Google has a bidding methodology called Budget Optimizer that attempts to maximize the traffic you receive for the keywords in a campaign. This is useful for early buying cycle keywords. However, every keyword should be reaching some goal regardless of where it falls into the buying cycle. It was difficult to track the effectiveness of these campaigns until recently when Google made some changes to Google Analytics.

Now you can more effectively bid on early buying cycle keywords, or keywords that you want exposure for, but do not have direct returns by combining the new Google Analytics goals with a budget optimizer campaign.

Google Analytics changes explained

Google Analytics expanded the number of goals you can track from four to 20. However, it looks a bit different as you now have “goal sets.” Where each goal set has 4 goals, and you can have 5 sets per profile.

Second, Google added two additional goals:

• Page views per visit
• Time on site

Please remember with Google Analytics, time on site actually means time on site minus the last page visited, as Google analytics only tracks data when there is a click. For instance, if your site visitor exhibited this behavior:

• Page 1: Time 5:00
• Page 2: Time 2:00
• Page 3: Time 1:00
• Exit via closing the browser window

In this example, Google does not know the browser window was closed and that they should stop tracking time on site. Therefore, Google Analytics would report 3 page views and 7 minutes on site for this user.

Using goals to measure branded or early buying funnel keywords

I’m a fan of bucketing keywords by where they fall in the buying cycle. If someone is in the learning phase of the buying cycle they need an informational page. If they are in the buy section of the funnel you need to monetize the click by encouraging them to buy.

This creates situations where keywords (and often display or content ads) reach a user who is at a different point in the funnel than the ads you’re displaying and you might not be able to monetize the user—at least for now.

For instance, the keyword “plasma vs LCD TV” is a learning cycle keyword. Buying a high-end electronic device is expensive, and takes thought and time before even beginning initial searches, much less actual purchases. Therefore, this keyword will rarely lead to a purchase as its a research oriented search. However, that does not mean it’s a bad keyword. When you have keywords that describe your products or services, but cannot be directly monetized, you have three options:

• Set a different conversion goal for the keyword, such as a newsletter subscription; and then set a value for what a newsletter subscription is worth
• Use an attribution management bid system
• Use a budget optimizer campaign

Use budget optimizer campaigns to increase your exposure

The budget optimizer works by your giving control of your bidding to Google in an attempt to maximize the traffic you receive. The optimizer does not care which keywords get clicks, it just cares that your budget is spent and that it gets you the most clicks possible.

The benefits for a publisher who measure RPV (revenue per visitor) are obvious. As long as your RPV is higher than your CPC, you want as much traffic as possible on those keywords. However, for those who sell a product or service, there is a unique way of using the budget optimizer to maximize your company’s exposure.

If you set ROI or profit based bids by keyword then do not use budget optimizer.

If you consider words to have unique values, then do not put those words into a budget optimizer campaign.

However, if you have keywords that, are early in the buying cycle and do not directly lead to revenue, describe your industry and products well but are hard to monetize and you want exposure on because they are words in the news, branded terms or for other reasons then putting these keywords into a budget optimizer campaign can be a useful way to maximize your exposure on non-direct ROI keywords. With the budget optimizer campaign, set a “branding or exposure” budget. The goal of this campaign is to move searchers into your buying funnel so you can monetize them at a later date.

However, you still need to make sure that these keywords are helping you reach goals.

Setting goals for budget optimizer campaigns

If you set a goal for these keywords such as a newsletter subscription or contact, then you should be able to determine what those conversions are worth and then set keyword bids. Therefore, words that lead to those types of conversions should not necessarily be in a budget optimizer campaign.

A few metrics for measuring budget optimizer campaign keywords are:

• Page views per visit
• Time on site
• Video views
• Bounce rate
• Send to a friend
• Bookmark
• Print this page
• Tweet This (or other social actions)
• Download product specs

The above goals do not directly lead to revenue; they lead to exposure and show levels of consumer engagement.

It just so happens that the new analytics goals will let you measure these items much more easily. Follow these easy steps to be able to measure the effectiveness of these early buying cycle keywords:

1. Set goals for the budget optimizer keywords, such as 3 page views per visitor.
2. In Google Analytics, set goals for time on site, page views per visitor, or use one of the expanded goal sets to track the social sharing items.
3. Add early buying funnel keywords to a budget optimizer campaign.
4. Let the budget optimizer campaign send you traffic. It may take up to two weeks for budget optimizer to really get going; have a little patience here.
5. Examine your analytics to optimize your budget optimizer campaign
   • If a keyword is not meeting your goals – delete it
   • If a keyword is meeting other goals (such as newsletter subscriptions) then move it to your normal max CPC or conversion optimizer campaign
   • If a keyword is meeting your budget optimizer goals, but no other goals, then leave it where it is
6. The last step is to measure if your overall revenue is higher while the budget optimizer campaign is running. If yes, then as long as the increased revenue is higher than the money you are spending in the budget optimizer campaign, then you are in good shape. If not, then lower the budget optimizer”s budget.

Every keyword, ad copy and landing page should increase revenue. If it does not, it needs to go away. However, you cannot always measure direct revenue for every keyword or traffic source.

Therefore, you should set appropriate goals for a keyword regardless of where it falls in the buying funnel to make sure your entire budget is working toward turning a searcher into a customer.

Engage consumers early in the buying cycle, so when they are ready to buy your company has already been part of the conversation. However, do not just spend money to receive clicks. Make sure every single click is helping to increase your overall profits.

The fourth quarter is “the most wonderful time of the year” for many retailers, and managing paid search programs well through this period requires particular attention to detail.

Let’s take a look at some of the common trends we see in Q4 data and discuss how to, and how not to address these effects through anticipatory bid management.

We’ll use actual data from one of our client’s first holiday season with RKG to highlight some of the common phenomena. The first holiday season is always challenging, because we don’t have data to use to help us anticipate the timing. As such, this data reveals some missed opportunities that we can model the next time around.

On each chart 100% means the average week between mid-September and mid-October. Lifts above or below reflect the week’s changes from that norm. We’re using “sales dollars” as a proxy for value because it is the most widely used. A better metric is margin dollars with frauds and cancels knocked out.

Newsflash: Sales go up at holiday!

This happens for two reasons:

• Traffic volume increases. More people search, more people buy => higher PPC sales and advertising costs.
• Shopping behavior changes. Not only are there more consumers in the market, their propensity to buy and how much they buy fluctuates throughout the period.

