ClickEquations Blog

• 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

Follow us in real-time @clickequations

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

Get Our Tweets in Real Time – Follow @ClickEquations.

One of the new features in the May Release of ClickEquations, is support for multiple revenue allocation models. A revenue allocation model defines how the revenues resulting from your paid search campaigns are allocated to the various keywords that were clicked as part of the purchase process.

The method of allocation is critical because the success or failure of keywords is generally judged on their ROAS (return-on-ad-spend) or ROI (return-on-investment), and what looks like a highly profitable keyword when using one method could turn out to be a very unprofitable one using a different method, or visa-versa.

The paid search world – and online marketing in general – has been thus far largely based around ‘last-click’ allocation. In this method, the keyword that is clicked just before a purchase or conversion gets 100% of the revenue credit for the sale.

To look at a simple example, suppose someone visits your website three times within 30 days before making a $100 purchase.

• Visit #1: Search Query ‘Organic Dog Food’ | Keyword ‘organic dog food’ (Exact Match)
• Visit #2: Search Query ‘Natural Dog Food Coupon’ | Keyword ‘Dog Food Coupon’ (Phrase Match)
• Visit #3: Search Query ‘Dog House Pet Supplies’ | Keyword ‘Doghouse Pet Supply’ (Broad Match)

In AdWords, and most web analytic software, and most paid search reporting tools, the full $100 revenue from the purchase would be credited to the broad-match keyword ‘Doghouse Pet Supply’. The trouble with this, and the reason why multiple revenue attribution models are necessary is that this doesn’t really provide a full or accurate picture of what happened or why.

Allocation Issues
Each of the three keywords obviously played a role in this customer’s purchase process. We have no way of really knowing which was critical and which was incidental.

• If they hadn’t visited our site during the initial ‘organic’ search would they have chosen our ad when they later did the ‘coupon’ search?
• If they didn’t find us during the ‘coupon’ search would they have recalled our name when they did their final search?
• If we didn’t purchase our brand term as a paid keyword would they have just clicked our organic listing in the same search results?

These and dozens of other questions can never be answered.

First-Click Allocation
The most common alternative revenue allocation method to Last-Click, is called ‘First-Click’. As the name suggests, this method gives 100% of the revenue credit for the ultimate sale to the first keyword a person clicks within the defined conversion time frame. In our example, the full $100 revenue credit would go to the exact-match keyword ‘organic dog food’.

This method is based on the view that the initial visit, the first time the person becomes aware of your site, is the valuable one. It presumes that regardless of any subsequent steps and visits prior to conversion, the initial contact was ultimately responsible.

Linear Allocation
A more democratic approach is to simply divide the revenue up equally among all the paid search keywords which the user clicked within the target date range before converting. This ‘Linear’ method divides the $100 up giving $33.33 going to each of the three words in our example.

Weighted Allocation
The mathematical simplicity of first, last, or linear allocation makes them easy to understand, but for a variety of reasons many marketers don’t feel they distribute revenue in a way that fully represents the role and impact of the different keywords.

Weighted allocation attempts to correct for this by shifting the revenue across the keywords in a way that more accurately reflects their contribution. Our weighting in ClickEquations is automatic, and based on the past performance of each keyword in the converting chains.

The Right Allocation Model
We’ll take a deeper look at the pros and cons of each allocation model in a future post. There clearly isn’t a universal ‘right answer’ as it depends upon your business, the sales cycle buyers go through, and your own views on what’s important or what you’re trying to encourage.

We do however, share the agree with the growing industry consensus that last-click allocation is the worst choice (despite it being the industry standard). Our opinion is that a move to Linear allocation, while far from perfect, represents a major and simple step in the right direction.

All of the Above
One of the many limitations to better revenue allocation solutions – beyond the lack of options – has been the fact that when choices are offered, it’s been a one-way-or-the-other choice.

Switching allocations models has been, typically, a semi-permanent solution in that all revenue will be processed using the model you choose, and there will be no future way to reverse that change.

This inflexibility is one main reason that even when given the choice many users haven’t yet left last-click allocation behind.

In ClickEquations all allocation models are supported simultaneously. We calculate revenue, profit, and conversions using all four supported models every day. This means you can change allocation models at any time and all revenue numbers in all reports are immediately retroactively updated.

So you can choose ‘Linear’ allocation and spend a few minutes looking at last months’ results, then choose ‘First-Click’ and go back and review those same reports.

An even more powerful reporting option, is that you can access the revenue report for each keyword on all four allocation models together in ClickEquations Analyst, so you can see the impact of the different models side-by-side.

