You think you are customer-centric and data-driven. But are you really?

An interview with Stéphane Hamel.

Earlier this year, I had a chance to interview one of the most distinguished thought leaders in the field of digital analytics: Stéphane Hamel. You know him from his many innovations such as his Digital Analytics Maturity Model (DAMM) (2009) and Web Analytics Solution Profiler (WASP) (2006). Stéphane was also recognized as Most Influential Industry Contributor by the Digital Analytics Association (2013) among many other awards.

“We did big data – and didn’t complain”

Q: Stéphane, you’ve been on the job since the Web first got started and even before. Tell our readers about your journey to the forefront of digital-analytics thought leadership

A: I have been in the digital analytics space fulltime for well over 10 years, but really have been working in data-driven business for a good 30 years now. Back in the day at companies such as the Montreal Stock Exchange and many others we essentially did big data working with huge amounts of real-time data – but I don’t remember that we ever complained. It was difficult, it was complex, but we didn’t complain. It’s just what you had to do.

Then in the early 90s when the first web servers came about I remember having to convince my employer that they needed a website. And then again during the years of the Internet bubble I had to convince companies that doing analytics made sense, i.e. that a website wasn’t enough. You have to constantly measure & improve.

“Digital analytics was hijacked by marketing”

Q: How have you seen digital analytics evolve over these years?

A: Coming from the IT background I saw the time when in the late 2000s analytics was eagerly taken over by marketing and ecommerce in order to measure and optimize campaigns. But I wrote an article back then already that “web analytics has been hijacked by marketing”. Marketers saw the web as mostly a marketing channel back then as opposed to a business channel. So analytics was used narrowly for measuring campaign and shopping cart conversion rates, yet ignoring so much of what analytics should be contributing to the business.

Today, the use of analytics is much broader than just marketing and ecommerce optimization. It’s also about CRM, sales, customer support and self-service, business processes, and ultimately it should be about the customer.

“You think you are customer-centric and data-driven. Are you really?”

Q: How far along are companies with putting the customer at the heart of their analytics and their business?

A: When I speak with companies, often the conversation starts because they may have a technical concern or specific optimization in mind that they want help with. I usually then say that I know a lot about analytics but I don’t know their business, so please help me understand: “Are you customer-centric? and “Are you data-driven?”. And invariably companies will say “yeah, yeah, yeah, we are very customer and data oriented.”

But when I then ask “what are your goals and KPIs?”, or “how do you do it in order to be customer centric and data driven?” … often they don’t know what it is that they are doing. Sometimes it’s more like they heard about the notion … but there is not much more behind it unfortunately.

“Beware of blanket statements “

Q: After decades of customer-centric thinking, what’s still holding companies back?

A: Beware of those blanket statements that the Internet is awash with. For example, the “Top X things you must do for mobile immediately or you will perish.” kind of statements. What should your company’s mobile experiences be optimized for? It very much depends on your customers and your business. Analyze what your users are trying to accomplish using mobile devices and take it into account in your design and optimization.

I also see a lot of marketers chasing the next big thing. They have heard about growth hacking and now they are for example gung ho to create a viral video. But they don’t even have the basics down of what it is that they are marketing and what their business goals are.

Then people have the expectation that they can just call in a consultant and they are going to come in and magically identify the problem and the solution. It doesn’t work that way.

“The tide of expectations in analytics is rising”

Q: And why are marketers still struggling with analytics?

A: Complexity has gone up dramatically. Today’s marketers and eCommerce pros have over 2,000 MarTech solutions to choose from, all bringing different ideas and pitching to help increase their business. So the expectation in analytics have risen as a result too. Not to mention that customers now interact with you across these different MarTech solutions and on top of that also via their multiple devices.

“You can’t improve one thing by 1000% but you can improve a 1000 things by 1% and ultimately the impact will be exponential”

Q: What are the customer-centric analytics components you recommend?

A: A lot goes into being customer centric. For example, most fundamentally can customers actually reach you e.g. by email and do you reply? On Facebook do you just broadcast and brag or do you actually listen and reply?

But part of that eco-system is also to include Clicktale and understand and solve issues one experience at a time. The saying goes, “You can’t improve a single thing by 1000% but you can improve a 1000 things by 1%”. and at the end of the day the impact will be exponential.

Something like Clicktale is interesting because you can find that little thing that interferes with a customer’s experience and fix it and the effort of fixing it might be very low and fast. You can uncover opportunities for enhancement bit by bit, find glitches and improve them. You find out what it is that drives conversions by learning one customer experience at a time. You can quantify the impact via aggregated heatmaps and conversion analytics across your customers and segments.
This makes much more sense vs. throwing dollars after every supposed next big marketing thing without optimizing the experiences you have.

Many  thanks to Stéphane for your continued contribution and leadership in the analytics industry.

About Stéphane’s work today:
Stéphane Hamel is a seasoned consultant and distinguished thought leader in the field of digital analytics. He works with companies to help them assess their digital analytics maturity and take it to the next level. Stéphane also coaches agencies to help them build their own analytics centers of excellence, i.e. to “train the trainer”. Stéphane is an experienced teacher and speaker who shares his passion for digital analytics – be it technical ‘how to’ or assessing organizations’ digital capabilities and maturity.

This interview first appeared on the Clicktale blog.

The Rise and Fall of Web Analytics (and the rise of CX)

Back in the early 2000s when you went to industry conferences such as SES,, eTail, ad:tech, and of course the eMetrics Marketing Optimization Summit, the common refrain was: “web analytics — everyone should really be using them.”

The Rise

This was the time of dawn for Web analytics in terms of its use for marketing and eCommerce optimization. Back then web analytics were still a nascent niche, understood by relatively few, and used productively by even fewer.

