ClickEquations Blog
6 Tips for Better PPC Analysis
This post originally appeared as my column on Search Engine Watch.
The idea of a good paid search account is a myth. An account is simply an aggregation of campaigns. Campaigns combine ad groups. Ad groups roll up text ads and keywords. Keywords and text ads exist only to attract search queries.
Effective PPC analysis is about finding the segments in your account that deviate from the norm. In many cases, you’re leaving opportunity on the table.
The “norm” is all about context. Winners and losers are different than their counterparts. Here are 6 useful tips for setting context and hunting down losers:
- Internal Benchmarks
- Against Potentials
- What’s Changed?
- Trend Charts
- Against Goals
- External Benchmarks
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1. Internal Benchmarks
We’re all obsessed with comparing ourselves to other people. How does my conversion rate stack up to my competitors? What’s their clickthrough rate?
There’s value in competitive benchmarks (see number 6), but getting competitive data can be expensive, time consuming and not always as actionable as focusing internally.
Setting internal benchmarks, i.e. judging you vs. yourself, is the most realistic way to assess your potential.
Take text ad testing as an example. Text ads play a central role in determining your clickthrough rate (the biggest driver of Quality Score) and attracting an audience that will convert.
Judging a text ad is all about comparing its performance against peers in the same ad group or campaign. You’re trying to find the combination of offer, headline and other factors that drive higher CTR and conversion rate. You need to monitor and ostracize your underperforming text ads.
Text ad monitoring in ClickEquations Adviser
Benchmarking against an average can also help you spot weak segments. Google Analytics has a useful visualization to show how segments like keywords compare to the mean for various metrics.
Here’s an example of charge showing bounce rate by keyword vs. the site average from my blog (in this case, lower is better).
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2. Against Potential
In some cases, you can spot losers by comparing their performance against a known threshold. For example, Quality Score has a defined range:
- 1-4 is poor
- 5-7 is okay
- 8-10 is “great”
In plotting out the distribution of Quality Score for a number of clients, we’ve found that 7 is the average. Anything above that is a reward, anything below that is a penalty.
Armed with that information, you can monitor your account for keywords that slip below the 7 mark.
In other cases, there isn’t a defined target, but there are best practices (or good practices) you can pick up from trial and error or the feedback of people with larger budgets, experience or sample sizes.
For example, you could choose to focus on building out negatives for keywords using broad match that have an excessive number of search queries. Or, you could prioritize analysis on campaigns where Impression Share Exact Match is low.
If you don’t have a system to alert you to segments that might be missing their potential or violations of best practices, a simple spreadsheet with conditional formatting can help you quickly spot the losers.
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3. What’s Changed?
As Search Engine Strategies New York keynote speaker Avinash Kaushik said:
“While we obsess about our brand terms and our top ten key phrases the reality is that the long tail of search means that our organic and search campaigns focus on tens of thousands or hundreds of thousands of keywords.
One effective strategy to deal with this purely data problem is to focus on what’s changed.”
Focusing on what’s changed makes it easier to manage large, high spend accounts. Instead of having to pore over reports to spot the losers (or winners), you can focus on segments that are spiking up or dropping rapidly.
There are three parts to building an effective what’s changed report:
1. Segment – Campaign, ad group, keyword, text ad, etc.
2. Metric – Pick the data points whose change you care about
3. Time Period – You two time periods to define a change.
I suggest you start with Ad Groups and Keywords. Changes at the campaign level are more likely to send you digging deeper anyway.
Keep your metrics as actionable as possible. Focus on KPIs like Gross Profit, ROI or Cost-per-Acquisition. Week over week and month over month comparisons are a good place to start.
You’ll end up with a report like this:
What’s Changed Report built with ClickEquations Analyst
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4. Trends Charts
Sometimes, just trending your data over time makes it easy to spot issues. In this chart, I used dual axes to show leads over time (left axis) and the cost-per-lead (right axis).
You can quickly spot issues on 3/2 when Google leads tanked and 4/6 when Yahoo leads decreased. Now you know where to drill down.
Every great dashboard has some version of this chart. Just like you segment the data, you can take it even further by segmenting your charts.
Sparklines let you embed mini-charts in your reports. It’s a great way to see the trends underneath the data when you’re presenting tables.
Here’s a sample chart that shows the absolute value, week/week changes and 12 week trends for a variety of metrics for Yahoo.
This chart was built with Microcharts. Hat tip to my coworker Matt for his Excel wizardry.
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5. Against Goals
One of the most insightful ways to add context is to contrast your progress vs. your own goals (assuming they’re realistic, of course). A pacing report is an easy way to get started. (Thanks to Josh Dreller for the name).