Click To Enlarge

One warning about making allocation model changes: ClickEquations bid-rules run every night and will use the revenue numbers defined by the allocation model set at the time they run. So you can freely and quickly change models in the web application while browsing your reports, but don’t forget to set the model back to your ‘official’ model before the nightly bid calculation run.

Other Allocation Issues
There are many other issues relating to revenue allocation; the time frame considered, the dates of clicks and conversions, and the number and treatment of subsequent conversions, to name a few. We’ll take a look at these and other advanced allocation issues in the next post.

NOTE: Part II of this post is now available.

We’re on the road this week celebrating our May release!

Our first stop Mon-Weds is the Shop.org Online Marketing Summit in Scottsdale AZ.

The workshop is a nuts and bolts, practical and tactical event that provides you with the tools necessary to optimize your organization’s online marketing.

We’re exhibiting (May 5th & 6th) at booth 11 where you can see ClickEquations in action.

Then on Thurs-Sat we’ll be attending the MediaPost’s Search Insider Summit in Captiva Island FL. Say hello if you’re there!

The ClickEquations May 2009 Release is now live for all clients.

This release adds a number of important core capabilities on top of our existing strengths. There are new bid algorithms and features, powerful new management features including bulk editing, and even richer support for data including support for multiple conversion events, optional revenue allocation models, and compatibility with Google Checkout.

Complete details are available in our Release Notes, but here’s a quick summary:

• Multiple Conversion Events - You can now track up to six different conversion events in ClickEquations. This allows you to track for example, newsletter sign-ups, downloads, video starts, add-to-cart actions, or any other actions users take on your website in addition to traditional sales conversions. Each conversion event can then be viewed in reports. Use of the new conversion events requires updates to the ClickEquations tags on your website.
  .
• Negative Keyword Support - You can now view and manage negative keywords directly within ClickEquations Manager. Negative keywords provide an important control to save money, target your ads, and improve your Quality Score.
  .
• Bulk Editing Capabilities - You can now add and edit keywords or negative keywords in ‘bulk’. Several types of bulk editing are supported – you can simply enter a list of keywords and attributes, paste copied lists, or make edits in Excel and then import them. This feature can be used to easily clone campaigns from one search engine to another.
  .
• Multiple Item Editing - You can now also make simple changes to multiple items right within the ClickEquations Manager interface. For example, to change the bidding rule for any collection of keywords, you would simply select them within the keyword editing window and change the match type or bidding rule for all of them with a single choice in the keyword editing palette.
  .
• Google Checkout Support - You can now track sales and revenue transactions made through Google Checkout. These conversions are tracked using your normal shopping cart feature and are included in all ClickEquations reports.
  .
• Multiple Revenue Allocation Methods - You can now use four different methods of allocating revenue back to your keywords to track and measure your results. While Adwords and most packages use a simple default ‘last-click’ allocation method, many people believe this doesn’t properly value the role all keywords play in generating a conversion. In ClickEquations, you can now choose from last-click, first-click, linear, and weighted allocation methods for use as your primary revenue reporting method. This primary method drives browser-based reports and bidding rules. Via ClickEquations Analyst, however, you can see and compare the impact of all four allocation methods in any report or dashboard.
  .
• Global Bid Rule Options - You can now more precisely control the application of your bid rules in three important ways. First, you now have the option to define a global maximum bid to ensure that none of your rules exceed a specified bid amount. Second, you can specify the minimum size of a rule-based bid change to avoid frequent small changes. Lastly, you can control the maximum position at which you want to make bid increases – so you don’t overpay for the very top spots if there isn’t sufficient incremental return in your business case.
  .
• Cost-Per-Acquisition (Lead) Bid Algorithm - You can now choose to create bid rules that target a specific CPA on a keyword or Ad Group basis. These are perfect for lead-generation campaigns with a known CPA or CPL target. You can define these rules to run against any of our six supported conversion events.
  .
• Bid Rule ‘Intensity’ Control - You can now specify how ‘aggressive’ any of your bid rules are in seeking the defined goal. Higher intensity settings will spend money more liberally to seek the goal faster (raising the bid more dramatically to try and hit a target position, for example) where lower intensity settings will limit spending but perhaps hit your targets more slowly.
  .
• Simplified Product Margin and Naming - You can now directly update product name and margin information right from within ClickEquations. This makes it easier to use our Net Profit and true ROI based reporting on any campaign or keyword. Simply upload a spreadsheet with your product SKUs and associated names and margin levels, and ClickEquations will calculate the true net profit for every keyword (and ad group or campaign) based on the items sold in each conversion event. This provides much more accurate and actionable information than typical ROAS or Gross Profit reports.

There’s a lot of power and capabilities in these features, and we’ll dig deeper into the details and ways they can be used to improve your paid search management in future blog posts.