Top 5 Behavioral Analytics Features In Product Analytics Tools
Behavioral analytics drives product analytics in numerous ways. It can give you a clear insight into user interactions, points of satisfaction, and the scope for improvements needed in the product development lifecycle. This article lists the best 5 tools and methods you can deploy with a product analytics tool to improve customer satisfaction and retention.
Building a product that creates value for users is about how you can ‘follow the data’ as meaningfully as you can. This means that you need to tie in product analytics to fit the needs of the users. Sometimes, that involves selectively choosing the metrics that are closely associated with user actions and behavior. What matters the most, after all, is how users perceive your product and the value it produces for them.
Therefore, organizations must put behavior analytics at the forefront of analytics, which can make the product customer journey a well-thought-out and planned approach. It is a powerful methodology that will enable you to find out what exactly evokes users’ responses from product interactions.
Behavior analytics is by definition, a set of analytics methods and strategies that organizations can employ in product analytics to collect and measure user engagement and behavioral data across platforms and devices. Hence, measurement of the success and impact of every feature, product revamp, and email and marketing campaign should come under the microscope of how it impacts customer behavior.
Studying behavior data is one of the best uses of product analytics tools, as they are a clear indicator of what the user wants and does not want based on the actions they perform. Behavior analysis has a broad area of application, from email, website, chat, apps, notifications, surveys, and basically any platform that allows tracking user interactions.
Tools And Methods Used to Track Behavior Analytics
There are many useful tools and methods that preserve user’s privacy while helping companies assess what they are doing right or wrong in their product development and managagement. User behavior analysis is what helps drive product improvement in a way that can hugely benefit the users’ journey.
Here is a list of some of the tried and tested methods that you can use in your product analytics strategy to analyze user behavior:
1. User Segmentation / Cohorts
Reaching the right audience for your product or service involves an extensive understanding of your target market. Market/user segmentation and behavioral cohort analytics involves classification of users into sections for various targeting.
User segmentation generally involves separating users into demographic, geographical, technographic (device and platform-based), and need-based segmentations. Cohorts, on the other hand, are users who get grouped together by following patterns of actions or possessing certain characterizations within a segment.
These categorizations help you recognize the most valuable set of users, who are:
- The most retainable
- Constituting the core-market
- Generating the most revenue
- Influencing a better market impact
Negative correlations can also help you retarget a category of users, tweak the UI, include more promotional campaigns, or cut down on certain resources.
Customer behavior drives, not some, but all of your product analytics. How customers respond to each product decision determines your journey forward in the product development cycle. But the recent concerns about user data violation and the non-consensual use of data helped organizations realize the importance of a more diligent collection of user behavioral data.
It prompts us to relook at why non-privacy-conscious behavioral data collection is detrimental and could lead to the devaluation of your product in the market.
2. A/B Testing
User behavior is complicated, as people’s preferences are deeply tied to their usage requirements, psychology, and even physical and cognitive abilities. For example, Facebook launched its website optimized for color-blindness as CEO, Mark Zuckerberg himself, suffers from the disorder.
Accessibility testing, performance testing, and device-compatibility testing are typical applications for product optimization to make websites and applications more user-friendly. A/B testing is one of the key tools for such tests by which companies can examine the actions from the users’ end to make simple changes in the UI or even tear down an entire backend process to match user preferences.
3. Heatmaps
Heatmaps are tools that can highlight the areas of maximum and minimum activity on a a webpage by tracking mouse movement through clicks and screen scrolls. Heatmaps are very straight-forward tools that, with a little insight into reading them correctly, can help teams understand where user attention is concentrated.
Heatmaps can help many areas of product development, such as:
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Product information: Do you think your product information is grabbing the attention of visitors to your product page? You might want certain product features and aspects of the webpage to stand out in your product information for the users. Heatmaps will be able to show you whether users were able to interact with your page that will lead them to successful conversions in the way you designed it.