First, set your goals. Each time period (say, a week), you report on that week’s performance against those KPI’s. Then, you add the context of results-to-date vs. those goals.
Next, and most important, you project the likely performance for the end of your time period (say, a month). Start with the simplest projection. Take the average daily results for each KPI (ex: 10 leads per day, $200 spend per day) and multiply it by the number of remaining days in the month.
Here’s an example:
By their nature, pacing reports work well at the summary level. It’s much less common for PPC managers to have segmented targets.
If you have enough account history, however, you might be able to set goals at the campaign level. In that case you might consider using a bullet graph in your analysis. You can easily scan and find underperformers with the additional context.
Source: Charley Kyd at ExcelUser.com
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6. External Benchmarks
It’s nearly impossible to get conversion rates on your competitors’ sites, but there are a number of useful tools that can help you get intelligence about which keywords your competitors are buying, CPCs, etc. These tools typically work by using panel based research or by scraping search engine results pages.
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Compete Search Analytics
Compete.com (now part of TNS) offers an accessible Hitwise alternative for seeing two key data points:
- Who’s winning traffic for keywords and
- Which keywords drive the most traffic to your competitors
They have a free version of Compete Search Analytics that you can try without signing up. [Disclosure: Compete gave me a free Pro account for evaluation purposes.]
Here’s a sample report for the word “laptop”
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The Search Monitor
The Search Monitor has a lot of useful features for competitive intelligence and, in particular, affiliate monitoring.
They also have a unique report that lets you see what dayparting strategies your competitors are using.
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AdGooRoo
AdGooRoo has a suite of PPC and non-PPC tools. Agencies in particular will like their spend benchmarks, which help you see how much your competitors are budgeting for PPC, so you know whom you’re competing against most often.
Price points vary, though most tools offer reduced feature free option or some full featured free trial for a limited period of time.
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No Losers Allowed!
You don’t need to use all of these techniques to be successful at PPC. But, the larger your account, the more competitive your vertical and the higher your paid search spend the more likely there are losers who are dragging down your performance. It’s time to kick them off the cool kids table.
5 PPC Cures for Your Cyber Monday Hangover
Cyber Monday is over, but the damage it could have done to your paid search campaigns isn’t.
The National Retail Federation estimates that 11 million more people planned to shop on Cyber Monday, a 14% over last year. This is just the beginning of the holiday rush. If you optimize now, you can make the most of the holiday season. Here are our 5 favorite retail cures:
Separate Out Your Brand Terms From Brand Plus Terms – Some of the fastest rising queries this holiday weekend were “Walmart Black Friday” and “Target Black Friday Deals Online”.
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These are “brand plus” terms: some version of your brand modified. It’s the plus part of these search queries that can skew your performance and analysis.
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Is a search for “walmart online” as valuable as “walmart black friday deals” or “walmart bath towels”? Can you effectively target them all with one text ad? Would you want to send all to the same landing page?
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The answer to all three is, obviously, not. Many retailers lump together their brand terms with category terms with brand ones (ex: a Bath Towels ad group that includes “walmart bath towels”) or fail to separate out obviously different brand terms (ex: www.walmart.com).
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Improve your targeting and analysis by separating your brand terms into unique ad groups and campaigns. Start here for some ideas.
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Tag and Analyze Multiple Conversion Events – Google’s Retail blog reported an interesting trend that “searches for “printable coupons” on Thanksgiving and Black Friday were up about 50% over last year. Google Search was also used to develop in-store shopping strategies, as “Walmart Black Friday Store Map” surfaced as a fastest rising term, blurring the lines between online and in-store shopping.”
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This isn’t surprising to anyone who regularly reviews their search queries (see point #3), but it can be a real eye opener to exec who see a surge in traffic (and cost), but a decrease in conversions.
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If you just analyze online sales, then the knee jerk reaction is to decrease bids as soon as conversions go down or pause words that don’t convert. But, you could be analyzing only a part of the value.
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Chances are you have micro-conversions on your site that correspond to some value in offline sales or future sales:- Printable Store Maps or Circulars
- Email Newsletter Signup
- Store Locators
- Find Local Ads
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Each of these events need to be tagged and considered when you’re evaluating the effectiveness of your account. Sure, not everyone is as valuable as an online sale. And, yes, you can’t always perfectly tie them to revenue. That’s okay. Awareness is the first step.
