Tag Archives: metrics

An Inspiring Ice-T, the rise of AI, and other CMSWire CONNECT observations.

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“Ice-T? Why would they have Ice-T at a conference dedicated to customer experience?” Well by the conclusion of my two days at the CMSWire CONNECT conference in Austin last week I had my answer.

But more on Ice-T later.

First off a nod of thanks to my CMSWire editors Dom Nicastro and Siobhan Fagan for arranging for me to attend the conference as a CMSWire contributor. It was great to spend time in person with people I’ve been writing for over the last six years. It was also an excellent opportunity to meet other members of the CMSWire team too. 

Early encounter with AI personas

My two days started off with attending a very thought-provoking Breakfast Briefing from Erin Reilly of the University of Texas on The Rise of Virtual Beings and how they are transforming the customer experience. I must admit I hadn’t given much thought to the use of three-dimensional avatars beyond gaming applications, but her examples of AI-driven personas certainly gave me pause to think about how the digital landscape is continuing to evolve.

Metrics of CX – data and experience

In his discussion on The Customer of the Future, the University of Texas’s Art Markman discussed the application of cognitive psychology to customer behavior and how we measure it. One point that really caught my attention was the observation that

 “If we spend time just looking at data we start to think that every interaction is a digital experience. We need to look beyond that and embrace the real-life experiences and engagements.”

This really resonated as I’ve had several conversations recently about the relative importance of quantitative and qualitative metrics when it comes to determining the quality of content-driven interactions. This drove home that both are equally important. As one later speaker put it, and I’m afraid I missed taking a note of who it was, it’s no good knowing the ‘What’ if we don’t know the ‘Why.’

Katrina Taylor of LuLu Lemon also summed it up nicely in her excellent presentation on Human-Centered Design for Omni-Channel Delivery when she stated:

“You can go through all the data in the world, but you will learn way more in a 30-minute conversation with those on the front line who interface with customers.”

Intelligent content drives personalization

I must admit my heart gave a little jump to hear Matthew Shaeffer from REI talk about the need for intelligent content in his talk on Modernizing the CX Stack. His observation that Intelligent CX  needs to be a series of uniquely assembled interactions driven by content that is structurally rich, and semantically categorized was great to hear. Engineering content in such a way is key to delivering the granular levels of personalized interactions most companies are looking to achieve, and it was great to hear of a major retailer adopting this approach.

Tarunam Verma from Lowes made a smart observation during his presentation on Hyper-Personalization that what we think of as personalization isn’t just about applying technology, in reality, it’s a mix of culture, mindset, and the technology.

Is AI really Augmented Intelligence rather than Artificial Intelligence?

The second day of the conference had a strong theme around the impact of Artificial Intelligence (AI) and Machine Learning (ML) with some excellent observations and talking points discussed throughout the day. Here’s a snapshot of some of the ones that caught my attention:

  • “Use AI in support of creativity not instead of creativity” – Karna Crawford (ex-Ford)
  • “AI is most useful currently as a back-office application that detects operational inefficiencies.”  / “There are two waves of AI: (1) recommendation engines – which are established, and (2) generative – which we are still trying to figure out.” / “Don’t implement AI just for the sake of it, know what problem you are trying to solve. / AI requires us to rethink how we do things.” – Daniel Wu (J.P. Morgan)
  • “Think of AI as ‘Augmented Intelligence” that helps us do our tasks better, not ‘Artificial Intelligence’ that will replace us.” – Raj Krishan (Microsoft).

One of the best questions of the day came from CMSWire facilitator Kate Cox who posed her panelists a pretty philosophical question:

“If I use AI to craft an email and you use AI to read it, are we actually communicating?”

Ice-T on Walls and Boats

Which brings us back to Ice-T as the conference closing keynote. I wasna sure what a former gangster, turned rapper, turned actor would have to say that would be relevant to an audience full of technologists. In fact, I was in two minds about staying, thinking I’d leave a bit early to get ahead of the Austin downtown Friday traffic exodus; but I’m glad I did as he delivered one of the best conference keynotes I’ve seen.

It was entertaining, full of amazing stories, and above all an inspirational discussion on handling change. Here are just a few of his observations that I jotted down:

  • “There are walls – things that you can’t change – and obstacles that look like walls. Get over the obstacles by talking to people that have already got over them. But then make sure to put in the work that they put in.”
  • “Don’t ever get annoyed at the lack of results from the work you didn’t do.”
  • “Anything you do you bring your perspective to it. That’s your value. Make it your own thing.”
  • “Don’t complain, just figure stuff out.”
  • “Take opportunity when it turns up. A lot of times the opportunity is right in front of you. Just get in that boat, at least for long enough to say ‘I don’t like it.’ If you don’t you’ll never know.”

And if the CONNECT conference was one thing, it was a great opportunity to learn from, meet, and network with a whole raft of new people. Thanks to all I chatted with be it after presentations, at vendor booths, or over coffee or meal breaks.

Here’s to getting in the boat.

Stop Using Customer Metrics to Live in the Past

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Admit it, we all do it. I’m talking about how whenever we post something online, we can’t help but check back later to see how it was received. Thumbs up, likes, retweets, comments, downloads, page views. We all love metrics, whether it’s just “did anyone like the picture of my cat I posted on Instagram yesterday” all the way up to complex reports about web traffic, journey flow, click-through rates, and all that good stuff it takes a data scientist to sift through. We have so much data available about customer interactions that the true meaning is often forgotten.

