ClickEquations Blog

Average Position occupies an important place in the mythology of paid search.

Many people covet or chase higher positions, and there are several possible reasons:

1. The assumption that ads in higher positions get more clicks simply because they’re in higher positions.
2. As we all know ‘higher is always better’ – especially when it costs more.
3. And of course, eye tracking studies prove, um, er, that people look higher more often.

(The empirical and anecdotal evidence I’ve seen suggests that the power of higher positions is much less than most people seem to imagine. In a future post I’ll go into this in great detail. This is not the real subject of this post.)

As a result, there is a lot of attention paid to the Average Position metric. And a LOT of money is spent on upward bid changes made because of the number this metric reports.

So how good is this number? Probably not very good.

Let’s take one tiny little case study to demonstrate.

The keyword is ‘cat treatment’. And on Saturday Jan 3rd it produced about 25 clicks in one of our accounts. The average position for the term (in broad match) was listed as 4.55. This is the average of all the positions in which it appeared during the 1543 impressions it enjoyed that day.

Now be honest, despite all you know about averages (including the fact that it could have appeared in position #1 760 times, and in position 8 783 times) when you see that 4.55 was the average it makes you think it spent the day bouncing between position 4 and position 5. Right?

But did it?

Let’s look at Google Analytics’ handy Keyword Position report for this keyword on that day. This shows the position the keyword was in when it earned its 25 clicks.

Yowza!  This keyword covered more ground than Paris Hilton in NYC on Saturday night. (I always wanted to see how much Google traffic a single Paris Hilton reference caused.)

It was in all three top positions, and everywhere on the right side from position 1 to position 6.

Keep in mind that this is a map of clicks, not impressions. So maybe the impressions did cluster closely around the 4.55 average and the few stray impressions way up to top 1 and down to position 6 just all got clicks. Or maybe the actual impression distribution was extremely broad and the 4.55 average, while it is true, is really not useful to us in terms of analyzing keyword performance or making bidding decisions.

At this point only two things are really clear;

1. We really need better information. If the search engines won’t provide the actual impression and click position distributions, and/or make the the position-at-time-of-click a macro that can be delivered in the target URL, they should at least provide the standard deviation for the average position so we have some idea of what it really means.
2. We should resist the urge to put much faith, or make too serious of decisions, based on the reported Average Position of any keyword.

Here’s a wild one to end the year:

One of our clients bought a keyword, got a click, and made a sale. So far so good.

Actually they made three sales, to the same person who clicked on that one keyword.

• One conversion was during the visit following the click.
• One was made an hour later when they returned and bought some more.
• And then again 7 days later and bought even more.

Here’s the surprising part: Google Adwords took revenue credit for all three sales as one conversion and applied the total as revenue on the day of the click.

The second conversion could have come from click on a follow-on offer in the first purchase confirmation email. The third one could have come from a click on a banner ad the person saw 6 days later. Should that first keyword get the revenue credit for all three sales?

There is no easy answer.

But this does end the year where I think we’ll spend a lot of time next year – improving both the understanding and practice of revenue allocation.

All paid search campaigns are an effort to gain some type of return; we spend in hopes that we get back more, either in terms of gross revenue or net profit. If we can’t measure how much we get back, and/or if we can’t easily and accurately associate that revenue with the keywords or other sources of traffic to the site, we can’t measure our return correctly. And if we can’t measure return correctly we can’t come to conclusions about our current efforts or make decisions about what to do next.

It’s a giant problem and the stakes in PPC have risen to the point that we can’t ignore it anymore. I know this blog will devote a lot of attention to it in 2009 and I believe it will become a common theme in the industry.

After all the recent attention on Quality Score, I had planned to turn my attention to bidding, and write a series of posts on this important PPC topic.

But I think Ad-Rank deserves a little attention first.

Ad-Rank doesn’t get very much attention – certainly a lot less than bidding, and even a lot less than Quality Score. But Ad-Rank determines your position, and to some degree whether your ads display at all.

Ad-Rank Defined
According to Google, “Ads are positioned on search and content pages based on their Ad Rank. The ad with the highest Ad Rank appears in the first position, and so on down the page.”

