How often have you heard that keyword level performance data can be misleading? That PPC managers need to consider the phases of the buying cycle when evaluating terms? That specific keywords tend to steal conversions from the more general keywords that started the customer’s consideration, and that you should keep spending money on the general terms even though the efficiency looks awful?

It’s pretty obvious why the engines might want to trumpet this story: it makes them money. By convincing advertisers that they should spend money on general search terms regardless of the observed efficiency advertisers are encouraged to spend without the moorings associated with ROI goals.

Real data about the buying cycle

Google and Compete Inc. presented a study of the buying cycle that managed to answer none of the salient questions.

We presented a study almost three years ago at SES that challenged the notion of the buying cycle, but decided it was time to revisit the topic.

First, we grabbed data from a number of retail clients representing different verticals and different business models (such as pure plays, catalogers, brick and mortar retail). We then sought to answer the questions:

  1. How often do potential customers see multiple ads before placing an order?
  2. Does the interaction happen the way search engines say it does?
  3. Did we find that the first ad, the last ad, or a combination of ads a potential customer saw led to a purchase?
  4. Do the different types of retail businesses witness different behaviors?

Impact of cookie window length

First, let’s talk about cookie windows. Longer windows show greater impact by multiple ads. But for a retailer, unless your Average Order Value (AOV) is huge, you need to place some “make sense” limits on how long to give credit to an ad. Most of our clients have windows of 14 to 30 days with some shorter and some longer depending on what the data suggests. Out of respect for the argument that there is this long consideration cycle, I went ahead and looked at a 45 day window for these clients.

Impact of non-branded searches

We looked the complete list of searchers that someone did before purchasing, and for the purposes of the study, only looked at data for buyers who did at least two non-branded searches. We define “brand” as the retailer’s trademark and variants exclusively, hence “Sony Cybershot” is a non-brand phrase for Best Buy, but a brand phrase for Sony.com. For well known retailers there is a 4% – 8% impact of non-brand clicks being followed by brand clicks as customers remember that they found the perfect ring at Zales. We count these as non-brand orders, and and not used for our study unless there was more than one non-brand keyword involved. With those parameters understood, we found that interesting cases of multiple non-brand keyword touches occurred in between 10% and 15% of the orders for the vast majority of retailers. A few higher, a few lower. That’s not zero, but it’s not earth-shattering either.

More interesting: when we spent some time studying the impacted orders we found that in only about 35% of the cases did the story play out as advertised, with general searches being followed by more specific searches; in about 15% of the cases the other keywords were simply slight variations on the initial search (eg: “VCR sales” and “Buy VCR”, or “Nikon lens” and “Nikon lenses”) and in 50% of the cases the initial keyword had no relationship whatsoever to the last keyword prior to the order (eg “loveseat slipcovers” and “gold earrings”).

The more we extend the cookie window the greater the propensity for the keywords to be unrelated, indicating that, in fact these were separate shopping events, and that person looking for loveseat slipcovers, bought from someone else :-( Our research on what the person actually purchased was anecdotal, we just tested 15 or 20 samples and found that in each case the order related to the last keyword, not the first.

Those sites that appeal to hobby enthusiasts see more customer interactions from views of multiple ads than general retailers. Indeed, the impacts of AOV, business type and vertical were all quite interesting.

What this means about the buying cycle

To our thinking this confirms several tenets of search marketing strategy:

  • The engines are not evil, but neither should they be expected to look out for your interests
  • Cookie windows matter and should be carefully considered. I’ll publish our methodology for helping retailers determine their window over on the RKG Blog in the next week or so.
  • Within paid search, “last click” credit allocation schemes seem to be a better proxy for the truth than either “first click” or “shared credit”
  • If Keyword level performance data suggests a keyword is underperforming, it probably is.

Researching your own search data is a valuable exercise. It may help you determine whether the Buying Cycle should impact your keyword efficiency targets, or whether, for you, it’s much ado about nothing.

See for yourself!

George Michie is Principal, Search Marketing for the Rimm-Kaufman Group, a direct marketing services and consulting firm founded in 2003. He regularly writes for the Paid Search column here on Search Engine Land.

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: SEM | Paid Search Column

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About The Author: is Co-Founder and Chief Marketing Scientist of RKG, a technology and service leader in paid search, SEO, performance display, social media, and the science of online marketing. He also writes for the RKG Blog. Follow him on Twitter at @georgemichie1.

Connect with the author via: Email | Twitter | Google+



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