Understanding how users are using your product is key to creating a better product that meets their needs. Marketers have traditionally relied on customer surveys and interviews to understand what users like about their products. These customer interviews have been essential for me to get a better understanding of how users view the product, but as a product manager, it’s not the complete picture.
User data collection enables companies to take an in-depth look at what their customers do on their sites. There is a massive amount of data available to gather—everything from where a user came from to how long it took to purchase a product.
It takes both the qualitative (customer surveys and interviews) and the quantitative (user data) together to get the full picture.
However, there are so many data points that you can collect, so what can you do about it?
Product analytics takes that data and turns it into something viewable and usable. This is a wonderful tool to develop your products into the best versions of themselves. Going even further, product usage analytics focuses on a specific product. Product management experts use this to get a complete view of what their customers are doing with their products.
Whether you’re a product manager, a user experience designer, a marketer, or a product team member, once you understand the purpose of product usage analytics, implementing it within your own product management cycle is simple.
Product usage analytics studies data from a specific product to determine how users are interacting with it.
The traditional way of gathering data is to talk to your customers. However, this relies too much on subjective experience. Maybe your user feels uncomfortable about saying something negative and thus leaves too positive a review. Or perhaps a customer had a bad experience and will be overly critical.
When you use customer analytics, you get data on what customers actually do. You’ll see what they like and what they don’t like, how long they interact with something, and what makes them leave.
This sort of product usage data provides you with objective data about your customers. That data can save you from wasting your budget on developments that were never going to pan out.
What Type Of Data Does Product Usage Analytics Track?
Product analytics tracks various data meant to provide product teams with all the valuable information they need to create the best products for their customers. The following product metrics are integral in the creation of a successful product.
Personal data: This includes your geographic region, gender, age, and web cookies.
Engagement data: This tracks what you use a service for, like sending messages, visiting social media, or clicking on ads.
Behavior data: Everything you do can be tracked, from as insignificant as your mouse movements to things like purchase history, repeat visits, and products you linger on.
Using this data, product usage analytics can provide valuable insights into why your customers do what they do. Such analytics typically covers the following items:
the churn rate, or the rate at which customers stop doing business with you;
product stickiness, which is the number of customers who use a product regularly and how often that use occurs;
the retention rate, especially among segmented audiences;
the results of A/B testing;
friction points, or those areas that slow users down or halt them entirely; and
the most popular features.
Are Product Analytics And Marketing Analytics The Same Thing?
While these are very similar, especially in what they seek to accomplish, product analytics and marketing analytics are different for one fundamental reason. That reason is evidenced by their names.
Marketing analytics tracks metrics about how customers reach your site. While this helps understand where a customer journey starts, your product team needs different information.
Similarly, business analytics tracks data to optimize business decisions. So product analytics, marketing analytics, and business analytics are typically used by different teams. But there’s a lot of overlap in the data looked at and the way that data is analyzed.
Make Sense Of The Data Collected
While easy to gather, surface-level data does very little for a product team trying to develop or improve a product.
Data collection puts a lot of information at your fingertips, but it won’t do you much good without a meaningful way of looking at it. That’s why finding a data analytics tool is so beneficial—it can turn raw data into easily understandable visual data.
So what exactly do you do with all that data? Once you’ve analyzed it and a good analytics program has turned it into usable data for you, here are a few things you’ll get a better picture of.
The customer journey: How did your customer get to you? With this, you can see where customers came from, which pages they visited, and what led them to ultimately make a conversion or bounce.
Retention rates: Are your customers staying or leaving? With analytics, you can increase the things that make people happy and cut those that aren’t working.
Revenue: At the end of the day, if you’re not making money, something is going wrong. With this metric, you can learn how you make your money, understand how to reduce the amount you spend to get customers to you, and shorten your sales cycle.
Why Is Product Usage Analytics Important?
When a product is still relatively new, there’s not enough data to analyze with product analytics software. During this time, surveys and customer interviews are the best way to get insights into how you’re doing.
Usage analytics is another tool for product managers to use just like customer surveys. Once a product has enough measurable data, you can look at exactly what’s working and what isn’t.