Ad-Rank = CPC bid (Max CPC) × Quality Score

So we bid to gain Ad-Rank.

And we care about Quality Score because (among other things) it helps us achieve Ad-Rank.

Ad-Rank and Quality Score
Quality Score is important because it is weighted equally with your bid in determining where/if your ads run. The two factors are intertwined and the result is interdependent.

As the chart at right shows, you can get the same Ad-Rank with a lot lower bid by improving your quality score.

And as Quality Score gets more important, bidding gets less important. Not unimportant, but less important. It’s a zero-sum game.

Ad-Rank and Bidding
Yet while Quality Score is getting more visibility and mind-share than ever before, I’m not sure its ascent is being considered when thinking and acting on bidding.

Creating bidding strategies and running bidding rules or using bidding algorithms that don’t take QS into account at all, seems strange and seriously sub-optimal.

Traditionally bids are decided in an effort to impact position, and often the assumption is made that when an increased bid resulted in a higher ROAS or ROI, it was the change to the bid that was the direct cause – but I don’t know of a rule or algorithm in any PPC software today that either a) checks the actual position impact or b) checks to see if a Quality Score change was a mitigating factor.

It should of course now be noted that both bid and quality score increases have other impacts beyond their influence on Ad-Rank; Google has said that minimum bid and quality score thresholds are set for achieving Top (as opposed to Right Column) positioning, for example. So there are cases where it’s wise to increase your bid regardless of Quality Score issues.

Ad-Rank and You
The core tenant of High Resolution PPC is that we’ve all been lulled into an over-simplified view of how paid search works, both to accelerate our adoption, simplify our understanding, and keep us from complaining about really unfair or opaque aspects of the system that is taking our money.

Ad-Rank is an open secret. It’s well documented, easy to understand, extremely important, and almost never discussed. Time to change that.

A lot of advertisers have keywords on which their desire and instinct is to ‘bid to position’ – meaning they want to rank in the top slot (or the top 3 slots) and are willing to pay almost anything to do so.

This is generally defined as a ‘branding’ requirement, although it may be more accurately described as a form of vanity bidding.

In preparing for next Tuesday’s Quality Score seminar with Bryan Eisenberg, I’ve started thinking about the impact of Quality Score on Bid-to-Position.

It’s easy to think about Bid-to-Position is based on the out-dated thinking of PPC as a pure auction. The strategy itself implies a willingness to pay ‘whatever it takes’ to attain a certain position in the rankings.

(Or at least pay an amount more than economically justifiable – many Bid-to-Position rules do allow you to set a MaxCPC over which the desire for a certain position will yield to some economic reality.)

But as the role and impact of Quality Score increases the ability to bid your way into a position gets harder and harder, and in many cases ultimately impossible.

Position is not driven solely by bid anymore. And in many cases bid won’t even be the largest influencing factor.

We can see this by looking at Google’s new ‘First Page Minimum Bid’ which, according to Google is “based on the exact match version of the keyword, the ad’s Quality Score, and current advertiser competition on that keyword.”

If that’s what it takes to get on the first page, then this obviously has a lot of implications to anyone hoping to ‘Bid-to-Position’.

1. First it reinforces the notion that all of your keyword work should be striving toward Exact Match, because Exact beats Phrase which beats Broad.
2. Second it says you had better really worry about the Quality Score of the keywords you’re trying to position. A lousy QS will sink your chances of attaining any position, let alone a top one.
3. Bids are only important in the context of these first two.

On Tuesday Bryan and I will dive deeply into Quality Score and how you can and why you need to focus on improving it for the keywords in your campaigns. This ‘secret formula’ has impact on every dollar you spend, and every click you get – or don’t get.

The impact of Quality Score on various bid strategies and campaign goals is just one of the topics we’ll cover. Please join us if you can.

Google is again modifying both the calculation and impact of their ‘Quality Score’ metric. As with most Google changes, the stated goal is improving search quality and user experience. The coincidental result is that Google will make more money.

