A Look at Google Multi-Channel Sales Funnels

August 26, 2011 by  
Filed under Website Analytics

You cannot manage what you do not measure.

This single phrase simply can’t be ignored. Without measurement there is no gauge on progress and it becomes virtually impossible to determine if your efforts are effective at building your business and reaching your goals.

Despite this, I find it incredibly stunning how many business do not take full advantage of the analytic suites available to them. They install what they call ‘tracking’ when in fact, the information they are recording means little to maximizing the effectiveness of there overall objectives.

More specifically, determining how effective a particular channel of the business is often requires tracking visitors through what is called a funnel. In a funnel, the visitor enters at a specific point and is guided toward an end objective. That objective can be anything; a download, a contact us request, or in ecommerce—ideally a sale.

However, a visitor seldom follows a perfect liner path to a conversion. More often they start at one point, go through a series of channels along the way called micro-conversions, go back to a few earlier channels (or find new channels), then complete the final objective—the macro conversion. Each of the micro conversions play a role in the macro conversion, without them, the macro conversion doesn’t happen.

Understanding what micro conversions—or points along the way—they took to complete the objective is critical in fine tuning your marketing efforts at each step. Tracking only the last contact point of the funnel (i.e. the last page or ad the user clicked before they reached the site which in turn lead to the conversion) vs. tracking every point along the way is ineffective and leaves a lot on the table.

Let me illustrate using the following example. A visitor clicks your PPC ad but then after arriving at your site leaves at some point and does not complete the sale. They come across your Facebook page a week later, look over that, then take an offer you had on the page to download more information about a specific product via an email optin—and they leave again.

A week after that they read over the info about the product and click a bookmark they had made of your site upon one of their initial visits. This time they decide to make the purchase.

If you were only tracking from the final entry point to the end conversion you would believe that this conversion originated from a ‘direct referral’ such as a bookmark, by directly tying it into the address bar, or by another similar method—and that is true to a certain extent. The conversion did come after the directly linked to the site, but that was not where the funnel truly started.

You see, the way your customers interact with your entire sales channel, not just part of it, leads to what happens in the end. If you knew exactly which channels they interacted with before they reached the final point leading to a conversion, you could setup more fine tuned marketing efforts at each stop along the way.

Thanks to Google’s introduction of multi-channel sales funnels, the landscape has changed and we are now able to see a more complete representation of the exact path—and even timeframe—taken to a given conversion (in our example 3 weeks from beginning to end.)

Multi-channel sales funnels include tracking for but not limited to:

  • Paid and organic search (for all search engines)
  • Referral sites
  • Affiliates
  • Social networks
  • Email newsletters
  • Display ads
  • Custom campaigns that you’ve created, including offline campaigns that send traffic to vanity URLs
  • And more …

With this new information in front of you it is now possible to see that in fact the first contact with this new customer in our example came through your PPC advertising and not through the direct link alone—and this was approximately 3 weeks prior to the actual conversion occurring. Although initial visit did not produce a sale, it did get them interested enough to get to know your company further (through your Facebook page) and in turn, the information they downloaded after opting in to your email was what might have finally pushed them to come back (through the bookmark) and eventually buy.

Armed with this detail, you can now see that without the PPC they likely would not have started the process, and without the information you presented them with for download, they may have gone elsewhere. So each step in the process was an integral part of them making a purchase.

How do you setup and use the multi-channel sales funnels?

You don’t really need to setup multi-channel sales funnels in Google Analytics—they are a set of reports. However, although you do not need to setup anything in particular that directly relates to the reports, you do need a few things active within your Analytics account for the reports to be made available to you.

  1. You must have either Goals, or Ecommerce Tracking turned on for your website.
  2. You must be using the new version of Google Analytics (click the “New Version” link from your Analytics dashboard to activate it.)

  3. Once you’ve got those two items in place, you should now see a new tab called “My Conversions” at the top of your page within Google Analytics. Use that tab to navigate to the multi-channel funnels area.

  4. For even more detailed information about your advertising campaigns make sure you link your AdWords account to your Analytics account.

More often than not, those who become customers don’t simply follow a straight line path to a resulting conversion. With the various channels available to them today they may click an ad, visit one of your social media pages, follow your tweets, read your emails, and more. If you knew precisely the route they took to generate the final conversion you have more power to optimize your marketing at each point along the way—increasing your opportunity of closing more sales. That’s what multi-channel sales funnels do for your business.

Google Introduces Weighted Sort

August 25, 2010 by  
Filed under Website Analytics

If you want to fine tune your website in an effort to increase sales you absolutely must pay attention to what your website analytics is telling you. In short, you must know where your problem spots are if you are going to be able to correct them.

Now, there are a number of website metrics that should be focused on in an effort to uncover problems. One of them is your bounce rate — both website wide, and on individual pages throughout the site.

Now, don’t confuse bounce rates with exit rates. The two represent different items. A bounce rate can be defined as follows:

Bounce rate represents the percentage of initial visitors to a site who “bounce” away to a different site, rather than continue on to other pages within the same site. Or in other another way of saying it is the percentage of visits where the visitor enters and exits at the same page without visiting any other pages on the site in between.

It goes without saying that ideally you want your bounce rate as low as possible.

To determine where you have problems associated with bounce rate it is best to drill down on a per page level and determine which pages produce the highest bounce rate. Until now, doing this worked similar to the following: you locate the content sections of your site within analytics, you click the bounce rate column to sort from highest bounce rate to lowest, you are presented with a list of pages from 100% bounce rate to lowest and then you start to scan / scroll / analyze those returned based on what is really important and indicates a problem area.

