We all want to know which sites, search engines and keywords are sending us traffic. But what about direct type in traffic? When people access your site URL by typing it in from memory, it can be a great indicator of your brand preference, success of your offline and online marketing efforts and customer satisfaction.

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.

Big news in alternative payments this week: your friendly neighbourhood Amazon has just launched it’s challenger to PayPal and Google Checkout - cleverly dubbed Amazon Checkout. For 2.9% + $0.30 for all transactions over $10, 5.0% + $0.05 for transactions under $10, and tiered volume discounts above $3,000 per month, you too can offer patented 1-click ordering.

There are a few reasons you might consider adding Amazon Checkout to your roster of payment options, including:

• Access to 81 million (no, I didn’t forget a decimal) people already hold Amazon accounts. This is roughly 30% more than PayPal. Customers would not have to create a new account to checkout with you, nor share any additional personal information. If a customer has multiple billing and shipping addresses on file with Amazon, that can be very convenient for the customer.

• Through IP-targeting, Amazon can recognize Amazon.com customers and display the 1-Click checkout for them.
• Show cross-sells and upsells in your cart. And if you show Amazon products in your upsells (eww), you can earn Amazon Associate commissions.
• Call it a halo effect, but having the option to checkout through Amazon Checkout may carry some brand equity - provided experience with the Big A was positive. Plus, Amazon customers are likely aware of the A-to-Z Guarantee, which you now offer by virtue of the Amazon Checkout option.

Amazon promises increased conversion: “Amazon’s familiar checkout experience, 1-Click ordering, A-to-Z Guarantee, and tens of millions of customers who can checkout without re-entering information helps you optimize conversion on your website.”

But Scot Wingo was apt to point out that Amazon Payments comes with a price:

Amazon’s biggest weakness in general in the world of ecommerce technology like this is that they are trying to be both a technology provider to retailers and a competitor. Large retailers (TRU, Borders, etc.) have left Amazon’s third party business en masse because of this and I don’t imagine they will be jumping for joy to add Amazon’s checkout to their sites. For example, you won’t be seeing Wal-mart.com add this any day soon.

This actually plays to PayPal and Google’s advantage and I’m sure as a first response we’ll see them play up these fears: “Do you REALLY want Amazon seeing all of your transactions, learning about your top sellers and then using that data to compete with you?” The fact that Amazon has a well documented history of using partner data to their advantage in the third-party selling world will make this argument very believable.

What do you think? Would you test out Amazon Checkout or do you think the risks outweigh the benefits?

We’ve all heard of “banner blindness” - the phenomenon of completely ignoring anything that resembles an ad when surfing the website.

Image Source: Jakob Nielsen

For this reason you want to avoid sticking important links and calls to action in the right hand sidebar. You especially want to avoid colors and fonts that resemble typical paid search ads.

Home page

Product page

Silkfair product page

Same goes for navigation menus:

There are instances where even Internet Retailer 500 retailers really display Adsense on product pages:

I strongly believe reputable retailers should completely avoid paid search ads on their sites. But what’s worse, on Chapters Indigo, you can’t even distinguish the ads from the recently viewed products from the cross-sells because they use the exact same colors and fonts.

Further Reading

Yes, there is solid research to back this argument up. Thank you, Mr. Jakob Nielsen:

Banner Blindness: Old and New Findings

Fancy Formatting, Fancy Words = Looks Like a Promotion = Ignored

If you’re not familiar with Steve Krug’s web usability classic Don’t Make Me Think, it’s an entertaining and informative introduction to web site optimization. Though its screenshots and examples are quickly looking “old school” - its principles still stand. I “think” any web design and ecommerce professional should give it a read, and then give their own websites the “don’t make me think” test.

Today I’m going to apply the concepts from Don’t Make Me Think to The Source - a chain of electronics retail shops we used to call Radio Shack here in Canada, until it was acquired by Circuit City. I’m a fan of Circuit City’s web design and marketing, and have praised them many times before on this blog which is why I had high expectations from The Source’s web presence. But I found myself “thinking” very hard on this site.

This post is not intended to slam the design, but to point out areas that could be improved based on generally accepted design and usability principles.

