It’s interesting to know that your daily average number of visitors is 49,000. Or that the average visitor sees 4.2 pages. Or that your Yahoo Search Marketing paid search click-through-rate average is 2.1%.

But before moving these numbers from interesting to important, or accurate, or actionable, you should always take the time to look inside them. Because the average may cover up some huge difference in the numbers which lie below.

That’s exactly what is apparently happening with the age-old banner ad click-through-rate numbers now that some research has been done into exactly who was clicking on those ads. The report documents:

…just 6% of the online population yet account for 50% of all display ad clicks. While many online media companies use click-through rate as an ad negotiation currency, the study shows that heavy clickers are not representative of the general public. In fact, heavy clickers skew towards Internet users between the ages of 25-44 and households with an income under $40,000. Heavy clickers behave very differently online than the typical Internet user, and while they spend four times more time online than non-clickers, their spending does not proportionately reflect this very heavy Internet usage. Heavy clickers are also relatively more likely to visit auctions, gambling, and career services sites – a markedly different surfing pattern than non-clickers.

 The problem of averages is rampant in paid search analytics, where CPCs, CTRs, and conversion rates as well as more important numbers such as ROI are often seen in ‘roll-ups’ of campaigns or ad-groups, or some type of classifications. It’s handy to see these averages, but don’t forget to dig a little deeper before taking any resulting actions.

I wish could trust these numbers. But I really don’t. They could be high or low, and as usual the averages don’t matter.

There is an interesting back and forth on the ClickFraudNetwork blog between these guys and Shuman Ghosemajumder from Google.

• I personally have no doubt there is an issue.
• Or that it’s very hard to track/detect.
• Or that the search engines aren’t being as transparent and forthcoming as they should/could be.
• Or that Click Forensics is both sincere and at the same time trying to promote a business.
• Or that if the engines believed it was as small a problem as they say, they could be much more convincing.

I applaud Click Forensics and their CEO Tom Cuthbert for the initiative and effort of setting up the ClickFraud Network. But until it’s cut loose to be a truly independent entity run by a consortium of vendors and advertisers, it’s credibility is legitimately in question, even before you get to the obvious technical problems/limitations.

At some point the industry needs to face this. Thus far it’s buried in the growth and all the other changes and issues. Perhaps it will stay that way for another few years. With so money at stake that would be unfortunate.

Take a look at this report snippet from onlynaturalpet.com. As part of our initial work on the account we’ve been cleaning up the organization of many ad-groups, so since early December there has been quite a lot of campaign and ad-group reorganization going on.

Weeks later reviewing a portion of the January results, we see clearly the impact of the way latent orders are handled – a bunch of ad-groups with zero spend, zero clicks, but orders and revenues.

Of course this only shows half the story. Each of those ad-groups has been recreated in a different location within the campaign, so there is a corresponding ad-group elsewhere in the report which shows both clicks and revenue for this same time frame, but as compared to peer ad-groups that weren’t part of the clean-up, the new ones suffer from much lower revenue (because all their trailing revenue is still being reported here in the old groups).

For beyond the fact that reporting both clicks and revenues when they happen as opposed to attributing revenue to the click that provoked it distorts reports by assuming that costs and revenues are constant when they’re not (see the earlier post for a better explanation), we have the problem that after making organizational changes your reports have severe limitations (they’re sort of worthless) until many weeks after the changes.

This post is part of a case-study series on the Commerce360 management of paid search campaigns for onlynaturalpets.com. It is being done with the kind permission of Only Natural Pet Store, and some data has been changed to keep PetSmart guessing. For your convenience, we’re keeping a list of all posts in the series.

The following numbers are based on data CI collects from hundreds of manufacturers, retailers, and shopping comparison engines. From within that world, these are the number of people who used different shopping channels/sources before their purchase.

