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Application analytics: How to leverage analytics during app creation

There probably isn’t a better time than now to develop an app for your business. By the end of 2023, mobile apps are expected to generate over $935 billion. Customers are hungry for apps that can provide instant access to services. Of course, simply having an app isn’t good enough. 

Consumers will only use your product if it brings value to them. In other words, it meets their needs and provides the best user experience. How can you make sure you’re meeting these goals? Having the best hosting provider helps, as does a fantastic interface and design. But to achieve this, you need to look at data. 

Of course, data is only as useful as the insights it provides. That’s why application analytics is so helpful. But what is application analytics, and how can it boost app development? We’ll discuss that, and more, below. 

What is application analytics? 

Application analytics: How to leverage analytics during app creation

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You don’t need to attend computer science events to know how important data is in the modern world. If you’re running a website, you’re probably sitting on a mountain of data. 

Each time a user interacts with your application, they leave a digital footprint. How long did they linger on a certain page? Did they complete a certain conversion goal? Did they view a video for longer than 10 seconds? Application analytics is the process of turning all this data into actionable insights. 

The right analytics programs present data in easy-to-understand and accessible ways. This might take the form of tables, graphs, or other forms of visualization.

Application analytics is often to improve apps. In this article, however, we’ll look at how data can help guide apps during development.

With the right data-driven insights, you can create apps with high levels of conversions, user retention levels, and engagement.  

The two types of application analytics 

If you’re building an application you’ll probably be interested in one of the two main types of analytics. These are performance analytics and usage analytics. Let’s look at both in more detail.

Performance analytics 

One thing we can say for sure about users is that they don’t like to be kept waiting. That’s why it’s essential that as well as making an app that looks good, it performs well. 

This is where performance analytics come in. As the name suggests, this tells us how well an app is performing. 

Below is some of the information that performance analytics can tell us. 

  • How often an app is crashing. 
  • The responsiveness of an app. 
  • Information relating to uptime. 
  • Whether cached data is being sourced correctly. 
  • Any glitches that might arise during usage. 

To provide the best experiences, you’ll want to monitor performance analytics closely during development.

Usage analytics 

The second kind of analytics relates to user behavior. What are people doing on your app? What aren’t people doing? This information is critical for building an app that optimizes conversions and engagement.  

Below we’ve listed some key information that can be gained for usage analytics. 

  • The number of conversions that occurred per session. 
  • The speed at which users are adopting new features. 
  • Whether users are returning to your app after using it. 
  • The customer engagement score (CES). 
  • The amount of time it takes a user to realize the value of your application. 

Like performance analytics, usage analytics is essential during app development. Instead of guessing what your users want, you can find out directly. 

How to use application analytics 

There are a lot of reasons to be excited about application analytics. There are many ways it can help to build better mobile applications. Let’s look at some of the useful aspects of application analytics, and how they can support app development. 

Embrace predictive analytics 

There’s been a lot of talk about artificial intelligence in recent years. Thanks to science fiction, many people think of AI as a terrifying monster. But AI isn’t going to end the world (not yet anyway). 

Instead, AI powers many of the application analytics programs that businesses use. Using a feature called predictive analytics, AI can provide predictions of future trends. This includes how users might behave in the future. By anticipating behaviors you can better meet the needs of users with your app. 

So, when choosing your analytics software, make sure that predictive analytics is a feature. 

Offer better personalization 

Application analytics: How to leverage analytics during app creation

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Modern users love personalization. That isn’t an overstatement; over half (56%) of buyers say they will become repeat shoppers after a personalized experience. If you didn’t know, personalization is offering experiences that are tailored to individual customers. But knowing what users want isn’t easy. 

That’s why application analytics is so useful. You can segment user data and identify the kind of content that users are likely to respond to. For instance, a user could log on to your app and see a list of offers that are relevant to them. You can boost sales and other important conversions. 

Predictive testing 

It’s fair to say that crashes and other issues can be very off-putting to users. If they run into too many problems, they’ll stop using your app. It’s much better to nip these problems in the bud as quickly as possible. That’s why testing mobile applications is essential. 

Predictive testing is a form of application analytics that looks at user journeys. It can identify the actions that users are taking that result in crashes. You can then modify your app to prevent these problems from occurring.  

Improve security 

Application analytics: How to leverage analytics during app creation

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Cybersecurity-related issues are constantly on the rise. Many businesses haven’t taken these issues seriously and learned the hard way. Customers have found their details compromised and their trust has been damaged.

Application analytics can help ensure that you’re always one step ahead of cybercriminals. By analyzing data, you can spot gaps in security and even predict future attacks. By doing so, you can ensure top levels of security for your app.   

Better understand your audience 

Application analytics: How to leverage analytics during app creation

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The term ‘know your audience’ is commonplace in businesses. You might think you know your customers already, but think again. To build the best application in the modern world, you need to know your audience down to a T. 

Thankfully, by leveraging application analytics, you can dig deep into your audience. Let’s look at some of the ways you can learn about your audience. 

Build detailed customer reports  

Before beginning any application you need to know exactly who you’re building for. As mentioned, this means knowing your audience on a more granular level. In the past, we had to rely on simple market research and a lot of guesswork. Today, that approach won’t cut it. 

Not only should you know their demographic and buying patterns, but their interests, and their behavior online. What topics do they tend to search for, and what device do they use? 

With the right analytics tool, you can learn all you need and more. Before you even start work on your app, you already have a very detailed picture of your audience. You can use this to guide your app creation. The end result should be an app that matches the wants and needs of your audience. 

Analyze user behavior 

The best way to understand your audience is to observe them. From the moment they log on to your app, what are they doing? Are there any tasks that they are struggling to complete? Thanks to an application analytics feature called real-time analytics, we don’t have to wait for this information. 

Real-time analytics, as the name suggests, brings us data as soon as it comes in. You can literally watch users as they navigate your application. You can better track user journeys and spot pain points. You can use all this information to enhance in-app development. 

Make the most of big data 

Application analytics: How to leverage analytics during app creation

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Does your business have access to large sets of data? If so, you can make use of big data. Big data can provide even more detailed information about application users. Big data modeling tools can help increase the accuracy and consistency of your data. 

By analyzing big data you get information that helps with many aspects of application development. Thankfully, by leveraging application analytics and analyzing big data, you get information that helps with many aspects of application development. Additionally, utilizing tools such as an online form builder can further enhance your understanding of your audience and optimize your app accordingly.

For example, you can use big data analytics and recognition software to gain insights into user behavior patterns, preferences, and trends. This allows you to make data-driven decisions in designing and optimizing your app to meet the needs and expectations of your target audience.

This includes: 

  • More in-depth customer information. 
  • Access to user experience analysis and reports. 
  • Access to real-time data reports. 

Conclusion 

Building an app without application analytics is the equivalent of driving to a new location without a map. You can create a fantastic UI, and choose the best web hosting (or even an alternative such as Pantheon web hosting). But ultimately, you’ll fall short of building the best app for your audience.   

Application analytics gives you the insights to build an app that meets the needs of your audience. In this article, we looked at some of the best ways you can leverage the tool. Let’s recap some of the biggest advantages of application analytics. With the right analytics tool, you can

  • Leverage predictive analytics to spot trends in user behavior.
  • Offer more personalization to your users. 
  • Bolster app security. 
  • Build more complete user profiles. 
  • Analyze user interactions to improve your app. 
  • Unpack big data for even better insights. 

So, before starting work on a new app ask yourself, “Am I making the most of data-driven insights?” If not, now’s the time to make a change.