(If you want to play along, you can click on the image to enlarge and see if you can predict which 10 issues I’m going to address in this post).

Continue Reading:
Home Page Design: Applying The Dont Make Me Think Test »

Before we dive into the link pool, I want to remind you of 2 webinars happening on Wednesday:

Christmas is around the corner, and that means cyber Monday is coming up fast. What did Top 500 Retailer Danskin do last year, what did they learn and what’s in store for holiday 2008? Join Sitebrand and Danskin for a 29 minutes of Danskin: Can It Repeat Its Cyber Monday Mega Success? Wednesday, July 30 at 2:00 PM - 2:30 PM EDT.

Marketing Experiments is offering Optimizing for PPC marketing Experiments on Wednesday, July 30 4:00 to 5:00 p.m. EDT. This is your chance to have your pay-per-click ads optimized in real-time by the Marketing Experiments team.

It’s never too early to register for the next Elastic Path webinar. We’ll be joined by Bernardine Wu from FitForCommerce for The Art & Science of Choosing Ecommerce Technology.

• Buy.com’s been in bed with eBay, listing thousands of products without listing fees. What does this mean to you? Kevin Packler discusses the ramifications for medium to large businesses not using eBay as well as smaller businesses using eBay.

• Holly Buchanan gives 3 reasons why your wish list doesn’t convert. This makes a lot of sense!

• Fortune Small Business tackles the issue of handling international payments for large, wholesale orders - including foreign exchange and the cost/benefit of wire transfers vs. credit card/Paypal.

• All you design and usability experts will find Invesp’s roundup and commentary on navigation menu lessons interesting.

• New research from Nielsen Online reports 80% surveyed purchase from a store who’s site they’ve previously visited. Your online store may be drawing local traffic from visitors who don’t know you have a brick and mortar store close by. Sitebrand’s Creating an In-Store Experience Online shows an example of geo-IP targeting in action for one of its clients.

• This week’s Get Elastic posts were keyword research / web analytics / PPC focused. Rich Page contributed a post to YouMoz this week called Stop Wasting Money on SEM that continues the brainwave.

Because the AdWords system rewards keywords with high click-through history (relative to competitors) with better ad positions and lower cost-per-click, click through rate is considered an important performance metric. Along with a keyword’s relevance to ad text and landing page copy, click through rate influences a keyword’s “Quality Score.”

Every PPC campaign is bound to have a few (or few thousand) keywords with low click through rates. You can identify them easily enough with web analytics and campaign reports, but what do you do with them?

You have at least 6 options:

1. Do nothing. You’re always going to have stinkers, why major on the minors?
2. Try to improve your Quality Score, which should improve ad position, which may positively affect click through rates.
3. Add negative keywords if you’re using broad or phrase matching.
4. Create a new Ad Group. Pull poor performers out of your current Ad Group and start over with better ad text and landing page.
5. Create an AdGroup for branding purposes. You don’t expect clicks, but using your company name in the headline is free exposure.
6. Pause or delete them. Either way, you stop bidding.

But before you take action based on click through stats alone, it’s important to dig deeper as to why the click through rate stinks.

Potential Reasons for Low Click Through Rate

If your average ad position is high (1-3), it’s probably not a Quality Score issue. It’s more likely one of the following:

• Your organic rankings for the keyword are so good, people aren’t clicking on your PPC ads, and the “double listing” of your PPC ad improves your organic click through rate! You pay nothing for the additional branding, and removing the keyword may even slightly hurt you. Do nothing, except maybe “do a little dance.”

• Your keyword has low commercial intent - meaning people aren’t interested in a purchase, they want information. Are you bidding on “wii news” because it got 22,000 searches in June? Kill the keyword phrase, and consider adding “news” as a negative keyword.

• Your keyword is broad or phrase matched with insufficient negative keywords in your campaign. Use yesterday’s Google Analytics hack to expose the actual search queries that triggered your ad, and add negative keywords as necessary.

If your average ad position is medium (4-10), you may have any of the above problems, plus:

• You’re in the Automatic Match beta. You have been automatically included and your ad is showing up for synonyms to your broad matched terms, while your competitors are not. If you are part of the beta, you will see a checkbox to opt out of Automatic Match from your Campaign Settings. Just opt out, don’t be a guinea pig for Automatic Match.