1. One Channel Before Purchase – 37%
2. Two Channels Before Purchase – 25%
3. Three Channels Before Purchase – 16%
4. Four Channels Before Purchase – 8%
5. Five or More Channels Before Purchase – 14%

Two things to note:

• Each visit through an email, organic or paid search, shopping comparison engine, or retailer site counts as a channel visit. In other words, if you came through two different shopping engines those are counted as two different channels in the above list even though they’re the same channel.
• This data does not document the number of visits to a single website. A user who went through four channels to four different sites before purchasing is in the ‘Four Channels’ data.

This is really interesting data, and generates a lot of thoughts on the issue of attribution. More thoughts on that in a future post.

The paid search engine tracking tools and major web analytics packages can (generally) track these delayed purchases. They assign credit for this delayed revenue back to the paid search channel and even the engine, campaign, ad-group, and keyword responsible for the click.

Most use a 30-day timeframe during which delayed purchases are credited properly. Some allow you to specify the timeframe – SiteCatalyst/SearchCenter for example allows you to track delayed purchases for up to one year. (Set the evar expire date in the Admin control panel.)

But there is a timing problem in PPC reports. They show the clicks/expenses for the requested period, and the orders/revenue that took place in the requested period. But there is no requirement that the reported clicks cause the reported revenue. In fact, it’s an open secret that in many cases they don’t.

(There are other issues causing inaccuracies in these reports too, as posted earlier.)

There are three sources for the data in a paid search report:

• Left-Over Transactions. Revenue from clicks/visits that occurred prior to the initial reporting date. The clicks and expense of these clicks is not included on the report.

---

• In-Period Transactions. Clicks and their resulting revenue when both occurred inside the reporting dates.

---

• Incomplete Transactions. Clicks and their expense for which some of the orders and revenue occur after the final reporting date. These orders and revenue are not included in the report.

So for a report on paid search ‘last month’ in a company which has trailing sales for about three weeks after the initial click (not at all atypical), the report would include:

• A stream of left-over transaction revenue, starting with 21-days worth the first day of the month stretching all the way into the third week of the month.

---

• A good number of in-period transactions where the click occurred on or after the 1^st of the month and the sale closed by the last day of the month

---

• The full expenses but an unknown amount of revenue for incomplete transactions from every day except the first week of the month. It should be noted that the revenue from these incomplete transactions never ‘fills-in’ for the ‘last month report’. Even if you wait the full 21 days and then run it, it will report the same revenue total it did on the 1^st of the new month.

The theory or justification for allowing this sloppy mix of data to pass for an actionable report is this: the left over transaction revenue is probably equal to the incomplete transaction revenue. So on-balance the report is probably pretty accurate.

And in some cases that’s probably true.

Unless your business has seasonality. Or product line changes. Or sales/promotions by either you or your competitors. Or impact from weather or other external major events. Or unless you add, delete, or modify your keywords. Or change your bids. Or test new ad-creative. Or work on your landing pages. Or in any other way change anything that might impact your customers, market, business, campaigns, or website.

Depending upon the degree to which you do any/all of those things, you’re going to need to take these reports with a proportionately large grain of salt.

• If you’re working aggressively on your PPC campaigns, trimming keywords (because the reports you now know you maybe shouldn’t trust told you that they weren’t making you any money – ah the irony), narrowing match types, and lowering bids, for example, you’ll see an exaggerated improvement in the following period as left-over revenue continues to come in from your old running keywords, higher-priced bids, and broader matches.

---

• Seasonality such as that we experience with a number of major apparel manufacturers, causes an artificial boost in some campaigns as a new season kicks in, as sales pickup aggressively from all the pre-season shopping that went on in the preceeding weeks. Another side effect from the current reporting method is that we don’t gain accurate visibility into when starting pre-season advertising is a good idea. With true-attribution we’d know.

---

• As promotions or seasons end, you get the opposite effect with exaggerated swings down. Now fewer latent conversion occur due to pricing or inventory issues, making a lot more of last periods click-cost become a lot less profitable (and perhaps even pushing into the red) more than any report will show.

