PPC Without Pity

This week, Google rolled out some new reporting features that are pretty interesting. If you run a performance report now, you might see some additional options for conversion reporting: “many-per-click” conversions, and “1-per-click” conversions.

Confused yet? I know I was when I first looked at this. Apparently, Google now has the ability to track multiple conversions that come from one click on your ads. For example, if you have newsletter signup and product purchase conversion events, and someone both signs up for your newsletter and purchases a product after clicking on an ad, you just got a “many-per-click” conversion. The “1-per-click” conversion tracks exactly what it says: one conversion on one ad click.

I can see where this might come in handy for someone with multiple conversion events in a campaign, but this is old news to anyone who’s familiar with setting up multiple conversion goals in Analytics. It could be useful if you want to see which keywords/ads are the most engaging, though. If you see that a keyword is getting a ton of many-per-click conversions and another is getting only 1-per-click conversions, that’s yet another metric to compare campaign elements for optimization.

While I’m never one to shy away from more analytical data, I’m not quite sure how to use this new functionality just yet. Got any ideas? If you do, let me know in the comments.

You can read Google’s official announcement regarding the feature here: Inside AdWords

Last week, I wrote about some changes going on with Yahoo demographic targeting. This week, I wanted to follow up with some more specific reasons why I think demographic targeting for pay-per-click campaigns is less useful than the search engines would have you believe.

There are three main reasons why I think web demographics are unreliable:

1. The inaccuracy of demographic statistics online – a great deal of user demographics that search engines use is pulled from third party data vendors, opt-in data, and algorithms that provide “estimates” of user data (source, source). None of these sources could possibly provide information with 100% accuracy. Third party data providers have an incentive to overestimate the value (and accuracy) of their data, opt-in demographic data is by definition incomplete (since you’re not gathering information on 100% of users), and I’d be surprised if my life could be quantified by a computer program. These are the building blocks that you would base your ad planning assumptions on. If you’re targeting 35-40 year old females, how can you be sure that any of these methods could accurately estimate the actual person who is seeing your ad fits into those categories? That brings me to…
2. One computer DOES NOT equal one person – I’m sure that there are plenty of households out there that share a computer. How many times have you looked up something on someone else’s machine? Despite all the big talk about demographic targeting, there’s really no way to truly target the person. Our ad process ends at the computer screen – you can’t control who is using it. You have no certainty that the user viewing your ad through the lens of the computer monitor is actually the owner of the machine, or the person that all of these fancy demographic programs have data on.
3. Reliance on voluntary data – Of the three sources mentioned in point #1, two of them rely on voluntary data – the third-party data (probably) and the opt-in data (definitely). For starters, you only reach a small percentage of people who will actually take the time out of their day to volunteer this data. I’m willing to bet that a vast majority of people prompted for this information either are too busy to fill it out correctly, or choose to provide inaccurate or invalid data due to privacy concerns. Then, you have to take into account the people who filled out the information, but provide misleading information either through carelessness or willful inaccuracy.

After you take all of this into account, what percentage of your audience do you think has completely accurate demographic information? Ten percent? Five? Maybe less? There’s probably no way to even know. Instead of relying on these vague demographics, do yourself a favor and spend more time analyzing the data that you know is correct – historical keyword reports and analytics tracking. These sources will provide a much greater wealth of insight than the lazy demographics put out by the search engines.

I can’t believe I’ve gone this long without discussing my favorite PPC management trick: the detailed keyword filter for Google Analytics. You can find simple instructions to set it up at this Semvironment blog post. It only takes a few minutes to set up, and is well worth the small investment of labor.

Once you set up the filter in your Google Analytics account, you’ll be able to view the exact search queries that users are reaching your site on. This is especially helpful if you’re running a lot of broad match keywords in your campaigns. Normally, you’d never be able to tell exactly what users are typing in before Google shows one of your ads. After getting a few weeks of data from this filter, you’ll realize that Google takes a very liberal interpretation of what is relevant to a broad match keyword. After all, more impressions equals more potential clicks and revenue for Big G, so what incentive do they have to make sure your broad match keywords are super relevant?

