Brands have always been faced by a serious challenge when it comes to measuring the success of marketing activities, whether that’s by sales generated or ROI. The first issue is which model to go with? Last, first or somewhere in between? Whichever model a business uses is essentially trying to simplify a complex of different customer journeys into a single point of measurement, while ignoring the vast amount of ‘other’ contact points that consumer might have with the brand. As such, each model can tell a different story so it’s important that brands keep an open mind in order to truly understand the true performance of marketing.
To illustrate this issue, in my own field of expertise, email marketing, the most common models include a range of different element, from types of action (sent, opens, clicks), timeframe (days, weeks, months from action) and order of touch (first, last, any). The most popular way to track attribution when it comes to email is measuring by behaviour or conversion as a result of an email click. However, this can still be problematic because in the real world not everyone will click through from your email to go on and make a purchase immediately.
In fact, there is strong evidence that consumers might not even need to open the email in order to register the sale or offer mentioned in the subject line. This is highlighted by the UK DMA’s 2013 Consumer Tracking Report, which showed that 23% of respondents mentioned “visiting the company’s website via another route” as a likely response to an interesting email and 25% cited “visiting a shop or retail outlet”. This could leave you wondering how best to measure the impact of email marketing when people haven’t even clicked through, but in that wealth of data available to brands there is some that can help.
The answer to the great attribution dilemma is to dissect the details, and analysing the revenue from all marketing channels is a good place to start. For example, the diagram below is taken from one of our clients and shows average daily revenue in the month on days in which email was sent (orange) compared to the average daily revenue for days which no email was sent (blue). As none of the bars include revenue attributed to email, it is clearly illustrated that ‘email days’ deliver higher revenue through non email channels.
To take this data further, brands can also break the figures down to look at the variety of channels they use for a single month. The graphs below still compare days when an email was sent to those when they weren’t, but this time they look at the ‘first touch’ or ‘last touch’ marketing channel involved. The diagrams highlight that using either of these attribution models is likely to mean brands either overstate the influence of some channels or underestimate the impact of others, for example email is one discipline that often plays its role ‘in the middle’ rather than at the beginning or end. A brand’s email may not yield an open or a click, but according to the tables below it could be responsible for a 20% uplift in sales.
Ultimately, by delving a little deeper into the data they have available to them and not relying on a single attribution model as gospel, brands can understand the true impact of their marketing activities.
By Dela Quist, CEO at Alchemy Worx.
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