Why Not Do It Right?

First let’s define who we’re talking about. As far as I know, everybody creates their paid search reports using the erroneous methods described above. Google, Yahoo, MSN, Google Analytics, IndexTools, and Omniture SiteCatalyst/SearchCenter are the ones I’m familiar with. Please leave comments if you know of any package that can properly relate clicks to revenue.

The obvious question is why. Why don’t paid search reports match clicks to their resulting revenue? Why doesn’t last month’s report include only the clicks that took place during that month and the sales that resulted from those clicks?

The answer seems to just be that this is how it’s always been done. It’s undoubtedly easier computationally. There are interface issues to doing it the way I’m suggesting.

Since the same software doing this reporting (the engines or your analytics package) knows both the average number of days for your latent conversions and the number of days for which they’re configured to allocate sales (as well as their allocation rules relative to multiple visits, but we’re leaving that complexity out of this discussion) a ‘last month’ report could include a simple flag disclaiming that ‘Report Incomplete – Additional Revenue Expected for 17 more Days’ or whatever.

Using accounting terms, it’s time paid search reporting moved from a cash to an accrual basis.

I don’t know why. I’ll see if I can’t get some folks from the engines or analytics vendors who might be willing to talk about this ‘on the record’ for a future post.

• Deleted Cookies or other internet issues – Everyone doing business online has learned that all tracking has some significant limitations, which impact accuracy from a little (5% is considered typical) to a lot (cookie deletion rates have been reported in excess of 40%).

---

• Offline Conversions – Many visits that start with a paid search click end with a purchase in-store, via phone, or at home from a different computer. These cross-channel transactions typically aren’t tracked in the paid search reports.

---

• Attribution – Many visitors come to your site several times before they purchase, and use different tracked channels for each visit – once via paid search, another via email, another by typing in the URL. Which visit gets the credit for the sale depends on the capabilities of the system and in some cases the revenue attribution option is set in your analytics package. In any case, usually only one click gets the credit which means other do not.

---

• Latency – the fact that many people buy on a different day than their click, and paid search reports don’t accurately match clicks-to-purchase beyond the boundaries of the report time frame.

Each of these were mentioned in the comments of our Friday Quiz post question about problems with paid search reporting. And each definitely contributes to PPC report inaccuracy.

Deleted cookies became a visible issue most recently when Comscore reported that nearly 1/3 of all visitors removed cookies (first and third party) at least once per month. (More on the story here, and here.) While if true this behavior would overstate unique visitors (the metric in discussion in the report) it would cause PPC revenue attribution to be understated – as cookies are the most common way analytics packages and search networks connect visitors to their later purchases.

Offline conversions are an obvious and well discussed topic. This fact also under-states PPC revenue and attributions. There are inceasing ways to connect revenues from some channels (like phone orders) back to the PPC click that caused them, and via surveys and other methods many multi-channel retailers are learning how to at least factor offline sales back into their understanding of their paid search results.

Attribution is another systemic issue – people visit multiple times via multiple sources and at some point you (or your reporting software) has to decide which visit source gets the revenue credit for an eventual sale, if cookies or offline didn’t make it impossible to track in the first place! (Some very thoughtful posts here, here, and here.) The industry default is ‘last click’ but some analytics packages (such as SiteCatalyst and Coremetrics) provide control over that. (related post here)

What I Meant Was

These three issues – cookie issues, offline conversions, and attribution – are reasonably well understood and thereby can be taken into account by analysts and marketers. In my experience that’s not true for the issues we’re calling purchase latency, and that was the issue meant to be the ‘answer’ to our quiz.

A paid search report for a given time period – I used December 2007 as the example in the question – shows the PPC clicks count and expense during that period, and the sales from PPC (based on the selected allocation method) during that period. But any connection between those click and that revenue is in effect a coincident of time.

