Web Marketing Today

Understanding Goal Funnels in Google Analytics

The conversion funnel is a key process for most commercial websites. Whether you are using a website to drive leads to your B-to-B business, or asking people to download a coupon for your brick-and-mortar retail store, getting a potential customer successfully through the process is critical.

Your website should instill confidence in your brand, to encourage prospects and customers to take action — by filling out your web form, placing an item in a cart, or diving deep into your content.

If the story isn’t strong from beginning to end, you need to understand what part of that story needs improvement. In Google Analytics, a funnel attached to a goal will do exactly that. For assistance in setting up tracking goals, read “Using Google Analytics for Lead-generation Tracking,” my previous article. A funnel will track what percentage of visitors followed your sales process step by step, and then inform you where visitors are falling out — i.e., not completing the next task you are asking them to do.

Setting Up Goal Funnels in Google Analytics

Once you have a goal to measure, think about how you want your prospects to achieve it. This could be getting a prospect to a landing page or a contact page. For complex sales — custom products, services, high-ticket ecommerce items — this is an unreasonable expectation. You will likely need to begin nurturing prospects even during their visit by presenting compelling reasons for them to engage with your business.

Imagine a manufacturer looking to sell high-end capital equipment such as injection molding machines. Likely it will be looking to quote other businesses on their products. So for that company, a goal funnel structure may look like this:

Landing Page > Product Specifications > Quote Form > Quote Acknowledgement

This would be four separate web pages, each critical in beginning a relationship with a potential customer.

To create a funnel to study how this sales process is working, set up a goal that triggers whenever the “Quote Acknowledgment” page is reached. While setting up that goal, toggle the funnel “On,” indicating that you want to study a set of pages ahead of that action. In this example, I’ll set up a URL Destination Goal that will trigger when the Quote Acknowledgement page is viewed.

Create a Funnel to study the pages leading to the quote page.

Create a funnel to study the pages leading to the quote page.

In the image above, you are naming the funnel steps, and entering the web pages that are in the funnel. Note there are only three steps in this portion of the setup, even though we have a four-step process. The fourth step is implied, and it will always be the URL destination you are setting up the goal for — such as “/thank-you-for-contacting-us.html.”

Once the goal is made active, Google Analytics will begin storing and tracking the data and you can start viewing it in near real time.

Increasing Conversions with Google Analytics Funnels

Pictured below is what an ecommerce sales process funnel may look like. Each step the shopper takes in completing a purchase is laid out, and we can see where consumers are potentially giving up on the sale. From this, we can glean a few important things.

Example of an average ecommerce sales process funnel.

Example of an average ecommerce sales process funnel.

Notice 57 individuals added items to a shopping cart during the selected time frame. So that’s the baseline for which we are making determinations on the success of the process.

Of those 57, 14 then went on to create accounts, or 24.56 percent of those who added a product to the cart. Of those people, 64 percent went on to adding a Billing address. So at this point, 9 of our 57 cart sessions are still engaged.

Funnel depicting 9 active cart sessions.

Funnel depicting nine active cart sessions.

To further the example, we see all nine sessions manage to continue throughout the rest of the process and complete the order.

This brings the overall success rate of the funnel to 15.79 percent. The benchmark number will vary by industry and product, and you will always be looking at ways to improve it. After all, more conversions will mean more revenue.

Note that this isn’t your ecommerce conversion rate. Your conversion rate is the number of visits compared to number of transactions. So the two items you’re looking to improve initially are the first and last numbers in the funnel: Add to Cart and Checked Out.

The example above shows two important things.

  1. Shipping rates aren’t hurting check out completions. All 9 individuals that selected a shipping method, and therefore saw the cost, completed the transaction.
  2. This example may have an issue with a coupon box. If your cart asks for a coupon code input prior to starting the actual checkout, some of the 43 people that didn’t move to step 2 may have gone out looking for coupon codes, and never came back.

Funnels for Lead Generation

The examples above are not applicable for a lead generation funnel. I previously described that type of funnel as:

Landing Page -> Product Specifications -> Quote Form -> Quote Acknowledgement

However, some of the same kinds of determinations can be made. If, for example, a high percentage of visitors never get to the product specifications page in Step 2, pay close attention to the content of the landing page. Potential customers are making a quick decision that your offering is not what they want.

Check for keyword-to-content consistency. If the keywords driving traffic to that web page should be effective, then the content probably needs reworked.

If you’re seeing a high exit percentage on the product specifications page, perhaps the product being offered isn’t what a majority of buyers are looking for. That might not be a website problem, that could be a product issue.

Lastly, if you see a high number of visitors on quote page and then not complete it, you may wish to revisit the form itself. Is it too long? Does it not function on mobile devices? Try to capture the minimum of information that your sales team needs — on a higher percentage of web visitors.

Kevin Webster
Kevin Webster
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