• Your ad copy stinks compared to your competitors. They have tested and found winning headlines, calls to action and display URLs. They display prices that are lower than yours. They offer guarantees and free shipping in their ad copy. Customers trust their domain names more than yours. Go to the SERPs and see for yourself. And test out different ad versions.

If your average ad position is low (10+)

• You may be bidding too low vs. your competition or for the Quality Score Google has assigned you. You may have set an initial CPC that was low and performed fine, but competition has entered the picture. Or Google simply decided to raise minimum bids for whatever reason. Increase bid as long as it makes sense to, and within what you can afford.

• Your Quality Score stinks because your keyword is in the wrong AdGroup. For example, putting “learning toys” in the “educational toys” AdGroup, means your ad might display with “Educational Toys” in the headline, pointing to a landing page that never references “learning toys”. The searcher is more likely to click on results that use “Learning Toys” - it’s more relevant, though it describes the same thing. And, your Quality Score suffers when your ad text is not as relevant to the keyword. Create new Ad Group, but don’t delete similar keywords like “early learning toys” unless they also have poor history. Otherwise, you lose that history.

• Your keyword is irrelevant to your products. Perhaps you’re a victim of sloppy outsourced keyword research, or a consultant that didn’t fully understand your business. Nix that keyword, and any others that don’t belong.

Can low CTR% be a good thing?

There may be instances you want to lower click through rates. For example, if you sell high end furniture, adding “From $2999″ to your ad for “teak outdoor patio set” will weed out the shoppers looking for Ikea-grade, who are thinking frugal but not expressing it in their search query. Plus, you’ll likely increase click through from luxury buyers. Your conversion rate, cost per conversion and ROI will improve. (It would make sense that Google factor conversion rates into Quality Score, since it is a better indicator of relevance than click through rate. Perhaps it’s one of the “other relevance factors” Google keeps to itself.)

What About Keywords With Low Conversion Rate or Negative ROI?

That’s a bit trickier.

Low conversion rate

Why spend money on keywords that don’t convert, right? The problem is, a keyword may have a 0% conversion rate but still be responsible for many sales. According to a 2005 comScore study, searchers who ultimately purchased online performed an average of 13 searches before converting, resulting in 12 non-converting searches for every sale. If the sales cycle exceeds your cookie expiration dates, some keywords may never get the conversion credit they’re due. (Great article on non-converting keywords by Frederick Marckini at Clickz)

What’s more, online searches can result in telephone orders, or even offline sales - which are even harder to reconcile, since there’s no cookie that tracks those.

Negative ROI

Keywords with negative ROI should be investigated. Are bids too high? Can landing pages be improved? Is broad match burning your budget and could keyword research help? They can even be a blessing. Lessons you learn from attempting to salvage negative ROI keywords may even benefit your campaign as a whole if you can apply “better practices” across the board.

If margin on the products or overall sales are low, you may decide to kill the keyword based on negative ROI to allocate budget for clearly profitable keywords and products.

The takeaway is to never kill a keyword simply because of a low metric. Always investigate the possible reasons for the low metric.

Are you a Google AdWords advertiser using Google Analytics? STOP! You MUST read this post because you are losing money daily and we are going to help you stop the bleeding.

There is a problem with the default functionality of Google Analytics when used in conjunction with AdWords. Google Analytics (GA) doesn’t report the actual phrase a shopper entered into the search bar, only the keyword phrase you are bidding on.

Let me explain:
- You bid on the keyword ’shoes’ using ‘broad match’
- A shopper searches for ‘blue suede shoes’
- The Traffic Sources > Keyword report in GA shows the search as just ’shoes’

Even worse, Google likes to use synonyms when your terms are under the broad match type (called automatic matching or extended broad match).

- You are bidding on the keyword ‘running shoes’ using ‘broad match’
- A shopper searches for ‘Adidas Gazelle’
- Google shows your ad, but wait, you don’t carry Adidas shoes

Why would Google do that?