The fact is that every such PPC report is filled with revenue from left-0ver transactions (whose clicks took place before the reporting period) and what we’ll call incomplete transactions (whose revenue at least partially might come after the reporting period). Any hope of even approximate accuracy is based on the idea that there is a consistency over time for those keywords, those clicks, and those items across the time periods before and after the report. That’s not a good hope to base tens of thousands of dollars (or more) of spending decisions.

Our Winner

So I’m naming Tim Schaeffer the winner of our first Friday Quiz and a $50 iTunes Gift Certificate. Tim posted first, and concisely described the problem as:

If your product / service has a long purchase cycle ( 2 weeks), if someone clicks on your ad Dec 22nd. but doesn’t buy until Jan 3rd then the Dec 2007 report would show the click but no sale … and Jan 2008 report would show a sale but 0 clicks (assuming you only had 1 click on the keyword or just for logic sake).

More To Follow

In the next post I’ll share a lot more thoughts about this issue of conversion latency and it’s impact on PPC reporting.

Thanks to everyone for visiting and particularly those who participated in the quiz. Look for more on future Fridays.

The official press release makes clear (for the first time to my knowledge) that their intent is to migrate HBX customers over to SiteCatalyst. For the time being the product will be renamed SiteCatalyst HBX, which the release says will “continue to be supported until the key features have been integrated into Omniture SiteCatalyst.”

From my experience, that was done in 2002.

But the transition/migration is still a very large project since the site tags are incompatible (at least they have been until now) and more importantly SiteCatalyst ‘Classic’ has infinitely more capabilities and tagging requirements and options.

More importantly, the user interfaces and everything else about the two programs will require just about complete retraining of every user. The resistance will be high and the migration, if unprompted, would take a long time. It looks like Omniture is being wisely aggressive with events, training sessions, and a general gung-ho attitude.

I presume they did this acquisition for market share purposes, and who needs two incompatible code bases and two sets of training and customer service issues to chase the same market?

But are they the same market? Only partially.

It would be great to see Omniture use this opportunity to build a true mid-market product, both in recognition of market realities and in service of their higher end market and broad optimization platform.

Here’s what I would do:

• Rename HBX back to HitBox. The HBX rename was an attempt to upscale a downscale product. SiteCatalyst HitBox is a recognized, respectable and mid-market sounding name.

---

• Retool SiteCatalyst HitBox as the lite, mid-market version of SiteCatalyst Pro (you know they’re not going to call it Classic). Give it a streamlined UI and strip out all the super-power-stuff that many won’t ever use. Enable a one-button upgrade to Pro.

---

• Include free ‘taste’ features from Pro: Three Alerts. Two Classifications on Product, Pages, and Campaign Tracking Codes. A|B Comparisons on up to two metrics. Five Dashboards. Five Bookmarks. Two Targets. Three eVars. Two Correlations. Three Calculated Metrics. And killer video tutorials showing how and why to use each one of them.

---

• Price SiteCatalyst HitBox very aggressively. I’d suggest about ¼ of the cost of Pro with a minimum of $3000 per year. Leave the free stuff to Google and Microsoft, but provide serious analytics and more importantly an upgrade path for a price anyone actually doing business online can afford.

Here’s why:

• They need it anyway. The vast majority of SiteCatalyst users and more importantly prospective users in existing client companies can’t handle or digest the ‘Pro’ feature set and UI. This will certainly be true of HBX users who suddenly face 2X or 3X and controls, options, menus, etc. The company rightly prides itself on depth of adoption inside client companies, and could probably double it with an approachable UI version. (No economic loss here, Pro companies just get the option to let some users log into the HitBox version) And ultimately perhaps 25% of HitBox users migrate into Pro users or cross-product suite users over time.