There are two changes this time:

• Quality score will now be ‘position adjusted’ to take into account the location of the text-ad when the click-through occurs. This makes it ‘more accurate’. Makes me wonder why this didn’t happen a long time ago. This increases the value of extensive text-ad testing.
• Quality score can now cause an ad to move above another ad it would normally rank below IF this jump pushes the ad to the top of the page (rather than the right edge). (That’s a bad quick summary, read the Google announce for the details.)

You can read some worthwhile thoughts here and here and here or here or here.

Beyond these details what strikes me is how important quality score has become to paid search management and results.

Quality score drives bid requirements, quality score drives ad position, quality score drives impression share, and now quality score drives the chance to leapfrog your way to the top center of search result pages.

What Do We Know About Quality Score?

Although quality score plays a central role in how your money is spent and made in Google Adwords, it is officially a ‘secret formula’.

Like PageRank on the SEO side, Google makes only vague pronouncements while pundits and practitioners share theories and recommendation endlessly – but nobody can tell you definitively how to maximize your quality score.

It still isn’t even that easy to see your quality score, although it is getting easier. Google recently changed the way they display quality score – giving it an integer value – but it’s still under a ‘work for it’ pop-up in the Adwords interface. On the positive front, they have finally added quality score to the API (thank you!) so third-party tools can begin to make use of it.

But also like PageRank the scores tend to clump around certain values, and the distinctions between close numbers aren’t obvious.

Also, and this is just a hunch, I’d bet nearly anything Google doesn’t maintain or use the number as an integer. So two keywords from two different bidders that both show a QS of ’7′ might in fact be one with a 7.0001 and another with a 7.9998.

Four Conclusions

1. Google has an awesome business. They sell a product with secret specifications which are subject to change, and charge whatever they want without even telling anyone why or how. Nobody but the Mafia selling protection services to local merchants ever got away with this before.
2. Advertisers have to really play the ‘chase the quality score ghost’ game. Obsess about CTR’s and align as many of the other known factors as possible. Live with the fact that you’ll waste time trying to please the QS algorithm because there’s no published list for how to get into quality-score-heaven.
3. Advertisers should continue to clammor for more openness from Google as to what counts, how much, when, and how we’re charged accordingly. Neither #1 or #2 should be true.
4. I need to spend a lot more time thinking and writing about Quality Score. It’s a big deal.

Each time someone executes a search, they’re asking a question.

They search because they want to learn about something. Or find out where something is. Or discover who has it or knows about it.

They may just be curious, or the question may have been provoked by some urgent problem.

The question could be simple or complex and the searcher might be sophisticated or incredibly naive.

Search Engines answer questions. That’s pretty much all they do.

Search results offer an ordered list of answers to the question the search engine thinks you’re asking.

Paid search advertising is your chance to raise your hand and let the searcher know that you think you have the answer to their question too.

In the next post we’ll discuss what it means to the organization of your campaigns to think of yourself as a professional answer provider.

This post is part of a series on High Resolution PPC, a framework for understanding and managing paid search advertising.

Target, Value, Satisfy, Understand. That’s the mantra of High Resolution PPC.

The idea is to stop thinking about mechanical components like keywords and bids, and instead focus on a logical marketing progression.

We want the tools to support our work process instead of having to build a work process that serves the tools.

The First Step is Targeting

Targeting means showing your ads to the right people. Paid search ads are delivered as answers to questions. People type in a search query and you pay for the privilege of having your ad be one potential answer to that question.

So you must know:

• What questions do you want to answer?
• What answers do you plan on giving to those questions.

Campaigns, Ad-Groups, and Keywords are your targeting tools.

Keep in mind that they’re called ad-groups, not keyword-groups. The goal is to segregate keywords, controlled using the match-type option, so that all the queries attracted by a single ad-group are questions answered by the text-ads in the ad-group.

In other words, you want every searcher to see a a text-ad that is directly relevant to their search. To do that, you must organize your ad-groups around the search queries they attract, not the keywords they contain. Every search query that causes your text ads to be displayed, should be highly relevant to the text ad that is displayed.

Let’s illustrate with an example.

