January 5th, 2009, 7 Comments »
For at least a year, Barracuda Networks has been running large ads in Vancouver’s airport. I think I’ve seen their ads in other airports, but can’t confirm that (anybody?). I snapped a bad photo of one of several large display ads in the baggage collection area:
You can see better versions of their ads on their website.
I’m always puzzled when I see these ads. Barracuda makes humming boxes that companies install in their networks to protect against email spam, viruses, phishing and so forth. This one costs about CAN $650:
The Barracuda Spam Firewall is compatible with all email servers and can fit into nearly any corporate or small business environment. It is used by small organizations with as few as 10 employees and large organizations with as many as 200,000 employees. A single Barracuda Spam Firewall handles up to 100,000 active email users. Multiple units can be clustered together for even greater capacity and high availability.
According to YVR, about 4.1 million international passengers passed through their gates in 2007. What tiny fraction of those passengers are potential buyers of Barracuda’s products?
The math gets murky, but according to BC Stats, there are about 81,000 technology workers in BC. Of course, not all of those are potential Barracuda customers. Plenty of those have no interest in the IT concerns of their companies. Others work for companies that have fewer than 10 employees. Let’s be generous and imagine that one third of these tech workers might possibly be or know somebody who could become a Barracuda customer.
That works out to 6 out of 1000 British Columbians who might be the target market for these ads. That fraction is certainly lower for foreign visitors. So–best case scenario–that ad might be relevant to one out of every 200 passengers. In truth, I suspect the number is closer to one in 1000.
And yet this is a sadly commonplace scenario. Most offline ads are incredibly dumb–they’re irrelevant to 99.9% of people who see them. Barracuda runs these ads as an act of faith. That one or two out of the madding crowd of visitors grabbing their bags might take an interest, and start on the long, treacherous path towards an IT purchase. And do the folks at Barracuda Networks have an accurate sense of the return on investment of these airport ads? What do you think?
On a vaguely related note, I saw an enormous barracuda in shallow water in Panama a couple of weeks ago. It was at least three feet long, and just cruising gently by in about three feet of water.
7 Comments »
April 21st, 2008, 10 Comments »
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.
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