Recently our friend and advisor Avinash Kaushik wrote a blog post in which he used ClickEquations Analyst to showcase a number of advanced analyses for paid search. Each of these used a report or dashboard which is provided to all ClickEquations customers.

In this and the next few posts we’ll dig a little deeper into these reports, sharing some background about how they were created, how they can be customized and used, and how they can help you to improve your paid search campaigns using ClickEquations.

Keywords By Engine
The first report Avinash covered is a new one, set to be released in a mid-July update. It’s called the Keywords by Engine report.

This report uses a single CQ Analyst query to pull all keywords with at least 1 click over the past month, along with the number of conversions for that keyword.

This information is then pulled into a an Excel pivot table, which allows us to see how the keywords compare across engines based on either clicks or conversions.

To sort the data, you simply point to a cell in the Google, Yahoo, or MSN columns and right click. Then choose Sort > Sort Largest To Smallest. The keywords are then sorted based on the number clicks in that engine, and the other engine columns show how many clicks each keyword got in those respective engines.

As Avinash pointed out, this provides a view of pure opportunity.

Running this report for client after client has shown vast differences in how keywords perform between the search engines. While there are many differences between the engines, and some valid reasons why one keyword or another would perform differently in these different environments, it seems clear that all of your top 10 or 20 performing keywords in Google shouldn’t be non-performers in Yahoo and MSN.

Yet that is frequently exactly what is happening.

Very often it’s simple oversights that will be highlighted. Such as versions of brand terms, mis-spellings, or even domain name addresses that turn out to have been left out of one engine or another.

This report offers a great way of prioritizing the additions of new keywords to Yahoo and MSN accounts which you wish to expand. The first step would be to verify that the keywords producing great Google results (in terms of either clicks or conversions) aren’t already in those engines.

If they are there then you’ll want to try and understand why their performance is so (relatively) low. Differences in matching algorithms and search queries could explain it, so review the search query report for the ad group in the ClickEquations web application. Perhaps there are other keywords in the same ad group which are capturing those clicks or conversions in that engine.

Or it could simply be a matter of the keyword needing better ad copy, or perhaps it’s position is poor and a bid adjustment is needed.

If the keywords are missing, taking the time to ad them in each engine could be an effort with a great return.

Variations
The default query in this report gets keyword performance data for 30 days. Using the Quick Change palette you could pull data for a longer time period – perhaps 3 or even 6 months – to see if the result patterns change.

And while we’ve pre-built these keyword comparisons for both the clicks and conversion metrics, you could easily modify or extend the report to compare impressions, CTR, or even ROI. That’s the great thing about ClickEquations analyst – you have the full authoring tools to modify any of the predefined reports.

Last week our friend and advisor Avinash Kaushik put up another of his legendary blog posts, and we’re pleased and honored to say it features paid search analysis done in ClickEquations Analyst.

In the post Avinash looks at five different advanced PPC analysis ideas, and provides his spin on why they’re important and how you can benefit from them.

Go read his post. This week on blog posts here we’ll provide some more in-depth review of the reports and dashboards he mentioned and some additional information on how ClickEquations clients can use and extend them.

We’ll be at SMX Advanced this week in Sunny Seattle.

Stop by our booth to say hello, get a demo of the latest version of ClickEquations, or just chit-chat about PPC.

I’ll also be speaking on three PPC panels covering some of the topics often discussed here on the blog.

• Text Ads – Tues 9:00 AM
  Writing Killer Ad Copy, The Interactive Edition – So few words in ad copy; so much pressure to get the right audience to clickthrough. This session looks at ad copywriting tips, demonstrates some new approaches and techniques plus will involve the audience, as well.
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• Quality Score – Tues 12:15 PM
  Google Quality Score, Under The Microscope – Our “Up Close With Google Quality Score” session at SMX West in February had even the Google AdWords reps in the back of the room taking notes. For SMX Advanced, we’re taking it up a further notch, getting so close with Google’s often mysterious seeming quality score factors that it hurts. Learn the current thinking on quality score assessments and how to use QS to your advantage.
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• Match Type – Weds 9:45 AM
  Matchmaker, Matchmaker, Make Me …. A Broad Match? Exact Match? Negative Match? – Should you go broad match, especially when some are questioning whether broad match either goes too far or not far enough these days? Would doing exact match be better? How does the strategy shift depending on the type of product or service your pushing, or where you want to reach people in the buying cycle? This session covered advanced theories and applications for keyword matching management.

