Data analytics tools are software applications designed to analyze and understand how users interact with their products or services. These tools enable companies to gather data on user behavior, such as actions performed within the app, how often they use the product, what features they prefer, and how long is the time of interaction with specific features. Then, the data is analyzed to provide information on how to improve the product. It’s data-driven and you can’t afford not to use it in 2023. What are the top data analysis tools for tracking product performance in 2023?
How can you choose the best product analytics tool?
Product Owners are responsible for the market success of the application. Therefore, they look for typical features like user behavior analysis, event tracking, action tracking, A/B testing, and conversion funnel analysis. Sure, you can find these in popular applications like Google Analytics or Mixpanel, but there are some very interesting alternatives.
To find what you looking for, pick some critical criteria for comparison purposes.
Pricing. Let’s get it out of the way. For many, it’s a major factor between investing in something or letting it go. You should highly consider it, but don’t let your decision be determined solely by price. Think about the value that comes with the pricing, not the pricing alone. Some tools give you important insights that will affect the return on investment (ROI), and it’s really important you get that information.
Integrations. Linking your analytics tool with other software used on a daily basis gives you enormous opportunities. Connecting your product with customer relationship management (CRM) software or marketing automation tool provides a more in-depth look into your business operations. That directly impacts ROI and scoring of the team’s efficiency.
User interface (UI). Learning new software takes time. The best products are intuitive, leveraging users’ muscle memory. Putting a strain on users’ time and forcing them to learn new ways to operate is not a good idea. That’s why you need to look for products that are powerful yet easy to use. Your team should extract data in no time and make them work for you, driving decisions.
Probably the best-advanced way to ensure your choice is valid is by asking your Product Manager. Does he or she think that the product in question can improve product road mapping? It is absolutely driven by data, hence data analysis tools for tracking product performance. It’s also important in the grand scheme of things. The analysis opens the door for staff augmentation, leading to team augmentation services. That way you can finish and further develop your product. Smoother and faster.
Criteria for choosing the best software
There are also a few other factors that can impact your decision. It’s always to search for them while evaluating products on the market.
- Automatic data capture. You don’t want to waste time and gather it manually.
- Dashboards for the most important KPIs. Making sense of data comes easier when it’s clearly displayed and presented in a digestible format.
- Highly detailed user segmentation. Getting to know your users should occur by dividing them into groups and leveraging granular analysis.
- Displaying data funnels. Dividing into groups is not enough. Following their journey as their travel through the app is also important. Profiling is not enough; behavior is everything.
- Data filtering based on specific dates. The software should allow breaking the data into smaller chunks. For example – date-based filtering. That way, you can analyze each session and understand why users behave the way they did (after implementing a new feature, for example).
Naturally, there can be additional criteria. Ultimately, it’s up to you what will you choose and for what reasons.
The best 10 data analysis tools
Here’s the list of top data analysis tools for tracking product performance. You can implement them into your product development strategy.
ProductPlan. It allows teams to visualize their strategies and prioritize actions. It has over 25 roadmap templates. From IT infrastructure to IT service management. From marketing strategy to a content calendar. From Agile roadmap to DevOps roadmap. You can track and measure anything you want. You can integrate it with JIRA, Slack, Trello, and more.
Heap. The tool helps automate user analytics. It captures every user action performed on a website. It’s dedicated to medium and large-sized companies. It has conversion charts, path analysis, and an event visualizer. You can integrate it with HubSpot, Salesforce, Shopify, and more.
Zoho Analytics. Advertise as a “modern self-service BI and analytics platform”, it does exactly that. You can source and blend data from many different platforms and directions, such as Excel, HubSpot, MailChimp, Google Ads, stripe, and more. You can integrate it with Salesforce, Microsoft Dynamics, and a lot more.
Craft. It’s an end-to-end product management platform with some great built-in sets of good industry practices. Your teams can collaborate with ease, using state-of-the-art visualization, and collaborative planning features. You can integrate it with JIRA, Slack, Google Drive, and more.
