Attribution within analytics has been a contentious topic for some time now but many advertisers seem to have made little progress. Why? Because they are either not looking at the data available to them or because they don’t know how best to attribute credit to different online sources.

There is often no real right or wrong answer when it comes to attribution though; it’s about finding a logical and sensible model that works best for your particular business and it doesn’t have to be complicated either, it’s purely about taking a more holistic view of visitor interaction and touch points and being careful to give each source the credit it deserves based on the data available.

If you fail to do this you risk making ill-informed decisions that will negatively impact on your marketing activities. But is it just for the bigger advertisers to worry about? Absolutely not, everyone should be concerned about attribution and the value of their online marketing activities if they wish to successfully optimise their online activity. So, this article is going to help you attribute your data more accurately.

What is Attribution & what does it mean?

Let’s go back to the beginning. Most web analytics packages (including Google Analytics) are by default last-click wins based systems. What this means is that the last touch point in a user journey, that is the last source or keyword, is the one that will have the credit assigned to it in the form of sales and revenue (or other) data, depending on what you, are tracking and what you as a business, define as a goal or conversion.

Whilst the last-click wins system is ok and does have some advantages, it doesn’t always give us an accurate reflection of performance upon which we can base optimisation decisions. This is especially true for industries that have more visits per sale in the user journey, i.e. those that typically have longer buying cycles, such as travel, for example.

The image below shows an example of visitor paths for a certain period, taken from one of our travel clients’ Google Analytics account. Note the number of visits and also the number of touch points in the user journey in many cases.

This is quite typical of a client with a longer buying cycle such as the travel example above, given that visitors often compare offerings from different providers and space out their research over time as they look to plan the perfect holiday, often over 6-9 months in advance of the actual departure date.

After all, most of us have only 4-5 weeks a year to potentially spend on a holiday and with the costs of travel ever increasing, people are spending more time making sure that they are spending their hard earned money on the right holiday.

What we typically see is that someone may well visit a site from a PPC advert using, for example, the keywords ‘escorted tour holidays 2013′, before leaving the site and returning several days later via another source (often by directly typing the URL into their browser) to compare their offering and perhaps request a brochure or download a pdf brochure.

These visits continue by various sources and often with differing keywords, which tend to be more brand oriented as they progress through the cycle and compare the offerings, refining their searches up to the point of purchase.

Once the holiday is booked though, it is the last source that gains the credit for the sale, meaning that brand performance is often heavily over reported as many people complete on brand terms, whilst non-brand generic keywords are left not getting the credit they deserve.

Evaluate before you cut back the spend for non-brand keywords

When advertisers see that prospects have converted via brand terms, they typically cut back on non-brand advertising significantly, due to the apparently higher cost per sale of these keywords, in favour of maintaining brand presence. They are then surprised when their sales start to fall.

But they really shouldn’t be surprised because the non-brand keywords that were essential in generating the first click in the path to purchase have now been removed from the visitor path!

Looking at the example below for one of our travel clients we can see both the last click and assisted conversion figures for all sources, for a particular time frame. Such data can be eye-opening for many as it often paints a very different picture of true performance and channel contribution.

There are many different methods of assigning keyword value (which I shall save for another post), but before we get in to this, you need to take a look at the data available to you. If you are using Google Analytics, look at the main ‘Reporting’ view and you will be shown your usual view of reports in the left-hand pane. Under ‘Conversions’ is the option ‘Multi-Channel Funnels’, which will show you the assisted conversion data by channel (and can then be segmented further).

It is important to remember that a particular channel can play three interaction roles in any conversion path, these being:

  • Last Interaction – is the referral that immediately precedes the conversion
  • Assist Interaction – is any referral that is on the conversion path, but is not the last interaction
  • First Interaction- is the first referral on the conversion path; it’s a kind of assist interaction

The Assisted Conversions report in Google Analytics summarises the roles and contributions of your channels nicely, but remember- Multi-Channel Funnels data collection lags by up to two days; therefore, data from today and yesterday is not available in your reports – something to bear in mind when reviewing this data.

How Receptional’s PPC team use such data

How each individual business use this data will and should vary dependent on the business and how visitors interact with your site, i.e. how many days/visits to purchase, etc. We in PPC at Receptional are always keen to look at attribution and assisted conversions, as we frequently see that PPC, as a source, deserves more credit, especially non-brand, generic keyword activity.

Using a real world example, with a client of ours that had set up last-click brochure requests, we found that much of the non-brand activity based on that metric in isolation was unprofitable, with a cost per brochure in excess of the target £100 maximum. When we started to factor in assisted data, allocating assisted conversions a value of 0.25 of a conversion each time, we then found that the picture shifted dramatically.

Non-brand generic keywords have shown themselves to be the assisters, offering huge value as an important step in the visitor journey, whilst brand keywords are the transactional keywords that people actually convert on and these are the keywords that Google Analytics gives credit to due to the last-click methodology.

The addition of the assisted data confirmed our suspicions that we would see transactional and assister keywords, but we were surprised at how important some of the generic keywords were.

If you’re not currently looking at the assisted data by source, keyword, etc. Then I would implore you to do so. Better still, analyse the data, think carefully about it and give all of your sources the credit that they truly deserve.

If you would like any help analysing this data and help in attributing credit to all the relevant sources, get in touch with us and we will be more than happy to help you improve your digital marketing.


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