It is this second factor that allows us to bid differently, and makes anticipatory bidding imperative. An increase in the volume of traffic by itself does not change the value of the traffic or what we can afford to pay for each click; it is the changes in the traffic’s value that allow for bidding adjustments.

So, yes traffic volumes spike:

But it’s the change in conversion rates and average order sizes that is interesting and actionable:

(There is undoubtedly social commentary to be made over the fact that AOV dips at gift giving season—we spend more on ourselves than on our loved ones?—but it’s also important to recognize that discounting leads to thinner margins which may in turn demand different efficiency targets.)

When we roll these phenomena together we get the true picture of changes to the traffic value over time.

If the goal is to maximize sales during the period at the same efficiency as normal then we should push/pull bids proportionally to the changes in traffic value. That way we maintain constant efficiency, and generate the most sales possible. (Folks who budget search instead look to spend the budget at the lowest cost to sales ratio possible. This is a totally different problem, and, we think, the wrong approach to paid search.)

So, how did we do?

Not bad, given that we didn’t have good data to use to help us anticipate the changes. From this perspective it looks like we may have overspent just a touch the first two weeks in November, and may have underspent a bit the week of the Christmas holiday and the week after.

But hold on! This view ties the clicks and costs on a given day to the sales that happen that day. We know because of order latency that many of the orders placed today came from clicks on ads long before. This suggests we might have actually underspent during the ramp up and left opportunity on the table. So, let’s instead tie the orders to the time of the clicks that drove them and see what that reveals.

Well, it’s not an entirely different picture, but it is slightly different. By this view we were pretty much on target for those first two weeks in November, and it was the two weeks after that where we may have left a bit of opportunity on the table. Good to know! We’ll use these insights this year to do our jobs that much better.

Some folks out there will suggest that you should push the gas much harder early on to catch consumers in the “early phase of the consideration cycle.” I’ve heard folks say they’ll increase their cost to sales threshold by 50% or even 100% prior to the real increase in conversion rates, arguing that those “inefficient” weeks will appear very efficient when viewed by the orders those clicks seeded. I say: if the data from previous year supports that, go for it! But we haven’t seen shifts that dramatic, or anywhere close.

One other pitfall to avoid: Black Box bidding systems that don’t allow for anticipatory bidding. We see data that looks like what’s below every year from agencies that allow the algorithms to do it all, and every year the algorithm reacts too late during the ramp up and overspends greatly after the holiday ends.

These folks didn’t fish enough when the fish were biting, and fished too much when they weren’t. Overall, they may hit their efficiency targets, but they won’t end up with as many fish as they would have had with a smart analyst at the controls.

No two retailers will show the same trends, so let your data be your guide.

Here’s to a profitable Q4!

I went to a party last week. It was put on by a big online player, mainly to thank agencies who buy large gobs of display ads for their clients. And strangely, one of the hosts began apologizing to me (over the gurgling sounds of me thanking him for the free drink—how they let me in there, I’ll never know). “As an individual, between you and me, I’d never advocate a lot of this inventory. Hey, I come from the performance side. I worked [in a senior position for a search advertising platform].” But in his current role, he was doing a pretty good job; thanking the buyers of digital display media is a fun job, made easier by their rampant demand for it.

Search ads sell themselves with performance, to those who obsess about it. Venue: spreadsheet or analytics interface. Brain usage: left brain, mostly.

In a funny way, display also sells itself, to agencies and advertisers who—for other reasons—just plain want it. Venue: the social scene. Brain usage: right brain, mostly.

Are those two worlds about to collide? Maybe they are, and it could be the death of those thank-you parties. You guessed it. The display people are now armed with spreadsheets, analytics and attribution models. And while the search nerds go rock climbing to beef up the neglected studly parts of their personas, the guitar players, prom queens, and jocks at the agencies want into the nerds’ world. Armed with slick studies and recently-purchased designer specs, they’re banging on the door of performance marketing. It’s high school in reverse!

But are there really lenses in those glasses? And are the new attribution models favored by the display people making any sense?

One of the got-good-grades analytical types, Wister Walcott of Marin Software, doesn’t think so. At SMX East recently, he threw down the gauntlet. At 6-foot-8, Wister is a nerd you don’t want to mess with.

Leaving display aside for now, and focusing just on the paid search side of the equation: a lot of people now believe in the myth that for accurate bidding, you would need to look at clicks prior to the last click. Walcott, using data from brand etailers Marin Software works with, busts that myth.

Problem: 74% of purchases can only be attributed to a single click anyway. By definition, that’s the last click. Attempt to “attribute” that purchase to prior clicks or other factors? Good luck.

Beyond that, when multiple clicks can be tracked, you don’t find confirmation of the convenient “purchase path” fairy tale that people begin with one type of search (say, a generic term) and wind up with another (say, a specific branded term). Some buy cycle behavior may resemble this stereotypical model, but on the whole, the real picture of what influences people is much more complex than that.

So the next revelation: when you bucket keyword queries down into distinct types, only 7% of sales can attribute significant influence to some kind of click other than the last click.

Ergo: unless you’ve got some awfully compelling evidence to the contrary, paid search marketers, don’t be dislodged from your current practice. Which is, as you know, relying on performance data associated with the last click prior to purchase.

To be sure, there are probably several shortcomings to this case study. It makes no attempt to latch onto users over extended periods of time, doesn’t refer to a variety of potential influences such as email, direct navigation, display ads or even organic search.

But that scenario mirrors the real-world optimization environment you work in as a paid search marketer. The choice is clear: you can react as best as you can to (admittedly imperfect) data that is pretty close to 100% certain, or you can rebalance your keyword spend portfolio based on little more than hand-wringing and hearsay evidence.

So what might be “compelling evidence” of purchase behavior being influenced by various touchpoints? Don’t expect consensus here, but do stick to your instincts.

Former Canadian Prime Minister Jean Chretien perhaps said it best: “A proof is a proof. What kind of a proof? It’s a proof. A proof is a proof. And when you have a good proof, it’s because it’s proven.”

Incoherent babble, on one hand. But it aptly captures the determination to stick to your guns, for now, when you suspect you’re in the process of being bamboozled.

And how might we gather better evidence to better confirm our suspicions one way or the other? Two ways: by trusting complicated studies that aggregate other people’s results, or by gaining better tracking capability and looking at your own analytics data.

