action, such as leaving a comment, subscribing to a newsletter, or downloading an ebook, it’s not counted towards that metric.
A high bounce rate is usually a bad sign because we want the user to perform actions, i.e., making a purchase, which means going to the next subpage within the website and kicking off the purchase process To identify the source of a problem, you can conduct a UX audit (and we can help you with that!). It’s worth remembering that this metric will not always be reliable. In a blog example—if a user found all the information he/she needed from that blog post, why should he/she search further on your site? A matter of argument. That’s why the time spent on the site is an equally important metric.
Retention is a percentage of people who continue to use your product in a given time frame. It’s usually monitored on a weekly or monthly basis. Imagine that in week 0, 10,600 users registered on your portal. In the first week, 43.22% of the same users came back, 40.08% in the second, 38.10% in the third. In this case, we can say that the retention in those three weeks was 43.22%-40.08%-38.10%.
It’s a metric that the potential investors often require because it indicates how engaging your product is and whether the users are loyal across weeks or months.
We can observe a significant decrease of active users in the first weeks or months, although it’s normal. There is a retention curve, meaning that after the decline, the number flattens and stabilizes.
Conversion rate is the percentage of people who performed a given objective, which is essential for your business, such as making a purchase, filling a form, or replying to a message. You can measure a few conversions rates on your website at once.
If you want to understand your users better, you can create a conversion funnel. Imagine that one of your objectives is for the users to register on your site. In the tool you are using, you can create a process consisting of steps that the users must take. You can then record, and analyze the percentage of users that finished the process and break that down to check at which stage users drop out the most if, for example., they decided not to make a purchase. You can find the problem and solve it. In the graphic below, you can see that many users left the onboarding at the second question, only 23.6% saw the third question when registering. That can mean that for example questions 2 and 3 are too hard or time-consuming and make it not worth it for the user to finish the registration. But you would need a closer inspection and tests to know for sure.
That is only the tip of the metrics iceberg. You may not need all of them—remember that the trick is to tailor them to your needs. The ones I’ve mentioned in the article are the most common and often misunderstood. If you want to make your product better, remember to take the time to build useful product analytics.
If you are interested in working with Utilo, contact us—we will be happy to show you how we work and listen about the challenges your company is facing.
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