Once you’re ready for product analytics, you’ll find the following benefits for your product.
A Better Customer Experience
Product usage analytics can help you with your product development, but the biggest reason to embrace it is to create a better customer experience. Product experience is the reason your customers are there in the first place.
Product analytics helps customer satisfaction in several ways. There’s the obvious—creating a better, more satisfying product—but there are more subtle ways too. These include removing bugs or design flaws, making processes smoother and more engaging, and being transparent about your changes and what you do.
Whenever you make changes to your product, there tends to be a percentage of users that are not happy with the changes. By using product usage analytics, you can justify the hard data behind a change in your product. For example, you may come across friction points with your current design that impacts a large number of users. By communicating this change, you can be clear to your users why you made the changes you did.
One of the most significant challenges of selling a product is figuring out what your customers want.
There’s always an element of luck involved with successful product creation, but product analytics puts you in the driver’s seat. With hard data at your side, you’ll start to notice trends and patterns. You can predict with more accuracy what customers will like in the future.
For example, you can use run a/b tests to see what customers react more to in the way features are implemented. You can identify the most popular features of your product, or the ones with the most friction points.
By combining the above with more qualitative approaches like surveys and interviews, you can identify what customers are really looking for in your product.
Less guesswork means less money wasted on efforts that never come to fruition. It also means you’ll have more users who are satisfied from the moment they land on your site. According to research, 59 percent of customers who have a bad experience will never return to that business. Product usage analytics can prevent that from happening to you.
Who Should Use Product Analytics Data?
Simply put, everyone can benefit from the use of product analytics.
The product team: These are the people at the heart of making a product better. The more information they have, the better their efforts will be. There will be less revision and a better launch.
The product manager: Obviously, the person leading the team should have access to the data. This will help them make better decisions while increasing important metrics like retention and conversion.
Marketing: Marketers use product analytics to see where to put their advertising efforts. This can help them increase visitors, foster better customer relationships, and increase sales.
User experience designer: When user experience designers know what works for customers and what turns them away, they can forge more meaningful and satisfying customer experiences.
How To Implement Product Analytics
Despite the many benefits of product analytics, many companies still struggle to use it. Part of the reason for this, beyond budget constraints or a lack of personnel, is the common idea that data analytics must be challenging to implement.
It doesn’t have to be difficult, however. These three steps form the basis of everything you need for this tool to work for you.
Have a clear plan: Without a goal in mind, how can you know what data to collect?
Create a tracking plan: Think of every user event that will help you with your plan.
Choose the right product: Do your research to find the right program for your specific needs.
There are many, many data points that you collect. As helpful as it can be, there’s plenty of data that simply makes you look good, but doesn’t help you understand how customers use products. These are known as vanity metrics and can easily lead you astray.
What your product needs is a North Star Metric. A North Star Metric is a metric that best reflects the value that you are delivering to customers.
What this North Star Metric can be will vary. For some products, it can be daily/weekly/monthly active users. It can be retention rates. It’s the one metric that you want to focus on above all others to deliver value to the customer.
Again, with so much data that you can collect, it’s easy to miss the forest for the trees. There’s a quote, like many, that are misattributed to Albert Einstein that says:
Not everything that counts can be counted, and not everything that can be counted counts.
Find your North Star Metric, find the ways to collect the data, and combine that with customer interviews and surveys to build the best possible product.
The benefit of using a data warehouse with a business intelligence tool is that your company has complete control over the data you collect, how you analyze it, and what you use it for. On the downside, running this option requires dedicated, knowledgeable employees. It can also be costly and take a long time to set up.
On the other hand, a cloud-based analytic tool frees companies from maintenance. These tools can also be much more user friendly because they are designed to answer the metric-based questions you’ll be asking. The only thing to really take into consideration is the variety of analytic tools available.
Many programs track usage metrics and display them as something usable, but they have different features. You’ll want to research which ones are the best for your needs before choosing one.
No matter what you’re selling, product usage analysis can help you optimize your efforts. It takes some time to learn the best ways to use your customers’ data, but doing so is well worth the investment.
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