Supposed you knew that all of the following search queries would be coming into your account, and you could hand match them to appropriate text-ads before the results page was delivered to the searcher.

• Discount Dyson Vacuum
• Dyson Vacuum Features
• Dyson Vacuum Coupons
• Compare Dyson Vacuums
• Cheap Dyson Vacuum
• Dyson Extra Cyclone

Wouldn’t you want the 3 price-related queries to get a price focused text ad, and the three feature related queries to get a feature-related text ad? Doesn’t it make sense that this would produce the highest click-through-rates and the highest ROI?

Yes, of course.

This is why you have to think about queries not just keywords, and use ad-groups to target the groups of people you want to talk to.

The Second Step is Valuing

Once we’ve targeted the right people using different ad-groups, we can then look inside the ad-group and take advantage of the fact that we don’t have to place the same value on everyone in that group.

Match-Types, Negative Keywords, and Bids are some the core valuing tools.

Extending our previous example, suppose experience tells us that people who search for ‘Cheap Dyson Vacuum’ just don’t buy from us (we’re not that cheap). That has no value, so we add ‘cheap’ or ‘cheap dyson vacuum’ as a negative. But ‘Dyson Extra Cyclone’ is a very specific feature so people who search on that are far into the buying process, we see that query frequently with a high conversion rate. Make that an exact match and bid it up.

You get the idea. By correctly using these tools, watching our search queries and continually refining our campaigns, we can group queries within an ad-group, value them appropriately, and manage both budgets and returns.

The Third Step is Satisfying

People decide how well our paid search advertising does. They decide how to formulate queries which trigger our ads (or not) and they click (or don’t) and buy (or not).

Text-Ads, Landing Pages, and ultimately your offers, website, and checkout process are your satisfaction tools.

When we’re targeting accurately, and valuing properly, we have the ability to focus on satisfying those who see our ads and visit our site. Trying to do so before we’ve completed these steps means, by definition, that we’ve got too wide a range of people coming to really have a fair shot at measuring the results of any attempts at improvement.

There is little doubt that text-ad writing, let alone testing, is the paid search option that gets the least attention and effort as compared to its importance and potential impact. Rewriting a text ad and doubling performance – in terms of CTR which even if it does not improve conversion rate can proportionally increase revenue – is common. We’ve seen many ad re-writes produce 10x-20x CTR improvements. Try that with a better bid.

But writing is hard. Writing is subjective. Writing takes quite a lot of time. None of these make it less important.

All the same is true-er for landing pages, website experiences, and shopping carts. This all very hard, time consuming, and costly work. But it is ultimately directly responsible for the success or lack thereof of paid search campaigns. Even within whatever limitations exist, it should be considered, managed, and measured.

The Final Step is Understanding

Even in this greatly summarized view of the paid search process, there are a lot of moving parts. Each exists by the hundreds, thousands, or hundreds-of-thousands in typical campaigns. They occur tens-of-thousands of times every day as impression and click counts increment. And we have weeks and months of history for all of this to consider and trend.

Paid search can only be managed effectively if you can learn from this data – look into it and find information.

Website and Search Analytics are your tools for understanding.

This means knowing which metrics are important. And when trends are really trends. And how all the numbers affect each other.

It also means that you need the ability to get at the data that can inform you, and easily produce the reports and dashboards that will do so for both you and your colleages or managers.

The key is continuous improvement. Paid search campaigns are never perfect. And they exist in highly dynamic environments. Only through hard work to understand the campaign and know the best move to make next to improve it can you really drive great results.

Summary

The shift into the T-V-S-U mindset is a big one. It changes the process of managing paid search and the way you think about and use the options and tools the search engines provide. More importantly, it aligns your search and marketing goals, and makes it easier to prioritize your PPC efforts and measure your results along the way.

In future posts we’ll dig into each stage and step of this process in more detail. Have questions before then? I’d love to hear them, or your comments.

This post is part of a series on High Resolution PPC, a framework for understanding and managing paid search advertising.

