Q: What is the current state of digital analytics in the enterprise?
Dave Edelman: Companies are at different stages of maturity in their use of digital analytics. The most advanced are able to do fairly sophisticated attribution analyses where they can look at a number of interactions and weigh their contribution to an outcome. They can chop down their data to look at interactions on an individual customer level, and can have excellent data on the quality of the interactions they’re having.
But even those companies are finding it hard to stay abreast as new channels are added: things like mobile and other kinds of sensors such as social data and text. As new interactions can be captured, it’s becoming more fragmented. It’s an area where the growth and scope never stops, and it’s become a difficult challenge of integrating and using it to tell a story of a coherent journey.
More basic companies are at an even earlier stage of setting up analytics systems that can accurately track what’s going on. A lot of the challenge of analytics is bringing discipline to the data, to your processes, to your technology – and for everybody to have a critical sense of focus.
Andrew Dennis: A few facts: there is 100% enterprise adoption for digital marketing analytics and all enterprise digital program asset activity is being recorded. So, there is no lack of data. However, the inherent measurability of digital programs is both a blessing and a curse to marketers and their organizations. Specifically, just because everything is measurable in digital marketing doesn’t mean that everything is worth measuring. The incredible volumes of available data hold tremendous potential to improve an organization’s digital marketing programs, but, more commonly, serve to overwhelm and distract its digital marketers and leadership.
We have seen a small group of leading marketing organizations evolve from activity-centric web and digital marketing analysis to true business-oriented program measurement. Many others will soon follow their path.
Q: How can marketing teams tap more of their digital analytics potential?
Dave Edelman: Marketing teams need to focus on pointing their technology, tools and data toward supporting the analysis of initiatives they want to take to market. An example of this is a bank that was trying to dramatically scale the acquisition of new customers. There were many places where a customer could fall out of the funnel: they could come in through search, land on a page, look at products, then start an application, then fall out of that application. If there’s a credit product, they might not get adequate credit. It’s a whole cycle of a journey where it can be incredibly illuminating to point analytics toward understanding where are the fall-off points for which segments of customers coming in through which sources. The more you’re pointing analytics toward understanding key journeys, the more practical you can be.
Too often, enterprise digital teams are broadly trying to upgrade analytics, bringing on new technologies and building massive data lakes. The challenge is, it takes forever to establish foundational capabilities versus starting in a more focused way against a specific set of goals, seeing what you can get out of the systems you have and then expanding. Usually having that kind of short-term iterative impact is going to turbocharge the organization faster, show the proof of concept and then unlock the funding for investments you might need.
Andrew Dennis: Marketing teams can start by building on the simple truth that for every digital marketing effect, there are clearly identifiable causes. In many cases, digital marketing is a cause-and- effect medium where actions are taken and the corresponding results are quickly known. The best of the best tie intelligent experimentation to clear analytics, mastering performance improvement and gaining key knowledge and experience. They spend as much time discerning why something happened as they do reporting on what happened.
An example of this is a $7B office retail supplier that invested in a focused initiative to detect root causes and drivers of current KPI performance. Identifying and then implementing 22 specific e-commerce enhancements over 30 days, the retailer saw an 18 percent lift in conversion rates, and a 4 percent average order increase. Further, they took a second of load time off over three million product pages, which helped bring down the site abandonment rate by 12 percent. It was that deeper examination of the “why” behind the analytics data, coupled with a focus on what to do about it, that helped them to achieve breakout success.
Q: What’s changing the most or most rapidly in digital analytics?
Dave Edelman: What’s changing most rapidly in digital analytics is the sophistication of the tools. The technology is way ahead of marketers’ ability to use it. A fellow CMO stepped back and said, in order to execute certain kinds of use cases, they need to get the connectors in place and carve a pathway through their technology architecture. For example, to do something simple like trigger-based retargeting of visitors who hit their site and abandon, the digital team asked, ‘What is the pathway of tools we will use to get that done and be able to measure it on the back end?’ For about 15 different of these use cases, they created standard pathways through the tools to set up, run, measure and optimize what they’re doing. There’s new visualization capability in many of these tools so that you can see exceptions and what’s important, and actually tie red, yellow, greens to the campaigns that you’re running. That’s making it a lot easier to use these tools to make fast decisions.
I think one of the most exciting areas in digital analytics is the ability to go beyond clicks and analyze words that people say, words that people type, to be able to bring new insights to how people interact, what they see, what they do, what they say. That can be exciting from a social media perspective to understand the most important attributes that people talk about when looking at this car versus that car in social media, for example. So there are some interesting areas now as we get into some of the community aspects, some of the video aspects of digital analytics that are new areas for marketers.
Andrew Dennis: I’ll highlight two significant changes. First, marketers’ digital perspectives are rapidly changing. Specifically, effective digital marketing teams are taking more of a “radar” than “mirror” digital perspective – meaning that they are studying the market as much or more than they are studying themselves. This shift in perspective leads to rapid learning – leveraging innovation and proof-driven digital tactics – that would slowly or never form within most marketing organizations.
Second, there is incredible growth in the levels of investment and focus in mobile analytics – albeit largely in “catch up” mode. According to Google, more than 50 percent of search queries now come from mobile devices. While reaching this mobile tipping point didn’t happen overnight, driving mobile conversions and enabling mobile journeys is not a simple extension of web capabilities and analytics.
Q: What’s on the horizon for digital analytics in the enterprise?
Dave Edelman: We’re starting to see two areas on the horizon. One of them is much more sophisticated decision-making capabilities. Looking across the ever growing range of touchpoints that people have with a brand, whether it’s through mobile, for example, based on previous actions, new “decisioning” engines are an important capability helping marketers to strip away the complexity and manage the next best action in a way that’s as personalized as possible.
For example, a fast food company can anticipate as you walk by their franchise on your way to work at your usual time, that you may want to order the thing you regularly order so it pops up on your screen. But if you’re traveling and you’re not in your usual place, they know the time of day that it is, they know what you generally order, they know that there’s one of their franchises within two blocks of where you are, and they send a different kind of message and allow you to set up your order with just one touch. That kind of decision management looks at who you are and manages your context. It tests, learns and optimizes over time. That’s something that we’re seeing more companies adopting as an important part of their arsenal.
The second area is the Internet of Things and being able to bring back more data, not just about what people buy but how they use and interact with things over time. More companies as they move from just the transaction where they sell you something to actually selling what in essence may be more of a service requires another level of digital analytics, especially for companies that are building in new kinds of software into their products.
Andrew Dennis: Three things. The first is prescriptive analytics. Marketing executives continually plead, ‘Can this analytics thing just tell me what to do – where to invest, why, and how to improve?’ Intelligent, data-driven guidance through prescriptive analytics is approaching rapidly.
Number two is a deeper understanding of industry-specific analytics. The depths and richness of the differences between industries, specifically, the audience you’re targeting, the digital objectives, the levels and types of digitally-impacted revenue – these vary greatly across industry segments. Diving deeply into the industry-specific nuances and performance drivers is like advancing to new depths of exploration in the ocean.
Finally, and a bit under the radar, we see movement on the outsourcing of digital analytics. This is driven by the complexity and importance of digital analytics – along with the challenge of building and maintaining an effective analytics function. The rise of competent analytics service providers has certain marketing executives weighing their options and listening to vendor pitches on the value and risk/reward scenarios of analytics as a service. Tapping into a shared core of best-in- class analytics systems, knowledge and resources is increasingly viable and appealing.