It tells you whether they took certain actions, such as using the chat, or clicked on a relevant button or link on the page that led to conversion, or missed aspects that were important within the page.
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CTA effectiveness: A major application of heatmaps is to estimate the effectiveness of a CTA button on a page. You can tell whether the CTA content, placement, or design is working by the number of clicks that it gets. Are users scrolling past the CTA button? They may not be ready to take action based on the information presented. Are they confusing some other element on the page to be their next point of interaction instead of the CTA button? You may have distracted the user from the main intent of the page.
Additionally, you may simultaneously use the A/B testing method and the heatmap tool to get the full picture of the customer’s behavior with your CTA button.
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UI elements: No matter how great your product may be, the customer’s experience in using your application can be a huge contributor to how far customers can explore your product. If the UI is too slow, uncomfortable to the eyes, or fails to make an impact, users will be more prone to leave the page before they can understand the product value. Heatmaps are the easiest methods of UI analysis to understand the functional aspects of a webpage.
- Content placement: The placement of all content, starting from the visuals, text, and background to the whitespaces plays an important role in making a webpage visit successful.
- Backend error detection: If the heatmap shows that users are performing a click action but it is not producing the expected results on the next page, this clearly means that there is something amiss in the backend code. Errors in the database and broken links are easily noticeable with the help of the heatmap tool.
4. Activity / Flow Maps
Activity maps are used to portray user activity from different geographies, regions, and cities, which will give an insight into where users are coming from and show the distribution of users.
Flow diagrams or maps show the sequence of events that users followed after entering the homepage of your website.
Product analytics tools that include activity maps and flow maps help companies determine which users are benefiting from your product, where they are from, and how they move through each action item.
The activity map helps you see, at a glance, the events and actions that take place in various parts of the world. Meanwhile, the flow maps help you visualize the customer journey from one point to the other.
You can separate the events that you would like specific inputs on, for a deep dive into the user behavior. For instance, if your product is tailored for usage in and around certain geographies, this feature helps you adjust your market messaging, use cases, and product reach. You can then use the flow charts to get a bird’s eye view into the customer’s choices and actions, helping you analyze the page paths to allow for a better user interaction.
5. Funnel Analytics
Customer journey through the conversion funnel helps product managers make better decisions. Funnel analytics is a joint effort from every team inside the organization, from sales to UI development, and the product management as a whole. This is because funnel analytics touches every stage of the user’s interaction with your product. For example, if users are brought on to the product page from an email campaign, the content, the visual elements, and the inbuilt functionalities will help users make the decisions that will lead to a conversion.
Funnel analytics can tell you where in the funnel you need to pay more attention to. Suppose your landing pages are not producing a target number of conversions, or your e-commerce products are often abandoned in the cart before checkout/purchase, there must be some action or stimuli that the users are missing out on. You could then enable push notifications to remind users of the items in their cart or offer them a discount to push them onto the next stage of the funnel. Or you might discover an error in your code that is blocking them from advancing forward.
Responsible Collection and Use of Behavior Analytics Data
Invasive collection of user behavior data is any data that you collect without the knowledge and consent of the user. However, if you prioritize data privacy without compromising on data quality, you can achieve greater results in your target market.
As GDPR rules are tightening across the globe, companies are facing severe backlash and loss of revenue over violations. This just goes to show that short-term gains will eventually lead to irrevocable setbacks.
First party data collection is a new wave in the aftermath of the third-party data collection restrictions. Another way to push data privacy to the center of analytics is to curb behavioral data collection that gives away personal information or potentially read user details, such as Session Recordings. Tracking cross-website user data and deploying tools that record post-logout data, etc., are some other concerns for user data privacy that have already led many well-known businesses to rethink their analytics strategies.
On the other hand, safe and responsible use of user behavioral data is economically less intense over an organization’s lifetime, as you can build your own repository of tools that ensure the quality, functionality, and genuineness of the data that you collect.