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Behavior tech is the modern way of ‘panning for gold’ in marketing big data

big data
(Image credit: Image source: Shutterstock/Mikko Lemola)

It’s no secret that modern enterprises are drowning in data. With marketing big data amassing a vast array of website activity and customer behavior, it’s often difficult to focus on the right data. Tracking millions of visitor sessions creates a massive volume of intelligence – which is good as it gives marketers and designers the big picture, but also makes it difficult to drill down to specific parts and visually identify the problems – and do this quickly enough to take action.

But it’s really worthwhile. Within your mountain of data are buried gold nuggets that can mean improved user experience, fewer drop-offs, increased dwell times, better conversions - and less drain on your valuable Dev team resources. This all ultimately brings significant revenue gains. So it’s critical to get on top of big data and make it work for your business, using proven enterprise-grade tech, especially around user behavior.

Enterprise data is often obsolete 

Most companies are using Google Analytics to gather data, but it has its limitations, not least the fact that it cannot process retroactive data. What creates the struggle for product managers is the length of time the whole process takes. From deciding what they want to look at to actually getting the data can take weeks rather than days - it’s often so slow that it makes the results obsolete and so meaningless to the PM or designer. Usually the larger the firm, the larger the delay.

However, modern tech to the rescue! With today’s leading user behavioral systems, data is being tracked continuously. This extensive set of data is being collected throughout the page or wherever the tracking script is placed - tracking URL changes, click boxes etc – 24/7. This means staff can extract data immediately and retrospectively – and so easily that they don’t need dev resources. Not only do they not need to wait for data collection, but also if they miss something they don’t need to wait for the whole process to re-run. This instant data output means the end of obsolete data. It is a huge time and resource saver – and means managers can make informed data-driven decisions immediately.

Taking such an approach is not just beneficial to fast-moving e-commerce sites, but for any business websites, because it saves developer time. The dev team have huge demands on their time from across the business – including marketing, sales and support – for changes, troubleshooting, bug fixing etc. Reducing this drain on resources is good for the company overall.

Drilling down into big data visually 

User behavior tools are designed to handle and analyze big data seamlessly in a unique way. They are based on sessions where the activity of each website visitor is recorded. This logs the clicks, actions, scrolls, searches etc (or events) of everybody visiting.  With maybe one million sessions per month for a given website – but many times more events tracked for each session – this builds a massive volume of data.

The clever bit is filtering down to meaningful data in seconds in order to get results and act quickly. Traditionally, product managers have struggled here because they can feel overloaded with data. The behavior tool easily visualizes the data as a video of activity, which quickly jumps to the right section to highlight where the issue might be.

Being able to immediately see specific drop-offs in a particular workflow is a real step forward – currently the more quantitative analytics/basic tools may show that one page is causing the problem, but not which specific item is causing the problem among many on that page.

Another use case is meeting demographics and accessibility requirements. A website catering for cruise ship holidays may see a larger percentage of older visitors.  Their habits and behavior are different from youngsters – so creating a standard website may not work as expected. Designers can quickly learn how to improve and make changes – if the data shows that they miss a button, or the content is in the wrong place for example. Ultimately the user behavior data can visualize how people are behaving and make the user experience better.

Whatever the type of website requirements, it might be time to question how usability testing is implemented. Such testing might collect feedback but it does not necessarily reflect real world usage. behavioral systems can perform such preliminary testing, but often there’s no substitute for live data – especially if it produces immediate feedback.

Tracking user behavior in mobile apps 

It’s not just website user behavior that can be tracked. Given the growth of mobile devices, and the level of investment into apps, app data can now also be gathered to build a greater understanding of users. Tracking both mobile app and website data is invaluable for marketers as it shows users’ cross-platform journeys.

For example, it would show how a user behaved on the website during the day, then how that same person used the app in the evening on their mobile. This powerful intelligence/insight can be used for a number of marketing objectives including: where to invest more, what content to serve – and on which channels, improving customer journeys, deciding where to serve ads.

This is a huge growth area, and understanding user behavior on your app is money in the bank. Enterprises are putting lots of investment into apps rather than the website (which are often just marketing pages) and for good reason – it leads to increased and repeat product purchases via the app.

Which datasets & tools should enterprises focus on? 

User behavior analytics data is important for a range of users in a business. Ecommerce giant Alza, based in the Czech Republic, uses behavioral analytics in different ways including:

Product Manager: they combine visual & quantitative data to see the whole story. A PM can define various events, create funnels and then check the conversion rates of each one – such as basket abandonment or upsell buttons. Then he or she can simply use these funnels to see only the relevant recordings. It’s invaluable to observe users in action and help understand user behavior and ensure they fit the needs of the customer.

UX designer: A/B testing is an excellent method to help figure out if a design is working. But it doesn’t answer why certain behavior is happening – including how people browse, move the mouse, what they click, which text they read. Recordings enable designers to literally see where the issue is and such unique insight provides more confidence to make improvements.

Category manager: Heatmaps are most useful to category specialists to show very quickly where people click (and dwell) the most. That way, they can determine which drop-down menus or buttons are most relevant and which content works best.

Content specialist: Content managers also use heatmaps to watch which details of the pages are getting the most attention. If an element isn’t working, they have to collaborate with UX to create a better flow.

Other businesses use it in additional areas:

Data analysts: exporting APIs means raw data can be extracted to better understand click streams. A huge volume of data is available from events, drop-offs, click frequency, to visitor frequency etc. This enables an even deeper understanding of users, particularly for BI purposes.

Support staff: recording sessions are particularly useful for identifying, sharing and fixing issues quickly.

Why is sharing data through departments/offices so critical? 

It’s not enough for such a data tool to appeal just to marketers or product managers. With the ability to share with other departments and superiors, in an easy to understand visual way, it makes it more valuable to the business information workflow.

It removes any guesswork around an issue. With a simple share button a unique link to replay the specific recording can be sent to a developer to fix the problem, for example.  Nobody has to mark-up a screenshot or email a description – it’s a case of simply sharing the exact segment recording, adding a note in session, and one click to send the link to the recipient. 

It’s useful for management reporting. It might be for regular management updates, as well as sharing the link where a problem is happening and suggesting fixes before implementation. 

Also building a business case for your idea and presenting to your superiors becomes more powerful.  With the ability to show data in a straightforward way for everyone to visualize and understand quickly - rather than the usual lists of numbers or a few graphs - you can show the previous conversion rate, the changes you made, and how the rate went up 5 percent.  One tiny change can make a small percentage improvement – and can mean an extra gold streak for businesses.

Rather than using standard templates and a list of key datasets, today’s intuitive and versatile tools mean that businesses soon understand how to identify and solve their own problems, and focus in on data that is important for them. Each company is different, as is their approach to data, they often know where they want to go with data and they should be able to setup the tool to reflect their needs.

Enterprises can drill straight down to the gold nuggets 

Enterprises are simply drowning in data. Big time and big data. So much so that it’s often difficult to focus on the right analytics for your business. The visual elements of user behavior systems help answer that. And by drilling down to specific parts and replaying user actions, and by sharing with other parts of the business, marketers can efficiently and speedily mine those gold nuggets.

Yes, you need big data to give you the numbers for the big picture, but if you can’t generate the focus to analyze and address really specific issues – in real-time - it’s a serious waste of resources.

Petr Janosik, Founder and CEO, Smartlook

A visionary entrepreneur with 15 years of experience in customer behaviour analytics & web development, Petr leads the Smartlook team that helps businesses make better data-driven decisions.