ClickEquations Blog

The world of paid search has changed dramatically over the past 3-5 years.

The PPC management techniques that were appropriate a few years ago are woefully inadequate now. But not everybody is living and working in 2009.

Are you stuck in the past somewhere?

Here are 10 signs a paid search strategy is stuck somewhere around 2003-2005:

1. Keyword-Centric Mindset
   Keywords have long been seen as the center of the paid search universe. But keywords only exist to attract search queries – the words and phrases searchers actually type. You should be more worried about your query list than your keyword list.
2. Large Ad-Groups
   Every keyword related to a single subject used to get lumped together in one large ad group. But a far better strategy is to create small keyword groups which focus on matching searchers to relevant text ads.
3. Categorical Campaigns
   Campaigns have long been used to organize ad groups and keyword by category – often mirroring the navigation of the target website. But broad and deep campaigns provide roll-up numbers that are devoid of meaning. It’s far better to organize campaigns around topical AND performance similarities so the reported metrics really mean something.
4. Minimal Ad Testing
   Have two or three text-ads per ad group that have been there untouched for months? Testing better text ads can improve click-through-rates by 2x, 3x, even 5x.
5. Lots’a Broad-Match
   Broad Match makes it easy to connect with everybody who might be interested in your keywords. Except many of these folks have little or no value to you. Use Broad Match as research and shift your money and keywords to Phrase and Exact Match as much as possible.
6. Very Few Negative Keywords
   Zero negative keywords? Less than 5 or 10 negative keywords per ad group. You are a generous person who helps the economy by paying for clicks every day that have no chance of ever making you any money.
7. Never Check Impression Share
   Your ads aren’t showing for the keywords you’re bidding on, and you don’t even know it. Keeping a close eye on all four Impression Share metrics should drive many opportunities and priorities.
8. Brand Terms Everywhere
   Your brand terms are intermingled throughout your ad groups and campaigns. Since you don’t separate the keywords (and use negatives to equally isolate the queries) all of the reporting numbers in your ad groups and campaigns are compromised.
9. Irrational Faith in Bid Management
   Your software provider or search engine has ‘bid automation’ which you count on to handle bidding. You’re not worried about problems with revenue attribution, sparse data,  offline conversions, multiple success events, etc.
   
10. ROAS-based Targets
    You measure performance and make decisions based on the ROAS, not the ROI of your ad groups and keywords. By ignoring the realities of cost-of-goods everything seems better than it is and decisions aren’t based on actual implications.

The list above represents a ‘low resolution’ view of the world that just isn’t accurate or adequate anymore.

What do you do if this describes you or someone you know?

Clearly there are things to learn and better decisions to be made on each point. But more broadly, I think it requires a new level of technical understanding, a new operating philosophy, and in many cases better management and reporting tools.

Many of these topics have been discussed in greater detail in earlier posts.

In the next few weeks I’ll be releasing an e-book called ‘High Resolution PPC’ with a new framework for managing and understanding paid search in 2009.  (Reserve your copy now)  It has many goals, but one is to help everyone get out of 2003.

If you’re going to buy the same keyword multiple times with different match types assigned, how should you organize them?

Buying the same keyword more than once, with different match type settings, is an idea we like, as explained in our Match Type Keyword Trap series.

But this practice begs the question – should the same keyword appear more than once in the same ad group, or should you split them into different ad groups?
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Separate But Equal
In terms of the effectiveness of the keywords at their match types it doesn’t matter. Google will match them appropriately no matter where you put them.

But I favor splitting them into separate ad groups for five reasons.

