Activating Value in Digital Analytics
Digital analytics is a core part of any savvy business. Despite the growth in maturity of platforms and the differentiation between product, web and experience analytics, there is still a huge challenge in two areas: identifying meaningful opportunities for businesses and translating behaviour into customer insight. With the speed of innovation in the digital analytics field, trying to bridge these problems makes it an incredibly exciting time to be in data – or anywhere for that matter!
For any businesses with the goal of continuous growth, it's critical to understand the changing needs of customers and where gaps exist in meeting those needs within digital environments. Companies that are investing in digital analytics are those that see a digitally transformed future, one where we need a modern understanding of analytics to be successful.
Over the next few minutes, we’ll cover the role of digital analytics in a modern digital business.
This series will also examine digital experience analytics and a model-based approach to improving digital analytics across teams.
The Role of Digital Analytics
Since the acceleration of digital transformation, you’d think that digital analytics would be a core capability invested in as part of any transformation. That’s not the case. Instead, the pace of change in digital analytics means that businesses are left holding older models of digital analytics, less sure of where it fits in the agenda.
The role of digital analytics is clear: to uncover opportunity for the business to capitalise upon.
This clear mission carries a lot of complexity, especially in adapting the traditional ‘business intelligence’ models of insight to digital and in the depth of analytics around identifying needs and wants of customers.
That sounds simple enough, but the path a business takes to develop a mature digital analytics practice isn’t all that easy. We’ve found, though, if businesses answer these three questions, the path ahead is clearer.
1. What data do I have?
Just like analytics of any sort, digital analytics starts with a question: what data do I have?
When examining the main digital channels brands and customers use and mapping across what information is available, businesses can identify gaps in what data is being captured.
The most commonly used digital channels, in aggregate, with the types of data that businesses expect to be able to use relating to them. There’s lots more, so this is taking an 80/20 view.
This snapshot provides us with a view of the core parts of digital customer journeys, as well as defines where data exists to be leveraged. It’s rare to have an organisation that doesn’t have some version of data from each of these five sources. In most cases where digital analytics is still maturing, the biggest difference is in how connected the data from these sources is.
Connectivity is critical, and there are lots of vendors and articles describing how tools can connect, integrate or otherwise organise your digital data – so we won’t spend more time on that here.
Additionally, businesses need to make the data they do have work for them. That means working with experts to help ask the questions that can be answered now, and integrating the answers into your decision making processes. Many businesses struggle here – and have far more data than they can unlock. When not sure about what type of data exists, it’s always worth exploring simply to check if value is being left on the table.
Between the digital channels most businesses are involved in, a lot of data exists. At the same time, savvy data-minded teams are considering how they can capture data that will help them even more.
2. How can I capture more, higher value data?
Let’s start with a truth: it is difficult to talk about digital analytics and data capture without talking about specific technologies! You’re probably already used to the short-hand of using vendors in place of types of data – for example ‘Google Analytics’ instead of ‘our website data’.
An appreciation can be seen for the breadth of data coverage, by examining the same digital channels through the technologies we use to collect and examine data.
This diagram shows a micro-view of technologies that capture available data from these primary digital channels. Technology logos are shown higher or lower based on the depth and richness of data captured in that channel. Feel free to PM us your opinions on our ratings.
This view of digital analytics shows two things:
In order to capture more data, a business needs to critically examine the options for where they are missing data – a new app, online customer portal or eCommerce domain – and what technology is best suited to capture data in this way. Probably the most common example would be developing a new website.
Most companies already have Google or Adobe Analytics on their website, so probably assume that once they launch a new website, they’ll re-implement that same analytics solution. Some good questions to ask before defaulting to that option are:
That’s not to say that businesses need to be continually evaluating and rotating technology suites. Most purchases of this sort are strategic, and not prone to quick change. Instead, for businesses where the current suite isn’t going to change anytime soon, consider a few tips on how to improve data quality and value.
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Continually asking whether the data being collecting in your digital journeys is robust, complete and high quality will ensure that you’re finding a technology solution set that gives you greatest coverage of the customer journey, with enough depth to find insight that drives value.
3. How can I increase the speed to insight?
Lots of businesses already have comprehensive coverage and depth to digital data. With all the information being gathered, these businesses can optimise digital operations and craft incredible customer experiences with ease. Or are they?
Having data is brilliant. Making something of it and deriving insight that fosters better decisions is a different ballgame.
As data and analytics teams everywhere will attest, there is a specific skill set required to interrogate complex data and to identify noteworthy patterns, trends and features. That skill set is not purely technical – a very strong understanding of the needs of the business and characteristics of the data is also required. Jumping from life insurance data to digital advertising data is a big change!
Any organisation who has even one person who can balance all of these skills should consider themselves lucky and it’s a guarantee that person is being overwhelmed by requests from all angles. Businesses who have been succeeding in utilising analytics data well have been able to make investments in 3 areas:
Automating Reporting and Insight
Most businesses focus on automating reporting dashboards. After all, they are easy to share, easily accessed and (usually) visually compelling.
At Drumline, we’ve invested our energy into automating insight. For us, this means using the domain knowledge of subject matter and industry experts to be built into tools that allow us to identify the highest value elements of regular reports, deep dives and bespoke analyses, and to call out recommended actions immediately.
While more effortful to craft, this approach provides a significantly more scalable way of moving from data collection to action, and it prompts a discussion immediately rather than simply having another unequally interpreted dashboard.
Embracing a data-driven culture
Many others have offered thoughts about building and maintaining a data driven culture, so we’ll keep it short.
Fundamentally, this means that everyone involved in the value chain of data-to-decision understands they play a valuable role: as a data creator, data consumer or both. Appreciating the importance of their role, and the power wielded for decision making allows ‘non-technical stakeholders’ to value how they interact with and use data.
So let’s be democratic.
Embedding tools that democratise data
Tools that provide users with the ability to answer questions easily or allow users with different backgrounds to gain insight collectively allow ownership and accountability of data-based decisions across a business.
Tools like ThoughtSpot do this by using natural language processing that allows business users to write ‘queries’ as a normal question.
Tableau, PowerBI, Datorama and Google Data studio provide easy data visualisation for across a broad group of stakeholders.
Technologies like Google Analytics, Amplitude or Mixpanel deliver functionality that is broadly applicable across many stakeholders and teams in an organisation. This wide applicability results in a broader set of stakeholders seeing value by finding their own insight.
Summary: The Role of Digital Analytics
The role of digital analytics seems simple – and as with all things worth doing, there’s a lot under the surface.
To support uncovering business and customer opportunity, digital analytics functions look to address these three questions:
These needs are persistent. Though with the expanding capabilities of new technology, answering these questions is getting easier. One of the most significant boons is Digital Experience Analytics, and it provides new answers to old problems. This is explored in greater depth in Part 2 of this series.
If your business is unsure about the pain points customers have, or wanting to map the whole customer journey, consider:
If the answers aren’t clear, it’s time to figure those out. After all, improvement only comes from an honest assessment of the current state.
Evan Rollins is the co-founder of Drumline Digital, a digital partner committed to scaling personalisation for growth, activation and lifetime value. Evan loves data, and believes that what we do tells other people about us more than what we say. He's passionate about finding new ways of using data easier, faster and more effectively to make the lives of customers better, and help businesses make smarter decisions.