Early on, web analytics seemed like a wondrous opportunity to learn almost everything you might ever want to know about your anonymous website visitors. So practitioners and industry analysts were telling each other that they might become the most sought after people in their companies because they know the customer better than anybody else.

So it seemed in the heydays.

Over the years, companies learned how to invest in the right people, process, and technologies to take advantage of web analytics. Today they are mainstream and nobody would doubt that they are a must-have and must-master type of analytics.

The Fall

But meanwhile web analytics had to get off its high horse.

They are now only one of multiple digital intelligence sources needed in order to navigate an online business towards success.

Web analytics are and will always be a critical controlling and management tool, especially for top level numbers. But by themselves they leave so many gaps of insight about customer behavior and interests that other, newer, more nimble and more granular analytical solutions have sprung up to fill the blanks.

The Rise of CX Analytics Providing Customer Insights that Web Analytics Can’t Provide Anymore

One such example on the rise today — and in mission critical use with the early majority of adopters — are digital customer experience (CX) analytics. CX analytics show visitors’ actual behavior and experiences on your website including their in-page interactions.

They show a-ha insights that would be hard or impossible to answer with web analytics.

Today’s experience management platforms such as ClickTale do this by adding a range of visual layers to web analytics through many types of heatmaps, replays, form analytics, and other conversion optimization insights. They provide intuitive ways to gain insight from these in integration with the rest of your ecosystem of digital analytic solutions including web analytics but also VoC, A/B testing, etc.

You see everything from where the mouse is moving within pages to how specific visitor segments are interacting with drop-down menus, accordions, shopping carts and other dynamic content.

All stuff that you don’t see from traditional web analytics unless you invested a prohibitive amount of custom tagging.

Typical CX Analytics Use Cases Filling Gaps in Web Analytics

Here are a range of business use cases where CX Analytics are mission critical for customer insights and conversion rate optimization (CRO).


  • Are there common behavior patterns and issues that cause potential buyers / registrants to drop out?
  • Are there friction points or distractions in our checkout process that we can eliminate?


  • Which form fields or error messages are tripping potential customers up?
  • What is causing hesitation to enter text or submit the form?
  • Should we make our forms shorter? More clear? How?


  • Are buyers vs. non-buyers scrolling down on our long pages and engaging with our many content sections under the fold? For example, are buyers scrolling down our entire home page to review our offering in its entirety?
  • What content within pages is actually perceived as valuable by potential customers? For example, if we have a picture vs. a video at the top of a page, how or where does that focus customers’ attention?


  • How much information is the right amount?
    • Not too much to put customers into analysis paralysis when deciding to register or purchase something.
    • Not too little to prompt buyers to research elsewhere


  • How effective are our drop down menus for helping visitors find what they are looking for?
  • Are visitors engaging with the menus? Which ones do they browse vs. ignore?
  • Should we simplify or expand our menus?
  • Should we better highlight certain options that we want more visitors to notice?


With responsive design you essentially have three websites in one. Site layout and content can change dramatically requiring dedicated analysis and optimization for each responsive design and breakpoint.

  • What are our phone, tablet, and desktop visitors experiencing on our site?
  • How can we make their experiences better?
  • What’s the best placement for links, banners, offers depending on each device and responsive breakpoint?


  • How are visitors using site search for products, articles, or customer support tips?
  • Are they using the search refiners to narrow down their search results? Which ones?
  • How can we make searching a better and more successful experience in order to increase the middle of our conversion funnel?


Today’s ever more dynamic websites often include single page applications where all the interaction happens within a single URL yet you have all kinds of modal windows to interact with or quick product views etc. It’s like a desktop experience within the browser.

  • Which logical screens are being noticed vs. ignored?
  • How can we make it easier for visitors to navigate the application and its functionality?
  • How can we increase adoption and productivity by providing greatest ease of use?


The famous bounce metric in web analytics makes little sense anymore. For example think of two visitors who both had a single page view only in their session, ie a classic bounce.   But one scrolled down extensively and read the entire page in detail in effect viewing multiple logical pages, eg your entire elevator pitch on the home page. That wasn’t a bounce at all.

  • How many visitors from our marketing campaigns are engaging vs. bouncing?
  • What experiences work for which segments?
  • Why aren’t more campaign visitors converting?


  • Is there any difference between the genders how they browse and perceive our products, checkout process, or content, e.g. price conscious vs. brand focused?
  • Any difference by demographics?
  • Tenured vs. new customers?


  • How can we avoid unnecessary customer service calls by making our self-service portal easier to use?
  • Why are customers struggling (for example think of banking bill pay, account transactions, or ability to find self-service options)?


  • Which of our self-service functions are so complex that we would be better off pro-actively encouraging customers to get help via live chat or call center?


It’s easy to see how web analytics by itself is way outside its element for answering these questions because it is focused on page views and how visitors go from page to page. But it doesnt’t answer what’s happening within the pages.

In theory you could custom tag granular detail also with your web analytics solution but that would be a prohibitive effort. In contrast, CX analytics are designed to capture the granular behavior out of the box.

That’s why CX Analytics are used hand in glove with web analytics at many of the world’s leading companies today.

But for every house-hold name enterprise that is using CX Analytics religiously as part of its digital intelligence eco-system today, there are others like them that still remain ignorant.

In my view of the adoption phase of CX Analytics, we are just now crossing the chasm from early adopters to early majority.


Geoffrey Moore's Adoption Curve

As I wrote earlier in “the Fourth Digital Analytic revolution is on!“, my prediction is that we’ll reach full majority adoption in the next 2-3 years because the business case is obvious.

And the more dynamic and more mobile the web becomes the greater the gaps in web analytics and the greater the pressures.