Now, I should mention that you could get this data out of a Search Query report in AdWords. The Analytics filter method has two advantages, though. One, you never have to worry about that heartbreaking “134345465 unique queries” entry in your report data. Two, you’re able to get detailed keyword data not only for Google, but for your other PPC campaigns that you have hooked into your Google Analytics profile (more on this later).

By using the keyword filter, you’re not only able to weed out ineffective keywords by adding negatives and changing match types, but you’re also able to get a feel for what users are actually searching for on your site. I’ve had a lot of success finding popular terms in the keyword filter, creating an AdWords ad group around them, and raking in the conversions. Not bad for a free web analytics package, huh?

If you’ve already installed conversion tracking for your PPC accounts, and you’re looking for a more robust solution for tracking user activity, there are plenty of options available, most of them free. If you’re willing to put in a little time and effort into adding some additional code to your site, you’ll reap major rewards in terms of useful information that can be used to further optimize your account.

For all of my clients, I recommend that they install Google Analytics on their site. It can be kind of a pain to install (you need to copy and paste a javascript code snippet on every page of your site – if you have a site template you can save a lot of time), but once it’s in there are lots of really cool things you can do to extend its functionality. I’ll leave all the bells and whistles for another post, but even Google Analytics’ basic functionality covers most of what you need to look at to determine site visitor trends. Traffic data is broken down between paid and non-paid (organic) traffic, and you even get a pretty sophisticated breakdown of traffic sources by search engine, geographical location, and web browser. I could write a whole lot more about Google Analytics, but in order to do it justice I’ll be breaking functionality down in individual blog posts – there’s a lot of ground to cover.

Another free analytics package that’s caught my eye is Woopra. It has a similar functionality to Google Analytics, but the main difference is that Woopra can monitor visitors in real-time, while Google Analytics tends to have a lag time of several hours when tracking visitor data. Woopra can even let you chat with visitors as they visit your site, which I admit is a little creepy (though a really cool idea nonetheless).

A quick Google search will no doubt uncover a multitude of free (as in freedom) and “free” (as in “there’s a catch”) analytics solutions. In my experience, Google Analytics does the trick just fine with minimal effort. Stay tuned for more cool stuff to do with Google Analytics in future posts.

My biggest pet peeve in PPC management has to be when clients don’t bother (or outright refuse!) to implement conversion tracking on their accounts. Since conversion tracking is the most reliable method to determine whether your users are actually taking action after clicking on your ads instead of just browsing around and costing you money, it boggles my mind when people don’t want to make that small investment of time to cut and paste a javascript snippet onto their web pages.

To put this in perspective, let’s run through a hypothetical situation. Let’s say that you own an electronics store in the town you live in. Whenever someone buys one of your items, you don’t keep track of how much they paid for it. Also, let’s imagine that you don’t keep track of how much you paid for your merchandise from your suppliers, and you also don’t keep records of how much you spent on advertising in the local paper, billboards, radio ads, etc. It would be pretty hard to determine how much money you were making (if you were making money at all!), right?

That’s exactly what’s happening without conversion tracking. Without it, you’ll never know exactly how much you’re spending for a customer to “convert,” whether your conversion event is as simple as an e-commerce sale or as elaborate as a lead submission in a multi-stage purchasing process. Not only can you use this to determine how effective your ads are in generating actual sales, but you can also determine what keywords, ads, or campaigns are eating up your online advertising budget without producing profitable results. This is just the first step in optimizing a PPC account.

Next week, we’ll talk more about a more detailed solution to the problem of conversion tracking: web analytics. For more information on conversion tracking for individual PPC platforms, here are some links:

Google AdWords Conversion Tracking

Yahoo Search Marketing Conversion Tracking

MSN AdCenter Conversion Tracking