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How Much Website Traffic Do You REALLY Have?
Go to Google Trends and search “analytics” and you’ll see that interest in the topic took off like a rocket around 2006. According to BuiltWith, more than 26 million websites use Google Analytics. It’s great to see so many businesses embracing analytics but, there’s a painful lesson coming many are about to learn. That lesson is that making smart business decisions is tough even when your data is good. When your data is bad, it’s damn near impossible.
I’ve been helping business owners optimize their websites and generate more leads and sales from the web for seven years. In that time, I can’t think of a single instance where I inherited a Google Analytics account set up right—not one.
An improperly set up Google Analytics account can lead to all sorts of problems. For example, most websites actually receive WAYYY fewer visits than their owners believe they do.
That’s right, your website doesn’t get nearly as many visits as you think it does.
In this post, I’ll explain how this happens (and what you can do to fix it), and I’ll also explain why it’s such a big deal.
How to Remove Bogus Traffic from Google Analytics
When Google Analytics is set up incorrectly, more often than not the output is bad data—not incorrect data. You might be scratching your head right now wondering, “what the heck is the difference between bad data and incorrect data?” What I mean is that the numbers reported by Google are correct—it’s just that they’re not relevant to your business.
The following Google Analytics customizations should help you understand what I mean:
Filter Internal Traffic
When your employees arrive at your office, log on to their computes, and pull up the web, what default page comes up on their screen? For a lot of local companies, it’s their company’s homepage. Getting your employees to frequently visit your company’s website isn’t necessarily a bad idea. However, by doing this, you may be artificially inflating your website visits. If you run a large company, you might be juicing your numbers—BIG time!
The easiest way to remove employees from your Google Analytics data is to figure out the IP address for your office and then filter out visits (now called sessions) from that IP address from your reports.
Here are the steps:
- Log in to your Google Analytics account
- Select the profile from which you want to remove internal traffic
- Click “Admin” in the top navigation menu
- Look under “Account” and select “All Filters”
- Click the red box that says, “+ New Filter”
- Name your filter (something like “Remove ABC Employees”)
- What to do next is very apparent in the GA interface
Note: In addition to your employees, you also might want to consider removing various partners from your GA reports (visits from your IT guy, your accountant, your home computer, etc.).
Filter Visits from Robots
If you’re using the old school GA code, you’ve got to create a custom filter. That’s a bit more of an involved process described here.
Filter Traffic from Outside Your Service Area
If you own a local home service company (hvac, plumbing, roofing, remodeling, etc.), do you really care how many visitors from China or India hit your site each day? This “out of service area” traffic is of absolutely no consequence to your local/regional business. At the same time, taking it into account when you’re evaluating your website’s visit-to-lead conversion rate can lead to disastrous decisions (more on that below).
If you own a local/regional business, you want to create at least one profile in Google Analytics that removes visitors from outside your service area.
The Disastrous Decisions that Result from Bad Data
So your employees, some web spiders, and visitors from outside your service area are being included in your Google Analytics reports. What’s the big deal? The big deal is that, as I’ve mentioned above, making the right business and marketing decisions can be difficult when you’ve got good data. It’s damn near impossible when the reports you’re looking at are full of crap data.
Here’s one unbelievably common example:
Chasing Higher Conversion Rates Instead of Traffic
We received an inquiry once from a local plumber. He explained that with the help of an SEO company, he had built his website traffic up to 2,500 visits per month to his website. The trouble was that not very many of them were converting into leads or jobs. With 2,500 visits per month, he should have been receiving somewhere in the neighborhood of 250 – 375 leads per month. On his best months, he was receiving only about 45 leads per month (1.8 percent visit-to-lead conversion rate). He wanted conversion rate optimization help.
During an audit of his analytics data and website, we determined that the problem wasn’t with his website or its ability to convert visits into leads. The problem was that, of the 2,500 visits per month he was seeing in Google Analytics reports from his SEO company, only half of them were from the U.S. and only a quarter of those were from people living within his service area!
Effectively, he was getting 315 visits per month—not the 2,500 per month his SEO firm was reporting!
His visit-to-lead conversion rate wasn’t 1.7 percent; it was 14.2 percent.
Now, don’t get me wrong—for a local plumbing company, there’s still room for conversion rate optimization even with a 14.2 percent visit-to-lead conversion rate. However, improving a conversion rate like that is going to be a game of inches—a lot of work for a small increase. In this situation, armed with better data, the big leverage point is clearly increasing traffic.
A local plumbing company that’s been investing in SEO for any significant length of time ought to have considerably more than 315 visits per month from inside their service area.
Better Data Equals Better Decisions
In a previous blog post, I wrote about the importance of optimizing your Income Statement. When I was in college, I thought there was a right way to set up income statements and a wrong way, with nothing in between. Today, having been involved in running several companies, I see things differently.
If you run an HVAC company, it’s not necessarily wrong to lump your replacement revenue together with your revenue from service, but it’s NOT optimal. Similarily, you can put the salaries for all your HVAC techs under the Expense heading, but you’ll make better business decisions if you put them under the COGS or Cost of Sales heading instead.
At the begining of this post, I mentioned bad data vs. incorrect data. Now is a good time to revisit this point. It’s not wrong for the plumber in the example above to say that he is getting 2,500 visits per month. What Google is reporting is exactly right. The problem in this instance is that the default metric—and as a corollary, the metric being reported/evaluated—is the wrong one. This is an example of bad data—not incorrect data.
For a local/regional company, you would want to focus on visits INSIDE your service area. People from overseas and all over the country end up on your website for all sorts of reasons—don’t waste your time trying to figure out how to prevent it.
Setting up Google Analytics reports is no different than setting up your Income Statement. You can set things up in the standard “out of the box” fashion or you can work with an expert to customize things specifically for your business. Going the latter route may cost you a few bucks on the front end, but it will save you (BIG TIME) over the long-term.
About The Author: Ben Landers is the President and CEO of Blue Corona, a data-driven, inbound internet marketing company. Submit an inquiry to book Ben to speak at your next conference or event.
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