The shopper searched on blue suede shoes, not shoes! You don’t sell blue suede shoes. You have been making decisions based on inaccurate data.

Follow these simple steps to start seeing the EXACT phrases people are using when they click your AdWords ads.

It will help you find terms to add to your negative keyword list. You can also start honing your ad and landing page copy to better reflect how shoppers search.

The Google Analytics Exact Query Solution…

This solution comes from our friends at VKI Studios, a Google Analytics Authorized Consultant and overall great bunch of people (see their analytics blog for some great tools and tips). Specifically, Brian Katz. They have evaluated various means of cracking this nut, and we have their final solution. Credit and comparison of other methods are at the bottom of this tutorial.

1. Create a new Google Analytics Profile

We do NOT want to overwrite any core data, so a new profile keeps everything intact. Even Google says it is a good idea.

Select Add a Profile for an existing domain, select which domain, and enter any name for the profile you choose - the more descriptive the better. You will not have to add any tracking code or tag anything, so no need to get the ponytail guys involved.

2. Create the first filter

Locate your newly created profile and click Edit under the Settings column. Then click Add Filter.

Field A -> Extract A: Referral: (\?|&)(q|p|query)=([^&]*)
Field B -> Extract B: Campaign Medium: (cpc|ppc)
Output To -> Constructor: Custom Field 1: $A3

3. Create the second filter

Locate your new profile again and click Edit under the Settings column. Then click Add Filter.

Field A -> Extract A: Custom Field 1: (.*)
Field B -> Extract B: Campaign Term: (.*)
Output To -> Constructor: Campaign Term: $B1 ($A1)

As with almost all multi-part filters, sequence is critical and must be ordered accordingly using the “Assign Filter Order” page for the profile.

That’s It!

Here are what the results should look like when you run the Traffic Sources > Keywords > Paid report in Google Analytics:

The following set of results were obtained using an in-line filter to show bid-terms that would be different from the search terms

An unfiltered result would look as follows:

The above technique provides useful data as is but it does have some shortcomings in that it does not associate the newly overwritten Campaign Term field with Transactions, as is shown in the following screen shot:

It is probably the result of using session-based values (e.g.: all the Campaign fields) and pageView-based values (e.g.: Referral). Caught in the middle are the event-based eCommerce transactions.

In his book “Advanced Web Metrics with GA” (Page 199) Brian Clifton documents a method attributed to Shawn Purtell of ROI Revolution that uses 3 filters to show each Transaction with its bid and search terms appended.

We are experimenting with a combination of those filters and the ones described above to extend the solution to include eCommerce and will post the solution when we have it. So make sure you subscribe to the RSS Feed or by Email to be notified when it is available.

Hat Tips to Others Tackling this Problem

The original solution for this came from Brian Clifton, formerly of Google.

The solutions (Using Filters):
- How to Get Detailed PPC Keyword Data from Google Analytics
- NUDE: AdWords Keyword Data Exposed With Google Analytics!

An updated solution from ROI Revolution (Using JavaScript):
This solution uses the User Defined variable so it won’t be appropriate if you’re using the User Defined variable (created with _setVar()) already
- Exact Keyword Tracking with Google Analytics, Revisited
- Exact Keyword Tracking with ga.js

Comparison of the two methods

I checked out the two methods (Filters vs. JavaScript) . Since readers commented saying the filters did not work or “no longer worked”, I took a closer look. The devil is in the detail. Errors in their implementations may have been the cause of the malfunctions.

JavaScript vs. Filters

JavaScript
The two methods both extract data from the and Referrer and Campaign Medium checking the latter for “ppc” of “cpc” using regular expressions. They both concatenate the bid and search terms. The JavaScript method goes 1 step further by looking for the gclid value unique to Google AdWords. That may also be done in the filters but I don’t believe it would enhance the filter solution.

The JavaScript performs its magic at run time. It uses the “troublesome” _setVar() cookie to store the bid and search terms in the User Defined field. It does so using a generally accepted “kludge” to work around _setVar()’s issues (a topic all of its own).

The greatest disadvantage to this method is that it monopolizes the User Defined Value. With all its troubles, it is an invaluable resource that most will (should ?) be using to segment visitors. Since it is stored in a domain specific cookie it cannot store profile-specific data to different profiles (well, it can be pushed to greater limits but that is a blog post all of its own).