Since the dawn of time, paid search has been conceived of and managed based on four key components and common perceptions of their roles:

1. Keywords. Keywords define when your ads run. Choose keywords and phrases that people looking for your product or service would use.
2. Bids. Bids define how much you’re willing to pay when your ad appears for any particular keyword. Higher bids can help position your ads higher on the page and appear more frequently.
3. Text-Ads. Text-ads give you a headline and two lines of copy to attract and persuade searches to click and view your website.
4. Click/Conversion Reports. Basic reporting tells you how each keyword is doing, both individually and within campaigns, and ad-groups, in terms of clicks, conversion rates, and ROAS.

These four items remain important aspects of paid search today, but they’re not the most important variables, nor the best way to think about PPC.

We’re not operating in the same technical, competitive, or business environment as four or five years ago:

• In a world where changing definitions for match-type determine which queries cause your ads to run, worrying solely about keywords is inadequate.
• In a world where quality score has such a huge impact on where your ads run and how much you pay for them, worrying largely about bids is inadequate.
• In a world where a majority of your buyers visit your site multiple times before purchasing, text-ads remain important but must be considered in context of all user touchpoints.
• In a world where profitability is the real goal, then measuring intermediate metrics while ignoring the one that really matters – ROI – is illogical.

We’ve got a name for this old ‘keywords & bids’ view of the paid search world: ‘Low Resolution PPC’.

It was fine five or six years ago when the engines were simpler and the budgets smaller. It’s not fine anymore.

• Today you have to think about your user targeting based on the interaction of keywords, match types, and search queries.
• Today you have to think about your costs based on how quality scores and bids interact with match type keyword traps and negative keywords.
• Today you have to think about persuasion and conversion as a chain of events that starts with your text ad and continues through your landing page, your site, and the experience users have in your shopping cart.
• Today you have to think about analytics as a way to understand all of these variables and more.

It’s a high-def world, even in paid search marketing.

Introducing High Resolution PPC
But there’s more to High Resolution PPC than just a deeper consideration of the core mechanics of paid search.

We also want to shift the focus away from the mechanics of running paid ads and onto our relationship with the people to whom we’re advertising and how we manage that relationship.

We want to know who the people are conducting these searches, clarify why we want to talk to them, understand what will get their attention, and make sure to learn from our interactions with them so we can perform better in the future.

The Cornerstones of High Resolution PPC
In High Resolution PPC we manage our campaigns by using the options and controls in paid search to move clients through the marketing acquisition cycle.

Accordingly, we no longer think of search in terms of the four old cornerstones of paid search – keywords, bids, text ads, and operating reports – but instead in terms of the four stages of customer acquisition and management:

1. Target - To begin you define the focus of your efforts, using campaigns, ad-groups, and keywords to target specific groups of people who are asking the kinds of questions you want to answer with your paid search ads.
2. Value - Next you refine this focus within your target groups, using bids and match types and keyword negatives to properly value the different people who you want to attract to your website or landing pages.
3. Satisfy - With clearly targeted and properly valued searchers identified, the goal becomes delivering text ads, landing pages, and offers which satisfy user desires and advance them toward and through conversion.
4. Understand - Throughout this process we capture, analyze, and present meaningful and actionable information about each specific phase and the overall. Here you’ll apply improved reporting standards and metrics.

Each of these corresponds to specific tasks in the management of your paid search campaign, certain options that control your campaigns, and reports that provide metrics which guide the way or measure progress. (Watch future posts for details.)

Why the Change
The driving factor in moving to a High Resolution PPC approach is a desire for better returns on our investment of both time and money.

As with any other investment, we control risk by increasing the depth of our visibility and understanding, and then manipulating the options we have at our disposal.

With a High Resolution PPC approach, you regain control over your paid search campaigns, both in terms of having vastly better visibility into what is happening but also by understanding why specific results occur and how you can fix or improve them.

Next Time
In the next post on High Resolution PPC, I’ll dive a level or two deeper on the target-value-satisfy-understand process. This mental shift is the cornerstone, and once you start thinking about this logical flow in your paid search marketing, it becomes a lot easier to use the options in the engines more strategically.

{If you’re at shop.org in Las Vegas this week, stop by and say hello – we’re in Booth 115.}

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.