Most advertisers employ popular analytics solutions (and paid search platforms with reporting) that lack the capacity for multiple attribution. When current analytics tools make this new functionality available to the wider marketplace, you’ll get closer to being able to verify competing claims for yourself—as long as you understand how the technology works.

For maximum accuracy and comprehensiveness of user behavior tracking, these solutions are likely going to have to come from huge companies like Google that have access to more behavior data. Since the DoubleClick acquisition, and as their content networks and exchanges gain reach, their potential to develop a tracking standard has increased even more. That said, this will run up against privacy issues, especially in international markets.

I suspect it won’t be much longer that we’ll all be fumbling along using ecommerce attribution data from Google Analytics’ quirky means of tracking behavior from multiple sources, comparing it to our stats in AdWords, and wondering if there isn’t a better way to track things, and to customize our models.

Prediction: since some competing vendors have already raced ahead in this regard, then it won’t be much longer before Google plays catchup. Remember, buyers and sellers of media have often sought a mutually-agreed standard to audit performance: that’s what the “DoubleClick era” was all about back in the day. As with analytics generally, a shakeout is inevitable here. That shakeout will accelerate when Google releases products that address the new debates about multiple attribution.

I hope I’ve piqued your interest in this debate, but it’s just getting warmed up. Next time I’ll identify and assess the four major “camps” in the attribution wars.

Each report in your AdWords report helps you to extract data from your account so that you can make meaningful decisions to optimize your campaigns. In part one of this 6/90 series, I looked at six reports which will help you make ninety percent of the decisions you need to make on a day-to-day basis to manage your AdWords account. In part two, I’m taking a deep dive into the keyword report, as it contains so much data that can help you make good decisions it deserves its own article.

Setting Max CPC

If you use the AdWords conversion tracker you can see your conversion metrics, such as cost per conversion, ROI, total conversions, and so on for every single keyword. This is the data that you will use to set max CPCs for every single keyword in your account.

My favorite column in the report is called value/click. This is the total revenue that a keyword brought to your company divided by the number of clicks that the keyword received. Essentially, it’s your break even CPC cost. If you bid based upon ROI, then the formula for setting a bid is:

Max CPC = (value/click) / desired ROI.

For instance, if your value per click is $2, and you wish a 200% ROI on your account, then the formula is:

$1 = ($2) / 2

If you have a hard cost of goods, then you need to take margins into account before you see your true value per click. If you are a profit based bidder, you will use different formulas for determining your bids; however, the starting data is the exact same as ROI bidding.

When you are making bid changes, you should do so based upon hitting your goals. The easiest way to see how all your keywords are performing is to use the keyword report combined with the AdWords conversion tracking script.

Understand your Quality Score

There are many times it is more profitable—and smarter—to work on raising your quality score over raising your bids. If your quality score is under 5, then you shouldn’t even be worrying about your bids. If your quality score is five to seven, then you should be working on both. If your quality score is seven or higher, then you will have to make most of your rank changes based upon changing your max CPCs; however, you should also be testing ad copy for both quality score and conversion purposes.

Quality Score is kept at the keyword level for search. If you have a large account, it can be difficult to find the best places to start working on Quality Score. This is where pivot tables can help. Run a keyword report and include a minimum of keyword, quality score, impressions, and spend. Next, put the data into a pivot table so that you can see the average of quality score and the sum of cost for each ad group:

Please note that this is an average of all the keywords within an ad group. If your keywords have very different impression rates in an ad group, rather than using the average of all the keyword quality scores, instead add a column to your keyword report that is call Real QS that is calculated by the formula (quality score * impressions). Then in the pivot table, divide impressions by Real QS. This will give you the average quality score for your ad groups, normalized by impressions.

Now, look for ad groups with low quality scores and high spends. In the above example, you would make much better use of your time working on the ad group that has spent $20,874 with a quality score of 5 than ad group 1 which has spend of just $25 or ad group 12 that has an average quality score of 7.12.

When you find ad groups that have high spends and low quality scores, examine the quality score factors to see which ones you can improve. If you can raise your quality score from 5 to 7 in ad group 11, you could save yourself a few thousand dollars.

Please note that this one of my experimental accounts. Yours should not look quite so consistent with so many ad groups having exactly a 5 quality score.

First page bids

The first page bid is an estimate of how much you need to bid for your keywords to appear on page one in all the geographies your ad appears. If you are advertising to a small region, then the first page bid is fairly accurate. The larger your geography, the less accurate the first page bid becomes. For instance, if your first page bid is $1 in Fargo, ND but $3 in Chicago; and you only bid $1.25, then your ad will be on page one in Fargo, but beyond page one in Chicago.

Unfortunately, you cannot see first page bid broken down by geography—Google provides just a single number per keyword. In the above example, Google would display $3 as the first page bid as that this the highest number across all geographies even though a lower bid would make your ad appear on page one in less competitive geographies.

While you should set bids from performance data, and not just raise bids so that your ads are on page one, there may be cases when your keywords never get enough page one exposure for you to know if those keywords would perform well on page one.

Use this report to look for places where your first page bid is below your max CPC. You can use conditional formatting in Excel to easily see what keywords are not on page one.

Deciding what keywords to pause, delete or move

If keywords are not performing, then you should pause, delete or move them to a budget optimizer campaign. If you set bids by ROI, these would be the keywords whose bid would have to be at or near $0.00 as they do not directly lead to conversions. Please note, just because a keyword does not directly lead to conversion does not mean its a bad keyword. You will have keywords that start someone down the buying funnel, but as they are not the last keyword clicked the words will appear to have a zero ROI.

If you see the message, “This account is nearly an unmanageable size,” it is an indication that your are reaching your account’s keyword limit. If you wish to keep adding keywords, you need to pause or delete some first. When you run a keyword report, there is an option under “filter your results” to include keywords with zero impressions. Run a report over a long time span and then look for keywords that have never received an impression. These are the keywords that you would want to delete in order to make room for new keywords. If you have a seasonal business you may wish to pause seasonal keywords instead of deleting them so you can unpause them when their season returns.

Each keyword you choose to use in your account should help you reach your marketing goals. It is essential to understand how each keyword performs, converts and helps you achieve your goals. When you want to know detailed information about any keyword, the keyword report should be the first place you look to see the appropriate metrics. The one exception to this rule is when you want to see the search query that triggered your keyword. For that information you should use the search query report.