1. It’s easier to match search queries to text ads. This is the name of the game, and each keyword will attract different queries based on the different match types. So can you write better ads knowing that some of these queries will be exact, some will use the phrase, and some will be all over the broad-match-place? Probably.
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2. Reporting is easier to digest (pt 1). If you’re a search query freak like me, and have a great tool like ClickEquations that shows you nearly every search query, it’s easier to scan the queries in an ad group to see if they’re all appropriate and uniform in content and nearly so in performance if they’re segregated by match type.
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3. Reporting is easier to digest (pt 2). The roll-up data and averages of any ad group are only as worthwhile as the consistency of the performance of the keywords that make it up. Diverse keyword groups produce statisics-of-questionable-value (SOQV as it’s known in the trade). Broad match keywords perform very differently than exact match keywords and I don’t find it useful to see the average CTRs or CPCs or CPAs of them rolled-up together.
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4. Quality Score should be better. By the letter of the law on QS, we want high-as-possible CTRs and tight query-keyword-adgroup-landing page relevance. Both should be slightly better with segregated ad groups – although as with all quality score details, there is no way to prove this!
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5. Reporting is easier to produce. Google does not provide a macro to automatically tell you the match type of a keyword as part of the destination URL. This is one of the few areas where Yahoo and MSN have something Adwords does not (intentionally on the part of Google we can be sure). Therefore if you want to track, measure, report on the performance differeces of your various match types, it’s a lot easier if they’re in separate ad groups. There are other solutions, but this one is the simplest and most robust.

This is not a big deal. For many people, or even in certain situations within a campaign, repeating the keyword in a single ad group makes sense. But if and when possible, I split them out.

Note: This post was inspired by comments made on a recent PPC Rockstars with David @Szetela Podcast. These shows have become a regular part of my commute, and I recommend them highly! (Even the occasional ones when I’m an guest.)

Revenue attribution is how you (or the software tracking your online marketing activities) decides where to place the credit for the sales that occur on your website.

If someone who has never been to your website before does a paid search, clicks an ad caused by a keyword you bought, then makes a purchase, the attribution is easy. They keyword that you paid for to get the click, should get credit for the revenue generated by the purchase.

But very often, this is not the scenario that leads to conversions which take place on your site.

• People come multiple times before purchasing.
• They often come from different sources each time the come, occasionally repeating sources along the way.
• They sometimes make a series of purchases, either after all of their visits or interlaced among their visits.

These are just a small sampling of the issues and don’t begin to define or describe the complexities.

And this is not the post where I’ll try to do either. (Those will come.)

But was we work to sort out the right way to handle revenue attribution within ClickEquations, we’re capturing some data that I thought it would be interesting to share.

The following images document real-life ‘click-chains’ – sequences of visits to a website with resulting or intersperced conversions. They are a tiny tiny fraction of the sequences found in one account in a 30 day period.

• Rows with green ‘P’ cells are visits that came from paid search keyword clicks.
• Rows with white ‘N’ cells are visits from organic search, email, affiliate links or other sources.
• Rows with yellow ‘C’ cells are conversion events.
• The number in the first column represents the visit number for that person over all time.
• Only visits within a 30 day window are included although the visit count may have begun far earlier.

And if you’re into this kind of thing, they’re very interesting.

Click-Chain Histories

#1 – Our first contestant is a frequent visitor (note we’re starting with visit 37), loves those paid search ads, but does buy at least occasionally.

Four more after the jump (as they say)

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Months ago we were sharing our development progress with our advisor Avinash Kaushik and asking him for input in terms of the kinds of search analytics capabilities we should include in ClickEquations.

Avinash, like another charismatic leader, shared his passion for change.

“It’s fine to see the top 50 keywords by clicks, or the top 10 ad groups by revenue” he said, but what is much more powerful is to see what’s changed -- the keywords making money today that were not making money yesterday. Or the campaigns that performed well last month, and are not performing well today.”

There is a great post on the subject of this approach to reporting on his well respected blog, written about the time this conversation took place.

In our talk he went on to explain that “the top ten of anything rarely changes. With the Delta Reports you can truly see “what’s changed” and what changes is what’s actionable. If keywords were suddenly producing clicks or conversions, a marketer can and should go figure out why.”

This leads to another word you hear often when talking to Avinash -- “insight”.

“When they go and figure out why a keyword or campaign is suddenly performing or failing to perform, they’ll likely learn something about their business or market. Something they can capitalize on.”

ClickEquations Analyst Delta Reports
The conversation inspired us to add a major new capability to our ClickEquations Analyst Excel Plug-in.

