But you need to know who the customer is, where they are going, what they are doing and saying, and then capitalise on that information at speed and at scale.
Really knowing who your customer is and being able to have a relevant conversation with them creates business success – it’s what brands are striving to achieve and agencies are promising marketers. However, there’s a fundamental disconnect happening when it comes to identifying that customer and delivering that relevancy.
That disconnect often results in the failure of current processes and technology to find, target and truly convince a customer to buy a product or service.
There is a good reason for this. Global organisations are struggling with a consumer who has too many options for any given product or service, the communications they receive are all too often either irrelevant or delivered at the wrong time, on the wrong device. Or all three.
This is despite marketers investing in technology that is supposed to give them a better understanding of their target audience. Often though, this tech is disconnected, siloed and not able to look at the whole picture.
There is another way.
And not just another piece of software to add to an already confusing tech stack, but an end-to-end process that takes advantage of real-time digital markets. A process that combines the depth and rigour of direct marketing and the reach, personalisation and real-time dynamic approach of digital.
DM began in the Wild West days of mail order and direct response selling (1.0), moving into the late Eighties when direct selling became about brand literacy (2.0), followed by the advent of relationship marketing and the digital DM (3.0).
DM 4.0 is about the discipline of direct marketing in the digital age, not simply e-DM. If you defined DM in digital today, it would not be siloed. The adage is that the DM discipline is about the right message, to the right person, at the right time, but now it’s about doing that at scale – in an automated and intelligent way. Moving away from awful retargeting methods to pre-targeting and content-driven targeting at the point of consumer intent.
The theory is that when a consumer is online and reading an article or some content, that is who they are at that moment in time. However, the advertising that follows relates to products or services they have viewed or bought several days previously or even a month ago because brands have bought that consumer’s cookie, which is then out of context.
That can be both irritating and invasive. A better way is to use the content on the page, using machine learning and technology, to understand the most relevant message for that consumer to insert into editorial environments, resulting in 15 times higher engagement rates. It’s not rocket science. We call it “data directed marketing”.
But humans can’t keep up and this is where digital comes in. To achieve the above, a human is not fast enough to be predictive or reactive enough to process thousands of interactions and data variations. The answer to that is an algorithm, spinning away at the speed of response, processing live and connecting dots in real-time to discover the triggers and levers that make the difference.
Creating not serving intent
We start with the data, not the creative. The role of creativity in the process is still important but it’s equally, if not more, important for that creative to be driven by insight and data rather than assumption. Without that starting point brands veer away from strategic plans and fail to take advantage of the real-time digital markets available to them.
It’s about using the art of direct, in a scalable, personal way, to have more efficient conversations with the customer. The process uses AI and machine learning but it’s still rooted in a discipline and belief in commercial success.
The technology looks at the thousands of pathways in the customer journey and tracks them automatically, across every device. It looks at how consumers come into an environment, what they do when they get there and the decisions they make, in real-time. Those decisions are coded and mapped, and content is served to drive conversion.
For example, if a consumer searches “shoes”, within minutes the world is selling them a pair of shoes. Our mission is to get there before that happens, to use data to understand why that consumer needs shoes: are they going on holiday or planning a climbing trip? The brand can then serve content about climbing shoes and do that automatically, before the sales environment.
It uses the fundamental principles of direct in the modern age. Creating intent not just serving it. Marketing not selling.
It makes the conversion funnel faster and the response funnel efficient, it allows brands to engage in content to reach consumers before the competition. A brand’s market share is grown at that point. Without this process, brands can look to spend a disproportionate amount of money, far too close to conversion, which cannibalises marketing, achieves nothing and because it’s so visible it gets attributed the wrong success.
A four-stage process
The principles behind our model exists in three factors – what people see, what they say and what they do – which is then linked to what people buy. It starts with a four-stage process:
1. Attribution. The process starts with the customer journey and identifying event triggers to understand the value of exposures. This allows us to predict the value of the contact with a person by creative type, in different environments, in real-time.
2. Machine learning. The technology identifies the needs, actions and best messages for each potential interaction at each touchpoint. Dynamic content optimisation can be used to tailor an automotive banner ad, for example. The content of the ad can be adapted to reflect the needs and desires of the consumer, such as safety versus performance based on what we know and the outcome we seek.
3. Creation. By tapping into personal passions, content creation can be relevant and personalised. That doesn’t have to be about making five billion versions but perhaps a number of macro pieces that are identified in the desired consumer, with hundreds or thousands of personalised variations automatically served. We can ensure the right person got the best possible message.
4. Activation. This might involve sitting and listening for a trigger. A brand could wait until someone lands on a particular piece of content, exhibits particular behaviour or buy an audience en masse for the coverage but bid for it dynamically at an individual level. It’s all managed in real-time across any touchpoint, in owned and paid for channels, thus truly integrating digital advertising channels with the more traditional direct channels.
Using our proprietary approach – I listen, I see, I do – helps brands identify their next customer in real-time. Accurately finding and communicating with this next customer is not as simple as demographics, or even psychographics.
It involves collecting, organising and matching the brand’s different data-sets to our data. It includes a whole world of rich lifestyle data and social identities, email addresses to old school telephone numbers.
This is used to provide a holistic view of an individual’s characteristics with pinpoint precision, using AI to continually learn from every interaction and deliver content across devices in powerful moments.
A collision between the discipline of direct marketing and the ability to scale that with digital means brands can see who their customer is, where the next one will be, and target them across multiple devices and channels. It’s created using insights, garnered through data analysis and rooted in live consumer behaviour.
The world of marketing is firmly back in the heartland of direct. Welcome to data directed marketing.
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