You can have these reports automatically created and emailed to you as a reminder it’s time to examine keyword level data. You should regularly examine your quality scores, first page bids, and max CPCs to learn from your account, and make adjustments as necessary so that you can extract the most value from your AdWords account.

Many times we’re asked to present a plan for the next 30 – 60 – 90 days of a paid search program. This makes a great deal of sense when we bring a new client on board and have to fix or re-build their program. It takes time to build out a program comprehensively and laying out the priorities helps manage expectations. After that point that request for a “vision” or “plan” reveals a fundamental misunderstanding about the nature of paid search marketing.

Paid search is an amazingly powerful channel for capturing existing demand. It is not a demand generating channel. Like the yellow pages people only see the ads when they’re in the market for the advertiser’s products or services. Yellow page ads don’t make people interested in taking yoga; they convince people who are interested in yoga to try the advertiser’s studio. Paid search plays the same role, but it’s easy for marketers steeped in traditional channels to miss the implications of this fact.

For demand generating channels planning is of paramount importance. Television ads seek to 1) create awareness of a brand; 2) infuse that brand awareness with positive connotations; and 3) catapult that positive awareness into action. Marketers must plan the proper messaging and imagery for each phase, and plan the timing and budgets. Even direct marketers like catalogers must plan contact strategies, page counts and formats, circulation counts and frequency of touches. Planning is required because the marketer must generate interest and action, and the time lag between marketing investment and eventual payoff is both long and not guaranteed.

Paid search is different in every respect. Budgets don’t make sense for advertisers with shopping carts on their sites because the sales happen before they pay for the ads. We don’t have to plan what products to push or when; the ads will be served to the right audience at the right time and in the right volume to respond to consumer demand.

This is not to suggest that paid search requires no work. Paid search demands well honed processes for dealing with product turnover, landing page changes, promotional offers, seasonal shifts and more. Skilled analysts study data six-ways-to-Sunday to find nuggets of gold in search logs, in click-to-order intervals, and in new classification schemes that feed statistically meaningful differentiators to our algorithms. Reacting to shifts in consumer behavior and anticipating them whenever possible takes knowledge, skill and mountains of well-organized data.

However, it doesn’t really require a plan. Indeed, predicting what projects will be most valuable 30 days from now, or 60 is both impossible and unwise. The priorities change depending on all kinds of factors outside of the analyst’s control. Locking an analyst into an arbitrary schedule prevents them from adjusting to the priorities of the moment and thereby squancders opportunities.

Asking an analyst for a long range plan for a paid search campaign is like asking your stock broker what stocks you should buy and which you should sell 6 months from now. They can make those recommendations if you really want them, but usually you’d be wise not follow them.

Absence of “a plan” is unsettling, particularly when you’re working with an agency. You can’t see them hard at work at their desks every day, so it’s natural to wonder whether they’re asleep at the switch. This fear is compounded by the reality of PPC agencies that all too often are asleep at the switch.

Trust comes from results, and in PPC results come from smart people with great tools and great processes. Anticipating and reacting to changes in the landscape requires hard work, knowledge, skills and the flexibility to follow one’s nose.

Paid search accounts for about 50% of all digital advertising spending today in most major markets, give or take 10% (the UK clocks in as one of the most impressive English-speaking markets for paid search, clocking in at 58% of digital spend, according to econsultancy).

For we diehards, the reasons for running paid search campaigns are obvious. Believe it or not, though, many companies have failed to make the leap, or have only dipped a toe in the PPC waters. There is still much untapped potential in this channel.

So what’s holding people and organizations back? Perhaps it’s myths about click fraud, market size or performance. Perhaps weak real-life performance in pilot attempts. Perhaps a lack of in-house capability. Or (yes I said it) an ongoing SEO bias in the industry.

Whether or not you “do SEO,” you do SEO already by virtue of being indexed in Google and keeping track of whether that’s getting you any traffic or revenue. So in terms of incremental marketing dollars that need to be found in company budgets, clearly most of the untapped potential action is on the PPC side.

But the majority of the people doing SEM, and most of the industry chatter, Sphinns, etc. (80+%), are all over the organic search side of things: about links, redirects, how to deal with universal search, canonical-whatsitcalled and so on. It’s not unimportant, but I still think it’s disproportionate if you take all of that insider water cooler chatter at face value. That gang, and your developer or IT department, are probably going to tell management a lot of evocative tales about the power of organic search and analytics related to that. Think they’ll steal their own thunder by bringing up the urgent need for paid search? Don’t count on it.

Maybe, finally, it’s a lack of sizzle and excitement. Paid search still isn’t sexy for some reason. But profits are.

Let’s look at seven reasons launching (or revisiting) a PPC campaign is a must if you’re going put some sizzle back in your life. Or at least into your marketing campaigns as we anticipate an economic rebound.

1. Universal search will continue to play havoc with your SEO traffic assumptions. Do you want to “rank” in the theoretical world of an index of billions of pages, often winding up no better than below the fold or on page 2 or 3 of SERP’s, or drive additional, predictable traffic to offers you create directly, each and every day without fail?

2. A huge chunk of Google’s resources goes right into developing the paid search marketing platform, features, systems and services. Why not use them? They include: keyword research tools;  customer support and even industry research support, depending on agency status or advertiser size; advanced delivery and segmentation features like dayparting and geotargeting; advanced filtering methods like IP blocking, site exclusion, negative keywords, and more.

3.   Custom reports and analytics out the wazoo. All free. Want to get a breakdown of the return on ad spend for your New York State geo-targeted campaign, or to see a breakout of the number of clicks and conversions that came in the content network from parked domains? Want to see which of eight ads pulled the best CTR? That’s all in the AdWords back end. Try getting such actionable analytics from the, uh, “organic SEO helpers” division of Google.

4.   Content targeting has gotten gradually better each month… for 36 months straight. Suddenly content’s an overnight success, but it didn’t get there by sketching it out on a napkin. It’s taken years of Google turning the flywheel, optimizing each part, to increase the program’s scale and to up the average value per content-targeting click paid for by the average advertiser. Another hugely convenient channel with more volume and less risk than in the past. And wait! There’s more! Google has entered a game-changing new world in display advertising, rolling out the DoubleClick Ad Exchange. That’s integrated with AdWords.

