Q&A with Augie Ray (VP of Gartner)

Hi Team!

This week, I’m excited to bring a new voice to the newsletter - Augie Ray.

Augie is the VP of Gartner - Analyst of Customer Experience offering guidance on CX & Voice of the Customer.

I’ve been following Augie for a while now and am often blown away with the level of knowledge he has about CX & Voice of the Customer best practices.

As the goal of this newsletter is to surface key statistics and best practices pertaining to the #CX & #EX industry, I reached out to Augie who kindly agreed to answer some questions I had.

Check out the Q&A below 👇👇

Q1 - What is one thing you believe about CX, which not many others would?

I think most CX programs get CX wrong from the start. As a result, brands' CX struggles are not due to the reasons they often think (such as technology, data management, and the like) but because they've defined CX wrong, set poor CX metrics, and are pursuing a fundamentally flawed strategy.

The issue is that so much that is called CX isn't, in fact, customer-centric. What happens is that leaders know they should focus on customer experience, but they immediately ask what the ROI is.

That question isn't a bad one--we should know what the value of CX so we can scale investments appropriately. The problem is that the question isn't customer-centric so it isn't answered in a customer-centric way. As a result, many of the metrics companies set are very short-term and financial--in other words, very brand-centric rather than customer-centric.

CX is about strengthening customer relationships and earning greater satisfaction, loyalty, and advocacy from customers.

A good example of where brands go wrong is that they'll associate additional sales to customers as a measure of loyalty. But repeat sales may or may not be driven by actual loyalty. They might, for example, be based on the fact your product service is more convenient, or cheaper, or is protected by higher switching costs.

What appears to be loyalty can disappear rapidly when there's a change in the marketplace, such as a new entrant, and sales are lost. I look at the taxi industry as a good example of this phenomenon.

For decades, taxis looked like they had a loyal customer base--people arriving at airports or train stations or needing to get around cities were repeat purchasers. But taxis were, in fact, annoying to many people. Taxis were frequently dirty, rude, and frustrating, but they were the only option--until ride share companies like Uber and Lyft came along. Suddenly, all those seemingly loyal repeat customers evaporated quickly and decimated a good portion of the taxi business.

Taxi companies didn't have loyalty, at all, no matter how many times business travellers used their services. Which brings me back to how CX programs are created and measured.

If brands cannot shake themselves from focusing only on the financial results they can measure and not the strength of their relationships, they will struggle to get CX right.

Q2 - What would you consider to be the top 5 CX metrics if someone wanted to measure a great customer experience today?

I'm not sure that this has a proper or single answer. My answer would change from one industry to the next, and it would also be different if I was speaking to a digital team, a customer care client, or a product development leader.

I think, in general, there is too much focus on finding some perfect right answer to fit every situation and not enough on different companies or departments finding the answer that is right for them.

When working with clients, I try to focus on two things:

1. Whether top metrics are customer-centric or brand-centric. I advise that clients balance the measures they derive from the customer (such asking their satisfaction or NPS) with measures of what the brand derives from the customer (more sales, for example.)
   

2. Connect the two types of metrics together to understand correlation. In other words, can we prove that a more satisfied customer (no matter how we choose to measure that) is also a more loyal customer?

So, for example, for a brand that uses NPS in their customer surveys, I explore if they know that promoters deliver more value than do detractors.

Can the brand prove, using its own data from its own customers, that promoters buy more, buy a broader selection of products, have a lower cost to serve, churn less, create more referrals or have a higher lifetime value? 

If we can show this relationship, then we demonstrate how raising those customer-centric measures of satisfaction drive greater growth, higher margin, and better financial outcomes.

Q3 - Personalisation is an emerging concept in the customer experience space. From your perspective, what should a personalised customer experience ACTUALLY look like?

First, I am not certain that I'd consider personalisation an “emerging” concept. I believe personalisation has been part and parcel of interpersonal customer experiences since the beginning of time, and of course, we've had personalisation engines driving websites for over a decade. I am not making this point to be disagreeable, but in fact, personalisation is so mature that, at this point, many brands are finding the struggles and limitations of personalisation.

Gartner has predicted that 80% of marketers who have invested in personalisation will abandon their efforts by 2025 due to lack of ROI, the perils of customer data management, or both.

The easy answer to what a personalised experience should be is that it should be oriented to what is best for the customers. And therein lies the problem with the way personalisation is often implemented by brands.

The “next best action” (NBA) that brands want are clicks and sales, but the NBA for customers is frequently quite different. Personalisation that doesn't reflect the needs of customers and their context will tend to annoy rather than enhance the experience. And that is a high bar to clear, which is why my peers at Gartner feel many brands may abandon their personalisation efforts.

Q4 - ChatGPT has taken the world by storm recently. From your perspective, how do you think AI can have the largest impact in the CX / EX space?

I think a lot of people expect that AI can and will replace frontline workers and reduce costs. And, in time, that may be the case.

But I think the more powerful use of AI in CX right now is to better understand customers. For example, machine learning and AI have been used for years to gain better insights from customers. Whether it's evaluating the text of survey verbatims, of customer chat sessions or of transcripts from customer care calls, AI can help us better know what customers expect, what drives dissatisfaction, what's broken, and what CX opportunities are being missed.

I am less excited about how chatbots might change CX than I am with how AI can help us do a better job of understanding our customers.

Q5 - Finally, if you were a newbie to CX and wanted to make your mark in this space, how would you go about it?

If I were starting my career anew in CX, I'd put effort into strengthening my data skills.

As I advise clients who are hiring CX roles, one of my favourite interview questions to recommend is, “Tell me about a time you used customer data to uncover a CX problem or opportunity and how that guided your solution.”

This question is telling for a couple of reasons:

1. The first is to find if a candidate can cite an example of how they used objective data to reach a customer-centric conclusion.
   

2. The second is that often, candidates will cite examples of how they've used data to improve conversion rates on e-commerce sites or open rates of emails--but while both of those are great brand outcomes, neither is a customer-centric CX result.

Instead, I advise clients to listen for answers of how the candidate used good customer-centric insight (such as Voice of the Customer data, ethnographic research, and other forms of customer research) to uncover customer needs and wants and deliver a customer-centric solution that improved customer relationships, loyalty, and advocacy.

I didn't have the option of becoming a data expert at the start of my career. The programming I did in college was on punched cards, and I didn't have a PC on my desk until my third job after I graduated.

As a result, I learned about how to use, manage and analyse customer data over the course of my career.

But if I was starting out today, I'd be laser-focused on how to use direct, indirect and inferred customer data to identify the CX opportunities and problems that are not otherwise apparent.

If you enjoyed this type of Q&A content, please let me know via email so I can arrange more. I’m out here testing & learning as always ✌️

Cheers,

Ben