Atlanta-based FullStory — a Google-Ventures backed data analytics platform — yesterday unveiled Rage Grade, a new tool designed to help users identify and analyze what areas of their websites and apps are generating the greatest visitor frustration.
Rage Grade builds 55-employee FullStory’s Rage Clicks feature, which was unveiled in 2015.
Rage Clicks used machine learning to identify the sources of frustration-producing customer experiences by tracking and analyzing behaviors such as multiple and excessive clicking in one spot, or good old fashioned mouse flailing — two actions typically associated with slow or otherwise annoyance-producing digital experiences.
Meet Rage Grade
Rage Clicks enabled brands to recognize when their website visitors were getting frustrated and upset with their digital experiences — but it lacked the context of knowing how or why. FullStory is hoping to plug that gap with Rage Grade.
Rage Grade analyzes those digital frustrations more deeply to give sites a grade ranging from A+ to C-, depending on the level of frustration their visitors report.
That grade is then presented alongside an average grade for similar sites in the same industry. This comparison is designed to give FullStory clients a benchmark to use in measuring their own rage grades compared to their competitors.Rage Grade also records the top 10 sessions that contributed to the assigned grade, so brands can hit the play button to see for themselves exactly how their websites or apps infuriated visitors.
The proposed goal here is simple: with the data, grade and video playback in hand, FullStory customers will be able to improve their digital experiences based on feedback about the rage-inducing behaviors their users report.
Here’s a breakdown of how Rage Grade measures digital frustration:
- Multiple Frustration Signals: FullStory deploys a machine-trained algorithm to combine frustration signals like rage clicks, error clicks and dead clicks to determine real user frustration toward a broken or misleading UI.
- Abandoned Forms: Rage Grade automatically detects abandoned forms and factors them into its frustration score.
- Thrashing Mice: Throwing your cursor around the screen is a classic sign of frustration. Rage Grade captures those movements and factors them into the rage score.
Rage's Role in Digital Body Language
FullStory’s attempt to quantify rage is useful in brands’ quest to understand the digital body language of their website and app visitors. Considering that 90 percent of consumer decisions are emotional, the role of consumer rage cannot be underestimated.
As web psychologist Liraz Margalit, director of behavioral analytics for Tel Aviv-based Clicktale, pointed out in a 2016 CMSWire piece, “to succeed in the digital climate, smart businesses are... realizing the necessity of reading and responding to the ‘digital body language’ of their customers.”
For a fresh take on this ongoing journey toward understanding every dimension of the digital customer experience, CMSWire reached out to Margalit to gauge her current views:
“Our research has found that interactions and movements online can reveal the visitor’s psychological inner state," Margalit said. "Digital interactions — just like day-to-day real-world interactions — are based, in large part, on nonverbal communications."
Digital Body Language Reflects the Real World
She continued by explaining the intricacies of digital body language, and how it’s remarkably similar to the body language humans display and interpret on a daily basis in the physical world:
“When we interact with others in the physical world, we are continuously processing nonverbal signals such as facial expressions, tone of voice, gestures, body language, eye contact and physical distance," she said. "Similarly, there is a digital body language that helps brands identify what experiences their customers are having via their websites and apps."
Monitoring Real-Time DX
Companies use machine learning analytics and data science to monitor in real-time digital activities such as browsing behavior, click-through rates, hesitation and scrolling, among other actions, she added.
"When pooled together," she said, "the data allows you to infer the true meaning of each interaction by applying cutting-edge experience analytics."
(Editor’s Note: Learn how Liraz Margalit integrates cognitive psychology and behavioral economic perspectives to analyze online consumer behavior and deliver actionable insights during her session at CMSWire’s DX Summit, entitled Digital Body Language – Understand Customer Intent on Your Website on Nov. 14).
So Much More Than Words
As for brands investing heavily in voice of customer (VoC) programs — which may include surveying their website visitors for the sake of gathering constructive feedback — FullStory Founder and CEO Scott Voigt noted that, "Alas, most VoC programs only account for customer sentiments that are explicitly expressed through surveys and forms.”
“FullStory’s Rage Grade finally lets VoC advocates understand implicit VoC," he added. "Thanks to the power of machine learning, customer experience professionals can begin to understand negative customer sentiment and identify specific frustration points across all customers, not just the vocal ones."
Margalit concurred with those sentiments, pointing out the pitfalls of deploying VoC programs without the context that can come from data mining and analysis.
“There are a few problems with asking the visitors for feedback," she said. "Those who agree to report are usually the visitors who have had an extremely unpleasant experience. Thus, results are likely to be skewed and not representative of other users’ experiences."
Common Sense DX Design
London-based Convertize, the conversion rate optimization platform, also spoke with CMSWire about the need to look beyond customer feedback, especially since — according to Convertize CRO Benjamin Ligier, at least — the DX optimization process is much more basic than most care to admit.
“The real issue, [and this is not to devalue the practice] of doing your data analysis and surveys, is that there is a lack of common sense when designing a web experience. We call it ‘common sense UX,'" he said.
“This entails always putting yourself in your [new] visitor’s shoes and asking the following questions: where am I, why am I here, is this for me, what should I do and why should I do it?”
In other words, Ligier believes in prevention over cure, with that prevention coming in the form of web design teams with the emotional intelligence to begin by asking the simple questions.