We hope to see you in Seattle.

• On 3 panels at SMX-Advanced/Seattle, the preso’s are due soon. Work. 2 do. See you at the Quality Score, Match Type, and Text Ad Sessions.
• RT @JezChatfield: AdWords Extended Search Query Report Limitations – Google has it backwards. http://bit.ly/dqowV
• RT @YahooGuy: Yahoo is looking to buy companies that will allow it to become a bigger player in social networking. http://snipr.com/ikb7m
• Why doesn’t Yahoo buy some companies that will make it a bigger player in Search?
• Wired article http://bit.ly/cnxwm inspired a new way to visualize #PPC. Off to ClickEquations Analyst to turn sketches into reports.
• At CMO roundtable in Wash DC.
• Quote from the CMO’s on using social media to fake hype: “it’s shameless, but it works”.
• Thanks to Ben Franklin Technology Partners for their continued support! http://is.gd/F8tP -Alex
• First CTO of USA lunch talk about moving tech infrastructure, policies, and thinking fwd from COBOL to the cloud. Exciting in many ways
• Almost always real time data is really irrelevant. To be of value U should meet 4 pre-requisites: http://tr.im/moCw (via @avinashkaushik)
• Same search repeated, very different PPC results every time. Why?

• Did You Know? Quality Score is only calculated based on exact matches between queries and keywords, even on your Broad and Phrase KW’s.
• No idea who wrote it, but this is a great Quality Score article – http://bit.ly/izLOy Sets the record straight on key issues.
• Winners write history. Right now that’s Google (thanks to us) so these guys look lke idiots http://bit.ly/PaQUH I think not entirely.
• Completing review of near-final set of expanded ClickEquations Analyst templates. Amazing #ppc analysis. Release to clients soon. 
• DeTweet: “SEO is about optimizing your website for people using search engines, not search engines!” Shari Thurow #SMX (via @adCenterBlog)
• Lots of talk about old business models fighting new Here’s great idea to use new to help old. http://bit.ly/4F73W Of course they won’t.
• RT @KISSmetrics: How Google Analytics Tracks ‘Bookmark’ Visits – http://shar.es/1hq4 – via @justincutroni
• All PPC Tracking Software does as GA does in last tweet – they treat bookmarks of PPC visits as new PPC visits. Yet another data problem.
• RT @InsideAdwords: Managing keywords and the Search Query Report: In this week’s post, we’ll take a deeper.. http://tinyurl.com/q2hnrp
• Wolfram|Alpha isn’t sure what to do with your input. (How the math guys say ‘no results found’)
• RT @TheDaveCollins: AdWords Editor headed for retirement http://cli.gs/4nHPU8 (PS: I doubt it, but who knows…)
• RT @jonathanmendez: wondering what happens to “web” analytics as API traffic becomes biggest piece of the pie?
• What do you want to see on the Dashboard of your #PPC tool when you log in everyday?

