4 Key Things That Matter When Finding The Right Analytics Tool For You
The Need for Analytics
If you’re reading this then you likely either have, or will soon have, an app on the market. In today’s market, new apps are added by the thousands everyday; so how do you keep your app from becoming lost in the crowd and bring it to the top of the charts?
With so many competitors in today’s market, you have to do everything you can to ensure that your app is top of the line and gives the customer the best experience possible. For this, improving your capacity to capture data and measure it is very crucial. As Peter Drucker once said:If you can’t measure it, you can’t improve it.
“If you can’t measure it, you can’t improve it”.
– Peter Drucker
A great app analytical tool (or even multiple if that’s what is required by your app) is an essential tool for measuring and improving your app.
Where to Start? One Metric That Matters.
As mentioned above, you could need one or multiple analytics tools. Every app analytics tool is going to have it’s pros and cons, the key is to find the one that fits best with your business objectives. Although every good company has different needs, there are a handful of features that one would expect in a good analytics tool. It’s these key elements that we’re going to look at more closely, as well as discuss why these features should be important to you.
It’s important to keep in mind that, although there are many useful features out there, you will do more harm than good if you try to focus on them all at once. The “One Metric That Matters” concept states that it would be more beneficial to choose the one metric that matters the most to you and your business/app and prioritize that particular metric. This isn’t to say that you should ignore everything else, only that at any point in time, that metric should be the most important one considered.
4 Key Things To Look For
To help break it down, here are 4 key things to look at when finding the right analytical tool for you: Gather, Mine, Analyze, Interpret
1) Gather Information
Before a tool can perform an analysis, it must first be able to gather the data it’s analyzing. This data comes in two different formats: Quantitative data and Qualitative data.
- Quantitative Data:
This kind of data is numerical in nature and though it is excellent at answering the “how many” and “how much” questions, it tends to lack the in-depth insights about your user’s behavior. By aggregating the collected numerical data, we can better see a baseline, make decisions and track progress. Examples of quantitative tools include Google Analytics, Mixpanel, and Amplitude.
- Qualitative Data:
Qualitative data, also commonly known as UX analytics, is more user action based than its numerically focused counterpart. This data is usually collected through screen recording, touch points, and user feedbacks. This data allows you to make more informed decisions based off of real user experience of your app by enabling you to evaluate opinions that surface in your team. Good examples of quantitative tools are UXCam, FullStory, and ClickTale.
One key part of the gathering process is the ease of implementing an analytics tool. Some programs can have extensive procedures for learning the software and implementing it into your app. This is an added cost to you because of the man hours required for the switch, the cost of training, and let’s not forget the amount of time it takes to install, during which your system may be down.
To avoid this headache, look for a program that has a simplified implementation process that doesn’t cost as many resources to switch over to. At UXCam we have worked extensively to make this easy for you with just two lines of code that can be applied in seconds. The program automatically detects screens and doesn’t affect the performance of the app.
An analytics tool uses the collected data by mining/analyzing it through various techniques to output interesting, and ideally, useful results.
The tool can either aggregate this data and show the result or use sophisticated machine learning and artificial intelligence to find patterns. Tools such as Mixpanel uses these methods to predict user conversion. This complexity of analysis is an important factor to consider when finding the right analytics tool as it could be the difference between easily interpreted data or a data induced headache.
Finally, it’s important to note that some tools, such as Snowplow Analytics, also allow you to analyze the data yourself. This can be an important decision factor if you have a large quantity of data or if you desire the ability to do the advanced analysis but the custom tools lack the features to do so.
We as humans are inherently lazy. An analytics tool that does most of the work for us by enabling us to analyze data easily and make decisions faster is going to be the winning bet. After all: Your time is your most valuable commodity, so why waste it when you shouldn’t have to?
There are various ways that an analytics tool can help you visualize the data:
Clear and Measurable Reports
Reports and data received from the tool should be precise and clear to read. Without easily interpreted data, you are not going to be able to see the problems that need to be fixed, or get enough info to understand how to fix a problem, making the process more stressful and less effective than it should be.
An analytics tool should be able to allow you to filter the data precisely and easily. You’ll want an analytics tool that not only has this but can make the feature and the outcome easy to understand. This may include visuals, being able to sort data by different parameters and the ability to run searches for particular data. Without being able to see historical data and do advanced filtering, you would be stuck with a large amount of data, leading to a bad case of information overload.
One of the easy ways to understand usage data is through Session replay. Session replay is a qualitative analysis tool that allows you to recreate and replay videos with complete touch interaction of the user’s journey through your app interface, letting you see exactly what your user is experiencing. This gives a complete understanding of where the user’s struggles lie and what aspects to take a closer look at.
One of the newer, and arguably most useful, feature that an analytics tool can have is heatmaps. In summary heatmaps are a feature that allows you to see what spots on the screen are touched most often during the use of your app. This is shown with the use of a range of colors to represent the different frequency of touches. You can read more about the different types of heatmaps and how it works here.
Finally, an analytics tool should enable you to act on the data you receive quickly. Some tools enable you to decide on this data automatically. One such example of this is an A/B testing feature of an analytics tool that enables you to choose the winner of an A/B test and serve the winning test automatically.
A large number of tools use collaboration techniques, enabling you to collaborate with the rest of your team. For example, UXCam enables you to view the recordings and add comments on the section where you see issues. Through integration with Slack, it enables you to keep everyone on the team posted and up to date, saving time and headaches.
We hope this guide proved helpful for you in understanding the things that matter when finding the right analytics tool for you. Have questions or comments? Tweet to us on @uxcam and we’ll be happy to hear from you!