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Once you know, you can at least make an educated guess about the value/cost of keeping these keywords live. Plus, you now have a real reason and focus on closing your offline/online analytics gap.- Mine Your Search Queries – Holidays tend to bring out very specific search queries. Queries for deals, hours and hot products pop up more rapidly than in the rest of the year. Chances are that you’re using Broad or Phrase match. It’s almost a certainty, then, that you’re paying for searchers you can’t convert.
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Take the time now to mine your search queries, the actual words someone types, not just the keywords you buy. Sort the list of your queries by cost and add the irrelevant ones to your negative keyword list. It’s one of the easiest ways to cut waste from your holiday campaigns.
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For more info, check out our search query post or the Master Search Queries video.
. - Check Your Lost Impression Share Due To Budget – Impression Share displays the percentage of the time that your ads were displayed to people who entered search queries which match your keywords (at their specified match types). It’s a Google only metric that is reported at the campaign level.
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There are 3 additional diagnostic metrics that help you understand why you’re losing Impressions. Lost Impression Share (IS) Budget tells you when you lost impressions due to a campaign being underfunded. This is rarely a concern most of the time, but as the volume of online shopping increase, you could be hitting your caps. It’s an easy fix: if the campaign is profitable, increase the cap.
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To learn where to find Impression Share and how to analyze, check out our Impression Share blog posts and white paper.
. - Kill Underperforming Text Ads – Clickthrough rate (CTR) is one of the biggest factors in Quality Score and your text ads are far and away the biggest driver of CTR. Plus, you’re messaging will change as the holiday shopping season progresses.
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Now’s the time to review your past text ads tests and weed out any underperformers. If you’re not already text ad testing, it’s the perfect time to launch some.
Worried that you’ve wasted money on Cyber Monday? There’s still time to optimize before the real Cyber Monday. According to research done by Comscore and the National Retail Federation, the biggest online shopping day hasn’t fallen on the Monday after Thanksgiving:

Researchers predict that Monday, December 7th will be the biggest for sales this year. Time to start optimizing…
Paid Search Pros Video: Avinash’s Favorite PPC Analytics Tips
It’s a sad truth, but “most dashboards are on auto-delete” as our friend and Advisor Avinash Kaushik says.
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.
New Webinar: Master Search Queries to Save Money and Increase Conversions
Search queries, the actual words people type vs. the keywords you buy, are a critical and often underused tool in managing paid search as we’ve said on this blog before:
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
-Alex
Paid Search Campaign Winners & Losers
Suppose you had to quickly reduce your PPC spend. Where would you cut?
One very helpful analysis is rank your campaigns (or better yet AdGroups) by ROI. This tells you where you’re getting more return-per-dollar, and where you’re getting less.
To simplify this analysis we built a ClickEquations Analyst Report, which runs in Microsoft Excel. To use it you define three thresholds – a high ROI that you desire, a low ROI that you detest, and a medium ROI that is minimally acceptable.
With a single mouse click you can then find out what number of your campaigns and what percentage of your spend and revenue fall into each of these bands. On the next tab in the worksheet you can find out exactly which campaigns fell into each group.

In the example above, we look at how ROI falls into four clusters and two charts visualize the spend and difference between spend and revenue.
Armed with this visual, most people are encouraged to look inside the campaigns – probably first by running the Ad-Group version of this report – and find ways to fix the losers or kill the problematic groups or keywords.
But you can’t drive to those actions and decisions without information. This report is a good example of how ClickEquations Analyst can help you to understand the performance of your accounts, and make good decisions about how to prioritize your PPC efforts.
You can begin your use of ClickEquations with a 30-day free trial. Sign up here.
Rethinking Paid Search
Two years ago we took a deep soul-searching look at paid search management practices and technology and decided both were inadequate.
Since then we’ve developed completely new management practices and technology, and it’s time to roll them both out publicly.
The management practices are built around a framework called ‘High Resolution PPC‘. It’s based on the idea that there are three distinct stages in the paid search process and specific steps and checks to sequentially create a well formed and effective campaign.
The technology is our ClickEquations platform, and was developed based on the idea that paid search is not as efficient and effective as it could be because the software tools we have had are inadequate in a number of very specific ways.
Background
We’ve been professionally managing paid search accounts for about five years. As the market and engine platforms have developed, the size and complexity of the accounts managed has grown. Working with both venture-backed startups and Fortune 100 companies we live with high expectations, competitive sensitivities, and serious budget and ROI oversight.
While it’s been exciting to go along for the ride as the market exploded and the technology evolved, anyone who’s lived deeply in paid search management over the past years knows the day-to-day hasn’t been exactly a picnic.
It’s a lot closer to a horror show.