5.    Good guys get special favors. Are you a real company? You’re in luck.

• Google has taken steps to reduce the participation of some business models, like thin affiliates who compete with you for eyeballs on the same queries, or business owners with shady privacy policies;
• Google proactively filters click fraud, and actively polices and reduces payouts to rogue publishers in the content network;
• Display URLs and strong brand recognition help with Quality Score—Google seems to have tuned the system to help brands that consumers are more likely to deem “reliable” and “clickworthy.”

On the other hand, Google doesn’t bend over backward to protect your trademark, especially not if that reduces other advertisers’ choices. When it comes to the ecosystem, Google can be schizophrenic, but again, on the paid side at least you can pick up the phone and call someone.

6.   Transparency. You may not want all of it, but new tools like the Bid Simulator keep rolling out. The search engines are committed to giving you fuller information about many auction details. They’ve even rolled out a video of Google’s Chief Economist Hal Varian commenting on bid strategy. Think you can get an SEO position simulator tool out of the “organic SEO helpers” division of Google? (There isn’t one, remember, although to be fair, Google Webmaster Tools is pretty neat.)

7.  Rapid feedback and rapid results with less risk. There remains no better mechanism to gain rapid response to different ad copy variations, to gauge consumer keyword search patterns as they apply to your business, to learn about geo-specific buying patterns, etc. There is far less risk to testing offers, page layouts and marketing strategies rapidly—using paid search—than there is to tinkering with the nuts and bolts of your site’s content and architecture in the hopes of a medium to long term boost in organic traffic. SEO success is, for many companies, an after-the-fact pat on the back for years of a job well done. It is difficult to ramp up quickly. Paid search, by contrast, scales up quickly, and particular segments and tactics can be tested with relative ease.

Given the large spends now going into non-traditional promotion, paid search and digital marketing generally, we no longer need to advocate for dollars to “migrate” to these channels. Most big companies are in the process of figuring out how to migrate some dollars out of their bloated traditional ad spends. But in the process of ramping up paid search priorities can get mixed up, campaigns can languish, and no one around the company seems quite sure what needs fixing most urgently.

There are many hurdles to doing this right, which just makes the reward sweeter for those who do a lot better than their competition.

And for smaller companies, it sure is tempting to hold out hope that SEO and some mythical word-of-mouth can do it all for you. For most businesses in conventional industries that do a lot of their selling online, though, paid search can and should work. It’s about half of all digital ad spend for good reason. Trying to acquire those same customers through other channels, especially offline channels, will typically be costlier.

Paid search isn’t sexy. Nor is it tailor-made for penny-pinchers. It’s an ROI-driven direct response channel. But it’s worth the effort if you see it through! It beats just about anything short of magic.

Google offers numerous AdWords reports that allow you to view more data than most people have time to analyze. One of the tricks to working with PPC is to determine what data you need to look at every day or week, and then determine what data is useful to analyze when improving your AdWords account.

There are six reports that, when used effectively, can give you the majority of insight you need to analyze your accounts on a day-to-day basis. In part 1 of this two-part series, I’ll take you through these reports to find insight into your accounts. In part two, I’ll take an in-depth look at the keyword report to create actionable items from the data.

While these reports are easy to run they are most effective when combined with the AdWords conversion tracking script. This is a different feature than what you find in Google Analytics. The conversion tracking script sends data from your website back to AdWords so that you can see conversion information in your AdWords reports. In walking through these reports, I’ll make the assumption that you are using this script. If you are not, then you can still use these reports; however, you should marry up the data with the analytics package you are using to track conversions to get a complete picture of what’s going on.

The keyword report

The AdWords keyword report should be your starting place for analyzing keyword data. This report shows metrics by individual keywords within your account. For instance, the main data points to examine when reviewing information by keyword are:

• Impressions
• Clicks
• CTR
• Conversions
• Cost per conversion
• Conversion rate
• Value per click

There are three main uses of this report:

1. Set bids based upon cost per conversion or other metrics with your established bid methodology
2. Find low quality score keywords with high spends so you can optimize for quality score (note: it can be useful to use a pivot table to find AdGroups with high spend and low quality scores. See Josh Dreller’s In The Trenches column about mastering pivot tables for more info).
3. Find keywords that are not on page one (where the first page bid is higher than your max CPC). Remember, though, that just because your keyword is not on page one does not mean you should raise your bid to be on page one. If you cannot be profitable on page one, then you need to decide if this is a word that can be on page two; if not, you need to optimize the landing page, ad text, or other factors for this keyword before you raise your bid to be on page one.

In part two of this article, I’ll take a deep dive into the keyword report to show various ways of working with the data it produces.

The search query report

The search query report will show you the query that was actually typed into a search engine that caused your ad to be displayed. For instance, if you bid on the broad match “coffee mugs,” your ad could show for “yellow coffee cups,” “blue coffee mug” or possibly even “tea cup.”

Use the search query report to find words that are not converting yet are consuming your ad-spend dollars. When you find such words add them as negative keywords.

Then use the report to find words that are converting and are not keywords in your account—consider these to be Google’s gift to you to help you improve the overall importance of your campaign. Add these words as keywords so that you can bid on these words based upon their actual returns. Remember, your broad match keywords will never convert higher than your exact match keywords.

When you conduct keyword research, you should always consult the search query report as part of your keyword expansion methodology.

The placement performance report

The placement performance report is only useful if you’re advertising on the content network. It shows you the sites and individual URLs where your content ads have been placed. The first time you run this report, include the actual URLs where your ad has been shown. Click on the URLs and look at the actual pages where your ads have been shown. If your ad is not being placed on the correct types of pages, then you should examine the keywords triggering your content ads.

If the ads are being placed on appropriate pages, run the same placement performance report again, but do not include individual URLs. By excluding the individual URLs, it is easier to gain high level perspective on how each web site where your ads are being displayed is performing for your business. Alternatively, you can also use a pivot table to examine the domain level information from a report that includes URLs. When you find a site that is bringing you high quality traffic that meets your business goals, add it as a placement targeted site so your ad is always shown there. When you find sites that are costing your money, but the traffic is not meeting your goals, then block the site from showing your ads in the future.

The entire work-flow process for managing content sites can be found in this Search Engine Land article.

The ad text report

The ad text report will show you all the ads that your are using along with associated metrics such as cost-per-conversion or clickthrough rate. Use this report when running any ad copy tests.