---

• There is a mid-market. The distance between Google Analytics and SiteCatalyst is huge, in price and capabilities. Online businesses in the $1M to $10M segment haven’t been your target but there’s a lot of them. I believe SiteCatalyst Pro is a justifiable investment for them, but most can’t be convinced to make the leap. A way to ease into it – both financially and by tasting what large benefits the higher end could provide, would be very successful.

---

• Tomorrows Analysts are GA users today. From blogs to startups millions are getting used to GA, and will migrate to new and large companies over time and say ‘it’s good enough’ to bosses who don’t know better. Push GA down market with a legitimate mid-market option. Let all those folks in the $1-$10M companies get hooked on power and convince their companies to upgrade.

---

• Sell The Blades. Omniture has built an impressive suite of products, and beyond HBX this acquisition provides a bunch more. As these mature and continue to be integrated a broader set of customers can only get pulled either across the line or up into the Pro line.

---

• Data. It’s clear that data is the oil of the 21^st century. Anyone who can sit on top of lots of it and knows how to get at it (or will let someone pay for that privilege) will be fat and happy for a long long time. Taking another 25% to 50% of GA’s market share is like annexing Kuwait in terms of traffic, behavioral and transactional data. Given this, the other four reasons hardly matter.

Why not:

• Fear. The main reason not to do this may be a fear that less will be good enough, thereby spawning ‘downgrades’ and lower ticket new sales. I think it’s a legitimate worry. It should be taken as a challenge to prove the value of the high end and make SiteCatalyst ‘Pro’ approachable via a better UI and an experience that enables more customers to take full advantage. The value is there it just needs to be made more accessible.

---

• Resources. Yes it’s an additional project on a list that must be miles long. For all the above reasons, with the ultimately limited amount of information I have from the outside, I think it’s worth it.

Coda

I should disclaim all of the above with the information that Commerce360 is an Omniture Platinum Partner, I’m on their Customer Advisory Council, and I’ve been over time briefed and subject to NDA’s on future Omniture products. I’ve never had a discussion with anyone there about the HBX merger or HBX products or anything relevant to this post in terms of their product line directions or these suggestions. No animals were harmed in the development of this blog post.

Part of the reasons for this post is that I’ve seen this movie before. In the early 1990’s I had a lot of involvement and ultimately worked at Aldus, the PageMaker company when they were the hot young public software player in the darling space, revenues shooting past $100M and acquisitions rapidly growing the product line. They also had a huge industry player (Microsoft) giving away competitive programs (via the then new Office bundle) and one remaining legitimate competitor to each of their main high-end programs.

There are a lot of dis-similarities here too, but Aldus wound up acquired by Adobe for a number of reasons you would have never predicted in 1992.

I also want to be clear (if it isn’t already) that I’m a huge Omniture fan. I think SiteCatalyst and SearchCenter are the only reasonable serious analytics choice in terms of the features they provide. They’re far from perfect, but I’m pretty well versed in each of their competitors and would/do strongly suggest to anyone that picking any of them is, based on my experience with current versions, a compromise at best and a bad (or very bad) decision at worst.

This a great but complicated and important time for Omniture. They’ve been navigating it brilliantly, and I’m rooting for their continued success.

While looking at just about any paid search analytics report it should be easy to move up, down, left, or right.

It isn’t.

Adwords

In the Google Adwords interface, you can go down in a pretty natural manner – by clicking on a campaign or ad-group name. To go up requires a click in the breadcrumb nav bar. There is no next or previous, you have to go up then back down.

This might sound trivial. Until you do it for an hour or two. Or 15 times a day. It’s a massive time waste and more importantly ultimately prevents analysis. At some point it’s just not worth it to look over those last few ad-groups, or check that new theory on the two campaigns you’ve already seen.

Adwords Editor

In Google’s fantastic Adword Editor, the problem is largely solved by the 3-pane design. No matter what you’re looking at you can switch very quickly to another campaign or ad-group. And the tabs across the top make it simple and quick to go from keywords to negatives to text-ads.

