Over 99% of online advertising is wasted. This claim is supported by the most recent benchmark study by DoubleclickD noting that the average click through rate (CTR) is a mere 0.12 percent. Email isn’t any better. In Silverpop’s 2014 Email Marketing Benchmark study, they reported an average open rate of 20.2%. That means 80% of emails were never even opened. Of those which were opened, the CTR was 3.3%. That means, 0.0067% actually clicked through to a landing page, website or other destination. I’m no mathematician, but I think that’s less than 1 in 10,000. And that’s only talking about reaching a page. We haven’t even begun to address conversion.
Why do you think this is happening? There are many hypothesis to explain these low CTRs, but in my mind, the answer is – relevant content. It simply comes down to the experience was not relevant for the person engaged.
So how does an organization embark on developing a relevant content strategy? One must consider three elements:
1) Intention – what the customer wants to do
2) Identity – who your customer is
3) Context – the circumstances surrounding a particular moment
The combination of these three elements informs your content and your targeting. Engagement is the outcome of both working in concert. Content is both the creative; the language, imagery and experience design and the way the content is organized to be findable, consumable and shareable. In future posts, we will dig deeper into the world of content. But for now, we’re going to focus on the process of “targeting.”
Targeting is essentially done in one of two ways; 1:many and 1:1. One could make the argument that much of mass marketing is just barely targeted at all. It wasn’t that long ago that you chose CBS if you were marketing to senior citizens, daytime dramas if you wanted to reach housewives and sell them CPG goods (hence the name soap opera – little fun fact).
Essentially ads went out to as many people as possible with the hope that it will reach as many eyeballs as many times as possible. Success was measured by frequency and reach. It was commonly held that if someone saw the message seven times, they would remember it and act accordingly. This was 1:many targeting at it’s most basic.
With the advent of direct mail and the accessibility of demographic data, 1:many targeting became both more precise and more effective. Advertisers were able to target messages based on a basic understanding of age, income, gender and the like. Brands could choose media matching the demographics of their desired audience. Hence those who advertised in Playboy tended to be different than those whose advertised in Good Housekeeping. MASH appealed to a different audience than Matlock.
Fast forward to the dawn of the new millennia. With the advent of BIG data, the Internet, and mobile, the promise of 1:1 marketing was born. Its premise was that if you could amass enough data about the individual, you could target precisely and dramatically increase their engagement. Its flaw was not intent, but execution.
From a 1:1 perspective, a 360 degree view of the customer meant that a brand could understand all the ways a customer interacted or could interact with the brand. Whereas from a customer centric point of view, a 360 degree view means understanding what a customer sees in every direction from their perspective, what they are interested in and most importantly what captures their attention.
This new way of looking at customers and re-defining what a 360 degree view means is not just theoretical. Customers have taken the controls. They are creating the data for us and they’re doing in constantly. According to SINTEF, 90% of the world’s data has been generated in just the last two years. As the number of channels, devices and platforms has exploded along with the exponential creation of data, the ability to collect and use so much data taxed even the most advanced relational databases and campaign management technologies. Not to mention it has rendered the notion of frequency + reach = engagement useless.
There is hope. There are solutions and some of the best brands are earning the rewards of taking another look at their customers and the data they produce and are beginning to think differently about their customer experiences. Software like Hadoop and SAP’s Hana, allow companies to manage huge datasets of unstructured data. Tools like Brandwatch and Blab allow insights professionals to extract information and knowledge from disparate sources both in real-time and over time, yielding unique perspectives into customers’ behaviors, attitudes and commitment. This use of digital data is both highly responsive and highly predictive. The source of the data is customer generated, not contrived, and it allows a business to understand the customers’ relationships to the brand, its competitors and everyone around them.
More importantly, what has also changed is the way in which we can understand the data generated by customers and made available by today’s technology. At the core, we now understand that we need to think of language as data. And by doing so, we are able to shift our paradigm from trying to capture “facts” and expand it to include the compiling, curating and analyzing ideas, intent, sentiment and context. This shift allows us to map data against individuals in pursuit of true 1:1 customer experience. It also enables us to create relevant 1:many experiences using content archetypes aligned with personas as a means of engaging the unknown customer, a key for all acquisition-marketing programs.
Content archetypes are the anatomy of content for a specific set of circumstances. They are the means by which we can understand the commonalities within a group. They take the form of a set of content scenarios for each persona or segment and can even by narrowed to fitting a specific channel. They enable us to identify and more importantly recognize a group, which will respond the same way when presented the same content delivered via the same content types.
It is through the identification of content archetypes that we are able to convert language into data and then compile, curate and analyze the data so as to make it available to inform content strategy and creative design, but more importantly define the data attributes that can be consumed as triggers for decision and recommendation engines. Which if done successfully give the technologists the level of detail needed to write functional specifications that lead to technical specs, which become the architecture and building plans to create and deliver contextually relevant, omni-channel customer experiences.
Over the last few posts, we’ve identified the core questions needed to drive relevancy; who are your audiences, what are they interested in and how do you engage them. The “Who” question was answered in terms of data-drive personas. We began the “What” answer in the last post about understanding customer journeys. In this post, we’ve completed the “What” question by understanding the role content archetypes play in understanding what people are interested in by the way the talk and behave.
That leaves us to the “How.” There are really several parts to this answer. There’s the campaign component, where and when do I engage to drive the most impact. There’s the user experience discussion around how to craft the most relevant experience for each audience. And of course, there’s the entire question of the technology needed to deliver the right experience, especially at scale and across all channel, devices and platforms. In the next post, we will begin to examine where and when to engage. We call it building a customer interaction model. And while it might sounds like campaign strategy, its actually the key the most impactful user experience regardless of the content type, format or channel.
Curious about how to make your CX personal? Join us for a webinar on Tuesday, Oct 7 with Loyalty360 to learn how.