Over the past few decades, web analytics has evolved from a discipline reserved for web pioneers to a now widespread practice and vital source of customer data for companies of all sizes. A continuously developing field, it has expanded and accelerated right alongside the digital world it serves to measure. And Neil Mason has seen it all from the start.
As a Digital Transformation Lead at Accenture Digital and Director Emeritus of the Digital Analytics Association, Neil has spent his entire career as an analyst, from the early days of the Internet to today’s multi-device, multi-channel context. At our last Digital Analytics Forum event, Neil shared his vision of the digital analytics sector’s journey from 1.0 to 4.0. Keep reading for his take on what it means for today’s (and tomorrow’s) digital analysts.
Set your time machine dial back a few decades. Imagine an era when digital data was scarce and largely unavailable. Analysts had to rely on offline data to understand consumer behaviour, as online activity was rare, and rarer still was any digital data resulting from these interactions.
These were the days of what Neil calls digital analytics 1.0. Data came from just one channel – the web – and only one type of tool was available to measure that data: web analytics tools (such as AT Internet’s solution. We look good for our age, but we were around even back then!).
“The data was sparse, the technology was also very rudimentary, so we placed a lot of focus on trying to extract as much value from the data as we possibly could to help [clients] understand the world they were operating in and the decisions they had to take,” Neil remembers. These constraints ultimately helped shape the way he approached analytics over the course of his career, with a focus on drawing actionable value from the numbers.
During this era, the analyst’s role was that of technician whose time was mostly spent working with the tools and handling data, rather than interpreting the larger picture of customer behaviour and understanding how all the data fit together, Neil recalls.
“I knew I was in trouble when one day it took over 25 hours to process the previous 24 hours of data,” he remembers with a laugh. “Something had to change. Luckily, the technologies began to evolve.”
An ecosystem emerges, data booms and blooms
Fast forward to a few years later, when an array of digital measurement and optimisation tools begin to appear, such as solutions for A/B testing, multivariate testing and VoC.
“We begin to develop an ecosystem around our analytics, but it’s still focused on one channel: the web,” explains Neil. This is digital analytics 2.0: As analytics capabilities become more sophisticated and data becomes richer, analysts have a role of reporter. They begin considering how to make this information easier to visualise, digest and interpret for others.
This era soon gives way to the current one, digital analytics 3.0, which is marked by a true “proliferation” of analytics, says Neil: Digital channels, user devices and customer touchpoints all multiply, creating an explosion of data. “Web analytics” expands to “digital analytics” as it becomes necessary to measure and understand user behaviour across a combination of channel interactions and devices used. The analyst’s role is no longer just about reporting web data – it involves analysing multiple data sources, leveraging more sophisticated technologies, and weaving impactful stories from the numbers.
“Digital analytics 3.0 is a fragmented, complicated world, but the tools are now enabling us to tame the data and begin to deliver on the promise of what digital analytics has always been about – understanding how people interact, how they use our products and services, and how we can better serve them by delivering better user and customer experiences,” says Neil.
But as the pace accelerates with AI and machine learning, many of us can feel it: Change is on the horizon. We’re on the cusp of digital analytics 4.0.
Digital analytics of tomorrow
To understand what digital analytics 4.0 is all about, it’s important to examine what’s happening on both the “digital” and “analytics” fronts, says Neil.
On the “digital” front, we’ve of course gone beyond simple “online web” interactions to new types of experiences (with interface-less voice assistants or wearables, for example) that take place continuously. Even the “offline” physical world is becoming increasingly digital (think “phygitalisation” of brick-and-mortar stores and the merging of the online-offline customer experience), leading to even more data on the user’s cross-channel journey.
“New categories of analytics are starting to emerge that weren’t there three, four or five years ago. In-store analytics is a good example of that,” notes Neil. “The kinds of data produced by these technologies seem quite familiar: heatmap of a store, path analysis, peak visit rates, storefront conversion rates… Sound familiar?”
On the “analytics” front, Neil cites the shift from descriptive digital analytics to predictive analytics, or rather the merging of the two. “These worlds are coming together. Predictive capabilities are being embedded into digital analytics technologies, and that is great news. I think that will only continue,” he adds, explaining that AI, data science and machine learning technology will continue to propel this evolution even further toward prescriptive analytics which give recommendations and guidance. “This has real implications for us as an industry,” he notes.
So moving into the era of digital analytics 4.0 means moving into a world where digital data is constantly being collected everywhere, whether we’re on a website or app, using connected devices or sensors, or visiting a physical store location. And it means doing even more with this data thanks to advanced analytics and AI-powered recommendations.
But what does it really mean for digital analysts?
“We need to think about how we’ll add value in a world where lots of the actual production is done by machines,” Neil reflects. “I think it’s a real opportunity and will go in one of two broad directions: Analysts will either become architects, designing or building the machines that do the work, or we’ll become storytellers.”
He underscores that the role of digital analyst will no longer be confined to analysing data, extracting insights and making recommendations to stakeholders, as the technology will perform this automatically.
For Neil, being a digital analyst in the 4.0 era will mean using data-driven insights to create real change within your organisation. And an effective way of doing this is via storytelling and crafting a compelling narrative that convinces people to do things differently.
“Stories are important because people remember them and are engaged by them. And most importantly, stories persuade people,” says Neil. “By adding the emotional human intelligence to the artificial intelligence, we can really help people think about the best course of action.”
And where does Neil see himself in digital analytics 4.0?
“For me personally, it’s too late to learn how to code… so I’m going to reflect more on how to be a better storyteller.”
Many thanks to Neil Mason for his contributions to this article.