The consumer journey is no longer a single pathway from awareness through consideration to conversion. In this piece, Ben Sidebottom, director, solution architecture, Visual IQ (pictured) discusses how modern-day consumers draw information about brands from a greater number of sources than ever before, encountering online and offline touchpoints, traversing a range of channels such as TV, print, social, and search. Users are also utilising numerous platforms, from smartphones and tablets, to laptops and desktops. This labyrinth of touchpoints equates to an infinite number of paths to conversion, making it all but impossible for marketers to predict the route a particular customer will take.

A consumer making a purchase from a retail brand may have seen a shop window display, watched a TV commercial, viewed a magazine ad, browsed the retailer’s website using a tablet, been retargeted via online display or video ads, clicked on a paid search ad, or any combination of the above. In addition – assuming the shopper is a previous customer – they may have viewed personalised web content on their laptop, received the retailer’s catalogue through the post, or been contacted via email with special offers or discount codes. This vast array of marketing possibilities opens up a wealth of opportunity for brands; but to take advantage of it, they need to understand and quantify how it all fits together.

So, how can brands better understand the complexities of the consumer journey, allowing them to reach consumers with targeted and relevant messaging that maximises the impact of every touchpoint?

Apply advanced algorithmic marketing attribution

Advanced marketing attribution is key to understanding the consumer journey, but many brands still rely on antiquated measurement approaches, such as last-click or subjective, rules-based methods. These distort the true value of marketing tactics and require the majority of customers to take the same path to conversion in order to be accurate.

Unlike out-dated approaches, advanced algorithmic marketing attribution takes a holistic look at all online and offline channels and uses machine-learning technology to objectively assign fractional credit to every touchpoint and attribute experienced by both converting and non-converting consumers. This approach enables marketers to understand the influences and synergies between channels; and identify the combination of tactics that produce the highest likelihood of conversion. More importantly, the insights derived from advanced attribution go beyond the channel level, drilling down to the most granular level of data – such as placement, device type, creative, keyword, etc – to empower specific and impactful optimisation decisions.

Take on marketing complexity

Consumers’ progressive dependence upon mobile devices, social media usage and video consumption, coupled with the advent of The Internet of Things, makes the ability to measure the impact of touchpoints across multiple channels and platforms an increasingly important and challenging task.

In addition to more traditional connected devices, new platforms such as smartwatches, fitness trackers, and connected cars, are quickly becoming mainstream. Previously inanimate objects in homes and offices – from security and lighting systems, to product packaging – can now communicate with one another via machine-to-machine communication using sensors and controllers.

These developments, whilst exponentially expanding the range of potential marketing touchpoints that consumers are exposed to, make it ever more important for brands to adopt an advanced algorithmic marketing attribution solution that can stitch together interactions across all channels and platforms to provide a holistic view of the consumer journey.

Separate the myths from the facts

While awareness of algorithmic marketing attribution and its benefits for understanding the consumer journey are growing, there are still a number of myths and misconceptions surroundings its adoption and use. While advanced attribution does require moving away from traditional siloed measurement approaches, there are misheld beliefs that it will disrupt marketing workflows and overburden technical resources, or that it is still in the development phase, and that it favours technology at the expense of creativity – but this is not the case.

In fact, algorithmic attribution is an objective, tried and tested, data-driven approach that has been delivering demonstrable results for over a decade. By increasing the granularity of information that can be extracted from marketing data, it enables marketers to achieve more with their spend – because they have a deeper understanding of their customers and crosschannel performance. Algorithmic attribution can help organisations to adopt an omnichannel marketing approach, focusing on the overall goals of their entire marketing ecosystem and – because advanced attribution providers use specialised software to aggregate and normalise data – it won’t have significant impact on technical resources. While algorithmic attribution is founded on advanced mathematics, creative input is an essential part of the process, and marketers always have ultimate control over how they are using the insights and optimisation recommendations produced by the solution.

Making sense of the consumer journey is a process that will only grow in complexity as available channels and platforms continue to increase and diversify. By embracing advanced algorithmic marketing attribution, marketers can quantify the true impact of every touchpoint and attribute along each customer’s unique path to conversion, across all channels and platforms. These granular insights can be used to create a holistic view of the marketing ecosystem, and to reach consumers in the right place, at the right time, with relevant, highly targeted messaging that works towards the brand’s omnichannel marketing goals.