The Delta Report tables make it possible to request information about any PPC metric, and get back a sorted list based on the difference between two time periods.

Or as Avinash would say, we show you what’s changed:

• So you can request the top 100 keywords making more money this week than last.
• Or the 5 campaigns whose click-through-rates have dropped the most dramatically between January and last September.
• Or the worst 5 ad groups in terms of declining impressions.
• Or just about any period-to-period comparison pre-sorted by the amount of change.

See These Reports In Action
The Delta Report tables in ClickEquations Analyst allow you to request any data for any time-frame, and build whatever report or dashboard you need. They automatically compare the selected timeframe to the prior period (this week to last week, last month to the month before it) or you can specify any two arbitrary periods to compare.

This is very powerful.

But we include pre-built reports that are ready-to-use and take advantage of these features too.

One is our Growth/Decline Report which shows you twelve different views of your campaign and keywords based on the amount of growth and decline against a variety of metrics including clicks, revenue, and profit.

This report is the subject of the next video in our ‘ClickEquations in 90-Seconds’ series -- which is now live on YouTube and below.

Video: ClickEquations In 90 Seconds -- Growth/Decline Report

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PS: Thanks to Avinash for the idea and inspiration.

Earlier we looked at the Google Adwords Impression Share metrics. These tell you if your ads are running when people type search queries that match the keywords you’re bidding on.

Very rarely will you find that the ads in your campaign are running anywhere near 100% of the time. Often you will find that they’re not running 25%, 50%, even 75% of the time when you probably expect that they’ll appear.

This will be shocking to some, and should be considered a huge problem.

The only reason to bid on keywords is if you want your ads to run when matching queries are typed. There is no logic to the idea that missing impression share is ‘ok’ because you don’t need the ‘extra impressions’.

• Isn’t it possible that the impressions you’re missing are the best – meaning highest converting – impressions? Or the most competitive impressions – those others are trying the hardest to take away from you? Do you really want to buy only the remnant impressions?
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• Or it could be that you’re getting the best ones, and missing the worst impressions – particularly if you have much lower impression share than impression share exact match (and if you’re keywords are well chosen). It could be that you’re missing lots of wierdo-broad-match Google Gumbo queries that you wouldn’t want anyway.

The point is that lost impression share is an uncontrolled mystery.

If your campaigns have high amounts (say over 30%) lost impression share you’re letting Google decide how and when to advertise your site and spend your money.

Shouldn’t you decide?

Divide And Conquer
As discussed in post II in this series, your first step is to break down your campaigns into logical units for which IS becomes meaningful. IS metrics across campaigns with dozens of dis-similar ad-groups aren’t actionable.

Of course, re-organizing campaigns is a large and difficult process. Adwords Editor makes it possible in a simpler matter than before, but it’s still a lot of work.

At a minimum your ‘must win’ ad groups should be isolated in ways that give you good visibility into their IS performance. Your core brand terms, which we’ve written about before in terms of organization, are a good place to start.

Then I’d suggest creating a slum for your losers, misfits, and keywords of questionable origin. Every campaign has them, ad groups that are a bit of stretch, a test, perform terribly but are hung onto for sentimental value, whatever.

Get anything you really don’t care about, or know deep down isn’t likely to work moved out of your bread-and-butter campaigns and onto ‘short bus’ campaigns.

You can let them run there, work on improving them, ignore them, whatever. But they will no longer be mucking up the impression share metrics in your more meaningful campaigns.

Now Do Everything Right
Once you have reasonably tight campaigns, and clear IS metrics for these cleaned-up campaigns, you can start working on a fix to the real problem(s).

Except for one tiny problem: You can’t fix what’s causing lost impression share.

Lost impressions are a symptom of a much larger disease – the overall quality of just about every aspect of your campaigns design and performance.

