Getting credit for an online conversion - and giving due credit to all recent influences - has been one of the hottest topics in digital marketing over the past couple of years. The urgency of the matter has grown as media costs -- especially click prices on paid search keywords -- have risen.
Marketers have been so hungry for better attribution of "keyword assists" (or simply, the non-overriding of the first click in the sequence towards purchase, whether that's over a matter of hours or many months), they've been willing to explore cumbersome customizations in a variety of analytics platforms, including Google Analytics.
But if you're looking to simply analyze the contribution of paid keyword searches on Google Search that preceded the keywords that led directly to a sales conversion (aka "assists"), you'd prefer to see all that data rolled up conveniently within Google AdWords itself, showing the data in handy formats that might make it easy to change your bidding patterns. In particular, earlier stage keywords (typically, before a last-click brand search) would now be revalued in your model; you'd bid them higher in cases where they made assists.
Earlier, when I defended the "last click"'s merits as an attribution method, I pointed to some data by Marin Software showing 74% of etail conversions only have one associated click - even counting assists. Moreover, Marin's approach bucketed prior clicks categorically, arguing that if a prior click was very similar in intent or style to the last click, then the extra information wouldn't be enough to cause you to alter bidding patterns anyway. That knocked the number of truly "assist-powered" conversions (that you could actually attribute properly) down to 10% or less.
This is where Google's new reporting needs to be scrutinized closely. In your individual case it could be quite valuable, but in current individual case studies Google may have on hand, anywhere from 70-95% of conversions only have one click to speak of. If Marin's logic above is even close to sensible, then it does underscore the limits to assist data. There will be some value attributable to assist keywords in around 10% of conversions, give or take. That's actionable but not earth-shattering. Of course, this is going to be most valuable to advertisers who have a lot of prior influencer clicks hiding behind a high number of clicks that are currently attributed to a last-click on the brand name.
To pump up the role of prior keywords, it might be fair to also point to assist impressions - views of the ad on Google Search where the ad wasn't clicked, but shown. But in those cases was the ad really seen? Perhaps not, but there may be some value in knowing what search keywords got the searcher's research motor running. Perhaps they clicked on a competitor's ad. Google is offering impression assist data as well with this release, which will be sure to delight trivia buffs, AdWords junkies, and Google's accountants alike.
Remember, we're not just talking about multiple searches all done in a single day, or in one session. Google is logging the time and date of every search by that user prior to a purchase/lead, and when a conversion happens, full funnel information is available as to the time lag between clicks and before the conversion.
Adding in impression assists to the mix, we may see past search query information for up to 20-25% of conversions in some advertiser accounts. Again, while not stupendous, this at least counts as extremely important and material to how you approach keyword value.
The ease of sorting in order of frequency of conversion by assist keyword helps not only to see the keywords in question, but with the "keyword transition path" view, you can see what last click converters they preceded, to better understand the consumer mindset. The screen shot below is a canned Google example while the program is still in beta. In my briefing I saw a more typical and valuable case example that showed the frequency (fictitious example to replace the one I saw) paths like "almond milk calories" > planethealthnut or "milk alternative" > planethealthnut. Whereas the brand might have got disproportionate credit for this conversion in the past, now, keywords like [milk alternative] or [almond milk calories] might attract higher bids, even more so if you experiment over time, allowing for more repetitions of your "research stage keywords" over many months.
In my opinion, "paths" work fairly well as a metaphor here and are not too misleading because the "funnel" steps tend to be relatively coherent and causal in practice. They aren't necessarily so, however. The reason these reports can look sensible is because they're drawn from a narrow universe of high-intent keywords that advertisers are avidly bidding on. You're not going to see a paid search keyword funnel path like "drawbridge in mexico" > james mcbleckr phone 415 > nike > air jordans used > nike.com largely because Nike doesn't have most of the keywords in that path in their paid search account. Truly generating causal paths out of all the things someone does online prior to a conversion is likely to be incredibly messy, but that's a much longer story.