The search engines are opaque (to put it kindly) on multiple layers. If you try to actually figure out what’s happening and why, you find key information is missing, available information is contradictory, and things aren’t exactly consistent. The Matching Algorithms used by the Search Engines and their rules change constantly.
The image of easy-management and easy-money that caught the media’s attention in the early years is ingrained in the imaginations of VPs of Marketing, Merchandising Managers, and even some Directors of eCommerce. Which means they have expectations and make requests that make the PPC Manager’s head spin – on a daily basis.
But most importantly, the amount of change that the industry has gone through over these short, jam-packed years has not been kept up with by either the ‘best practices’ or the ‘delivered technology’.
Paid search management is a young profession, one in which everyone has been learning on the job, sharing info via the web, and attending those endless conferences, but past a very small number of truly universal tactics there is no agreed upon ‘right way’ to organize and manage paid search, in even the most general sense.
That’s no way to spend $9 Billion or $10 Billion.
And the software tools haven’t fared will in this rapid-change environment either. The engines built interfaces that primarily serve their own needs. Instead of thinking about how paid search managers actually should and do work, and building tools to facilitate this effort, the tools are organized around the needs of the engines and their algorithms.
This leaves search managers often facing screens with 5 open applications, each which has one piece of the data or one tool they want, none designed for the whole job. In this environment work flow requires on a lot of application and context switching, cutting and pasting, and mental contortions supported by the acceptance of silly limitations and obvious inaccuracies.
We think it’s time for both the process and technology of PPC to catch up with the market realities and demands.
Introducing High Resolution PPC & ClickEquations
In the next few posts I’ll formally introduce both High Resolution PPC and ClickEquations.
High Resolution PPC starts with three primary goals – targeting the right prospects, assigning an accurate value to each, and then satisfying them. It provides the context for using the available paid search controls and options with clear ways to measure results and priorize work.
ClickEquations was and is being developed with three primary goals as well – delivering clear and accurate data, helping to prioritize opportunities and tasks, and automating as many PPC process steps as possible.
We’re excited to share the results of the last few years of work, and are eager to get your feedback.
After the upcoming introductory posts, I’ll deep dive into the specific components of each over the coming weeks and months.
Webmaster Radio Interview – Search Analytics & ClickEquations
Last week I taped an interview with WebMaster Radio, in which we discuss my SES presentation on SEM Analytics, and talk about ClickEquations and how it can help paid search managers.
If you’ve got a few minutes, check it out! Click the image below to go to the page where you can start listening.
And when you’re done listening, please rank the episode (if you like it) so it can get more visibility on the WMR ‘hot lists’ – thanks.
Keyword Click-Through-Rates (CTR’s)
One thought I wasn’t able to put in the last post about missing and misleading click data, was about keyword click-through-rates.
Do keywords really have click-through-rates?
Objectively they do because the engines report them. But does that make sense?
If A Keyword Falls In The Forest, And The User Doesn’t See It…
The user doesn’t even know the keyword exists. The user typed a query (which in some small percentage of searches was exactly matched to the keyword, but far more often was only related to the keyword) and was shown (if they even saw it) a text-ad (containing some specific copy) in some position on the page in relation to a number of other text-ads (not to mention the organic search results.)
What portion of the influence in that click, or lack thereof, did the keyword have?
- We know different text-ad copy produces different CTRs.
- We know different positions result in different CTRs.
- We know that the presence or absence of specific competitive adds produce different CTRs.
- We know different queries that may match to the same keyword in broad or phrase match type have different CTRs.
- We can assume that CTRs vary by time and the geography of the user.
- There must be a couple of other factors I’m not thinking of right now… (comments?)
So does the keyword really have a CTR, or do the combinations really have CTRs? Clearly the Keyword CTR is the average of a range of different situations and conditions.
The Average Average is Only So-So
There are a lot of averages presented in search analytics. That’s necessary as we can’t handle all the granules, but close attention must be paid to the composition of these averages, lest they be less than clear or useful.
If the campaign is reasonably constructed in terms of organization and match type application, and are being reasonably run (meaning the text-ads and bids have both logic and dilligence being regularly applied to them), then the average CTR as reported for keywords can be useful. If any of these elements are missing, the utility dwindles rapidly.
As with most averages in PPC reports, if you aren’t sure dive down and look at the components – the more performance diversity you find inside the less weight you should place on the average.
Know Your Metrics
Just another example of the fact that even the simple metrics of paid search have more to or behind them than you might realize, and how some understanding and healthy skepticism can help you get closer to truly understanding what’s happening in your campaigns.