So if you want to eliminate lost impression share, you’re just going to have to improve nearly every aspect of your campaigns:

• Build out your match type keyword traps. Increasing coverage of exact and phrase match terms, and bidding them properly, should garner more impressions for those terms for broad-match heavy campaigns.
• Harvest search queries to increase negatives and add new phrase/exact match keywords. Every step to remove excess and intelligently expand your keywords improves the value of the IS measurement and hopefully the number as well.
• Check and address quality score across your campaign. Ad Rank = bid x QS, and often QS isn’t thought of enough.
• Write and test more text ads. This is the most overlooked effort in PPC, can drive quality score which drives ad-rank, and more importantly can multiple CTR by many times which grows everything positive.
• Bid differently. As a component of ad-rank, which plays a huge role in Impression Share, bids are a factor. Notice that bids don’t have to be your first or only lever (And watch for our upcoming blog post series on bidding.)

Impression Share is an interesting, and perhaps unexpected, broad measure of the quality of our campaigns because of how it’s influenced by the wide range of factors suggested above. Paid search is way too complex, and still to opaque (and perhaps inconsistent and imperfect) to pretend that it’s a clear measure that will track ‘campaign quality’ in any precise way – but it is an indicator and one we can use in surprisingly far-reaching way.

Impression Share Wrap Up
A lot of the paid search process happens without enough feedback or context.

Any available metrics that help us understand and measure the funnel we’re trying to push people through, therefore, is very important.

Other than the laughably inaccurate traffic/click estimates in the keyword tool, impression share is our only way to get critical visibility into the size of the audience we’re aiming at and keep a scorecard of our progress toward reaching it.

Bonus Link: Watch our ‘ClickEquations in 90 Seconds’ video on how ClickEquations Analyst enables you to track and report on Impression Share.

What do you do to fix low Impression Share? That’s the question we were left with at the end of the last Impression Share post.

But before we get to that, there is something else about Impression Share that should be discussed.

Does It Matter?
Impression Share is only provided at the campaign level.

In most accounts, campaigns are roll-ups of many ad groups, and ad groups are roll ups of many keywords. Usually keywords and ad groups are not all of the same type or importance.

So before getting too flustered about missing impression share it’s worth stopping to decide if it matters, or more precisely if you can actually tell if it matters.

Suppose we have a campaign called ‘Bedroom Furnishings’ which contains 27 ad groups for everything from ‘nightstands’ to ‘sheets and pillow cases’. Within each ad group are 50 to 500 keywords, of various levels of importance and at various match types and bids.

For this business, suppose that within Bedroom Furnishings, 70% of sales are bedroom sets, 10% are headboards, 8% are lamps and the remainder are all kinds of little things. (assume all of these sales are profitable.)

In other words, only 3 of the 27 Ad Groups represent 88% of the company sales and profit.

In this case all the Impression Share metrics are useless.

The campaigns and ad groups are not organized in a way that allows us to use the IS information as it is provided.

There are too many different types of targets mixed into a single campaign. For some of the ad groups it contains we really want all the impressions we can get. For others, there are more firm ROI targets and beyond a certain point we can’t afford to bid. Still others just don’t matter much.

If we want to use and benefit from IS metrics, we need to reorganize so that one campaign holds the large volume (and profit) ad-groups, and within those ad-groups only the successful corresponding keywords.

Move the marginal keywords and ad-groups into their own campaign that can be tracked separately. And move all the other ad groups and keyword into a third campaign.

This is the minimum reorganization to make IS useful.

• At this point we can look at the IS metrics for our ‘large volume and profitable’ campaign and reasonably obsess about every % we miss.
• We can watch and work on the ‘marginal keywords and groups’ for these high profit categories, and make smart choices to improve them both in performance and IS.
• And we can watch the IS for all our other categories but probably not do too much about them.

A Bag of Rocks and Diamonds
Let me try and make the whole point another way.

Pretend you had a bag filled with 10,000 rocks and 100 diamonds.

If you knew the bag had a hole and a few dozen things had fallen out, you’d be concerned – but really not know how serious the problem was. Maybe all you lost was a few rocks.

Wouldn’t you feel better though if you could put the diamonds in their own little bag and really make sure that nothing fell out?

Keywords and ad groups are the same way. You can’t take great care of the good ones when they’re mixed in with all the junk. Separate and segregate.

