The Top Analytics Tools of 2021 for Web and Mobile Applications


30 September 2021

Third Party Apis



Reviewing products and providing feedback has evolved extensively over the last 50 years. Focus groups used to be the method of choice and product managers would almost need to pry out feedback just to get something constructive they could work on.

This was (and still is to some degree) the feedback model for tangible products such as toys, cosmetics, appliances, etc. but it is riddled with bias and doesn’t really provide the full story of how people use a product. Thankfully, with the digital age, our shift from tangible products to online applications has meant our ability to capture real-time usage data has evolved extensively.

At WorkingMouse, we develop software applications with an intention of achieving goals for our customers’ business and their customers. When we launch an application to market, there are certain aspects we need to track to ensure the success of the application (i.e., achieving the goals it was designed to do against data points).

Success tracking elements of an application can take different forms, we can track:

  • Conversions (e.g. sales)
  • Customer usage data (the data of how customers/users/visitors use the software application/website)
  • Overall performance of the application (e.g. when it’s crashed or has loading issues)
  • and many more!

Naturally, there is an array of tracking platforms in the market that specialise in tracking the above elements and presenting data in various ways.

Before I get into my recommended analytics programs, I am going to pick out a few aspects I look for in choosing between different platforms.

1. Data representation

When an analytics platform starts to track usage data, the sheer amount of numbers pulling in can make someone feel like they are in the matrix…believe me, I have been there. And as much as I love a good spreadsheet of data, numbers are meaningless without value.

So, it is incredibly important that the analytics platform you choose is able to synthesise data in a way that is legible for you and your team. Your team might flourish with line graphs, where some might do better with heat maps.

What to ask yourself here is two-fold; does my team understand the story behind the numbers from the graphical dashboards provided, and is this data represented accurately enough so the graph matches the story?

2. Mobile vs Web Technological Limitations

When implementing an analytics program, you will need to know what your technological breakdown is to ensure the compatibility between the analytics program and usage data. What I mean here is that sometimes (now not as often as it used to be), there are limitations in analytics platforms being blocked by certain code formats.

The best way to approach this is to know what technology stack/s your application is written in. From here, head to the analytics programs’ documentation and see if there is any limitation – if they do have one, they are usually pretty clear about it. Although, if you don’t think you have the full answer from their documentation, hit them up! Submit a contact form and ask them directly (and if they have no idea what you are talking about…don’t use them!)

3. Developer Necessity

If you have used Google Analytics before, or Google Tag Manager, you will know, there are code snippets that get slid into the backend of your website. This is a similar arrangement for analytics platforms for software applications, plus a little more.

Because analytics programs track elements of your application, it is important that you pinpoint in the program which areas need tracking. Some programs will need a developer to hardcode these tracking elements, whereas others allow for these tags to be arranged on the front end (even by a non-technical person!).

If a developer is needed to implement the tracking tags, just remember that this can be costly and needs to be maintained consistently. In saying this, the accuracy level is far greater when the tags are tracked by a developer, so this will come down to your implementation budget.

Below I am going to highlight a few of my favourite analytics software applications that are available in the market currently. Each of these have their own USP (unique selling point) so when you are ready to choose, I encourage you to recall these highlighted points as part of your decision-making process.

My Analytics Platform Recommendations

An illustration showing the various analytics tools discussed in this blog, including smartlook, pendo & fullstory, segmented into buget tiers for small, medium and large budgets.

Small Budget & New to Analytics

If this is the first time you have tapped into the analytics space and really don’t know where to start (because let’s be honest, it can be daunting), I would recommend a few programs:

1. Firebase

Firebase is what Google Analytics is for websites, except that is it for software applications. It is great at pulling in that preliminary data about how people are interacting with your platform, where they are logging in from and what devices/operating systems they are using.

Firebase is free to a certain extent, the paid version kicks in after a very high level of data storage, to which if you hit this point, you really should be using a different analytics platform (keep reading!).

I always recommend that using Firebase at the beginning of an applications’ lifespan is useful in validating user demographic data, high traffic periods and popular areas of the application.

2. Smartlook

If you are new to using analytics platforms and are worried about getting bogged down in the dashboards and data, this is a good one to start with. Its uncomplicated dashboard and lean feature set mean that it is easy to follow for new analysts.

One of its most popular features is the conversion funnels. I particularly like how in the representation of data from these conversion funnels, you can break down the drop-off points further and start to understand where potential issues may be.

For example, when analysing a particular application, I noticed a higher proportion of users on mobile dropping off at a crucial point. When looking into this further, I was able to watch a few session recordings of this happening and noticed the main button users needed to click to progress them to the next stage in the funnel was not an intuitive position. We were able to put some hours in, move the button and voilà more conversions.

a screenshot of the smartlook analytics tool dashboard

3. Hotjar

Similar to Smartlook, Hotjar is not overly complicated in its representation of data. It is a great resource for visual analysts. It compiles user behaviour into heatmaps of various kinds, such as a scroll map, a click map and a move map. From this, an analyst can triage the data and pick out areas of success or improvement.