The initial results returned using this method are useless. You get pages with 100% bounce rate that really don’t indicate a problem spot and for the most part are only listed at the top because of their ’100%’ measurement. Now, you might be asking how can a page with a 100% bounce rate not be a problem. I’ll provide you with a brief example of this very concept.

One visitor arrives at a page deep within the site (we’ll say the contact page) and then bounces leaving analytics with a 100% bounce rate. One thousand visitors arrive at the home page and 500 bounce leaving a 50% bounce rate for the home page. Although the visitor who arrived at the contact us page resulted in a 100% bounce rate, the more important bounce rate to pay attention to is the bounce rate of the home page. Why? More visitors arrived at the home page than the contact page and thus, the ‘weight’ of the bounce for the home page is more of an indicator of a problem point on the site. Think of it as working with a “larger data sample.”

Having provided this example it now becomes clear that the past sorting method offered by Google Analytics did little to quickly provide the information needed to help make decisions fast. Yes, you could get to it, but even after sorting you had to wade through pages of information to really find those pages that should get attention.

All that has changed with the addition of weighted sort in Google Analytics. Weighted sort enables you to now drill down on previously useless sort results based on the ‘weight’ each page (in this example) has over others on the site. This provides more relevant results faster and thus makes it easier to determine where to focus your attention when attempting to improve your website.

You can read more about the new feature and how to use it here:

http://analytics.blogspot.com/2010/08/introducing-weighted-sort.html

Tracking Google Product Search Traffic in Google Analytics

April 7, 2010 by  
Filed under Website Analytics

I recently had a member ask me this question and after some research found a number of answers. All were interesting.

The question we are looking to find an answer to is “how can we track traffic arriving from Google’s Product Search separately from all other traffic within Google Analytics?” For those of you not familiar with it, Google’s Product Search provides product based results on items that are loaded through Google Base accounts.

Here are two main options I found for accomplishing this.

The first option is a quick way to use filters in GA to segment the traffic. This option might be best for sites that have a lot of product linked urls listed in Google Product Search. The second method uses url tagging (we talked about this in recent posts) and can be arrived at two different ways and although works, might not be the best if you have a lot of urls to change.

Option 1 (Use GA Filters):

Using filters can help alleviate the need to tag many urls. We can setup a filter within GA that segments the data we are already receiving and breaks out the portion of traffic that comes from Product Search. Here’s how:

When you perform a search on Google, you’ll see that your results page has a URL that looks something like the following:

http://www.google.com/search?hl=en&q=product+search&aq=f&aqi=&aql=&oq=&gs_rfai=

The key point to note here is that when performing a search from the Google Search Engine all searches start with the following string:

http://www.google.com/search?

However, when you perform a search from Google Products the url looks something like this:

http://www.google.com/products?hl=en&q=product%20search&um=1&ie=UTF-8&sa=N&tab=wf

The key point to note here is that when performing a search from the Google Product Engine all searches start with the following string:

http://www.google.com/products?

Knowing this we can setup a filter using the Referrer field to differentiate between the two and then use the Source field from within Analytics to view the data based on referrer.

Tracking Google Product Search

Field A in our filter looks for a Referrer like one of the Google URLs shown above. Field B limits the data returned to only organic searches (AdWords ads can appear on the Google Product Search pages also, and we don’t want to mess up that reporting). The Output To section actually changes (or rewrites) the Source to “google base” instead of just “google”.

Here is what it would then look like in reporting:

product search source reporting

Option 2 (Use URL Tagging):

Method 1:
If you don’t have a lot of URLs to tag and want to do option 2 then you might be able to get away with the information presented here:
http://www.google.com/support/merchants/bin/answer.py?hl=en&answer=160634

Method 2:

If however you have lot of product URLs to tag and want a better way of doing it then the following might be a better option.

This method uses the same concept I had introduced in previous post on using Google’s URL Builder to for tagging.

In this method though we tag the URLs with:

?utm_source=google&utm_medium=base&utm_campaign=products

The components that are going to let us get segmented reporting on the traffic from Product Search within Google Analytics are source=google and medium=base.

When you go this route your reports will be broken down as follows:

product search tracking

Here are the steps to follow for tagging your URLs:

We are going to use the native Excel format for the feed to address the tagging.

1. Download your product feed and open it with Excel

2.Insert two columns to the right of the column that contains your product URL (column header should be “link”)

3. Write your tracking code into the cell to the right of the URL (see below):
tracking_productsearch_ga4

4. In the next cell to the right the one you just inserted, write the following formula, substituting cell numbers if appropriate:

=CONCATENATE(B2,C2)

You should see a result similar to the screenshot below showing the two cells merged together:

tracking_productsearch_ga5

5. Copy the cell formula all the way down to cover all of your products so that all of them having the tracking added.

6. Highlight all of your product URLs (in the third column of the spreadsheet) which now have the tracking code added, and then copy and paste them into Notepad

7. Delete the columns you’ve just created so that you only have the ones you started with.

8. Paste in all of your new URLs over the top of the old ones – you have to do this in order to get the spreadsheet back in a format to be uploaded – the extra columns will be rejected.

9. Upload revised feed to Google

10. After a day or two, log into Analytics and go to traffic sources. You should be seeing traffic from Google / Base showing.

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