Get our Tweets in Real-Time @ClickEquations

• RT @avinashkaushik: Prepare UR mind to be blown, even if U don’t believe him: Ray Kurzweil, Singularity, 4 Videos http://tr.im/kZqt (22 …
• Working on the sequel to last Revenue Attribution Post. http://bit.ly/anvdW There are a lot of dark corners to light up on this one.
• Now following lots of great folks met at #mpsis last week. Should have watched the real-time twitter feed more closely….
• Revenue Allocation for PPC – The Messy Issues Blog Post – http://bit.ly/TIui9
• RT @rimmkaufman: Google PlusBox Performance : Reaction to 6-months of PlusBox performance.. http://tinyurl.com/o2yhhj
• WOW (IF TRUE) is this great, right, and over-do: RT @YahooGuy: Google to allow bidding for trade names of competitors. http://bit.ly/egGy4
• Hyatt: This is not a ‘Big Welcome’ : http://bit.ly/uf3hm
• Pulling into Penn Station NYC. Have 20 min free. Anyone here want to learn how to improve their PPC campaigns?
• Per User is the right answer to the @replies debate. Good work @twitter, can’t wait to see it implemented.
• The ClickEquations Blog is coming to the Kindle Store. They say 48-72 hours. I love Kindle on iPhone, so there’s 1 subscriber!
• (I’m VERY suspicious of this…) RT @anilbatra: Hitwise: Paid Search traffic down 26% http://clop.in/D8CjHM
• New Yahoo #PPC Search Query Expand Report – Not Quite Up To Par With Google: http://adjix.com/daq5 (via @Szetela)
• http://twitpic.com/55co7 – Our blog now on Amazon for Kindle (but not iPhone)
• Good on Google for their new TM policy. Ha to them for claiming it’s about ‘ad quality and user experience’. It’s about $$ but that’s OK!
• Great article on role of Position in Bidding and PPC by George from RimmKauffman – http://bit.ly/B3SmV
• Client Training Today, 1pm EST – Learn new features like bulk editing, revenue attribution, conv events, etc – http://bit.ly/AM19X
• The new #Adwords interface includes a lot more complexity and is often confusing. That’s good for ClickEquations.
• Magic Quality Score Snake-Oil. Twitter search ‘Quality Score’ and buy all you want.
• RT @dberkowitz: RT @360i On the blog: Google’s New Trademark Policy and Its Impact on Marketers >> http://bit.ly/G0FJP
• Besides Google, free speech & common sense, winner from the new TM rule will, unfortunately, be lawyers. All may not win long-term

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Lucky enough to have a Kindle? You can now subscribe to the ClickEquations blog on your Kindle, at Amazon.com.

Right now the iPhone version of Kindle doesn’t support these subscriptions – hopefully that will change in the near future.

The last post covered the basics of revenue allocation in paid search, and discussed the four methods of allocation supported in ClickEquations; last click, first click, linear, and weighted.

Deciding between even these four allocation models is not simple. None of them perfectly captures the complexity of our interaction with the many different prospects visiting our site. None of them turns our paid search or online marketing efforts into a simple, accurate, clearly instructive number.

This is not true just in terms of the simple matter of how to spread revenue across successively clicked keywords. There are also other complexities in the real world that impact the accuracy and appropriateness of any allocation method.

Time Frames
While attribution is chiefly recognizing the fact that many visitors come to your site multiple times from multiple keywords before converting, it also matters that these visits and the final conversion event also occur over a span of time.

First, you need to define the range of time that will be considered when tracking the string of visits. This is generally referred to as the ‘cookie length’ or ‘cookie duration’ but we call it ‘Conversion Tracking Range’ in ClickEquations.

The default range in most packages is 30 days, although in ClickEquations and many others you can customize this range to be just about any length that is appropriate for your business. It should be set to a length which will cover the vast majority of full purchase cycles that occur in your business.

Since the purchase of paid search software is generally a long and considered purchase among high volume advertisers and agencies, we use a 4 month range for our own ClickEquations.com tracking, for example.

Assuming you’re using the standard 30-day length, if a person visits your site five times over two months before purchasing, only those visits within the 30 days prior to purchase will get any revenue allocation no matter which method you’re using. And since people often purchase many days after their last PPC visit, this can easily exclude the majority of the related visits if your range is incorrectly set to too short of a period.

Most web analytics packages provide ‘days to purchase’ reports. Consult these to see the history of your site and then set your cookie length appropriately.

Revenue Allocation Over Time
If visits happen over time on multiple keywords, allocation is going to spread the revenue to one or more keywords, but on what date should the revenue be recorded?

Should the keywords record the revenue on the date of the conversion event? Or should the keywords get the revenue on the date of the click?

There is a huge difference between these two options. The first results in keywords gaining revenue on days when they may not have been clicked, and avoids any matching of expenses and revenues. This is ‘cash basis’ accounting. Yet this is the most common method of revenue allocation.

The alternative is like ‘accrual basis’ accounting, where we’ll match our expenses with our revenues – if I paid for a click last week and it eventually generates revenue, that revenue is allocated to the day of the expense and I can see the net results for that day.

To look at this in greater detail, let’s revisit our example from the prior post, with a few new details. Suppose each of the three PPC clicks took place on a successive Monday morning, with the purchase on the fourth Monday. Three of these Mondays were in the current calendar month, but the first took place last month.

