Why experience data is the new currency for big business

According to new research, many marketing departments are awash with vast quantities of data, yet marketers don't know what to do with it.

In this post we discover why it's the type of data that is so often holding them back. 

When JetBlue – one of the USA’s leading domestic airlines – discovered a dip in its business passengers’ customer satisfaction scores at a Philadelphian airport, curiosity took hold.

Deep diving into the minutiae of the feedback at their disposal, its CX team revealed that the passengers were arriving at the airport for their early morning flights to be confronted with an issue.

Bleary-eyed, caffeine-starved and cantankerous, they were being hit with a wave of nausea at the realisation that not a single concession store was open for them to fuel up with coffee before their trip. JetBlue satisfaction surveys were bearing the brunt of their subsequent wrath.

The airline quickly responded to the issue at hand – bringing in coffee, water and juice to be offered out to customers before they entered their departure gate, first thing. Corresponding satisfaction surveys were taken a month later and surprise, surprise –a massive uptick in score occurred from the same, seemingly exacerbated demographic.     

The rise of experience data   

This story highlights two truths: how simple it can be to resolve a problem with the right kind of insight; and how important it is to have the right kind of insight driving your decisions in the first place.

Ian McVey, head of enterprise sales, Northern Europe at Qualtrics says that this type of insight is increasingly referred to as ‘experience data’, and that its value to organisations is profound:

“This type of experience data will have more and more currency in a world largely driven by operational data.  

“Operational data is so often just clutter, whereas experience data cuts through that. It’s data that essentially highlights your customers that are yelling and saying ‘listen to me and serve me in this way’.”

So what kind of experience data exists, how does it differ from the operational data McVey refers to and why does it help drive better decision-making?

“Experience data is Voice of the Customer (VoC) and Voice of the Employee (VoE) insight – it’s almost always verbatim feedback and commentary around a set of topics that either customers or employees will feed back to an organisation,” says McVey.

“Operational data is different. It’s the nuts-and-bolts stuff: clicks on website, sales on a product line, customer visits based on customer type…that type of thing.

“Companies are awash with operational data – but increasingly they’re finding that that’s not a positive thing, and that turning that into insight and action is extremely hard.”

Operational data is so often just clutter, whereas experience data cuts through that. 

Dearth of data scientists 

Indeed, a comprehensive piece of research by Qualtrics has found that marketers, in particular, are submerged in data that they’re struggling to turn into insight and then action. The study how marketers are turning ‘big data’ into ‘useful data’ finds that 86% of marketers believe they collect too much ‘operational’ data: sales leads, email click throughs etc.

Coincidentally 86% also felt this type of data wasn’t doing enough to help them offer better experiences to their customers. Worryingly, the result is that one in four marketers continues to rely on gut instincts to decode the actions of their customers.       

“Why gather the data if you’re relying on gut instinct?” says McVey. “The more you plug in, the more you have to analyse. Data scientists have never been in such high demand yet very few marketers have a data scientist on their team, making analysis ten times harder.

“64% don’t have the time for complex analysis, 51% don’t know what they’re looking for in data trends. They’re not data scientists, they’re marketers. They’re looking for a bridge between having the data and knowing what to do with it. And they’re crying out for a different kind of data.”

Data scientists have never been in such high demand yet very few marketers have a data scientist on their team, making analysis ten times harder 

Listening posts

Experience data may be the ‘different’ data to which McVey refers, but there’s a challenge for organisations who want to change their practices to start actioning this type of data, as he explains:

“What businesses need to do is put listening posts in place across a variety of channels and a variety of touchpoints and moments on a customer journey that catches that data in the moment from a customer related to an experience or product or service they’re receiving.

“This helps marketers position and understand a real-time narrative with their customers and that is disarmingly powerful – simple on one hand but quick and insightful on the other.”

This means creating feedback at the right touchpoints. If you’re a retailer you might like to learn like-for-like sales across your different stores. But then you may also wish to draw a correlation of how happy your customers are that go to the stores and what makes them happy or unhappy; how happy employees are that work in those stores; and is there a correlation between happy employees, customers and like-for-like performance in the stores.

In this equation, feedback or ‘experience data’ at point-of-sale is vital in deep-diving into what is specifically driving the correlations in store, which the operational data – the like-for-like sales, can’t provide on its own.  

What businesses need to do is put listening posts in place across a variety of channels and a variety of touchpoints and moments on a customer journey 

McVey says this is the ‘why’ behind the ‘what’, and is increasingly providing the differentiator for businesses competing against a backdrop of declining loyalty.

“Why is something happening? That’s the data that works best for marketers as it tells a story that ‘what’ data can’t.

“At the heart of this is primary, verbatim data from customers. At the core of experience data is asking questions at the right moment in time and garnering good feedback in return. We now have the power, thanks to advance technology, to contextualise who a customer is, where they are on their journey, and contextualise and ask a set of questions that are deeply aligned with an experience they are having at any given moment in time.”

Actioning data is ultimately the final hurdle for most organisations. Temkin Group’s State of VoC Programs 2017 research found that whilst many businesses considered their customer listening and feedback programmes as moderately successful, less than 25% of companies consider themselves good at making changes to the business based on the insights.

“People have always collected ‘feedback’ from their customers,” adds McVey.

“However, the problem was that it was just that – it was never seen as data. Now you have the tools to take open text comments and feedback with NLP (natural language processing) and machine learning to turn that sort of information into data. It’s turning feedback into a genuine data type and actionable data that people can use.”

And as with JetBlue, giving staff in CX positions the authority to make changes to the business based on the insight they’re collecting is what will ultimately make or break the business’s success.