A little bit of a big topic for another time, but the use of Impression Share highlights the need.

I’ve written about the problem of averages before. Impression Share is another place that getting average data for a disparate set of things can greatly diminish the value of the information. It’s up to you to organize so that the metrics provided are useful.

End of Part II
In the next post we’ll leave this issue behind and assume you’ve organized your campaigns in ways that make the IS metrics meaningful, and talk about what to do to fix what you find.

The issue of how to allocate credit across the different searches (or other visit types) that lead up to a conversion event is a deservedly hot topic.

This is true largely because the broadly used ‘last click’ allocation model (where the last keyword gets 100% of the revenue credit) is really inaccurate and inadequate.

There are several other attribution models, including first click, linear, weighted, and other hybrids. The pros/cons of each are worthy of extensive discussion. That’s not the topic here however. We have a related question and would like to get some feedback.

Should the allocation of credit ever extend beyond a single conversion?

Two examples below further frame the question. In both cases, assume there is a user-defined tracking period which applies. In other words if you’ve set a ’30-day tracking period’ in any case the look back for events would only extend back 30 days.

CASE 1

Search on KW1 –> Search on WK2 –> Conversion 1 –> Search on KW3 –> Conversion 2

Question: Should KW1 and KW2 be part of the allocation chain for Conversion 2? If so KW1 and KW2 could get partial revenue credit for both Conversion 1 and Conversion 2.

Or does Conversion 2 only allocate back to KW3?

CASE 2

Search on KW1 –> Search on KW2 –> Conversion 1 –> Conversion 2

Question: Should KW1 and KW2 be part of the allocation chain for Conversion 2?

Or should Conversion 2 be seen as an independent event (perhaps inspired by a follow on email or other interaction after Conversion 1.)

FYI, Google Adwords does allocate revenue to keywords from multiple conversions if no search happens between them.

Your Opinion?

We’d love to hear your opinion on this. Please take the survey below, and leave any other thoughts in the comments.

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What if your ads didn’t run?

You picked the keywords, placed the bids, people searched, but your ads didn’t show up?

It happens every day. In almost every one of your campaigns.

It’s documented in a metric called Impression Share (in Google Adwords, no MSN or Yahoo equivalent yet.)

Impression Share displays the percentage of the time that your ads were displayed to people who entered search queries which match your keywords (at their specified match types).

100 minus Impression Share is the percentage of the time your ads didn’t run when you thought they would.

If your campaigns are profitable, the missing impressions are missing profit. Who can afford missing profit these days?

Three things stand between you and this extra profit:

1. Getting your Impression Share metrics.
2. Knowing what they mean.
3. Taking the steps necessary to drive Impression Share up.

Finding Impression Share
To get an impression share report most people have to go to the Reports tab in Adwords, build a Campaign report, and edit the fields to include IS, Lost IS (Budget), Lost IS (Rank), and Exact Match IS. You can’t access these metrics at the AdGroup level (a shame we’ll decry another time).

Impression Share Options in Google Adwords Report Configuration

If you use ClickEquations, you can see Impression Share right in the Campaign reports, or in any report or dashboard built in Excel with ClickEquations Analyst.

Impression Share Metrics in ClickEquations

Understanding Impression Share
There are four Impression Share Metrics. IS, IS Budget, IS Rank, and IS Exact. The first three are relatively straight forward. The last is a bit confusing.

• Impression Share = The percentage of the time your ads where shown (for this campaign) out of the times it was eligible to be shown. Eligible means the search matched your keyword, your account was active, the geo-targeting and day-parting and other settings were right, etc.

The next two metrics explain the Impression Share you didn’t get. If your Impression Share is 70%, then your Lost Impression Share is 30%. But why didn’t your ads run those times? The next two metrics tell you:

• Lost IS (Budget) = The percentage of impressions lost due to budget constraints
• Lost IS (Rank) = The percentage of impressions lost due to low Ad Rank (cost-per-click bid x Quality Score).

