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Last click doesn't win: SEM, SEO & much more..
Last click doesn't win: SEM, SEO & much more..
By: Ronny Raichura

We are just 3 days from ad:tech New Delhi 2012 which will have the Master Class Workshop for the first time and will have leading speakers from Google, Communicate 2, etc. Here is a part of what Ronny Raichura of Communicate 2 shall be discussing thread bare at the sessions.

There are no exact statistics on how many advertisers still adopt only the traditional last click methodology of attributing conversions and revenue but considering my own experience, far too much credit is still being given to the final keyword in the users conversion path. In this article I will just consider the impact of changing attribution on solely SEM conversion paths but also touch on how it can benefit on a cross channel level too.

Why not last click for SEM?

Last click attribution just means that if a user searches and clicks across multiple keywords on search, across the length of the set cookie window, only the last click before the final conversion will be attributed the conversion and corresponding revenue. For example take the following scenario assuming a 30 day cookie window:

  1. User searches for “ blu ray dvds” on Google, clicks on an ad from Flipkart.com and browses the thriller section of the site but chooses not to buy
  2. 10 days later the same user searches on another keyword “inception on blu ray” on Yahoo! this time and again clicks the Flipkart.com ad, goes to the page for Inception but again chooses not to buy
  3. Another 10 days later the user searches for “Flipkart” on Google, clicks on the ad for Flipkart.com and buys the Inception DVD for INR 1500.

With a last click attribution, all reports would show that the keyword “Flipkart” drove 1 sale with a revenue of INR 1500 with zero conversions and revenue for the assisting keywords. We could theorize that if the ad was not present on the first two searches that the user would have gone to another outlet to find their DVD of choice.

Thus, not attributing any part of the conversion or revenue to the first two keywords will inevitably lead to inefficiencies in decision making with regards to which keywords to up weight bids and allocate budget to. A common user path is similar to the one above, with users searching on broad generic terms such as “blu ray dvds” for research and then converting at a later time on the company’s brand keyword, in this case “Flipkart”. As the broad generic keywords are relatively more expensive compared to brand terms, looking at data on a last click basis you would think to, perhaps incorrectly, to reduce visibility on these terms.

Further to that, note the part that Yahoo! plays in this conversion, it is the engine that the second click occurs on. Again, on the face of it with a last click attribution, the channel Yahoo! has contributed zero conversion and revenue and performance looks poor, but again without the ad being visible on the second search the final sale may not have happened at all. As a result, Yahoo as research channel may be vital to maximizing conversions and revenue on Google.

If not last click, then what attribution to use?

The answer to this question completely depends on your industry, your own existing path to conversion data and in some cases personal preference. Technologies such as campaign automation tool Kenshoo will allow for a set of default and custom attribution models of which some are below:

First click only – Similarly to the last click outlined above except all credit is attributed to the first click in the path to conversion. In this case the keyword “blu ray dvds” will be given the sale and the corresponding revenue. It is argued in a lot of industries such as travel where weather research keywords are the initial drivers of intent that this is the attribution model that should be used.

Prefer First – In this case a linear model is used so that the first click will get the majority share of the conversions and revenue, and this share falls for each subsequent click in the path. For the example above, the first click will be given 50% of the conversion and revenue, the second click will be given 30% and the final click will be given 20%. Again any industries where the initial searches are the big drivers of user intent then this is a model to consider.

Prefer Last – Similarly to above, but instead the last click will get the majority share and this share falls for each preceding click. For the example above, the last click will be given 50% of the conversion and revenue, the second click will be given 30% and the first click will be given 20%. This is the best model to use in industries where brand names are not as well-known and the last click keyword tends to still be generic in nature.

U-shaped attribution – In this interesting case, 40% of the conversion and revenue will be attributed to the first click, 40% attributed to the last click and everything in between will be divided equally. This method is useful for those believing the first and last clicks should be given the biggest emphasis, while all other clicks although important are not as critical.

Divide Equally – As the name suggests all clicks in the path are given equal share of conversions and revenue. This tends to be the most popular choice for many clients wanting to understand the value of each click evenly.

Custom – Kenshoo is one of the few tools that also offer the ability to customize what each click is worth as a attribution model. This is useful for clients with existing advanced analytics data where the average value of each group of keywords can already be mapped out and applied as part of the model.

Will this work across multiple channels including non-search?

With a correct set-up through redirects from your central tool, in this case Kenshoo, you have the ability to tag up all digital activity so that you can see how each plays a role in the path to conversion in the same way we did with keywords above

The good thing about Kenshoo is the standard path to conversion reports that will allow you to gather intelligence over a certain period of time on the value of assisting keywords. You can then use this data to understand how all channels interact with each other and decide upon a attribution model with a solid set of statistics behind you.

Considering attribution is key to conversion and revenue maximization.

Changing attribution models can be considered a frightening thought due to the lack of bench marking against past performance as well as potential impact on future performance. This is actually an unfounded fear as technologies such Kenshoo will allow for full reporting on a last click basis as normal alongside the new attribution model reporting. Switching the model will just allow you, or an automated bidding feature to make smarter decisions based on the assist value of keywords in the conversion path.

In summary, in order to start maximizing conversions and revenue for a given budget not only on SEM but across all channels, the path to conversion data needs to be analyzed carefully and acted upon using the appropriate attribution model. With the right technology partner there is no risk attached to such a change and will lead to some very valuable insights if nothing else!