Article

7min read

Understanding User Behavior Through Data

As part of our customer-centric data series, we are speaking with AB Tasty partners about how brands can use data to better profile customers, understand their needs, and forge valuable emotional connections with them, as well as measure overall digital impact and build a data-based, customer-centric vision.

You can catch the beginning of the series here. For our 8th installment, we spoke with Helen Wilmot, UX Director at Dentsu International. Dentsu is one the largest marketing and digital companies in the world and provides communication, marketing and digital strategies across a range of disciplines. Helen leads the UX strategy and research for Dentsu.

Why customers come to Dentsu

Dentsu is an integrated global company. People are often looking for the different channels they operate in, as well as having several disciplines collaborating under one roof to serve a client. More than that, Dentsu is a multi-national company with a network of global expertise focused on how to provide value to clients so that they actually see that they are linked to something that’s larger. Specific to the  UX and optimization team, they are tightly integrated with other channels such as brand and digital strategists, SEO, and commercial. All of those aspects are taken on board when they are looking at optimization.

That means growth is one of the major factors at play: “We are firmly focused on being customer-centric and providing value for the users,” says Helen. “We also live in the real world and we want to tie that value to real growth. We know that being customer-centric drives growth, study after study after study shows that, but it’s important that we can show that ourselves in our own behaviors.”

Understanding user behavior

Helen stresses that there is no single way to understand user behavior and as such it will often depend on what is appropriate for the research or business problem at hand. Dentsu combines many techniques when looking to understand customer behavior, often a balance of qualitative and quantitative data. In many cases they are looking for a breadth of data to make it accurate – interviews, usability testing, AI, eye tracking, data insights, and card sorting all play a part.

The techniques employed depend on the customer and the business model. Consistently, however, they are led by data. Researchers perform usability tests, both at a distance via remote studies and in-person moderated use testing. Having users try something out in their own environment using their own devices also helps Dentsu asses more natural behavior. They sometimes employ ethnographic techniques, which are borrowed from anthropology, as researchers are embedded in users’ real experiences. Looking at interaction with a topic or task in real-time, this research is more generative and exploratory but can help uncover larger issues. New technology in behavioral science and neuroscience can look at emotions, implicit response testing and eye behavior.

What customers say they want and how they actually behave

Specifically, when Helen’s team conducts interviews they look at how users behave as well as what they say. 

User testing should be about observing,” shares Helen. “If the user said they found the task easy, but they clearly didn’t, it’s a sign to use our critical thinking to evaluate that feedback.” 

So Dentsu always dig deeper to back those statements up with data. They have a rigorous approach to their research, including the use of a laddering technique used to get to the root cause of people’s thoughts and experiences. “It’s all working within the reality of how we know people’s minds work. We know that people are terrible at remembering exactly how they felt and terrible at predicting our own behavior. So that’s not to say that experiences don’t matter but as researchers, our job is to work within the reality of how human psychology works too,” says Helen.

The importance of testing and experimentation

Another way Dentsu works to validate user feedback is with a reliance on A/B testing. In the past, they have had users report certain things that motivate them, but the A/B tests do not back up that information. For Dentsu, testing out a hypothesis is a crucial part of their optimization process and it is unthinkable that they would go ahead with new ideas without testing them first. 

“I think it’s a bit of an act of hubris If you don’t go ahead and test,” stresses Helen. “The risk just absolutely shoots up, and you can’t de-risk a solution without testing it. Even if a solution is successful and is fit for purpose, there are always iterative changes that you can make. That is the beauty of a testing and experimentation mindset. You are never finished, and we never think that what we do is perfect.”

Testing allows Dentsu to move at speed. Some tests don’t always work, but Helen points out that losing tests also brings a wealth of information for other ideas. Knowing something doesn’t work for your users informs you for your next test and when you are working with future customers, it can point you in the right direction as to what techniques are currently effective for messaging and psychological persuasion.

The KPI’s and metrics within user behavior

For UX, one if the main KPIs is NPS (Net Performance Score), just as it was for Realise. In usability tests, Dentsu will look at the number of errors someone makes. If they are testing a certain structure or tree testing, they will look at success rate and directness. NPS compliments all of these because it has numerous studies behind it associated with growth. There is also a holistic view to take when it comes to user behavior metrics: what areas within the business are being affected by friction on the website? It could be customer support, payment or delivery, but they are all vital to the user experience.

A good user journey

A good user journey will always provide revenue. The two are intrinsically linked for Dentsu. If you get it right, people become more engaged in the brand, more engaged with what you are offering and it makes them more likely to do what you want. Helen wants to go further, though. Usability and revenue are vital aspects, but they are only the beginning.

Helen explains, “I think usability is the absolute baseline that we should aim for, and we really should be focused on delighting customers while creating emotionally resonant experiences. There is strong data on the link between emotion, memory and brand perception and by creating these rich, emotionally resonant experiences we can boost lifetime value. 