An area of success, validated by the heat map, would be seen in a navigation panel. Yes, it might seem that the navigation panel is just a list of options to click on, but there is a lot of research that goes into the design of that order. Therefore, when this is validated, it’s a success. It might also be the opposite, the heatmap data could provide an opportunity for improvement.

The use of Hotjar is great for a web application or a website. As with a mobile application, there is a lot more movement on the screen so it is harder to capture that in one map.

Medium Budget & Still Learning Analytics (but not a Beginner)

1. UXCam

This is an analytics platform that is specifically designed to track native mobile applications. This is great if your application is only available on mobile. If your application is available on web and mobile, then I would stick to a platform that offers both.

This analytics application is designed to inform multiple team members meaning it is great for high user volume applications. An example of a high-volume application is Instagram. It excels in being able to transform data sets for the appropriate groups. For example, an applications’ sales team are very interested in churn rates, where the product team is more interested in why users are churning. Although these two aspects are linked, the teams will analyse the data presented to them differently and provide different areas of improvement to ensure the continued success of the application.

2. MixPanel

I mentioned earlier that choosing an analytics platform should be influenced by the way the data is presented, especially in dashboards. MixPanel has brilliant (customisable) dashboards. This means that depending on your business objectives, you can keep certain KPIs at the forefront of your mind continuously.

Another benefit of MixPanel is its ability to segment easily. Creating segments to drill down in the data is important to understand your different types of users/customers. For example, if there is a particular drop-off on a page in the application and we segment the data to gain insight into the different segments involved, we can quickly find areas of opportunity.

This is a great tool if you have the budget to spend but also if you have an idea of how different metrics can paint a picture on a dashboard. If you have never used a dashboard before for custom reporting and segmentation, this program might be a little complex for you. You can always start using it further down the track.

3. Pendo

Pendo is rapidly gaining traction globally. It is a relatively new-to-market analytics program and is already gaining some pretty top-notch customers. It is a multi-app analytics platform which means it can analyse web and mobile applications.

Similar to MixPanel, it also has customisable dashboards. Comparatively, these dashboards focus on fewer graphs to depict areas of opportunity. What I mean by this is the dashboard screen isn’t a sea of 6 different graphs, it’s a good mix of 3 or 4.

One of the main features of Pendo is its engagement functionality, meaning it pinpoints areas of low engagement from your users and can address ways to optimise this.

a screenshot of the Pendo anayltics tool dashboard

Large Budget & Expert Software Analyst

1. Amplitude

This feature-rich analytics application comes at a steeper price point, but don’t let that be a deterrent. Amplitude (or more specifically, Amplitude Analytics) is a robust analytics product that sits with a range of other products within the Amplitude family.

When dealing with huge products that are released to the entire world, having a program that is part of (or integrates brilliantly with) a bigger network, can work in your favour. These kinds of analytics platforms are great for applications that also need to advertise, grow a community, (or on some occasions) manage staff, but most importantly, cohesively deliver the same brand experience.

This might sound a little off-topic, but think about it - you can open some applications (such as Facebook or Linkedin) and know exactly what application you are on due to the branding. I guarantee that if something looked out of place, as in not on brand (e.g. a colour or font change) you might not necessarily pick up exactly what is different, but you would know something is not quite right.

2. Upland (aka Localytics)

Similar to Amplitude, Upland is the parent company of a range of products that assist the success of an application (mobile and web). Localytics is its analytics arm which is feature-rich, highly integrable and great for high volume applications. Upland can gain information about customers from both web and mobile applications, while Localytics is their mobile application-specific analytics product.

As one of Upland’s sub-products houses the ability to market the application, the user journey from the moment of lead to customer can be tracked the entire way through their system. Moreover, by using a fleet of products housed by one brand, they can seamlessly integrate and provide insight about each customer at every stage of the buyer’s journey.

3. Full Story

My absolute favourite analytics platform to use and the one that got me hooked on analytics in the first place is Full Story. Why I like this particular analytics software is that it clearly labels dashboards and areas of improvement.

In saying this, I have placed it in this category because it takes a decent amount of know-how and analytics background to set up segments, dashboards and other areas of the platform to make it a success for you. Luckily, I worked with a product manager to design how each of our segments should look and what information would be useful to us to further the improvement of the application we were working on.

It’s a costly piece of software, but it saved me and the product team numerous hours of triaging data sets so we could make knowledgeable decisions and progress the application.

a screenshot of the Fullstory analytics tool dashboard

There are a lot of options out there, and new ones are hitting the market constantly. From a success point of view, having the ability to proactively analyse how users are interacting with an application is a systematic way to improve the user experiences through continuous iteration and receive positive results. As we saw in 3 Strategies for Product Growth, constructive criticism of a product is crucial to market penetration and the growth of your application.

If you are considering building custom software and implementing analytics tools on your next project, reach out to us for a free Product Strategy session!

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