The problem is that most of the metrics record what someone did in the past — typically an interaction with your content by either clicking a button or following a link. They don’t tell us why the person did what they did.


And knowing why is the most important part of understanding the customer journey.

Getting to the why (and why not) of customer behavior

There is an excellent video from Adobe entitled Click, Baby, Click that shows how reacting to clicks without knowing what is driving them can lead to an incorrect interpretation of customer demand. If you haven’t seen it, I highly recommend watching it — it’s a fun lesson you won’t forget.

So if action-based metrics don’t provide the information you need, do time-based metrics give a better picture of what’s driving customer behavior? They are probably a step in the right direction, but they have the same underlying issue — they still reflect past actions. You may now know how long someone interacted with your messaging but not why. For instance, time-on-page can be a false indicator: is someone engaged because your content is good and they enjoy reading it, or is it so obtuse that they have to keep plowing through it to find the answers they want?

Most people come to websites or interact with apps for one of two reasons: to get answers to questions or to complete a transaction. So maybe we should be measuring how well we achieve those two things. Instead of having page-based analytics, shouldn’t we be focused on content and transaction-based analytics combined with search analysis and time reporting to determine how easily, or quickly, customers achieve their goals?

On top of wanting to know what people do during a customer engagement and why they do it, it’s equally important to know why someone didn’t do what you wanted them to do. Why is no one clicking on that beautifully designed call-to-action button? Why isn’t anyone finding high-value content that would help them? This is where tools like heat maps can help you track where people engage with your designs.

Understanding intent

So if the current metrics are a snapshot of past physical actions, how do you realign for a future where interactions migrate from the physical to the digital or to even more esoteric forms of interaction?

Think about the growing use of voice-based assistants such as Siri and Alexa. How will you measure audio interactions?

In many ways we already do, but for a different need. When you call a telephone helpline or get passed to a call center representative with a message that says “your call may be recorded for training purposes,” chances are high that training is low down on the list of why the call is being recorded. Call centers have long used technology to record, index, and analyze customer interactions not just for what was said, but also for the way it was said in terms of tone and inflection.

Sentiment analysis may drive the next generation of metrics for voice-assistant-driven interfaces, not only allowing you to understand what a customer asked for and wanted but also, with the application of machine learning, allowing you to start to understand not just how someone feels about an interaction but also what it was they were hoping to achieve in the first place.

Once you understand intent, as opposed to past actions, you can start to deliver predictive customer experiences and look forward instead of backward.

How can we help you?

The only true indication of a successful customer experience is whether you helped the customer do what they needed to do in a quick, intuitive, and helpful way? Did you make their day easier or answer their question?

The more you remove friction from the customer experience, the more likely those customers are to return and want to engage with you again.

Measuring the Redefined Customer Journey

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Infinity Diagram_Layer5_Metrics

“You can’t manage it if you don’t measure it,” has been a business cliché for decades. It’s not a sentiment everyone agrees with, as not everything worthwhile can be measured; but measurements can provide useful insights to trends and behavior patterns. So how does measurement (or lack of it) relate to the redefined customer journey I’ve been blogging about over the last few months?

So far we’ve looked at four different aspects of the customer journey: the customer perspective, company activities, departments, and the systems involved.

The final level examines the means to measure and manage the return on the investment in a continuous customer engagement strategy by linking various key performance indicator (KPI) metrics to different stages of the engagement.

Typical measurements used in the various stages of the customer journey include KPIs such as:

Net Promoter Score: NPS is calculated based on responses to a single question: How likely is it that you would recommend our company/product/service to a friend or colleague? The scoring for this answer is most often based on a 0 to 10 scale

Revenue: The income that a business has from its normal business activities, usually from the sale of goods and services to customers

Total Cost of Ownership: TCO is usually a summation of the total cost of acquisition and operating costs plus any costs related to replacement or upgrades to a product at the end of its useful life

Return Rate: Usually expressed as a percentage of the number of products sold that are returned

Call Resolution Time: Within a support group, this measures the elapsed time between a customer reporting a problem and the issue being reported as being resolved. Most support groups have target resolution times to meet, and the duration of those target may vary depending on the customer’s status

Churn: Measures the proportion of contractual customers or subscribers who leave a supplier during a given time period. It is a possible indicator of customer dissatisfaction or issues with the overall customer experience

Likes / Impressions: Usually a collection of Web and Social Media metrics such as page views, followers, and the number of posts that receive comments, likes, or are shared online. All of which contribute to an overall Brand Equity, or a measure of how the overall brand, its promise, products, and experience are perceived

This is not an exhaustive list above, you may be using other ways to measure and manage customer interactions. Yet whatever measurements are used they tend to be the indicator of success (or failure) for individual operational departments or groups, and rarely, if ever, looked at in a holistic way to provide and overall measurement of customer satisfaction. It’s possible that you could be scoring highly in specific categories, yet still deliver a poor overall customer experience due to a disconnected journey.

By looking at customer related metrics as part of an overall ecosystem rather than separate KPIs it allows you to develop a clearer picture of a customer’s overall journey and their lifecycle value.