So Impression Share + Lost IS (Budget) + Lost IS (Rank) = 100%. These tell you what you got and what you didn’t get, and why.

The last one is trickier. For that reason I don’t think it gets the attention it deserves. And I’ll admit that I didn’t understand it until today when I started digging into this topic while doing some analysis work.

• Exact Match IS =  The impression share of your campaigns as if your keywords were set to Exact Match. That’s the official Google definition – the one that seems generally misunderstood.

So let’s try it a different way. Exact Match IS tells you the percentage of the time when your ads were displayed for search queries that exactly match the keywords in your campaign.

One minus Exact Match IS is the percentage of the time when someone typed EXACTLY your keywords in as their search query and Google still didn’t show them your ad.

Using Impression Share
The IS metrics are great because they tell you things you could otherwise never know about your campaigns.

Foremost, they tell what you’re getting and what you’re missing in terms of impressions – and from there the calculation of missing clicks, conversions, and even revenue/profit is rather simple (see chart 2 below).

This is huge. We can finally at least partially answer the perennial question ‘How much more could I make from my paid search campaigns?’.

Start With Exact Match IS
Although it somehow seems offered as an afterthought metric, I’d recommend starting by looking at your Exact Match IS.

This simplifies the world and if you’re buying anything near the right keywords provides a sense of how you’re doing in terms of getting shown to the people looking for you.

Google Exact Match IS (Chart from ClickEquations Analyst)
(Click to enlarge)

Exact Match IS Graphed As Revenue & Click Opportunity
(Click to enlarge)

If your Exact Match IS isn’t high (as usual there’s not simple way to say what that means, but let’s go with 70% or higher) then you really need to work your way down the list and think about your keywords, bids, quality score, ad copy etc.

Think about it this way: if Google doesn’t think it’s worth their while to show your ads to people typing in exactly the keywords you’re buying, how can you expect them to think running your ads is worth it for search queries you aren’t even directly buying?

Now Look At Impression Share
Let’s assume you have good to great Exact Match IS (you worked that out over the last 90 seconds right?). Now look at regular old Impression Share.

Google Impression Share (Chart from ClickEquations Analyst)
(Click to enlarge)

Here you’re likely to see something ranging from confusion (some highs and some lows) to a real bloodbath (all lows or at least no highs).

The reason these aren’t all 98.7%? The only easy answer is if you’re lucky enough to have some %’s in the IS Lost Budget column. And I say lucky only because that column is at least definitive. You can spend more and get those impressions.

Lost IS (Rank) theoretically explains the rest, but really it doesn’t explain very much.

Rank means Ad-Rank. Ad-Rank is Bid x Quality Score. Bid can simply be an insane fee you pay despite what something is worth, you probably don’t want to ‘win’ that way. Quality Score is determined by many things, as we’ve been over.

So Impression Share provides an easy way to see something, and know something that is very important to know. But it doesn’t provide a magical simple path to improving the problems it helps you find.

End of Part I

To solve our problems we’ll have to follow the path through our campaigns.

Impression Share forces us, if we look at it hard enough, to understand the roles of both bids and quality score, to think about our match type strategies, to organize our campaigns more effectively, to include the right keywords not just the most keywords, and to broadly see how interconnected the many options really are in a paid search campaign.

We’ll dig into that work in a follow up post later this week.

Seen some crazy broad matches lately?

Everyone has, and PPCProz is building a list of the zaniest, so we can all laugh our way to the poor house.

There will always be broad match in every campaign. But if huge portions of your traffic/revenue are coming through broad match you (or your agency) are not working hard enough.

And if you have a lot of broad match it’s certain that you’re:

• Paying too much per click
• Missing a lot of impressions
• Getting useless clicks
• Wasting money

I’ve written extensively about Match Types in the past, and proposed the ‘Match Type Keyword Trap‘ as a guiding principle of how and when to use them and most importantly transition your search queries into phrase and exact keywords, with appropriate bidding.

Broad match is an important tool – it saves time and energy, and provides a place to start.

But mostly – although not entirely – it is a training wheels set you should get beyond for the lion’s share of your PPC spend and revenue.