It seems that in the current climate, people are placing an emphasis on the bottom line and conversion, but, as Helen shares, the original thinkers on UX such as Donald Norman were looking to delight to provide insight into optimization. Brand and user experience are inevitably related and users who have an emotional connection with a brand will give you more and more chances to be present in their lives.

“It’s important to view delight as a bit of a North Star. If you make your users happy, you’ll make shareholders happy as well.”

You can find out more about our Customer Centric led by looking at our previous installment on how to solve real user problems with a CRO strategy.

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Article

5min read

Test More, Risk Less: A/B Testing as a Risk Mitigation Tool

Imagine this: You see a continual drop in conversions on your e-commerce website. In particular, customers are abandoning their carts and not completing their purchases.

Based on previous experience, you decide to take action by switching up a few elements on the checkout page.

But it’s still not getting you the results you’ve hoped for; instead, you see your conversions going even further down. What went wrong?

How experiments can come to the rescue

There’s always a certain degree of risk in business and any wrong move can be a potential loss in profit. How can you test your ideas without breaking your website and negatively impacting your business?

Thanks to A/B, A/B/C and multivariate testing, you can manage and even reduce that risk before making a big decision that could hurt your bottom line.

Before we go any further, let’s look at a simple definition of A/B testing.

A/B testing is a marketing technique that involves comparing two variations or versions of a web page or application, randomly presented to users, to see which performs better by evaluating how they impact your KPIs.

The results of such tests will help you assess the risk of your business decision as it presents an opportunity to gather feedback from the people with the most valuable opinions — your customers. Otherwise, you’d make the decision based on personal opinions rather than customer preferences, eventually leading you down the wrong path.

A/B testing helps steer you in the right direction by enabling you to test and learn quickly if something works or not before embedding it into the back-end or permanent coding.

If you don’t take steps to manage risks, you’d never be able to tell if your new ideas will resonate with your customers or if they’re worth the investment. However, when you run A/B tests, you can minimize the risk of any drastic business impact.

For example, you can make a pretty website by changing colors but if this change drives down conversions then you’ll have a nice looking but poor performing website. Thus, A/B testing gives you the green light to go through with an idea by monitoring how it’s affecting your KPIs.

Experimentation is the most efficient way to eliminate rolling out a bad idea for your website or prove the value of a change before investing time and resources. It’s a golden opportunity to learn what really drives conversions so you can use the data extracted to fully commit to any changes in UX.

Even if an experiment doesn’t turn out the way you planned, you can still use it as a learning experience on what your customers don’t want so that you stay on the right track.

To get the most out of your A/B tests, you need to leverage both quantitative and qualitative data when it comes to effective decision-making. In other words, running these experiments is important, but it’s the quick steps you take after based on the results that will make all the difference.

AB Tasty is a great example of an A/B testing tool that allows you to quickly set up tests and gather results to help you mitigate risk with ease. With low code implementation of front-end or UX changes on your web pages, you can gather insights via an ROI dashboard, determine which route will increase your revenue, and achieve the perfect digital experience for your customers.

In summary, always make sure you test new features or changes prior to release to make sure they take your business metrics in the right direction. Even if it seems like it’s a very minor change, it could still have a significant impact on your conversions and revenue.

Steer your A/B test in the right direction

While you’re running an experimentation campaign, there’s also another layer of risk when randomly allocating users to your variations as so often happens to be the case during an A/B test. What if there’s a variation that you notice is performing poorly? How can you quickly turn this off before more traffic is exposed to the variation?

Luckily, there’s a way to further minimize risk during an A/B test and that’s through dynamic allocation, a capability offered by advanced A/B testing solutions such as AB Tasty. 

Dynamic allocation seeks to limit loss due to the lowest performing variations so that fewer visitors are sent to the “bad” variations to maximize outcome, as can be seen in the image below.

For example, if you run an A/B test with two variations with the goal to increase conversions on the checkout page and variation B is performing well and has a high conversion rate, then the traffic to that variation is adjusted (and increased) accordingly.

One of the advantages of dynamic allocation is risk mitigation. This will enable you to confidently and safely test new elements. If they don’t work out as predicted, then the traffic allocated will be gradually reduced so fewer users will access it. 

Make risk-free and data-driven decisions with A/B testing

Any new changes or releases you have in the works shouldn’t be driven by your gut feeling but rather from a combination of quantitative and qualitative data, the kind of data and insights that you can only obtain from running tests and experiments. This enables you to optimize your website accordingly rather than speed up losses from a misguided UX change based solely on personal opinion.

A/B testing doesn’t have to be a risky endeavor. Features such as dynamic allocation can make all the difference when running A/B tests to avoid any significant loss in conversions from a poorly performing variation.

In the end, it’s a win-win situation: you get valuable insights while managing risk and your customers receive higher-quality products they actually want resulting in enhanced customer satisfaction.

With AB Tasty, you never have to lose a single conversion. Get started building your A/B tests today with our best-in-class software solution to explore how you can get maximum results with minimal effort thanks to our dynamic allocation capability.