Earlier this year, Craig had a chance to sit down with Avinash, Author of Web Analytics An Hour A Day, to get his tips for actionable paid search analysis and reporting.

Watch our first Paid Search Pros Video to learn:

• Why the “What’s Changed?” report is so actionable
• How to more effectively measure the Long Tail of search
• Avinash’s favorite ppc analytics tips

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For more advanced ppc tips, sign up for our upcoming webinar, “Master Search Queries to Save Money and Increase Conversions” on Thursday 7/16 and subscribe to our email newsletter.

Related posts:

1. Webmaster Radio Interview – Search Analytics & ClickEquations Last week
2. Avinash Revisited – Part II (What’s Changed?) Last week

Queries are vital because they can contain insight into the desire or intent of the user. If you sell tennis racquets, for example, and buy the keyword ‘tennis racquet’ (using the standard Broad Match) then your ad might be shown to someone who wants ‘tennis racquet restringing’, or ‘New Prince V14 Tennis Racquet’ or  ‘used cheap tennis racquet’ or even someone looking for ‘tennis racquet art’.

Are each of those people relevant to you? Are the ones that are relevant equally relevant? Can you write a single text ad that speaks directly to each of those people and persuades them to click and take action?

We’re tackling all things search queries in our next free webinar, “Master Search Queries to Save Money and Increase Conversions” on Thursday, July 16th at 1:00 EST. We’ll cover:

• What search queries are
• Where to find search queries
• The best way to organize your search queries to identify opportunities to save money and increase conversions
• Actions you should take daily, weekly and monthly to profit from search queries

Sign up for the free webinar!

-Alex

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1. Clarity II – Questions About The Queries? In the ear

These reports showcase a core feature of ClickEquations, the ability to compare performance between any two periods and to very easily see the difference between performance in those two periods. It’s a feature that was actually inspired by an earlier post on Occam’s Razor, and was the direct result of a conversation we had with Avinash early last summer.

(Click To Zoom)

In his original post, Avinash compellingly makes the case that top 10 lists are only of limited use. Or more accurately, they’re extremely useful but only for a limited time. Once you understand the top 10 of anything, it doesn’t tend to change so looking at the top 10 keywords or top 10 ad groups day-after-day really isn’t going to help drive constant campaign improvement.

But if you look at the top 10 keywords based on rate of change in volume, or based on delta in cost-per-click, or based on increasing ROI, then you’ve got some interesting and in almost every case actionable date. (Of course, 10 isn’t a magic number, it could be the top 25 or top X. If Letterman ran a top 11 list every night, would we all say Top 11?)

Prior Period & The Delta
Taking this insight to heart, we made it simple to pull two new pieces of data for any metric available within ClickEquations: the prior period version of that metric and the size of the delta between the current period and the prior period. So if you’re running a report for ‘this month’ and ask for the number of conversions for a keyword, for example, you also get back the number of conversions for ‘last month’ and the ‘delta’ between those two values.

We use this in many default reports to conditionally format numbers and present the % change represented by the new value. So in the dashboard below we see that revenue is down 3% in Google. (Click Image to Zoom)

The full What’s Changed Reports that Avinash mentioned display results for many different metrics – Revenues, Profit (ROI), Average CPC are the defaults – sorted by the amount of change in the current period vs the prior period. Each report shows the top 10 for each metric by amount of change in terms of both increase and decrease.

Each report also includes a handy bar chart showing the growth in revenue, in this case by campaign.

The default reports provide all of the above for Google and Yahoo (on separate pages), and cover both Campaigns, Ad Groups, and Keywords. By default they’re month over month reports, but using our Quick Change Palette you run them for any time period with a single click.

Making more significant customizations is pretty easy. You can change the metrics to shift Profit (ROI) to ROAS, for example, or any metric to any other. You can even customize the dates of the ‘prior period’.

All ClickEquations Delta reports automatically calculate values for the mirror-image prior period of any specified date range. So if you request a report for yesterday, the numbers will compare yesterday to the day before yesterday. If you choose this week, the report will compare this week to last week. But you can elect to specify the prior period as any arbitrary period, so you could compare this month to last July, or Valentines Day weekend to Presidents Day weekend, or whatever you’d like.

What’s Changed Reports can easily be created for other aspects of your PPC campaign too. Want a report to show the top 25 products selling faster this month than last month? How about one showing the geographies where sales are dropping the fastest? Each of these and many others are rather quick customizations in ClickEquations Analyst – after which they can be refreshed with one button push anytime.

A Sneak Peak
We’ve come to think very highly of these What’s Changed Reports as action drivers for PPC campaigns. So much so that in the next release of ClickEquations, we’ve moved the core What’s Changed reports onto the main dashboard. In a new tabbed-reports interface, you’ll be able to see the campaigns or keywords which are ‘changing’ anytime, and quickly dive into more details or to take corrective action.

Watch for more news on our upcoming release in the next few weeks.

Related posts:

1. Avinash Revisited – Part I (Keywords by Engine) Recently o
2. Avinash Kaushik on Advanced PPC Reporting & ClickEquations Analyst Last week

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.

Related posts:

1. Avinash Revisited – Part II (What’s Changed?) Last week
2. Avinash Kaushik on Advanced PPC Reporting & ClickEquations Analyst Last week

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.

Related posts:

1. Video: Impression Share in ClickEquations Analyst The post a
2. Video: Growth & Decline Report in ClickEquations Analyst Months ago
3. ClickEquations @ SMX Advanced in Seattle We’l

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.
  .
• 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.

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

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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.

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1. Revenue Allocation (Attribution) Models in ClickEquations One of the
2. Revenue Allocation Madness Here
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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.

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2. Revenue Allocation Madness Here
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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!

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1. See ClickEquations at Shop.org in Las Vegas Next Week! ClickEquat
2. Next Week At SMX-West ClickEquat

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.
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• 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.
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• 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.
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• 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.

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