How to turn customer data into customer intelligence
“What am I supposed to do with all this data?”
It’s a simple question we marketers ask ourselves almost daily. We collect huge volumes of data on how customers interact with our websites, content, social handles, and even with third party platforms, not to mention our products and services themselves, which makes the prospect of managing all this information increasingly daunting.
One of the biggest challenges for brands is to bring context to all their data, especially because it comes from so many different sources in so many different formats. This is the key to drawing out the insights companies need to create personalised experiences at scale, a goal that still feels out of reach for many marketers.
There’s a reason why it’s become so difficult to measure the effectiveness of a campaign, why more than one-third of banner ads in Europe weren’t even seen last quarter, and why we still find ourselves getting targeted with recommendations for products we’ve already bought. Brands spend more than ever on digital advertising, but a large percentage of their investment is going to waste.
Instead of delivering personalisation at scale, companies are relying on minimal data and rudimentary targeting to segment audiences. The difficulty is that a single customer is not just a single touch point. Their digital persona includes a large, complex, and constantly-shifting web of activity and interactions. And while this gives brands more opportunities to reach their audience, it also means they need to cut through more noise and degrees of separation to engage the right people or build a loyal following.
Which brings us to the distinction between customer data and customer intelligence. Customer data is an asset, the fuel brands feed into their analytics to better understand their audience. Customer intelligence is the insight they draw from this data, enhanced by the all-important context that makes this insight accurate and relevant.
Horst Stipp, EVP of research and innovation at America’s Advertising Research Foundation (ARF) said in a recent paper: “Advertisers have been quite successful with endemic alignments, such as commercials featuring an athlete shown during a football game or food advertisements on a cooking website”, adding that “Aligning ads with content can boost advertisement performance significantly and diminish advertisement avoidance”.
In other words, the context a message is delivered, along with your historic understanding of the customer’s needs and behaviours can help determine whether someone will engage with it, so make sure your creative approach and content are informed by a solid understanding of what your audience wants.
To gain this understanding, brands need to rethink the way they develop customer profiles. In many companies, individual departments still create their own profiles in siloes based on the limited of range of data they have access to. This one dimensional approach might seem logical to a team tasked with meeting a specific set of KPIs, but nothing could be further from the truth. Every department ultimately wants the same thing, which is to help drive sales, and the idea that disjointed strategies will motivate customers to engage with your content and make a purchase is fundamentally flawed.
Encouragingly, we’re seeing more companies come around to change and moving away from superficial KPIs like impressions, which do little to drive value. Seeing such a high percentage of their adverts go unnoticed has made it clear that a siloed approach to content and customer data is no longer fit for purpose.
Leading brands are now bridging the barriers that have traditionally kept their teams isolated and unifying all their data onto a single, unified platform. With every department working off a complete profile that takes into account all relevant data about each customer, companies have all the context they need to deliver highly-targeted experiences that resonate and drive real engagement.
What does this look like in practice?
Let’s begin with the travel industry, where changing customer habits have completely reshaped the process of planning trips and booking holiday experiences. This is the fast-moving environment in which Hostelworld operates, a company that continues to enjoy a loyal following but whose young tech-savvy audience is constantly looking for more personalised, more convenient digital experiences.
To keep up, Hostelworld realised it needs to collect, analyse and act on customer data in real-time, which is why it implemented Adobe Analytics as the foundation of its digital marketing strategy. With a real-time view of how people engage with its digital properties, the company has taken its understanding to a whole new level and seen a 500% increase in engagement for its digital communications.
The world of B2B advertising is evolving just as quickly as the consumer space. In fact, because B2B businesses often need to serve a two-tiered customer base of both direct buyers (i.e. procurement managers) and end-users, one could argue their job is more challenging. These brands must find a way to target two different groups who have vastly different priorities and speak with them in different languages, all while showing a consistent face for their brand.
This was the challenge facing RS Components, the world’s largest electronics distributor. To quote Head of Digital Insight, Andrew Morris, the company has to “look at the wider customer base rather than individuals, which is very different compared to a B2C environment. When you also factor in the need to engage with them in different languages, and the changing landscape of our market, which is attracting competition from established B2C online retailers, marketing becomes very complex.”
The answer for RS components was to gain a deeper understanding of its digital data and take control of its customer analytics, which began with the implementation of an analysis workspace. The workspace provides teams across the business with a place where they can share and analyse data collected throughout the customer journey. This gives stakeholders a 360-degree view of each customer across every digital channel and, crucially, makes it easy for teams to share insights that will help them develop more impactful and relevant content.
The next frontier for customer understanding is Artificial Intelligence. Our recent Digital Trends report with Econsultancy found that 28% of brands are already using AI and a further 29% plan to do so by the end of 2018. The technology promises to bring even more context to data analytics, stripping away many of the challenges companies face around attribution and mass personalisation, while also bringing an added layer of security to their data management. In essence, AI allows brands to bake customer intelligence directly into the systems they use to understand their audience.
Reverting back to our initial question – “What am I supposed to do with all this data?” – the answer is simple enough. Organise this information, remove any irrelevant data, and extract the golden insights that will help you understand exactly what customers want. Then deliver on those expectations.
The premise is straightforward enough, but the digital advertising ecosystem is not. With so many touch points to serve and such a dispersed target audience, it would be simplistic to call this an easy job, especially for brands that continue to keep their teams and data in siloes. If there is one thing to learn from brands like Hostelworld, RS Components, and other established players continuing to dominate their market, it’s that an evolution is necessary, one that will elevate your customer data into genuine customer intelligence.
Learn how Adobe Analytics and Adobe Advertising Cloud can help you deliver more adaptable and personalised customer experiences across every channel.
And see how we’re helping brands make the most of their customer data by here.