In addition, run this report on occasion to find ads that are performing below the averages for your account. Then go to those ad groups and write new ads to test which ones perform better. As you can have multiple ads running in any ad group, you should continuously be testing various ad copy. In addition, if one ad suddenly gets disapproved, you will have at least one more ad running so you will still maintain exposure in those ad groups while you fix the issue.

While most PPC marketers are always looking at text ads, do not forget your video or image ads. Use this same report to see the metrics for your other ad types. If you are running video ads, then you should be uploading multiple static images (with the same video) to see which opening image has a higher play rate, clickthrough rate, and cost-per-conversion.

The URL performance report is similar to the ad text report. It will show you where ad traffic is sending searchers on your website, and the associated cost-per-conversion and other metrics for that landing page. Analyze the URL report just like the ad text report. Find landing pages that are not meeting your goals, and test different landing pages and landing page layouts.

The geographic performance report

This is one of the more overlooked reports in AdWords. This report will give you information about where your ads are being shown and the associated metrics by geography. Even if you are a national advertiser, it can be beneficial to write ads for specific local areas.

One of the quality score metrics is clickthrough rate in a geographic region. If your ads do well in San Francisco, but poorly in New York City, then your ad will be shown more in San Francisco and less in New York City. As the New York City metro area makes up more than 10% of the entire United States population, a lack of exposure in that geography can significantly lower your total consumer base.

In the report, look for regions where you are not doing well and that have significant populations. It’s easy to overlay percentage of population data with the report to spot these regions. For instance, create a chart that shows:

• The regions where your ad is displayed
• The percentage of impressions and clicks you receive from that region
• The percentage of the population that lives within that region

Always take other factors into account when examining population data in isolation. For instance, say you have a physical location in Miami and your ads are not doing well in either city. It’s likely more worthwhile to work on getting your ads to perform better in your local market, Miami, before spending time tweaking your Los Angeles campaign, even through Los Angeles has a much higher population.

When you find underperforming regions, and those regions have a high enough population that you are willing to create a campaign just for that region, follow these steps:

• In your original campaign, exclude your ads from being shown in the new geographic area that you want to target
• Duplicate the existing campaign with the AdWords editor, and then change the geographic area to be the new region
• Write ads that are compelling for that region

If the region is not large enough for you to create a specific campaign for a region, conduct keyword research to see if consumers are using location specific words (such as Los Angeles plumber) in their search queries. If they are you can create an ad group that uses geographic keywords with associated geographic ad copy.

The impression share “report”

Technically, there is not an impression share report. The impression share report is an unofficial name that advertisers have given this report. To see impression share data, you need to run a campaign report, and in the reporting options select these options:

• Impression share
• Lost IS (rank)
• Lost IS (budget)
• Exact Match (IS)

Once you have the report, you will see how many impressions you are losing and why you are losing impressions.

If you are losing impression due to budget, then you can easily determine how many more impressions you would receive if your increased your budget. This is very useful for determining what your account could spend based on the current keywords in your account. If you are losing impressions due to rank, then you need to improve either the bids or the quality score to receive higher placement so these ads are shown.

Setting an AdWords reporting schedule

There is more information available in AdWords reports than you could ever hope to analyze and take action upon within any day. To cope with information overload, first define your business goals. Next, define what metrics will give you insight into attaining those business goals. Once you have defined those two items, then run the AdWords reports which will help you gain insight into those goals so that you can find areas where you need to improve your account.

Then create a reporting schedule based upon when you want to see and act upon the data. You can set AdWords report to be automatically created and emailed to you on a daily, weekly (Monday), or monthly (first day of every month) schedule. If those options do not meet your needs use your calendar to remind you to create reports.

Here’s a recommended schedule that’s easy to work with—though remember, based on your goals, budget and time, your schedule might differ tremendously.

Keyword report:

• Daily – examine changes in cost per conversion, conversion rate, and total conversions.
• Every Monday – examine changes in quality score, find areas of low quality score, work on improving your quality score.
• Every Monday (or daily for large account, highly competitive industries, or volatile bidding environments) – examine keywords not on page one.

Search query report: Every other Tuesday. Conduct additional keyword and negative keyword research.

Placement performance report:

• Every Wednesday. Examine changes in cost per conversion, conversion rate, and total conversions for bid changes purposes.
• Every other Wednesday: Examine sites you wish to block or add as placements.

Ad text report /URL report:

• Every Thursday. Finalize tests or create new text ads.
• Every Friday. Finalize landing page tests, create new landing pages, create new landing page tests.

Geographic performance report: Once a month (assuming you are not a regional specific business, then weekly might be more appropriate).

Impression share: Once a month (weekly or daily during high peak seasons) to help create next month’s strategy of how to improve your account.

Always conduct in-depth audits beyond these reports and use the other reports and tools as necessary. Google offers a tremendous amount of data that you can extract from your account. While these six reports will not give you every detail you will ever need to optimize your account, these six reports will give you 90% of the data necessary to improve your account’s performance.

Lately, there’s been a lot of talk about search without keywords. Recently, the topic came up again at SES San Jose in a keynote presentation from Nick Fox, Google’s business product management director for AdWords. In the presentation, Nick outlined where paid search could be in the next 5 to 10 years and covered two general topics—paid search without keyword terms and phrases and pay per conversion. In this post, I’ll cover the paid search part of his presentation. In my next post, I’ll look at the future of pay per conversion.

Why is search with no keyword terms important?

There are several important reasons why search without keyword terms has recently become important. Some of the reasons for this include:

Longer query length. According to a Hitwise news release, the number of 5+ search queries increased by 10% from January 2008 to January 2009. In the same time period, 2 word search queries decreased by 5%.

Unique search terms. According to Google, 20-25% of search queries in the last 6 months were new queries.

Increased searcher sophistication. In his keynote, Nick provided an example related to cashmere sweaters that demonstrated this point well. He stated in 2007, people searched for cashmere sweaters 47 different ways. In 2008, people searched for the same keyword phrase 73 different ways. It’s becoming a headache for advertisers to anticipate and react to so many different queries. Should advertiser prowess be measured based on mind-boggling attention to long query keyword detail?

Resistance to do-it-yourself advertising systems. Google recognizes that PPC advertising considerations (like keywords, ad copy, cost per click, etc.) can be cumbersome for some advertisers. New methods of connecting advertisers with searchers seem inevitable—especially for those advertisers who don’t like fiddling with self-serve systems.

