If you're smart and lucky, you named your site your main-keyword-dot-com and you get search traffic from visitors who use their address bars as search engines. For example, a search on "reusable bags" sends you automatically to "reusablebags.com" which sells...you got it, reusable bags.
Other types of type-in visitors could be:
- Loyal, repeat customers
- Late stage buyers who've already visited your site through search, PPC, email or affiliate link but needed time to make the purchase decision or comparison shop
- First time shoppers pre-sold from a newspaper article, blog post, social media reviews or word-of-mouth
Type in traffic may even be your highest converting traffic. This post will cover how to create a direct traffic report in Google Analytics, and how to compare direct traffic conversion against your site average. Plus, you'll learn how to exclude IP addresses for non-customer visits.
How to Access Direct Traffic Reports in Google Analytics
We're interested in looking at trends in direct traffic to see if the strength and awareness of your brand is increasing over time. Here's how you get the trend data:
1. Log into your Google Analytics account and click on "Traffic Sources" and "Direct Traffic" in the left hand menu.
You'll want to make sure you change the default date range to your last quarter, or the past year:
After you change the first date box, don't forget to click in the second date box once to make the "Apply" button live, then click "Apply."
2. Changing your graph to "Month" will show you an average figure per month, rather than each daily or weekly record. Believe me, this is much easier to work with. Just remember the figures are monthly averages:
Rolling over any point will show you the month average. The above image is Photoshopped to show you the year over year growth in type-ins for Get Elastic. Comparing this July's traffic over 2007, I see the blog's direct visits grew 330%, from 2152 per month to 7142.
3. Compare your direct visit conversion rates to your site average. If you click the little arrow beside "Visits," you can make some pretty useful graphs.
In this case, we're going to compare the type in segment to overall Goal 1 conversions for the past year. (Stay in "Month" mode)
The graph will even show you the spread between site and segment (not just for type in, you can use this for other segments of traffic like search engine and keyword):
Don't Forget IP Filters
But there's likely another type of visitor you're tracking - yourself! One thing that can really mess up this metric is tracking your own IP address and the IPs of others who frequent your site but are not customers. These visits could represent SEO, PPC, web design and IT consultants, employees’ home computers, the office IP block, SEOs and other web consultants, ecommerce bloggers (wink) and even competitors.
Direct traffic is not the only stat that suffers when you neglect to filter IP addresses. As mentioned in 8 Stupid Things Webmasters Do To Mess Up Their Analytics, it also:
- Understates your conversion rates. Your direct type-ins could be your highest converting traffic source, but tracking visits from employees, stakeholders and consultants dilutes your real conversion rate for this segment.
- Overstates average time on page. You think your visitors are reading every jot and tittle of your copy, when it's really your marketing team.
- Messes up your Content stats. Your “Top Content,” “Landing Pages” and “Exit Pages” will may be skewed by tracking the wrong visitors.
How to Filter IPs in Google Analytics
Once you've gathered all the IP addresses you need to exclude, go into your Analytics Settings, and find the Filter Manager in the bottom right:
You can also filter a range of IPs or use an advanced, cookies-based filter in your office which will compensate for dynamic IPs.
Then add each filter, naming each one intuitively so it’s easy to make edits in the future.
If you add a filter after reading this post, keep that in mind when you create reports in the future. Your direct traffic could drop significantly after creating the filter, and you can't apply the filter today and change yesterday's data.
Your trends may not show an upward trend, either. They may spike seasonally or after certain promotions you ran, help wanted ads or other "buzz" about your company. It really depends on you and your business.