It should be possible to rewrite the URL of the landing page before ga.js writes the Campaign cookie (again a topic of its own)

Filters
The filters run at data processing time and so, I expect those may prove marginally more reliable than JavaScript and cookies (although all subsequent visits from the AdWords campaign will rely on the keyword and other campaign data being extracted from cookies by ga.js or urchin.js) so that is no reason to choose one above the other.

By default, however, I am biased in favor of filter-based solutions because they are independent of the implementation and so don’t require updates to a site’s GA coding. Implementation is quicker and easier, as is propagation of the solution across profiles and GA accounts. In fact, in the time it takes to update the code on some sites (those that are not tagged as efficiently as they might have been) or in the time to get a site’s 3rd party developers to make the changes, a GA consultant could implement the solution for a number of accounts, regardless of the level of access the consultant has to the coding.

Note: Analysis and much of the technical write-up done by VKI Studios, Brian Katz

Our last post covered tips on using Google’s free Keyword Tool and how to apply your keyword discoveries to various aspects of marketing: SEO, PPC, site usability and even email marketing.

As promised, today we’re going to dig deeper into negative keyword research. The tools we’ll cover are the Google Keyword Tool, Google Suggest, Google Product Search and some surprises.

Negative keywords explained

If the term “negative keywords” is new to you, it refers to irrelevant or low converting keywords that you add to a pay-per-click campaign which tell the ad system not to show your ad when that keyword appears in a search.

To take advantage of the “long tail of search” (longer query combinations and product searches that are performed infrequently but can convert like crazy), marketers will bid on broad keywords using “broad matching” or “phrase matching.” If you phrase match “learning toys” your ad would appear for “learning toys for 3 year old toddlers.” Broad match would include even more searches like “best toys for motor learning.” The problem is, often times these match types cause you to show up for searches that have nothing to do with your products, or that don’t have a high “commercial intent” behind them. This hurts your overall campaign performance.

Why Google wants you to research negative keywords!

It’s in everyone’s best interest to prevent results like this:

Google makes more money if ads are relevant and searchers click on them instead of organic results, retailer can attract more clicks when there are less competing ads (especially from high budget software companies), and customers don’t get so confused.

Here’s how you use various Google tools to build out your negative keyword list to avoid your ad from appearing for irrelevant searches when using broad or phrase matching.

Google Keyword Tool

When using AdWords, you can access the Keyword Tool from inside your account.

This section assumes you understand how the Keyword Tool works. Yesterday’s post advised you to switch your match type to “Exact” to see exact search counts. Today we don’t care about keyword popularity. We just want to find as many negative keywords as we can.

If you switch the match type to “Negative,” all that changes is the square brackets from exact match are changed to the “-” sign before the keyword, so you can build your shortlist of negative keywords and import right into an AdGroup or Campaign, or save in text or .CSV format. This doesn’t change the keyword suggestions,

But remember that Google’s Keyword Tool does not give you enough negative keyword data, you still have to go digging further. You can manually add additional keywords, and then create one text file or .CSV

(Note that if you add “wooden” once, your ad will not appear for “wooden puzzles,” “wooden blocks,” etc. You don’t need to add “wooden + keyword” to your list. If you do carry some wooden toys, you should consider creating separate AdGroups for only the wooden toys you carry (better landing page selection, higher quality score, better ad text), for which you would add negative keywords for the wooden products you don’t sell - “blocks,” “puzzles” etc).

Google Suggest

Type in your keyword, e.g. “learning games” and Google will drop down suggestions.

Keep in mind 2 things:

1. The numbers that show are not keyword counts, but results of pages in Google’s index. The higher the number, the more competitive the keyword is, actually. But, because Google suggest shows long tail search terms, you can use this tool to pick out additional negative keywords the Keyword Tool didn’t bother to show.

2. You can’t see all the suggestions when typing in your broad match. You’ll need to go through the alphabet, first typing a space and then “a” - if no results, you continue until you hit a letter with suggestions:

Sometimes you have to apply this going-through-the-alphabet system on top of a suggestion, like “learning toys for a…, b…”

You’ll have to make notes on which keywords to add, maybe on a notepad. Make sure you add them to the appropriate campaigns - and you may discover new keywords to bid on in the process.

