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The Single Customer View (SCV) has always been a challenging term for me. It’s shown such reverence, and is bounded around so often in our industry, that it feels almost religious.
It exists everywhere, it is discussed in almost every client meeting, and everyone holds to the same ideology – that although they haven’t built it, or seen it applied, the single customer view is out there somewhere, and once you find it, enlightenment will surely follow.
Being an agnostic by nature, I neither inherently believed, nor disbelieved in the Single Customer View. But I was curious to investigate further, and so began asking my clients and peers “what do you mean by a single customer view”.
Unfortunately, I was left disappointed as the responses I heard all seemed to be somewhat lacking in substance or applicability, and were all peppered with terms like “holistic” and “360-degree” (not that there is anything wrong with using these terms, but when there are more buzzwords than actual words in a definition, you begin to wonder).
So, dissatisfied as I was with the conventional wisdom on the subject, I decided to dig a little deeper into the origins of the single customer view, and to track its evolution.
The Old Testament
Like so many of the concepts found in data-driven advertising today, the single customer view owes its widespread recognition to Customer Relationship Management.
When the Single Customer View first came onto the scene, it was described as a method through which you could understand and acknowledge active interactions that a known customer had had with your business, to ensure consistency in service, continuity in message, tonality and narrative, and a more seamless overall experience.
For instance, if a customer purchases a product in-store, begins a complaint online, and then picks up the telephone to call a customer complaints line, the Single Customer View aims to provide as much information to the customer services team as possible, arming them with the product purchased, the location of the store, the value of the product, the original online complaint, and any steps that have already been put in place to manage the customer’s query. That way, the customer services representative doesn’t need to trawl through the (already frustrated) customer’s experience so far, instead they are able to pick up the discussion from that point, and move forwards.
We still see much of this original Single Customer View today, referred to mostly in omni-channel marketing, marketing automation and marketing orchestration. It is principally first-party data driven, it relies almost exclusively on an ability to identify and unify known customer records, and manifests itself mostly in customer service, lead generation, churn mitigation, upsell and renewal.
As the adtech and martech worlds collided, the known and unknown universes drew closer together through the application of identity management, onboarding solutions and device graphing, and the original definition of the Single Customer View began to stretch. The SCV that had once only existed in CRM and had only taken active customer engagement (purchase, transaction, form submission etc.) into consideration, began to expand into the broader digital economy. Now brands could take into consideration more passive action across owned, earned and paid channels, for instance website and app visitation and digital media exposure/engagement. What’s more, they could start to link 2nd and 3rd party derived characteristics, such as socio-demographic information, content consumption and other web browsing activity, to their customer record.
This led to a major change in mind-set around the SCV, no longer merely a functional tool to better manage customer communication and maintain a consistent “voice” with those customers that were known and active, now the single customer view could be used to derive insights on the profile of the customer, identifying trends in the way in which consumers engage with owned and operated properties, high-level deviations in age, gender, income, and content consumption.
The New Testament
The explosion and fragmentation of audience data across the digital and non-digital ecosystem, from location, to web browsing, to mobile, to psychographic, to sociodemographic and so on, has led to the newer descriptions of the SCV focussing towards unification of different, isolated audience signals. In fact, the latest iteration of the Single Customer View has become synonymous with simply knowing as much about an individual user, or group of users, given as many linked 1st, 2nd and 3rd party data sets as possible.
This has inevitably led to the Single Customer View being viewed more within the context of audience profiling, composition analysis and persona creation. The SCV, viewed through this lens is directed towards identifying target audiences by highlighting significant skews within the “average” profile. It’s about being able to demonstrate that the average profile is, for instance; male, age 18-34, interested in technology, and frequents Costa, more than Starbucks.
Note the subtle change in terminology. We’re now no longer referring to customers as much as we’re referring to “profiles”, “users” and “audiences”. That’s because in this latest iteration, being an active, known customer is no longer a pre-requisite to building the Single Customer View. In fact, there is no requirement to use 1st party data sets at all in this iteration. For instance, a CPG brand, that has very little 1st party customer data, may work with market-research firms to establish a “base” through claimed behaviour and attitudinal statements, producing the SCV on the back of this information. Or a Fast-Serve restaurant, which has a limited customer data set, may develop its “base” through 3rd party location-based data segmentation, looking at those individuals that regularly visit its restaurants.
The Old Meets the New
So, is it possible to connect the two versions of the Single Customer View that I outlined above?
The answer is yes, in theory. Identifying known, active customers, and linking those customer records to digital identities that can be synchronised across different audience data sets for insight generation, and for informing a consistent, relevant conversations with the customer, is possible.
However, the practical reality of making deterministic bridges in identity, and merging profiles across the data ecosystem is complex and every link made between data sets sacrifices scale. Although Onboarding Vendors, Customer Data Platforms, Device Graphing Vendors, and Data Management Platforms have made the Single Customer View more accessible, it’s still one of the major challenges facing brands today, and It’s rarely executed effectively.
Although across its many iterations, the Single Customer View has managed to maintain a purist narrative, in short describing an ability to link data sets, unify the known and unknown for the purpose of deriving insight and informing communication along the customer journey. In my view, there isn’t one definition of the Single Customer View. For me, the SCV exists on a spectrum, ranging from the original approach of using known and active customer data to maintain consistency in communication, to the modern, “connected data” approach to audience profile analysis.
The two ends of the spectrum are vastly different, and their application within media and marketing are worlds apart. The need to clarify the brand’s definition of the Single Customer View, therefore, has never been more important. Neither has the need to establish the ultimate objective(s) behind the creation and application of the SCV.
To many see the SCV as the ultimate end point, however, in neither of the approaches outlined above is that the case. The SCV is always a means to an end, not the end in and of itself. We should all be able to clearly articulate the “why” behind the development of the Single Customer View, beyond simply a better understanding of our customers or audience targets. That’s a starting point, not the destination.
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