Assume for now we’ve chosen Linear allocation. And to make this example really clear and simple (something the real world is not) assume that these keywords received no other clicks during this time-frame. Lastly, assume each click cost us $10 – So we spent $40 to get our $100 sale.

In the common ‘cash basis’ reporting used by most web analytics and PPC management tools, a ‘month to date’ report would show that we’ve spent $30 and earned $100 related to this transaction. This reflects the fact that our first $10 click took place last month but the revenue is all allocated to the three keywords on the date of the purchase.

Our keyword report would show us that two of the keywords had costs and revenue this month, but one had revenue but no cost. The cost took place last month and therefore won’t show up in the report. Note that is also is why you’ll often see keywords with revenue and no clicks – the clicks that generated that revenue took place in a prior reporting period.

Of course, this same report (when expanded to all keywords during the timeframe) will show us costs for clicks that won’t produce revenue until some time in the future. This is why the reports don’t all look entirely whacky, but unless your business and marketing has absolutely zero seasonality or time-based variations of any kind is why the average monthly expense/revenue report for PPC – on a keyword or adgroup or any other basis – is of very questionable value.

The alternative, which incidentally is what Google AdWords does (but not Google Analytics nor just about any other package I know about), is to shift revenue back to the date of the relevant click.

The implication of this is that revenue numbers for days long gone can change. If you ran a revenue report for last week on Monday morning, but then someone who clicked a paid ad last week came to your site via a bookmark and purchased, that revenue would be credited back to the keyword last week, and your Monday mornning report is obsolete and inaccurate.

Since AdWords uses a 30 day cookie, any AdWords revenue report covering dates within the last 30 is ’subject to change’. Adwords only supports last-click allocation so this doesn’t make the kind of mess using this method would for first or linear allocation. But very few people are aware that this is what’s happening.

Subsequent Conversions
Each click-chain ends in a conversion right? But what happens if they buy again?

Suppose after our $100 order, the same person returns 3 or 5 days later – before they did another search – and buys again. Should the keyword(s) that received revenue credit for the first sale get allocated money from the second sale?

In ClickEquations and AdWords and most current systems, it does, within the same time range parameters as the cookie. This raises questions and issues in it’s simplest form, and not all the forms are simple….

In The Simplest Terms
As I’ve argued before, paid search marketing has become quite complicated. But it’s still easy to spend money and even easier to aviod the complex reality and accept overly simplified views of how the marketplace you’re participating in really works.

Reality however is sinking in. The broad interst and embrace of Quality Score is a level of detail and sophistication that wouldn’t have happened two years ago. The strong growing interest in revenue allocation is another example.

Moving away from Last Click allocation to some form of Linear or Weighted allocation is, despite all the other options and complexities (including those highlighted in this post), a substantial step.

That is not to say there is really a one-size-fits-all allocation solution. There are many valid reasons why different businesses should choose different allocation models and even use/apply them differently. And we’re just talking about revenue allocation within paid search; the real solution will ultimately have to allocate revenue across all visits of all types.

Until I write a more detailed post on that, I’ll stand by the idea that last-click has gotta go. But as this post tried to point out, it’s complicated, there is more work to do, and marketers should understand all the grains of salt with which they need to read the numbers on their daily and weekly and monthly reports.

• Using the new May ClickEquations release. It blazes on our production servers. Available to all clients ‘real soon now’.
• Our May Release Now Live. http://bit.ly/XjC7Y Bulk Editing, Rev. Allocation Choices, New Bidding Options. More.
• Off to Pheonix to Shop.org – Long day on the plane – Tell me if I miss anything.
• (via @szetela) Watch out: Yahoo is being more liberal with their Advanced Match #sem – http://is.gd/wGD8
• New post: Do dynamic page titles help Quality Score? – http://is.gd/wVnZ #ppc #
• Writing a post about paid search revenue allocation, that is turning out waaay too long. Very complicated issue. #
• http://twitpic.com/4nwg4 – Morning at Shop.org in AZ
• The hot weather tour continues in FL for search insider summit. Stickier heat than AZ already. #
• At SearchInsiderSummit, listening to @Zappos talk about importance of weighted revenue attribution.
• Attribution is a 5 year problem. Start with paid search, then expand out. Speaker comment at #mpsis

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