Google Shopping

Google Product Search is the shopping engine formerly known as Froogle, and confusingly labeled as “Shopping” from the links across the top of Google’s home page, or when you’re in Google Reader, or Gmail…

You can use Google Product Search to find negative keywords in a couple ways. Perform any keyword search, and scroll to the bottom to see more links, and check out the “Brand” and “Related Searches” links.

Clicking “More” expands the lists:

Adding brand names you don’t carry as negative keywords is very important. When a search query involves a brand name, it’s a strong signal that someone is looking to research or purchase a specific item, not check out other brands. So your general ad will have lower click through, which lowers the click through rate of your entire AdGroup, hurting all your keywords’ ad positions and possibly raising your cost-per-click.

Not to mention your landing page quality score will be lower if it doesn’t reference that brand. And, even if you do attract clicks, there a much smaller chance of conversion, though you still pay for the click. And if your broad matched keyword is very competitive, it could be an expensive click!

You can also turn to a review site like Buzzillions to glean brand names. Buzzillions aggregates reviews from retailers using Power Reviews, so there’s a good chance most if not all brands are represented. Simply go to Buzzillions, type in your keyword, and check out the brands listed in the left hand navigation:

(Numbers indicate the number of branded items with customer reviews, not number of customer reviews or keyword popularity.)

Or, use eBay for negative keyword research, as I wrote about for SEOmoz’ YouMoz Blog last year.

Google Analytics

Of course, using your Referring Keywords report, you can mine your Google Analytics data to weed out referral keywords that don’t relate to your business. And you can segment out non-paid and paid searches from your reports.

But wouldn’t you like to know which “long tail” terms your broad match and phrase match terms are bringing in? You can identify them with Google Analytics, but it requires a hack, which we will cover in depth tomorrow…

By now you’ve probably heard the news, Google has made keyword search counts available to all through its Keyword Research Tool (before it only showed relative search volume in little green bars).

There are many free and paid keyword research tools out there, but until this announcement, none were able to provide Google-only data. But like Avinash Kaushik said last week in his Analytics webinar, “The goal is not to collect more data – it’s about extracting insight from this data.”

So today we’re going to go through some tips on how you can tailor Google Keyword Tool’s data to your needs (much like you would with Google Analytics), and how you can apply this research beyond your SEO and PPC campaign to other marketing activities. We’ll also cover the limitations of this (and all) keyword research tool(s).

Google Keyword Research Tool Tips

1. Select Your Countries

Google will share search volume based on country (not sure if it’s calculated from Google.ca, Google.fr etc only or if they include Google.com searches performed outside of the US). So you can change the default US database to your territory. But if you sell to multiple countries from one website, or you target multiple countries from one AdWords campaign, you can select more than one country by doing a “Control + Click” or “Command + Click” - depending if you’re Mac or PC.

You can also simply select All Countries if you sell globally, anyway. Of course, there’s also multiple language selection - but I’m not sure why you’d want to select multiple languages at once.

2. Generate Keywords

There are a couple options for generating keywords - you can enter your own keywords, or use an existing URL. In the second option, Google will extract keywords off the page and generate related keywords.

Option 1: Keywords

Type in a few off the top of your head, or import an existing list from an AdGroup, for example.

In this case, if you’re a retailer selling “learning toys” - you could type in the obvious “learning toys,” “educational toys,” “baby toys,” “toddler toys,” “children’s toys.”

Choose to use synonyms or not. I’d use synonyms the first time, and if the results are irrelevant, go back and uncheck the box, and redo the search.

You can also apply negative keywords, for example you sell parachutes, you should exclude “coldplay” and “what color is your.”

Then, click “Get keyword ideas.”

Option 2: URL

Here’s a trick - don’t use your own URL. If you sell “learning toys” - choose the top search result for “learning toys” in Google and let Google extract related keywords off that page.