(Credit where it’s due: The idea of questioning KW CTRs, and many other ideas you’ll find in this blog from time to time, was first suggested by Bruce Ernst)
(Upcoming Events: I’ll be at the Semphonic XChange Conference in San Francisco on Aug 17-19, and am Speaking on “Identify, Analyze, Act: SEM by the Numbers” at Search Engine Strategies in San Jose on August 19th)
Clarity II – Questions About The Queries?
In the earlier posts in this series the point was made that it’s hard to get clear and complete information on the performance of PPC accounts.
This is true, in part, because some important information is either unavailable or plays hard-to-get. Examples mentioned included search queries, information about missing clicks, and results in terms of true profitability.
This post drills down on search queries; the others will be covered in future posts.
Finding Queries
Let’s start with an assertion: It is not possible or reasonable to competently manage paid search campaigns without full access to search query details.
This isn’t a nice-to-have. It’s required.
Managing without query details is like managing a baseball team without being allowed to know what happened at the plate. Suppose you’re told who gets on base and who doesn’t, but nothing else.
How do you rate or make changes to your batting lineup without knowing who strikes out, who hits deep long fly balls miraculously caught on the warning track, or who gets hit by pitches?
The analogy may not be perfect, but the point is that choosing to add, delete, change bids, add negatives, not add negatives, or modify match type without knowing queries is a bit of blind-folded juggling.
And yet, most people do manage paid search without full and detailed query reports – they have to because the data is not available to them. With very limited exceptions, you can’t get it from the engines, in web analytics software, or even in specialized paid search management tools.
Why Search Queries Matter (the short version)
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?
If you know the search queries that people clicked on when triggered by the keywords you’re buying, you can answer these questions and take action to improve the targeting and results of your account.
Without knowing, you’re left without the ability to fine tune your campaign, so you waste money and miss revenue opportunities.
Where The Queries Are(n’t)
When talking about this, I’ve found that people usually have either never thought much about the difference between queries and keywords, or have the impression that they do have access to that information but don’t use it aggressively so they haven’t realized the limitations in the little bit of query data they can access.
Let’s review what search query data is available in some of the most widely used SEM analytics and reporting tools:
- In Google Adwords the Search Queries report lists queries at the ad-group level, but it does not tell you which keywords triggered which queries. And they notoriously hide a massive percentage of them in rows marked ‘Other Keywords’.
- In Google Analytics does not display search queries at all, at least by default. It can be hacked to display queries, but from what I can see in the ones I’ve used you cannot see/link the queries to specific keywords (or even bucket them into adgroups).
- In Omniture SiteCatalyst & SearchCenter offer great query support if you purchase the optional ‘db universal’ VISTA rule (typically $5K). With this enabled you gain fairly complete search query reporting and it’s a metric you can use with the full power of SiteCatalyst reporting, meaning you can use the ‘break down by’ feature to subsort by query relating it to keyword, product sold, or just about anything. You can also access it via their Excel tool in powerful ways.
- In most stand-alone paid search management tools (like Clickable, Acquisio, SearchRev, SearchIgnite, Efficient Frontier, and others), search queries do not exist. They’re completely unavailable. These tools rely on the search engine API’s for data – they don’t have their own page/URL tags – so they just can’t get query data. Which means their customers don’t get it either.
There are many other analytics and paid search tools of course, and I don’t personally know the details of many of them. (I believe Marin Software does have their own tags and can gather query data, but I don’t recall the level of reporting, for example.)
If you know the details of available or unavailable query information and reporting, please leave details in the comments.
Missing Data 1, Good Search Reporting 0
Based on this review of the popular platforms people use for paid search reporting, it seems safe to say that the vast majority – probably at least 90% and maybe as many as 98% of search managers do not have the ability to look at which queries drove clicks (and spent their money) on a keyword by keyword basis.
Imagine if your sales records only told you what categories of items you sold, not which specific items or SKU’s were sold. How would you decide on inventory re-orders or future promotional plans. You couldn’t with any level of accuracy so you’d have to just guess and play the averages.
This is what the search engines want you to do. Your inefficiency is their profit margin.
It’s hard to understand why the web analytics and focused paid search software companies place such a low priority on this vital information. I have some theories, which I’ll share in future posts.
A Fair Shot
If it’s the search query/keyword combination that triggers ads, causes your money to be spent, and dramatically clarifies the ‘why’ of who clicked and converted, why should paid search advertisers have to manage their accounts without this information?
I suggest you ask your search engine account managers, or analytics / PPC tool providers that question.




















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