What would no-keyword search look like?

In the keynote, Nick mentioned that keywords were used as a proxy for relevance. Conceptually, there is no reason an advertiser couldn’t achieve the same results without having to directly manage a keyword list. Down the road, Google wants to state outcomes and have machine-based learning and algorithms come up with the best method of achieving specific outcomes. In the case of no keyword search, an advertiser (like a retailer) would provide information on products, product descriptions, pricing, etc. and Google would use the information to find the most effective way to place ads in front of potential customers.

In his keynote, Nick provided an example related to plumbers: a plumber would provide a list his services and Google would figure out a way to appropriately advertise the plumber’s services. Here’s a possible example of a list of plumber services Google could draw from:

• Faucets
• Bath sinks
• Kitchen sinks
• Bathtubs and showers
• Toilets
• Water heaters
• Water softeners
• Drain pipes
• Sewer lines
• Garbage disposals
• Laundry centers
• Gas vents
• Gas meters
• Backflow prevention

The advantages of no-keyword search

All in all, there are several advantages of no keyword term search. They are:

• Efficiency for advertisers—there would be no keyword research component to a PPC advertising campaign.
• There could be better connections between searchers and advertisers on natural language queries.
• It would allow advertisers to better connect with consumers and capitalize on all relevant advertising opportunities.

These are obviously initial ideas and now Google needs to figure how to make no-keyword search work. According to Nick Fox, it will be some time before Google shares specific product details. Sharing the concepts with the advertising community at this stage doubles as a feedback mechanism and a trial balloon: if too many people hate it, Google can modify its approach. We sure look forward to hearing more on this.

If you’re interested in reading more or chiming in on this topic, check out the Google groups keynote forum.

Interpreting test results for paid search campaigns can be surprisingly difficult. One reason for this is order latency. The fact today’s clicks don’t all generate orders today, but instead sales trickle in over time means that analyzing new launches and tests can be tricky. Two ways to address this complication are described below.

Problem: Successful tests can look bad initially because of order latency

For example, let’s say the order latency for a particular advertiser with a 14 day cookie window looks like this:

56% of the orders come in within 24 hours of the time of the click, 10% come during the next 24 hour period, etc.

So, on that first day you see 100% of the clicks on your ads, but not nearly all of the orders those clicks will drive—actually, quite a bit less than 56%, as clicks late in the day have less time to “mature.” For sake of simplicity, let’s ignore that bit. Doing so allows us to map out what a tremendously successful test might look like.

Let’s say an advertiser launches a new product category and new keyword ads are developed. Let’s say the advertiser’s efficiency target is a 25% cost to sales ratio, and let’s say their brilliant PPC firm nails the bids right out of the gate. The clicks generated on day 1 cost $1,000 and will eventually drive $4,000 in sales, but here’s what the results look like as they unfold spending $1,000 every day at perfect efficiency:

Yielding a day-to-day apparent cost to sales (A/S) ratio that looks like this:

The first few days of the test it appears that the efficiency is way above the advertiser’s comfort threshold. It takes the full duration of the cookie window, for the observed efficiency to match the actual efficiency of the advertising. Advertisers who don’t recognize this effect may cancel tests, or pull back on the rudder too quickly.

Indeed, what this suggests is that every launch and every extra bid push will appear to be less helpful to the top line and more harmful to the bottom line than reality. On the flip side, every pull back on bids will appear to be more helpful to the bottom line and less harmful to the top line than it really is because of the lagging orders from the higher click volumes that preceded the test.

The greater the order latency, the bigger the impact. We typically find that more considered purchases, and higher average order value advertisers have greater latency than average which impacts the proper length for the cookie window.

However, no one wants to wait 14 or 30 or 90 days to read the results of a test. In the example above, the PPC agency hit the bids right on the head from day 1. When that doesn’t happen, it’s good to find out sooner rather than later that you’re undershooting or overshooting.

Two methods for evaluating tests

Shorten the sales window. Instead of evaluating the test based on the full cookie window, study the data based on a same session or one-hour sales interval. In the example above, if 35% of the eventual orders normally come within the first hour of the click, extrapolate the results from the first few days based on that number. If the ratio of cost to (observed 1-hr sales/0.35) is on target, the test is probably on target.

If an advertiser is attempting to learn the top-line vs bottom-line trade off of bidding to a 30% A/S target rather than a 25% A/S target, compare the % increase in 1-hour sales to the % increase in cost. That should be a pretty good proxy for the A/S ratio on the incremental sales.

Tie orders to the time of the click. Most reports show the PPC costs for the day, and the PPC sales taken that day. It’s entirely likely that half of the sales taken that day came from earlier clicks. By running reports tying the sales to the time of the click, rather than the time of the order, you get a much clearer picture of what your actions on that day did for you over the long haul. This is particularly useful for studying past tests and anticipatory bidding at the holidays to see whether you anticipated the improvement in traffic quality appropriately.

The problem with the first method is that it assumes the latency for the new product category, or incremental traffic, will be the same as it’s been in the past. Not a bad guess, but potentially misleading. The problem with the second method is that you can’t use it fully until the cookie windows have elapsed.

By using method 1 during the early phases of the test and method 2 after the test is “complete,” a good analyst can avoid missing opportunities and overspending during the test, and get a dead-eye accurate read on the results after the fact.

Over the years, we’ve counseled advertisers to be wary of certain inflationary tendencies that are built into the very terminology and interface design of paid search. Experienced bidders know better but new advertisers can get tripped up.  Inflationary tendencies in paid search auctions include:

• New accounts being opted into content targeting at the same bid as search
• Bid estimators available at the setup phase
• The temptation to ego-bid as opposed to testing and optimizing
• Impatience in waiting out foolish competitors. (You want the house, but do you want it badly enough to pay $700,000 now, when down the street you’ll get the same one next week for $550,000?)
• The new “first page bid” notation in AdWords for lower-position keywords that suggests how high you should bid to stay on the first page of SERP’s (this could be set conservatively or aggressively. You need to take it case by case).

As market psychology shifts, these mechanisms have been less successful in holding up click prices. Advertisers are, in the end, free to bid lower. And, as we’ve seen recently with economic woes, many advertisers have gone into penny-pinching mode.

How can the bid simulator tool help?