You can also toggle between your 2 options without losing your keyword list or URL input, just click “Get keyword ideas” again to re-run the search. When you’re doing heavy-duty keyword research, sometimes you need to look beyond what you have brainstormed - so leverage your competitors. Just be sure to ignore keywords that are not relevant to your site.

3. Set your match type to “Exact.”

When looking at data, if you choose broad or phrase match, you’ll end up with inflated keyword counts because it will include longer queries that include your keywords. For example, “learning toys” would include searches for “learning to make wooden toys” with broad match, or “used learning toys” with phrase match. Exact match will show you the true keyword count.

Unless you’re using the tool to work on your AdWords campaign (building AdGroups or looking at advertiser competition or estimated bid prices for broad and phrase match), then you don’t need to see broad and phrase match stats.

4. Add or Remove Columns

By default, you can’t all the data available. Simply click “Show All” to see everything, and remove the columns you don’t need, like Average Position or CPC if you’re not doing AdWords. (Some AdWords advertisers don’t trust the estimates anyway).

Removing columns not only simplifies what you’re looking at, but helps you export only the data you need to text, .CSV or with the Table Tools Firefox plug-in.

5. Jump to Data

If you used the URL option, Google will “chunk” out your keywords into smaller groups, but you can navigate them through links:

6. Sort Data

Don’t forget that the Keyword Tool, Google AdWords and Google Analytics tabular data is sortable just like an Excel spreadsheet.

7. Download ALL Keywords, Don’t Build a List

You can click “Add {match type}” to build a list of the keywords you want, but this won’t keep your search volume data. So make sure you’re looking at the data you want to keep (the columns that are relevant), then click download {option} (text, .CSV):

Then delete the keywords you don’t want from there. For this reason, I suggest keeping your keyword lists tightly focused so they’re easier to work with and make decisions from, rather than every single keyword that might apply to your site (choose a category or a line of products). You could paste the data into one big spreadsheet if you want (a worksheet for every group of keywords). If you know of a more efficient way, please leave us a comment.

Applying Keyword Research

Now we’re ready to apply this data to various marketing activities. These are just examples, not exhaustive applications for each activity.

PPC

If you’re researching for PPC and you sort by advertiser competition (click twice to get low-high), you may spot a decent volume keyword that’s relatively cheap, like “learning express toys.” If you don’t carry that product (and you don’t because it’s a competing toy store), you’ll want to make sure you add “express” to your negative keyword list (if you use broad match).

Come back tomorrow, we’ll cover negative keyword research in more depth.

SEO and Site Usability

Sometimes there are two ways to describe the same thing. What are customers more likely to think of - “educational toys” or “learning toys”? “Educational games” or “learning games”?

You could take a wild guess, but keyword research will give you better insight. If you sort by “Approx. Average Search Volume” (not last month’s searches but average monthly search), you can compare synonyms:

• Applying keyword research to categorization and navigation labels

In this case, a toy retailer would do well to use “Learning Toys” and “Educational Games” as text links in navigation menus. Not only does it give an SEO boost to those category pages, but also has a better chance of being spotted by a customer who’s scanning the page looking for that keyword she typed in the search engine to get to the site.

If you discover highly searched keywords, you may even create categories or prioritize which links appear in your menus (to keep menus manageable, some retailers will “chunk” menus into 7-9 links, with a “view all” or “more” link to see all categories).

• Applying keyword research to merchandizing zones

Different types of products may spike in different months, so featuring them on your home page at different times of the year makes sense. You also provide the category or product page links a bit of an SEO boost by linking directly from the home page (makes it look more important in search engine’s eyes).

From content on Wonderbrains.com’s home page

Melissa and Doug and V Smile seem to be in-demand brands - why not feature them on the home page, or in the Educational Toys or Learning Toys category? Even if your sales data shows your sales for these brands are low, it may be because you’ve buried them in your site and you’re not attracting SEO or PPC traffic for these terms.

• Applying keyword research to site search

You can also manually tweak your site search to make the hottest brands appear on top (as long as your site search tool allows you).

You should also pay attention to synonyms that you may not have optimized internal site search for. Perhaps you lost 50 sales last month simply because you delivered “0 results found” for “educational games” because your category is called “Learning Games.”

