We know that consumers will engage with a brand several times before purchasing and we’re moving to a point where this journey can be accurately mapped and assumptions made.
While retail clients consistently favour paying on a last-click wins basis – ‘the last argument before purchase must be the most convincing’ – there are many examples of how marketers are more sensitive to their users’ psychology.
Examples of ‘engagement’
Here’s a few examples of where engagement mapping across the standard digital touch points – display (banners on publisher sites, ad networks), affiliates, email marketing, paid & natural search -has been relevant:
1.I went to a presentation a few years ago by a rich media vendor where a study showed the optimum number of times a banner should be seen (to maximise click-to-conversion rate) is three.
2.Another study showed that video ads should be between 10-20 seconds in length to optimise click-through rate.
3.A marketing manager at a mobile phone reseller spent greater budget on display than the click-conversions warranted – he could see data that showed users were more likely to convert if they’d seen banner ads, even though the last touch point before conversion was consistently clicks via PPC or SEO.
4.A gambling client of mine would pay the CPA bounty on a first-click wins basis; they were certain that getting a user to visit their site in the first instance was the hardest part of the sales process given the saturated market (their target market was users who were already a member of 3-5 gambling sites).
So some verticals rely on exploiting their users’ impulse to purchase with timed-limited offers specific to them while others feel they’re racing to reach their target market, and use engaging (sometimes uncomfortably distracting) copy to stand out; interrupting a user’s typical ‘ad blind’ journey.Others contrive for the user to encounter and compare their product in search cycles and user reviews; convinced theirs will win through on merit.
My point is that marketers are responding to their users’ psychology with competitors, buying cycles and the holistic digital journey in mind.It’s apparent that the brain reacts to repetition, unusual stimuli, and that our thought processes before ad engagement can positively or negatively affect that engagement (what was the user doing before we dragged them to our site?).
We are thinking in engagement maps, touch points and ad sequencing; and it’s clear this is having an impact on purchase probability.We’re moving away from dividing budget by sales channel and to spending on the combination and timing of digital media.
So why one commission?
But, why do we still tend to pay 100% of CPA bounty to the significant channel (whether first or last click, for example), instead of paying a significant percentage of CPA bounty to the significant channel?I don’t believe first or last click is how we should attribute credit, pay our acquisition bounties or plan our budgets.Many sales channels are adept at prolific cookie dropping, so that they exist in the majority of conversion paths.Others will even persuade users to delete their cookies so that a specific newly dropped cookie overrides them.
So what I’d recommend is a ‘best click’ model. This is how that might be achieved:
1.Use a first or last-click model as a foundation and rank your engagement points: highest for those you feel are doing the most selling (e.g. affiliates on a one-day click window, perhaps banners on a one-hour click window); lowest for those you feel are the most transactional (i.e. those that are the obvious route to buying a product – and retailer – a customer has already decided on) or are serial cookie droppers (e.g. PPC on brand terms, maybe one-day view windows on reach ad networks).
2.Arrange for the correct conversion tag to be written into the conversion page based on rank and timing, using them to award higher proportions of commission (and overall credit) to those high-rank channels where they appear in the conversion path.
Dynamic awarding & attribution: proportionate commissions
Our charts show how – by giving one channel a higher priority (because you rank it as being a better driver of ‘unique’ sales) – you can also give it a higher proportion of credit and commission. In the second chart, PPC is ranked as highest priority so – even when it appears as the second to last click – it gets the most credit.
This is a complex process but one that requires a useful exercise – to really think through which channels you believe in as drivers of sales you wouldn’t otherwise have, rather than those that deliver customers who were already committed to you and your product. Once in place, the way you rank channels and executions (like keywords) and attribute commission can be constantly refined.
Of course, even this model is flawed; any model that tries to pinpoint the significant engagement event among many is inconsistent with our users’ psychologies and prone to abuse. Still, attributing credit across multiple touch points, from both a reporting and awarding point of view helps to alleviate the distortion created by the sales channels currently fighting for that first or last click.
CPA sales channels should be incentivised for finding the right users and speaking to their psychology, and discouraged from just putting themselves at the right point of the conversion path to claim the final click. We can now pass a weighted proportion of the CPA bounty to an affiliate, or that can load a conversion tag for a weighted proportion of the time; all according to the attribution model selected.You may know this method as dynamic awarding or applied attribution.
Despite the flaws in drawing accurate conclusions from user journeys, I feel the marketing community intuitively builds a critical mass of engagement.I’ve lost count of the marketers I know that can’t prove why display contributes to post-view conversions, but are convinced it does (there’s a fair few that can prove it too!).Ad saturation here or under-exposure there can reverse the build-up of pressure – the critical sales point must be capitalised on before the pressure fades or is directed away by a competitor.Modelling this critical mass of engagement with correct statistical treatment (which is what the digital marketplace is acclaimed for), will obviously yield dividends.