It’s at that precise moment that the question arises: but just how low can I bid on a keyword while maintaining a decent ad position? I don’t really know what others are bidding, after all. Google’s new bid simulator tool is designed to answer this question. The tool obviously doesn’t show other advertisers’ bids, but provides relevant information that effectively answers the question indirectly.

Similarly, if you’re an advertiser seeking growth, and want to know how much extra it’s going to cost to make a significant jump in ad position, the tool has data in graphical form to help you answer that question. If it costs you $5.02 on average to stay in ad position 4, and you want to know what kind of price tag you’re looking at for position 2, the estimator will try to tell you (indirectly). It shows you lists of projected impressions at various price points, and you already know what your current ad position is. So, if you see that a significant increase in impressions will occur above $7.00, that may look like a decent tradeoff. If you see that a breakout in impressions and clicks (indicative of a significantly higher ad position) only occurs at $16.00, you’ll likely say “thank you very much, but I think I’ll stay where I am.”

The projections are based on the last 7 days’ worth of data for that keyword (on my wish list: longer time frames so low volume keywords can be eligible, or the ability to group keywords for projection purposes). Of course, past performance doesn’t predict future results, but by showing factually what would have occurred with a different bid, the prediction is likely to be in the ballpark. Here’s a screen shot from Google’s examples. It shows nothing dramatic, but you can see that jumping from the $2.10 per click range up to $6.36 or even $5.26 would be a pretty steep price to pay to gain a small amount of extra volume. Literally, it’s a steep pricing curve.

Real world examples: how pliable is the auction?

The next example, taken from a client’s account with keyword data disguised, shows the subtle tradeoffs involved in seeking the right bids and positions in a relatively competitive, high-cost auction. By spending 41.2%  more per click, we would have received 12.9% more impressions. But because those impressions would have been out of higher ad positions, the projected clicks rise more dramatically—by 44.4%. There’s no question that nearly any bid increase will lead to more costly CPA’s (lower ROI), but for those seeking increases in volume, the simulation can be helpful in gaining an understanding of just how pliable a particular auction is. And this information is richer than average ad position, in the sense that an average ad position of 1.9 could still be showing you in 4th and 5th spot more often than you realize, so your lower bid is costing you more volume than you might think.

Next, here’s a lower volume example from a less competitive auction. Not knowing what type of drop in volume we’d experience if we went with lower bids, we always kept to a relatively high bid, just to stay safe. The simulator tool tells us there is little buying support well below our current level, so economizing by dropping bids significantly is a good bet. In fact, at $2.21, the current bid looks kind of silly. The fact that the yellow dot, denoting our bid, is vertically on a y-axis above the next green dot in the plot on the graph, basically says we’ll see no volume decrease and no change in position until we drop to $1.54, and there, the drop is only slight. “Dude, just lower your bid to $1.54,” the tool seems to say. Thanks, dude.

Caveat: with low volume, we get an impressions prediction only, not clicks. So clicks could decline more dramatically than expected if you make big changes suddenly.

Finally, there are all too many examples of auctions that show significant opportunities to double and triple click volume, but the bid ranges to achieve that seem to stretch up and up and up, to ever-growing levels of insanity. From our current bid of $3, next stop $6. For a bit more traffic, next stop $8. Next stop after that, $13, and finally, you could really max out clicks by going over $19. All else being equal, that means someone’s probably chasing bids of $15 or more in an auction where we figure a click is worth around $2.50 with major pain starting at $4.00. Yikes! What are they doing? The bid simulator saves a lot of time here too. Experimenting over time to see how much money you’ll need to bid would be a big waste of time. Stand pat, or go up or down slightly, is the solution in many of these cases. There’s no point in chasing rainbows.

If you want to change your bid instantly while viewing the graph, you have the option of clicking on the presets and changing your bid, making either subtle or dramatic changes in positioning strategy. Or, you can enter your own bid if you don’t like what the presets say. I recommend often entering your own bid, because I like gradual bid moves. In general, projector tools don’t do a good job helping with real-world “walking up” and “walking down” methods that many of us have cautiously used for years (we make smaller bid changes over time, for various reasons).

Reasonably accurate projections—geared to the specific auction conditions and real time competitive bidding scenario in each keyword competition—are a great advantage over previous guessing methods. Before, it would simply take more time to gauge the impact of bid changes. You’d need to make the change and monitor the effect closely. With the bid simulator tool, you may be able to save time if you’re aware that there is little “buying or selling resistance” below or above your bid. In specific cases, advertisers can get away with making more dramatic changes.

Simulator beware

Back when I had more time, I used to play with a video flight simulator. Sometimes the simulator indicated I had successfully landed the plane. Even if I didn’t crash, under no circumstances would it have been wise for me to think to myself “say, I can fly a plane!” I’m no pilot.

Looking at a simulation is just that. Changing bids is, in the end, a serious business. Think about the information, and act intelligently on it. Don’t “believe” everything you see.

Is Google shooting itself in the foot?

Industry-watchers never tire of citing the flaws in AdWords. But anytime you go over the wish lists we’ve put forward over the years, you can easily point to the many feature requests where Google not only obliged, but exceeded the asked-for functionality. The bid simulator is a pretty radical step, in that it takes an apparently unfixable shift in the auction methodology (from a straight auction under GoTo, with all bids public) to a proprietary algorithm that includes bids as well as relevancy factors under a sealed-auction scenario, and appears to do a decent job of providing usable competitor information without revealing anyone’s private info.

It’s worth noting, on that front, that this feature first surfaced in a similar simulation offering released by Yahoo Search Marketing with its Panama release. Credit Yahoo with that first attempt at auction transparency.

By being so transparent in a recession, though, isn’t Google practically begging us to fix inefficient bids? If we see limited buying resistance below us, won’t we accelerate our bid decreases? Is Google trying to ruin its Q4?

Google would likely not persist with any feature or auction mechanism that was particularly biased against Google’s profitability in the medium to long term. In fast-moving retail, especially as the recovery unfolds in 2010, many advertisers will probably use the bid simulator to figure out the best way to raise their bids, not lower them.

So like most observers, I won’t worry too much about Google. In the end, only a small percentage of advertisers will actively use the simulator. And as Google diversifies its revenue stream, they know better than you and I whether their next few quarters of growth are looking smooth. Growth in average CPC’s may not be in the cards near term, but overall revenue growth is likely to elevate gradually from “flat” to “steady.” And that is of course from an incredibly high base that’s currently north of $20 billion per annum.