AE isn’t primarily an analytics package, so it doesn’t really solve this problem, but it’s a great example of how elegance and speed make you both want to use a tool and use it a lot more. You can jump into AE, look at things, make some changes, and even take the extra step of having to submit them (since you’re working off-line) and it feels efficient.

Omniture SiteCatalyst / SearchCenter

In Omniture SiteCatalyst the problem is exacerbated because there can be a lot more data (especially if you use a lot of calculated metrics as we do), the interface is way heavier, and let’s face it – SiteCatalyst is generally to painfully slow.

In version 13.5 SiteCatalyst added a very handy drill-down feature to SearchCenter data that makes it pretty simple and sometimes even quick to drill from engine to campaign to ad-group to keyword.

Unfortunately, moving back up the hierarchy is neither elegant nor fast, and there remains no way to go sideways other than going all the way back up (which basically means starting over).

In some cases the ‘Select Ad Group’ or ‘Select Campaign’ dialog box does allow a semi-direct way to switch from one to another, but the cost is three terribly slow transitions. (One for the dialog itself to appear, another to execute a narrowing search, and a final one to draw the resulting report – I just did one and it took a full minute to complete these three steps just to shift from one campaign to another).

Conclusion

I spent nearly all of today navigating the reports described above. With a nice little 4-way navigation button, or if the 3-pane design were moved into Adwords and adopted by Omniture, I’m pretty sure I could have been done by lunch.

The Search Query Performance report is the closest thing you can get from Google, or any of the engines as far as I’m aware, but it has several limitations.

First, it can’t associate queries with keywords. It’s a report for an entire campaign which means many ad-groups each full of keywords – often thousands. I’d argue that not knowing which keyword was matched to which query removes much (but certainly not all) of the utility of this report.

Second, Google groups large quantities of queries into buckets by match-type and hides the actual queries from you, listing only ‘other unique queries’.

Imaging your monthly credit card statement showed transaction detail for 50% of your purchases and lumped the rest in three groups based on size of the individual invoice (<$50, $50-$100, >$100) and just listed ‘Other Merchants’. Not a great way to review your budget is it?

Comparing the Google Report with a Campaign-By-Query report in Omniture SiteCatalyst (using the DB Universal Sources Vista Rule) shows Google disclosing only 38 unique keywords where Omniture lists 167 for the same period in one of our ad-groups.

And since Omniture can’t detect match-type differences (because Google doesn’t share that information via URL variables or their API), even that number is a bit low.

With a clear view of this level of detail (even at the campaign level, and moreso when we see which queries triggered which keywords) it’s possible to improve our ad-groups, negatives, text-ads, and even landing pages.

Next time I’ll dive deeper into making full use the information provided in keyword-by-query reports.

I’ve taken to calling the ones you buy ‘keywords’ and the ones people type ‘queries’. And about 100 times a week in one conversation or another I have to pose the question: Do you mean keywords or queries?

Beyond the linguistic fascination this poses, there is a very practical issue for paid search marketers. These diabolically similarly named elements interact in strange and important ways within your campaigns.

Confusion or indifference isn’t too good for the bottom line.

The Impossibly Simple Report

To understand the performance of any keyword (the kind you buy) it is vital to look at the queries (the ones users type) that get counted as clicks.

Of course, you probably can’t.

At least not using the tools and configurations you have today. Neither Google Adwords nor Yahoo Search Marketing or MSN AdCenter offers a report showing each keyword you buy and all the queries that were matched to it. Somehow they seem to think it’s unimportant (or perhaps not in their self-interest) to show exactly how your money is being spent.

There is a work-around of sorts: you can manually tag each keyword in every one of your campaigns to pass back the name of the keyword you purchased (see this post for info on the way to do this in Google, there are similar methods available for Yahoo and MSN) and then figure out how to grab that tag and marry it to the query string which is often (but not always) returned in the URL when the click actually arrives.