Aha! Sounds a lot like Eureka!, doesn’t it? Well, Aha! is a really good solution for anyone who needs a reliable and clean product development tool. From here, your Product Owners, Project Managers, and engineering team can plan and manage the whole product-making process. Slick visual roadmaps, easy goals, and objectives estimations, tracking progress, and product performance objectives. All can be set up and monitored with ease. You can integrate it with JIRA, Trello, Asana, GitHub, and more.
Quantum Metric. The tool is powered by Big Data and machine learning engines. It gives you a highly detailed overview of customer behavior. An interesting functionality gives you the ability to automatically record user sessions. You can view them later as normal video replays. You can also make logs of user behavior and draw conclusions from heat maps. You can integrate it with Salesforce, Slack Google Analytics, and more.
Glassbox. With it, you can create frictionless digital journeys. The tool works in real-time and can be used with both web and mobile products. It turns customer feedback into a more actionable dimension and provides a digital experience intelligence engine for accurate measurement. You can integrate it with Dynatrace, Google Analytics, Splunk, Adobe Target, and many more.
AppLearn. It’s a digital platform that integrated data analysis in key areas. CRM, HCM, ERP… With AppLearn you can get actionable data and improve user engagement. Digital onboarding is usually one of the first steps in improving the overall user experience.
dragonboat. It allows product teams to build data-driven roadmaps. It links OKRs, KPIs, customer feedback, and product strategies. All through and with Agile processes. You can automate custom reports for all stakeholders and reallocate resources based on the results of performance analysis. You can integrate it with JIRA, Confluence, and GitHub.
Inner Trends. It’s two, rolled up into one. The software combines product analytics and data science tool. It includes customer engagement scoring, a growth opportunity finder module, and user full life cycle tracking. The tool is especially useful for all SaaS products. You can integrate it with Mixpanel, Heap, Google Ads, and more. In fact, with any platform that has its own API.
Naturally, the choice is a lot wider. If you are looking for software because of its API and integrations, you also have a choice to use API development services.
Alternative: free product analysis software
If not paid software, then what? Are there any alternatives? Yes, and they are also capable of doing the job. Naturally, some of them have also “starter packs” with some level of data analysis available for the user. With it, you have limited functionality but it should be enough to get you going for a while and decide what you actually need for the future.
LogRocket. An interesting tool if you’re looking for an advanced session replay
Pendo. Best if you run a product-driven company
Amplitude. Good choice if you’re interested in analyzing customer journeys
Hotjar. Great heatmaps to discover user activity
Matomo. Best if you want enhanced search engine optimization (SEO) options
How to use data analysis tools to track product performance?
To effectively use a tool, you must first know why you need it in the first place. Top data analysis tools can be very effective and valuable but you need to break down business priorities first. Then, it’s about following some guidelines we post below. It’s not mandatory, of course, but it will elevate your process.
Identify metrics you want to track. Those metrics should be in line with your business and even more, product goals.
Gather the right kind of data. There are lots of products on a market, but not all give what you should be looking for. It’s user activity within the app, conversion rates, usage logs, and customer feedback.
Process the data. There are two kinds of models – those that meet the definition and those that are really useful. Data should always be processed and defragmented. Things like missing information or incomplete entries are just the tip of the iceberg.
Put the data into the tool. You can use Microsoft Excel or tools like Tableau.
Analyze the data. Identify user trends, features, and overall product adoption among users, user engagement, and patterns of usage.
Draw conclusions and implement solutions. Make sure that conclusions are practical and in line with what you wanted in the first place. Results should indicate a clear path toward increasing user engagement and revenue. Look for the most important patterns and implement your solutions accordingly. Prioritize tweaking features that are heavily used and try to estimate how much will it cost (time and money) to polish functionalities that underperform. Is it worth it?
The final word
Still not enough? You can also read our article on data analytics and business intelligence tools for FinTech. We also recommend a piece on best practices for data visualization. If you’re keen on using Amazon Cloud for your next project, we highly recommend a read on data analytics on AWS.
That’s only the beginning. The real test of your business model is the number of users you can attract. And that’s directly linked to the quality of your software. You can use staff augmentation for that, or you can build a custom software product from scratch. We make the apps in a way that gives you actual data to analyze. There’s always someone who can do it cheaper, there are always tools for low-code or no-code development. Are they all really enough to produce the right business outcome?