A provocative title perhaps, but we all know that the digital landscape has changed out of all recognition over the past few years. The web has shifted from the “web of things” (the content web) to the “web of people” (the social web). As a result we’ve seen the proliferation of acquisition and media channels with Facebook, Twitter, and YouTube figuring alongside the more “traditional” digital channels of search, affiliated, and display. The way we access the web has changed from relatively static devices accessing it on an infrequent basis to an “always-on” mobile experience.
As consumers, our digital lives have become richer, but as marketers, our digital lives have become far more complex. My ability to access content and services over multiple devices makes it harder for organizations I interact with to understand and manage that experience or to evaluate the return on their marketing investment in me.
I’ve always believed that in digital analytics we are on a journey. That journey involves three main phases of performance tracking, process optimization, and customer centricity. In the first phase we’re trying to get the numbers right. In the process optimization phase we’re trying to improve our business processes. And customer centricity is where we focus on the customer rather than just the channel. You can see a fuller description of the journey in a previous column. Since I first formulated that framework, the landscape has evolved in the ways that I described earlier, and being customer-centric is now not just about joining up the web channel with the offline channel, but having that holistic view across all digital channels as well as offline channels. The ability to understand a user’s interactions across all digital touch points and channels is what is meant by “digital customer intelligence.”
At a recent conference here in the U.K., I co-presented with one of our customers who is a good example of the journey I describe above. I’ve worked with this customer for over five years in a variety of different consultative positions. This has enabled me to see their evolution over a period of time. Their early days were all about establishing a coherent digital measurement capability. This meant getting the right systems in, and configuring them properly to produce the metrics and insight needed to run the business properly. This in turn meant investing in people, and gradually the digital analytics team grew from a team of one to six people today, which is pretty good by European standards.
As the tracking and reporting capabilities were bedded into the business, the team started to focus on optimization activities. They systematically reviewed every part of the acquisition and conversion process across their multiple products. They used techniques such as campaign attribution and multivariate testing to drive down costs and improve ROI. They were able to tune the fixed web channel to such an extent that they became one of the best in class within their sector according to independent benchmarking studies. They even started to look at joining their web data to their call center data to understand multi-channel journeys.
Then mobile usage started to take off. Within their sector mobile usage had a slow start, but then it expanded rapidly over the course of 12 months or so to the point where the team needed to start to look at it in some detail to understand what was going on. What they found was mixed. By looking at the demographics of people using mobile devices in their customer journey, they discovered that they were able to reach and appeal to people outside of their traditional customer profile. However, they also discovered that a significant number of mobile device users were having a poor experience and so were abandoning their journey or having to deflect back into the fixed web channel or the contact center. So having spent time tuning the fixed web channel, they needed to start going through the tracking and optimization phases on the mobile device channels to deliver the same level of user experience there as well and to provide a seamless integration of the two.
The customer is now in the early stages of digital customer intelligence. A primary focus is on understanding customer interactions across all channels across the total lifetime of that customer. While ensuring they don’t drop the ball in terms of making sure that the individual digital channels remain well-optimized, they’re looking to understand how a digital visitor’s relationship develops with the business over time from anonymous user to prospect to customer, across all devices and channels. They’re bringing together data from different systems to understand the relationships between the channels they use to acquire prospects and the channels that those prospects choose to use to become customers. That integrated data gives them the ability to understand the value of the customer relationship over time in the context of their digital acquisition strategies.
This story is by no means unique; a number of companies are pushing the boundaries of digital analytics and are actively doing many of the things that I’ve described above. What’s interesting is that this story is still relatively rare and that this company is not some huge global business with masses of resources at its disposal. They’re a significant player in their sector for sure, but also one that has invested in an analytics team and has created the environment to allow it to create business impact.
I might have exaggerated at the beginning. I don’t think that web analytics is necessarily dead, but it does depend on what is meant by that term. If by “web analytics” we mean aggregated reporting of activity across different digital channels with that data sitting in siloes, then I think it increasingly has a limited shelf life. If by “web analytics” we mean the collection of data on interactions across different digital channels and devices and having that in an accessible format, then it’s going to be a fundamental component of your digital customer intelligence capability going forward.
Digital Intelligence image on home page via Shutterstock.
This column was originally published on November 1, 2012.
The use of psychology in marketing and sales is not new, but it may be more useful than ever in an attention economy where time is precious and focus is rare. How can you tap into a demanding consumer to check whether there is an actual interest in your product?
According to a survey conducted as part of OnBrand Magazine's State of Branding Report 2017, marketers are well aware of the new technologies that are expected to be important to their brands in coming years, but the majority aren't rushing to invest in them before they're fully-baked.
Two weeks ago, Foursquare announced what could be the most important component of its data business: the Pilgrim SDK. So what does it do, and what does it mean for location-based marketing?
Combining clickstream data with machine-learning technology, behavioral analytics helps enterprises create a tailored online experience for each visitor to their web or mobile sites.