Attribution: It’s not rocket science, it’s simple data

Path 51's Simon Larcey considers why attribution has only recently become a hot topic, when in reality, it should be at the heart of every marketer's strategy.

Attribution has earned itself ‘hot topic’ status in the digital space of late, with agencies offering it as a new way of validating their media buying decisions.

We often forget that media is an investment: brands buy it expecting a return on their investment. Just reaching your audience numbers, your impressions or your click throughs does not justify a good campaign – reaching goals and achieving real business outcomes does.

This is where attribution can be most effective, being used to demonstrate success – or a lack thereof – and helping brands understand where their media dollar is going.

I’ve been playing around with attribution modelling for a few years now. Knowledge is power, so if you understand how your media works – the affect one media channel has on another and being able to evaluate the impact – you can be a lot more efficient and generate a much better ROI.

The question I’m asking is: why has attribution only recently become a hot topic?

Surely brands spending millions of dollars on media would expect to understand how that media affects its business goals straight out of the gates?

A quick catch-up on how attribution works

Let’s look at how you could attribute the effectiveness of TV against your website traffic.

Say you have just run a TV campaign for the past month, which was the first TV you have done in some time. A basic way to evaluate how that campaign affected your website traffic can be done in five easy steps:

  1. Aggregate TV spot data and website analytics
  2. Pick a period and look at the amount of web visits five minutes before each spot and then five minutes after each spot
  3. Subtract pre-spot visits from post-spot visits and work out the percentage difference
  4. All pre-spot visits accumulate to create a baseline traffic figure
  5. All post-spot visits accumulate to create a TV-attributed traffic figure

This will enable you to see the uplift TV had on website traffic, which is a basic approach to get a high-level overview of the impact TV has.

As an interesting aside, a July 2016 study from Datalicious found that TV advertising is “disproportionally expensive”, but 71% of Australian and New Zealand-based respondents still believed TV was effective in reaching audiences – a stat that was almost the same as the more easily attributable channels of paid search (72%) and websites (74%).

Anyway, if you want to get a bit smarter, you can start pulling data from Oztam, social, geo, creative, CRM – any type of data – to get more and more granular.

Because when it comes to attribution, data plays a major part.

Omnichannel Attribution

Trying to run what I call an omnichannel attribution model – which accounts for all media channels used, with a view to attributing each channel, each creative, each moment to a business outcome – is more complicated.

I once heard someone describe it as like eating an apple: it takes as many bites to complete the task as it does to achieve a business outcome from advertising. And whilst all the different advertising channels and messages used in a specific campaign will contribute to a business outcome, there are other factors that will affect a consumers buying decision that don’t involve advertising – brand relationship, personal beliefs even your current financial status.

Attribution will help make better decisions. These days you certainly cannot attribute the last click on a digital ad to the complete business outcome. How many times did that ‘clicker’ see that banner before? How many times did they see that brand on TV? How many times has that person been exposed to that brand before?

It’s the reason Google announced in May of this year that they would be moving away from ‘last click’ modelling.

“A lot of marketers, because it is very difficult, they just give up and assign the entire credit to the last thing the customers did. Maybe if they click on a display ad, such as search, they say ‘that thing was responsible for this purchase’,” Babak Pahlavan, senior director of product management for Google Analytics 360 Suite and Measurement, told a media briefing.

It’s a bit like Pamela Allen’s classic children’s book, ‘Who sank the boat?’ Do we really blame the mouse – “the last to get in, who is the lightest of all” – for sinking the boat, when a cow, a donkey, a sheep and a pig all piled in first?

Rather, accurately apportioning how much each channel is ultimately responsible for a sale is a case of working backwards and then applying some science to the modelling. Nothing will ever be perfect – but you can be confident you will be close.

Brands should partner with technology companies who can aggregate all the relevant data and evaluate results, enabling an attribution model to be formed. This accompanied with some test and learn campaigns will create a formula for future success.  

Simon Larcey is managing director at Path 51.


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