The UK has become a nation of multi-channel consumers, with 90% of people having shopped across more than one channel with at least one retailer, according to PwC. With almost two in five people (38%) using their mobile device to check the availability of products while on the way to a store and more than a third (34%) using it to research products in store, the divide between online and offline touch points is shrinking.
To succeed in today’s multi-channel world, brands need to embrace true omni-channel marketing, which can only occur when marketers have the ability to accurately measure the impact of each and every touch point that individual consumers are exposed to, across all devices, channels, and campaigns, both online and offline.
These insights can then be used to optimise marketing strategies, providing a personalised and relevant experience for each consumer – regardless of platform or device – and maximising ROI across a brand’s entire marketing ecosystem.
Yet the majority of brands have a long way to go to achieve genuine omni-channel competence, with marketers citing poor availability of data, lack of technology, and an inability to measure cross-channel performance as obstacles.
In reality, when adopting an omni-channel strategy, the two biggest challenges that brands face are the harnessing of Big Data and the current, low adoption rate of advanced (algorithmic) cross channel marketing attribution.
Harnessing Big Data
Omni-channel marketing is driven by Big Data and harnessing this valuable resource is a high priority for many brands. An ever-increasing number of devices and touch points are producing ever-larger volumes of data, with even medium sized marketing organisations generating tens of millions of impressions each month. Analysing each of these – and the various attributes (size, publisher, keyword, device type, etc.) that are associated with them – is a huge challenge for marketers, especially when the data is fragmented across many different data silos.
To make sense of the data and drive true omni-channel marketing, marketers must establish rules for a shared format and shared key performance indicators (KPIs) that are common across all channels. The data then needs to be normalised to those rules in order for meaningful performance analysis to take place.
Cross channel attribution
Once marketers have mastered the collection and normalisation of data, it needs to be processed through an advanced attribution model. Advanced attribution uses machine learning technology to apply mathematical algorithms to the cross-channel data collected, and objectively allocate fractional credit for specific marketing outcomes to individual touch points. This process uncovers cross-channel, cross-campaign, and cross-tactic performance insights to produce specific media buying recommendations and improve overall marketing performance. Advanced attribution can work at an incredibly granular level, identifying the optimal combination of marketing tactics – whether served on a desktop, tablet, mobile or other device – to achieve a wide range of business outcomes.
Despite its obvious advantages, only a very small minority of organisations have implemented algorithmic marketing attribution. The majority of brands are failing to measure the performance of their cross-channel marketing at all, while those that do largely rely on antiquated techniques such as last-click. Many marketers are dissatisfied with their inability to quantify the impact of one marketing channel on another, which is one of the most fundamental deliverables of advanced attribution. Without advanced attribution, an organisation’s ability to identify the combination of marketing touch points that will generate the greatest performance for each individual audience segment is also limited.
Advanced attribution solutions
These two barriers to omni-channel marketing – Big Data management and advanced attribution – are inextricably linked in making cross channel measurement a reality. Big Data needs to be collected, normalised and processed through an advanced attribution model to provide cross marketing performance insights and media spend optimisation recommendations. However, many marketers mistakenly believe that, in the pursuit of improved marketing measurement, they need to first master data management, and are therefore prioritising Big Data initiatives over implementing attribution solutions.
This illustrates a clear disconnect and lack of understanding of advanced attribution. Modern marketing attribution solutions are now available that harness Big Data, so organisations don’t need to build the necessary skillset or devote the required resources to do it in-house. Advanced attribution solutions are able to identify, collect, normalise, and integrate marketing data stored in various locations, in different formats, before applying the algorithms that will provide insights to drive marketing performance and ROI.
In short, an advanced attribution solution can help solve a brand’s Big Data challenges, whilst eliminating the top barriers to omni-channel marketing success, including poor availability of data, lack of technology, and inability to measure cross channel performance.
In today’s multi-channel society brands need to adopt cross channel measurement to drive a true omni-channel marketing strategy. Many are prioritising Big Data initiatives in an attempt to take control of their cross-channel performance data, but in fact an advanced attribution solution is a far better starting point. Once advanced marketing attribution technology is adopted, marketers are able to align and integrate Big Data, marketing attribution, and cross-channel measurement to bridge the gap between offline and online touch points, resulting in a truly omni-channel marketing strategy.