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The user journey can be a walk in the park – or a descent into a pitch-black cavern. We are spoiled for choice and all it takes to walk away from a business (even one that we love) is one misstep. One bad UX decision, one bug, one minute too long on hold. A whole new discipline was born out of the necessity to create the optimal user journey. And as ubiquitous as UX teams are nowadays, they are blind without the digital experience insights provided by a myriad of analytics tools. In this article, we’ll unpack how you can map a user journey from beginning to end using real-life data. Let’s jump right in!
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Digital experience insights are nuggets of information that can be collected from a digital environment to provide a better understanding of how users interact with it. These insights can be in the form of user behavior data, feedback, or analytics. For example, website analytics tools can provide valuable insights into user traffic, click-through rates, and bounce rates. Meanwhile, customer feedback tools can help identify areas for improvement based on user comments, suggestions, and reviews.
By using digital experience insights, product managers, UX professionals, and engineers can make data-driven decisions to improve the user journey – which can then help increase adoption and loyalty, accelerate the sales cycle, and ultimately drive business growth through a tangible impact on revenue.
There are several methods for collecting digital experience insights, and each has its own pros and cons.
Whereas web and product analytics give you quantitative data, tools for session replay and customer feedback give you qualitative data that can paint a fuller picture of what’s going on during the user journey.
When choosing the right method for your needs, it’s important to consider your goals and the specific insights you’re looking for. If you want to get a broad sense of how users feel about your digital experience, web analytics may be a better fit. But if you’re looking to understand how users interact with a new feature in your product, a combination of product analytics, visualization tools, and user feedback tools may be the best choice.
Combining multiple methods can certainly provide a more complete picture of your users’ digital experience. For example, you might use web analytics to track user behavior, customer feedback tools to gather qualitative feedback, and session replay to polish the specifics. By combining multiple methods, you can triangulate insights and make more informed decisions about how to improve your users’ digital experience.
Is there a platform that does all that? Well, glad you asked. Meet SessionStack – the digital experience insights platform that combines web, product, visualization, and customer experience analytics in one neat package. Built with ease of use in mind, it answers complex UX questions with intuitive analytics you can start using today.
Gain digital experience insights with SessionStack (it’s free!) >>
Roughly speaking, a user journey is the path that a user takes through your website or application that results in a desired outcome, such as making a purchase or completing a task.
This is different from a buyer journey (the overall journey people take when deciding to purchase something) and a customer journey (all the touchpoints between your brand and the customer during the buyer journey). The user journey fits into both of them as specific product touchpoints.
Understanding the optimal user journey is important because it can help you see the exact steps your users take and identify areas for improvement in your digital experience, such as removing obstacles that prevent users from achieving their goals (an unnecessarily long checkout process, for example).
Often, product managers and UX professionals start from scratch, with assumptions about what this optimal user journey should look like. Then, in the process of product development, it becomes clear that there are steps missing, or that users can go about finding value in unexpected ways. This is why it’s important to always be familiar with internal biases and be willing to look for real-life proof of your assumptions.
Digital experience insights come to the rescue – with them, you can map the optimal user journey with real-life (and often real-time) data on how users interact with your website or application. By analyzing this data, you can identify where users are dropping off, what obstacles they encounter, and what actions they take before achieving their goals.
Let’s say you run an e-commerce website. By analyzing web analytics data, you might discover that users who view specific product pages but don’t make a purchase tend to leave your website without even adding the products to their cart. This lack of visibility into the problem is causing you to lose precious customers and revenue, right?
By using digital experience insights surveys, you might discover that users find the checkout process confusing or difficult to navigate. Or, using digital experience insights such as click tracking you understand that there is a button that doesn’t work as expected which prevents users from adding the products to their cart altogether. Another path to take is to replay a few sessions to find what users do before leaving – for example, check the product description.
Armed with this information, you can make meaningful changes to the user journey: simplifying the checkout process, solving the button issues, or adding more detailed product descriptions, to improve the user experience and increase conversions. After you implement the changes, you can A/B test to see whether you are getting the results you expected (an increase in the products added to the cart and the overall conversions).
