Is Compete.com Total Bollocks?
In marketing, measurement is always a thorny issue. Traditional marketers sometimes shun measurement, in part because it’s downright tricky. For example, how can you accurately measure how many people see a billboard or a magazine article?
Web marketing makes things easier, because along came web analytics and a host of related tools to rely on. However, measuring reach can be difficult.
For example, at Capulet, we recently ran a small blogger outreach campaign for the Clean Air Foundation. We approached a bunch of bloggers to write about their Mow Down Pollution program, and some of them did.
Yet, how many people actually read those dozen or so blog posts? And how many will read them over the next year (or five)? That’s reach. And while there are a few tricks, there’s a lot of guesswork.
Reducing the Guesswork
A company like Alexa has, for years, been trying to reduce that guesswork. We’ve also been trying out Alexa competitor (heh) Compete. Both use communities of users who agree to install browser plugins and contribute their usage data to the company’s database. I’m no statistician, but I’m pretty sure there are significant issues with this method of data collection. But let’s ignore that issue for a minute.
I wanted to check out Compete’s data. I have access to the stats for a varied group of websites, so I thought I’d run some comparisons between the relatively empirical Google Analytics and Compete.com’s estimates.
The following table shows monthly visitor totals for nine websites, and the ratios between Google Analytics and Compete.com’s numbers.
| Type of Site | Analytics | Compete.com | Ratio |
| Blog #1 | 117227 | 32944 | 3.55 |
| Blog #2 | 2030 | 1879 | 1.08 |
| Blog #3 | 15050 | 688 | 22.5 |
| Blog #4 | 51007 | 6159 | 8.28 |
| Community site | 6610 | 619 | 10.6 |
| Services company | 1270 | 569 | 2.23 |
| Software company #1 | 30656 | 5161 | 5.94 |
| Software company #2 | 1143 | 1715 | 0.66 |
| Static site | 28653 | 3528 | 8.12 |
| Total | 253646 | 53262 | 4.76 |
I’d hoped that I might be able to find a consistent ratio between the two, but clearly they’re all over the place.
In the past, I’ve suggested that these services might be useful for comparisons. We talked to Vanessa Fox about this in our ebook. Here’s what she said:
All of the services are fairly notoriously unreliable. They all use different methods for gathering data that make them fairly inaccurate
by their nature. (Alexa, for instance, uses the Alexa toolbar, which is skewed towards a certain demographic of users.) However, a couple of ways any of these tools are useful are for trending over time and comparisons. If you use one tool to gather data on these two things, then while the data will be unreliable, it should be equally unreliable over time or between sites, so the trending should be fairly accurate.
Judging from my admittedly small data set, I’m not going to rely on Compete.com for comparisons anymore. Consider the table above. According to Google Analytics, blog #3 is roughly seven times more popular than blog #2. According to Compete.com, blog #2 is three times more popular.
Compete offers some explanations for this variance, but I can’t imagine why the ratios would be so wildly different.
There’s still probably value in, as Vanessa suggests, tracking trends over time. However, I wouldn’t use Compete.com for much else.
Add To My Data Set
If you’d like to contribute monthly visitors for a website from Google Analytics and Compete.com, please leave them a comment. If you don’t want to, you don’t need to name the site. Just indicate what kind of site it is.
I looked at the last year’s worth of data in Google Analytics, and dividing by twelve to get an average monthly total.