The actual process depends upon the tools you’re using, and in my experience this isn’t really complete, accurate, or practical.

That’s Why We Have Analytics Software, Right?

Nope. In their default state, neither Google Analytics or the larger more generally well equipped web analytics packages can tell you which of your purchased keywords drove traffic from which search queries either.

I can never decide if this is more or less startling.

• In Omniture SiteCatalyst the ‘Paid Search Keywords’ report is a query report. There is no capture of your paid search keywords (the ones you bought) unless you code them into the inbound URL’s and grab them as part of the Campaign tracking codes. If you do this, then use Excel to extract the keywords into a SAINT classification you should be able to run a classification report broken down by Paid Search Keywords and see the desired report. I’ve found this can work for queries which generate orders, but haven’t been able to make it work for every click. If you add SearchCenter, Keywords are tracked automatically so all that tagging and SAINT extraction goes away, but still only a fraction of the queries appear.
• HBX / WebTrends ML2 – I’m far less experienced at either of these, but haven’t seen nor been able to find simple complete keyword by query reports here either. Anyone with more definitive information is encouraged to comment.
• Google Analytics 2 – In GA2 you can pass in data via the target URL much as described for SiteCatalyst if you’re willing and able do tag the target for every keyword you buy (instructions here). I don’t believe (but am not 100% sure) that when tagged you can then produce a keyword by query report. Anyone?

What If I Pay More?

They say money can’t buy happiness, but let’s admit that it can make the misery a lot easier to put up with. In the case of search analytics, Omniture SiteCatalyst/SearchCenter can produce the report we all need and desire – if you’re aware of and then purchase the Unified Sources DB Vista Rule.

Once this little gem is setup, you get a new eVar with the user query properly populated (the vast majority of the time) and you can therefore break down SearchCenter keyword reports with an accurate query list.

There is still some separation between the SearchCenter data and the SiteCatalyst data (which the evar is) so not everything is full allocated across the queries (keyword cost for example so you can’t fully calculate ROI) but none-the-less this is fantastically useful for understanding and tuning your paid search campaigns.

Demonstrating some of the useful information in these reports was the reason I started writing this post, but as it’s far too long already, I’ll save the examples and details for another day.

(BTW: This feature is only a bonus of the Unified Sources Vista Rule – it’s main utility is to classify organic search traffic and referring URLs into your Campaign tracking code so that Campaign Reports cover nearly every traffic source, and you can SAINT organic and referring traffic along with other campaigns. This capability had also been very high on my wish list, so I recommend this Vista rule highly.) 

The Developing Trend

If the core process of paid search marketing is buying keywords to connect with users when they type queries into search engines, then transparent reporting on the way our keywords are matched with user queries is essential.

Without knowing which queries are being matched to which keywords, it’s pretty hard to select or tune your use of match types. It’s a lot harder than it needs to be to see better ways to organize your ad-groups or rewrite text-ads to address user concerns or intent.

And across the performance metrics tied up in the CTRs, CPCs, and Conversion Rates of those keywords, match types, ad-groups, and creatives, it becomes virtually impossible to optimize your campaigns and your spend to maximize YOUR revenue.

This fact is the primary driver behind our development of ClickEquations – you don’t have a fair shot today due to both the complexity of the marketplace and the information you’re selectively not being provided.

There are undoubtedly many reasons why we don’t currently get clear complete information. The rapid development of the engines and their software and the complexity of what they’re trying to accomplish dictates that they haven’t had time to get to everything. It also seems reasonable to assume that since their economic interests and those of their advertisers don’t always align, some decisions and prioritizations are made without putting advertiser interests first.

But advertisers also own some of the responsibility. Without a loud and clear call for the kind of information and transparency we all need to manage our campaigns and budgets, we’re going to continue to get all kinds of bells and whistles from both the engines and the analytics vendors while some very basic features remain difficult or unavailable.