Cracking the attribution challenge?
Posted on: Monday 26 November 2018 | Nikul Amin, Director of Consulting & Analytics - EMEA
Everywhere, the talk has been on the attribution challenge and how we can bring some science to bear on the puzzle.
Talk to any marketer about attribution and they’ll either roll their eyes or rant about how it’s important but hard to get right with long lead cycles and multiple touchpoints from a single customer. It is a longstanding quest to figure out which touchpoints are truly moving the needle.
Since the marketing age began, marketers have dreamed of being able to see exactly which campaigns resulted in sales and how their various efforts influenced those purchase decisions. In this perfect world, they would funnel their spend to high-performing channels based on their primary goal whether that was sales, brand awareness or lead generation. However, nothing is ever straight-forward, and attribution has been a bone of contention for marketers because it’s an area which is constantly evolving in complexity.
The complexity has further been exacerbated with the constant introduction of new channels and dispirit reporting solutions in the market place. It’s more difficult than ever to cut through the noise and measure the end-to-end marketing funnel from the development of a lead to post conversion relationship. Add to the mix that consumers live across a combination of online and offline worlds, today’s analysts, more than ever before, must learn the dark science of attribution as these environments intertwine.
As consumers interact with your brand across a growing number of screens and channels, it becomes increasingly difficult to know which parts of your marketing strategy are working. In Kantar’s recently released survey of 468 senior marketing leaders, 54% of respondents said that multi-touch attribution is one of the biggest gaps in their marketing research.
In recent years, attribution has matured somewhat from last touch to multi touch. However, if we investigate the evolution of digital marketing since its inception in the late 90s – with the development of mobile, and rapid proliferation of digital touchpoints and compare it with the methodologies used to measure them, we can see a clear disconnect emerging. Part of this is down to what people were tracking. Clicks alone are not fully representative of the value of a channel, and by refusing to acknowledge this a deception gets perpetuated in the form of inadequate measurement.
With the complexity of the customer journey increasing, taking a simple view of attribution does not help when you are addressing it. The evolution lies in the use of science to measure more accurately, not only the influence of the channel, but also to consider how channels are interconnected. Indeed, using an example, Acxiom working with a major financial services company, found that while radio as a media was thought by the brand to be underperforming, more detailed multi-channel media attribution modelling found it to play a key role in the journey to purchase for several critical segments. They were at risk of ‘switching it off’ when they lacked the full attribution picture.
There are a variety of factors that contribute to the current crudeness around the measure of digital marketing attribution. The first is a shortage of technical skills to employ big data technologies to manage the complexity around processing and transforming extreme volumes of hyper-structured data to enable advanced statistical analysis. Data is the fuel behind all your insight, so maximising this is essential for accuracy and analysis. The second is establishing the link between the business objective of understanding the true contribution of marketing activity, considering the interrelationships across channels, and the statistical methodologies required to get to the desired outcome.
To add another layer, the data required for attribution takes time to collect and isn’t necessarily available right away. There are two basic methodologies for obtaining the data necessary for attribution with one involving deploying tags to your paid media and conversion tracking on your website, and the other using historical data that your web analytics platform (Google Analytics, Adobe) collect. Digital media is always on and constantly evolving meaning attribution solutions need to cater their measurement for this. The problem is simply too big to solve as a whole. A more workable solution is for companies to take a more people-based perspective and look at customer trends on an individual level. Using identity resolution to map touchpoints, companies can then build models to trial on a broader scale to see of those learnings hold true.
Attribution is a very tricky landscape to manoeuvre and there are significant ramifications if you get it right—or wrong. With that comes power in the form of better insight on where and when to invest marketing budgets and better project return on investment. But having access to attribution data isn’t enough; marketers need the ability to take immediate action on the insights, and that’s something many marketers struggle with. By leveraging advanced attribution models directly in bid management platforms, marketers can quickly and efficiently adjust bids and channel budgets to maximize their investments.
Understanding the interplay across media and devices is what attribution is all about. To gain this understanding, you need a comprehensive, unified set of data. Through advanced analysis, that data -- when combined with performance insights across the marketing mix helps to identify the relative importance of different touchpoints toward driving a conversion. Across channels. Across devices and across the divide between brands and customers, bringing the two, closer together.
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