These examples were the starter – and now it’s time for the main course! Here’s how different digital experience insights help you map the user journey with real-life data. While in no way exhaustive, this list will guide you through the sometimes confusing process of uncovering the optimal user journey…
Web analytics insights, such as click-through rates, bounce rates, and time spent on page, can give you the broad strokes of where your users are coming from and how they are interacting with your website or application. By analyzing this data, you can identify which sources drive the highest quality prospects or what pages or features users engage with the most.
Example: you can narrow down the list of pages that are most visited by users and prioritize your UX improvements on them.
Product analytics tools allow you to track how users interact with specific features of your digital environment (website or application). This can help you identify which features are most popular, which are underutilized, and which drive the most value and conversions.
Example: if you notice that users frequently use a specific search filter but ignore others, you might consider removing the less popular filters, or redesigning them to make them more user-friendly and including a tutorial.
User segmentation involves grouping users based on common characteristics, such as demographics or behavior patterns. This can help you identify different user groups and tailor the user experience to their specific needs.
Example: if you notice that users from a specific geographic region tend to prefer a certain product category, you might consider featuring that category more prominently or creating a targeted marketing campaign for that region.
Funnels provide a step-by-step visualization of the user journey, from initial engagement to desired outcome. This can help you identify where users are dropping off and what actions they take before completing a desired outcome. They are great tools to use for conversion rate optimization and when running A/B tests.
Example: if you notice that users frequently drop off at the payment stage of the funnel, you might consider simplifying the payment process or providing more payment options.
Here’s our step-by-step guide to funnel analysis >>
Heat mapping provides a visual representation of where users are clicking, hovering, and scrolling on your website or application. This can help you identify which parts of your website or application are receiving the most attention and which are being ignored.
Example: if you notice that users are frequently clicking on an image but that doesn’t lead to a desired outcome*, you might consider repositioning it or adding more context to make it clear what the user should do next. *Figuring out what the desired outcome is is an entirely different task to accomplish!
Session replay tools allow you to watch recordings of user sessions on your website or application. They can help you identify user behavior patterns, such as where users get stuck or what features they find confusing. Session replays can be a game-changer for UX designers as they can show real-life scenarios in pixel-perfect detail, including the whole session environment.
Example: if during session replays you notice that users frequently struggle to find a specific product category, you might consider redesigning your navigation menu or adding a search bar.
Customer feedback tools can provide qualitative insights into how users feel about your digital experience. By analyzing this feedback, you can identify pain points, areas for improvement, and what users like or dislike about your website or application. This is an area that’s currently undergoing a transformation thanks to AI’s ability to sift through large amounts of user feedback from various touch points (on-site surveys, call centers, chats, etc.) and condense them into actionable insights – or even take actions to anticipate user needs.
Example: if you notice that users frequently complain about slow load times or difficulty finding information, you might consider working on website speed optimizations or redesigning your navigation menu.
User testing involves recruiting participants to perform specific tasks on your website or application while providing feedback on their experience. This can help you identify usability issues, pain points, and other user experience problems. It’s a rather cumbersome process that involves a larger budget but it can shed light on previously hidden frustrations or areas of improvement.
Example: if users report that they struggle to find a specific feature or get stuck on a certain page, you might consider redesigning the feature or improving the navigation.
Now it’s time for the fun part. Use these insights to make data-driven decisions to optimize the user experience, increase conversions, and improve customer satisfaction – here are some tips on how to do that:
Start by identifying the most pressing issues or areas for improvement based on your product roadmap and available resources. The learnings from your analysis will help you focus your efforts on the most impactful changes, thus driving the changes you desire most – an increase in adoption rates, conversions, or engagement.
Use A/B testing and other experimentation methods to test different solutions and determine what works best. Then, use your digital experience insights to refine and iterate on these solutions over time.
Don’t stop collecting and analyzing digital experience insights once you’ve made changes! Continuously monitor and analyze your digital experience to ensure that your changes are having the desired impact (and to identify more areas for improvement).
The result: a customer-centric product/service and more unified business processes.
When it comes to the user journey, businesses need to ensure that they create the optimal path for their users. With so many options available, even one misstep can cause users to abandon a business. Digital experience insights can provide valuable information on how users interact with a website or application, such as user behavior data, analytics, feedback, user testing, and visualizations. Combining multiple methods can help businesses gain a complete picture of their users’ digital experience. SessionStack does just that – a digital experience analytics platform, it combines all these methods into one easy-to-use package you can start exploring in under two minutes, with no complex instrumentation.
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