There’s an old adage that says “averages lie.” Nowhere is this truer than with PPC data. If you’re focusing exclusively on averages, your campaign is undoubtedly suffering. Some aggregation is necessary. but it’s a mistake to focus only on averages.
News organizations love to report averages. For example, in 2002 the CDC released data about the average height and weight of American adults. According to their data, the average adult woman is 5’4″ and weighs 163 pounds.
Now think about all the adult women you know. Are they all 5’4″? Do they all weigh 163 pounds? Of course they don’t!
Averages are a necessary evil when it comes to reporting numbers. Averages help us spot trends.
For example, the CDC data comes from a study that shows that Americans have gotten taller and fatter over the past 40 years. It’s a red flag for the health care community, and one that tells them that action is needed to reverse the trend.
The same thing goes for PPC. If your average cost per conversion keeps inching up month after month, it’s probably time to dig in and find out why. It could mean that increased competition is pushing up your bids – but it could also mean that your website is no longer converting as well as it once did, and it’s time for a refresh.
Averages are great for client reports, too. Clients (or bosses, if you’re in-house) don’t want to see thousands of numbers – they want to see the executive summary. I’d even venture to say it isn’t possible to create a client report without using averages.
But if you’re focusing exclusively on averages, your campaign is undoubtedly suffering. When you’re dealing with the amount of data that the average PPC manager looks at in a day, some aggregation is necessary, for sure. But it’s a mistake to focus only on the averages.
There’s an old adage that says “averages lie.” Nowhere is this truer than in PPC. Here are three ways averages lie.
Sometimes your averages look fine, but part of your campaign is really ailing. Take the time to periodically dig into the detail, even if your averages look OK.
Organizations like the CDC do this all the time. They study the edges of the data as well as the middles. They’ll look at the thin people to find out why they’re thinner than average, and they’ll do the same with the heavier people. The answers will help guide the next steps in reducing the obesity trend.
PPC managers should do the same thing. Study your worst keywords and ads:
Don’t overlook this important aspect of PPC management. Set aside time each week or month to make sure you’re looking at the minutiae of your PPC accounts.
At HeroConf, Kevin Lee had a great quote about averages. To paraphrase: “If my average temperature is 98.6, but I spike at 110, I’m dead. Averages can be misleading.”
In PPC, we tend to focus a lot of attention not only on averages, but on standard deviations from the average. Put simply, we’re taught not to worry about small fluctuations in average metrics.
Sometimes, though, this inattention due to smoothing of data can be fatal.
For example, let’s say you notice one day that your average conversion rate is a bit below average. You shrug it off, assuming it’s a normal day-to-day variation.
A week later, you realize that your client changed the PPC landing page URL a week ago, and you’ve been sending traffic to a non-existent page.
Yes, this actually happened to me once. It wasn’t fun.
While not every deviation is this serious, it’s not something to ignore either – just as you wouldn’t ignore a 110 degree fever!
You could spend all day listing the poor decisions made by Google and Microsoft that stemmed from looking at aggregate, average data.
Two well-publicized examples are the near match change and the ad rotation change. These were both Google changes.
But Microsoft is guilty too. Did you know that if you copy an ad and change everything but the ad title in adCenter, you’ll get a “duplicate ad” error? Yep.
When near match and ad rotation changes were announced, the screams of horror were heard around the PPC world. “What are they thinking?” we cried.
Well, what Google was thinking was this: “Our aggregate data shows that CTR on near match terms is no different from CTR on precise match terms, and that there is no adverse effect on results. So it’s OK to make this change.”
I have no doubt whatsoever that Google’s aggregate data showed that near match and near rotate wouldn’t hurt results. But that’s because most advertisers aren’t PPC professionals.
Healthy, fit Americans look at the average fast food menu and cringe, wondering how people can eat this stuff. But people do – lots of people. The fast food menu is full of food that people buy – which is how the chains make money.
Google is the same way. The average advertiser wants to buy traffic, not optimize for conversions! So really, Google is using averages to build their business.
So if you’d like your PPC account to be lean and healthy, beware of those averages.