Long story short: life is indeed a lot simpler when viewed through the prism of an AdWords account. And today, advertisers are getting what they desperately seek: easy-to-use information about paid keyword search attribution so that the last click doesn't override all other attribution data.
Of all the ticklish challenges being faced by digital marketers today, especially those buying search keyword exposure, one of the recurring points of debate appears to be the attribution problem. As more and more seasoned offline and online marketers compare notes in what is an increasingly cooperative effort, they all lament the fact that the "last keyword search" typically gets 100% of the credit for a sale or lead.
While Yahoo has tinkered with a means of crediting prior keywords with "assists," we're still far away from closing the loop on this issue. It will never be fully closed, of course. What influences me to purchase cannot be a 100%, slam dunk, exact science... and I hope it never is.
The problem is: once we accept that our attribution models aren't perfect, we're left stranded on Assertion Island. Seasoned offline agency types will simply asssert that offline ads are vital for "demand creation" and that search is "well down the funnel." The latter is by and large true. As for the former, sometimes offline ads are good at demand creation, but at what cost? How much is enough? Too much? Shouldn't the parts further down the funnel, the ones that don't fumble, and indeed "close the deal on," nascent awareness and demand, get more than their apparent share of credit for that ability to take the pass and put the puck in the net? And don't some kinds of demand and awareness "creation" actually do more harm than good?
Sticking to what we can know more about, you wonder who will come out and leapfrog Yahoo's basic assist measurement functionality, towards offering a product that attempts to estimate the contribution of a variety of media buys, and a variety of keywords, on a purchaser's ultimate decision. I suppose much of that would require significantly more acceptance by web users of the practice of being "followed around" throughout their entire online lives. (Panel studies that do look at "cross-attribution" issues do follow people around, as they volunteer to be followed. But that's just a sort of dog and pony show to attempt to prove a certain point about the power of different kinds of campaigns, with a relatively limited sample size. The real sticking points lie in getting past that point towards following nearly all users more closely. On that issue I am neither pro or con, or maybe I am con.)
And even then, being an industry where many entrenched interests are at stake, alternative scientific hypotheses are unlikely to be fully explored. Causation is subtle. If apparent causation is really just a spurious correlation, is the seller of weakly-effective media exposure likely to admit that? Even sellers of strongly effective media are likely to arrive at an entente with their less-effective brethren, in a compromise type of pitch that essentially says: "It's all good." (But is it?)
What spurious correlation, you ask? I'm still wrapping my head around the data showing that online display ads create a long term lift in sales volume, especially in combination with search campaigns, etc. But how much can we attribute that lift to the advertising, and how much to the fact that the ads show to users who are signaling a prior interest by visiting appropriate content sites? If we're attributing causation to impressions, as opposed to clicks (which are more reliable), what about the impressions of the written editorial contents of the visited sites? What about the impressions of written reviews, comments by friends behind the social network's wall, the very presence of like-minded friends in that milieu? The result -- more sales of goods in that channel to those people -- is surely not purely attributable to the ad impressions as opposed to participation in that milieu and digestion of (unpaid) content in that niche. Seeing a disproportionate lift in sales of one brand of (say) jeans or cameras over other brands not showing ads there would be stronger proof of that causation, of course. Unless the content, sites, or networks were expressly devoted to those brands (SonyLoversForums.com), which again nullifies any attempt to measure the ads' independent impact. Ads on brand-focused sites that pull buyers away from sites devoted to other brands would be very strong proof of causation, IMHO (you see a Toyota ad on AudiLoversForum.com, and buy the Toyota, for example).
Perhaps the uncertainties associated with full-blown causation models in purchase behavior is why we tend to cling onto what is most certain: what ad or link did the searcher or online application user click on most proximally to their purchase?
No question about it: as a keyword search advertising guy, I'm much more impressed by goals than by assists. And assists from keywords are easier to credit than assists from other media, in terms of both extent and cost.
Let's see if any analytics vendors are willing to take a stab at improving what vendors like Yahoo have already contributed to so-called "conversion tracking." It sounds complex enough that it probably can't be expected to roll out in 2009.