If you use keyword tagging for products (which may create keyword optimized pages in search engines, depending on how you implement), you can tag with synonyms.

• Other Applications

Boost your SEO by creating new content (or blog content), adding keywords to your title tags, or using keywords in “anchor text” for your internal linking and in external link building campaigns. Or use keywords and hot products in your email marketing headlines and offers. If you’re really daring, register keyword domains and redirect to your site (to capture type-in-traffic) or build out niche microsites.

Limitations

Despite how uber-excellent this tool is, it’s not perfect. Do keep in mind:

• This is historical data, which can never precisely predict the future. Just because V Smile was all the rage last year, doesn’t mean it’s this year’s hit.

• This data can’t show you conversion rates or your “real” click through. It depends on your SEO and PPC optimization, your competition, your product offering, the relevance of your offer, your price, your landing page, the economy…
• This can’t show you keyword profitability. Maybe you’re burning your budget on high volume keywords - the broad ones where people are just researching and not ready to buy (though you can estimate commercial intent with a tool from Microsoft)
• This data is only Google’s - and Google still only has ~60% market share. Maybe Yahoo and MSN traffic converts better for your industry, and your market prefers these engines.
• Some people claim the estimates are way off when reconciling against their AdWords keyword impression counts. But do keep in mind discrepancies can happen for many reasons:
  • you need to apply the proper geo-targeting filters

  • your campaign may be set to show ads more evenly over time, thus not appear for every search
  • you may exceed your daily budget some days and not appear for every search
  • your ad may not appear on page one every time - search was performed but your position was below 10
  • your match types are different
  • AdWords impressions include the “search network” (AOL, Ask, Shopping.com for example), while the keyword tool restricts to Google.com and Google TLDs (.ca, .co.uk etc)

  Got any other ideas how you can use the Google Keyword Tool? Have you played around with it and found it lacking? Discover a hack or have a tip I missed? Please leave a comment.

  And stay tuned, we’ve got lots of tips on how to maximize Google Tools this week.

It’s exciting to be part of a growing blog…I must admit one of the first things I do in the morning is visit Get Elastic to check the Feedburner stats. So today was very exciting to see our subscriber count crack the 4,000 mark, making Get Elastic the most subscribed e-commerce blog in the world. So a big thank you to all of our valued readers who have subscribed, shared with friends and co-workers, bookmarked, blogged about and linked to Get Elastic and attended our webinars! Like they say on the airplanes, “we know you have options, thank you for flying with us.”

If you’d like to find more ecommerce blogs to subscribe to, I posted a list of as many as I’m aware of a while back, as well as non-blog resources for ecommerce topics.

And if you’re a new subscriber this week, welcome! Friday’s are traditionally link lists to recognize other blog posts that are helpful to online retailers.

• Do testimonials help or hurt? You’ll never know for sure until you do your own testing, but before you test, you will benefit from the expert testing done by others. Marketing Experiments recently offered a free webinar on testimonial optimization. You can catch the replay of Are Your Testimonials Properly Optimized? complete with case studies.

• Marketing bloggers are also web shoppers - and often our blog content is born out of personal experiences, positive and negative. Tim Peter and Andy Beal share their experiences this week, reminding us that customers don’t want to buy the wrong thing and overnight shipping shouldn’t take a week.

• Invesp Consulting has a 2 part series on choosing an ecommerce platform, do check out Part 1 and Part 2. And don’t forget next month’s webinar is all about the ecommerce platform decision. (Though we are an ecommerce software company, the webinar will not be self-promotional).

• Before you get too excited about Google’s improved Flash indexing, read Rand Fishkin’s 7 Compelling Reasons Search Engines and Flash Still Don’t Mix for a reality check. If your ecommerce site is still full Flash, remember your content still exists on one URL, among other issues.

• Don’t have the budget for comparison engines but still want to play in the channel? Kevin Packler provides tips on how to optimize for Google Product Search over at the Mercent Blog.

• Chad White spotted an email-contest idea from Circuit City - have customers create wishlists, register for an account and be entered into a $1000 sweepstakes draw. Chad notes this type of promotion encourages browsing and product attachment, not just entering a name and email in a draw.