Breaking the Sales Plateau with Google Analytics

Mike Fitterer

Breaking the Sales Plateau with Google Analytics

Data is great……sometimes. Data can also be maddening and make you want to go all Office Space on the nearest printer.

These days businesses have an abundance of data at their fingertips. That makes knowing how to sift through information an essential part of every marketer’s existence.

Personally, Google Analytics (GA) has been making my professional career easier since 2007. Why only since 2007? Well, I was unaware of GA before then, so shame on me.

GA often holds the key for unlocking new growth opportunities when important performance indicators like revenue and conversions have slowed to a crawl. You simply have to know where to look.

Luckily for you, this post will cover 3 different breakdowns of GA data to help you identify new opportunities.

Assisted Conversions

What are assisted conversions?

Assisted conversions break down which channels played a role in a given conversion. They add clarity by breaking down how each channel in your purchasing process contributes to your desired outcome, which is often someone making a purchase, download, or contacting you for more information.

Where can they be found?

Go to: Conversions > Multi-Channel Funnels > Assisted Conversions

Please note that you must have conversion tracking set up in GA in order to see assisted conversion data.

Why are assisted conversions useful?

By my very scientific calculations, 95.19% of businesses pay attention only to the online click that results in a conversion. Thing is though, that’s a terrible way to do business.

In most cases, customers navigate to a site or social media profile a number of times before making a purchase or submitting a contact form. With assisted conversions, you have data revealing the role channels such as PPC and organic search play. Say someone initially finds your business via a paid ad, later returns via an organic search result, and finally converts after navigating to the site directly. That’s a pretty common scenario that assisted conversion data fully covers.

You can also change the importance of each touch point. Giving substantial credit to the first interaction someone has with your brand, as well as the last one, or giving increasing importance to each touch point, can be easily done with the model comparison tool. If you don’t like the default attribution options, custom models can also be created within GA.

Assisted Conversions

How should one use assisted conversions?

Assisted conversions can give you a useful overview of what channels are contributing to your bottom line. Select an attribution model that is right for your business and start funding each channel with an eye on how it’s performing for both last-click and assisted conversions. Areas of focus can also be derived with the help of assisted conversions.

How does this look in practice? You may be missing an opportunity to focus on a channel that is holistically helping to drive a ton of conversions. For example, if you have a $5k a month PPC budget under the assumption that it results in 10 conversions, but find that with assisted conversions PPC has a hand in 20 conversions, there may be an opportunity for further budget expansion and reach for PPC. It all depends on how you treat assisted conversions and factor them into your overall cost per acquisition.

Landing Page Performance by Channel

What is a landing page according to GA?

A landing page is the page a visitor first lands on when arriving at your site.

Where can I review landing page opportunities?

Go to: Behavior > Site Content > Landing Pages

Why is landing page data useful?

Landing page data helps marketers figure out which pages are driving people to a site and also how people are interacting with each landing page.

How should one use landing page data?

Having data on which landing pages are performing well (or poorly) helps identify opportunities for optimization. For example, let’s say one of your product pages has an extremely low eCommerce conversion rate, even though demand and cost remain equal. That’s definitely a red flag.

From there, a side-by-side comparison of the product page relative to others should be made, and you can install some click-tracking software like Crazy Egg in order to see how people are interacting with the page.

Another easy, yet pertinent, stat to review is bounce rate. If a given page has an abnormally high bounce rate relative to others in its category, you will likely want to review the meta description, title tag, URL, and content on that page. That will allow you to ensure they align perfectly with the top term, or terms, driving traffic to that page and make changes if they don’t.

Comparisons of revenue (assuming eCommerce tracking exists), time on site, sessions, new vs. returning users, and other key metrics can be easily done with a little sorting.

Goal Funnel Opportunities

What is the goal funnel in GA?

The goal funnel illustrates how visitors flow through your checkout process and eventually convert.

Where can I review the goal funnel?

Go to: Conversions > Goals > Goal Flow

Please note that you must have conversion tracking set up in GA in order to see goal flow data.

Why is goal flow data useful?

The goal flow data can highlight hang-ups and opportunities in your conversion path for specific subsets of site visitors.

Time spent improving the conversion experience can often lead to a better overall conversion rate, meaning more conversions vs. abandons once people enter the conversion funnel.

How can goal flow data be used?

Goal flow data is particularly helpful in improving your goal conversion rate. For example, let’s say you recently launched some updates to your checkout funnel and conversion volume has been lower since the launch.

Goal flow lets you look at user data such as browser, operating system, and screen resolution in order to see if a subset of users are heavily dropping out of the funnel at a specific point. You can then test to see if that step in some way is hampering the user experience for that group of visitors and make changes as needed.

Another example is understanding how mobile users interact with your site. You can review people navigating through the checkout process via mobile vs. non-mobile in order to review drop-off points in the process. If mobile has a massively larger drop-off point than desktop at one of the steps, improving the experience for mobile (less text entry required, more drop-downs used, etc.) would be a logical next step.

In Summary

As I said earlier, a little digging within Google Analytics can go a long way towards helping marketers uncover new growth opportunities. You just have to look in the right places.

And, if you feel like the recommendations within this post are just a bit too elementary for your skill level, feel free to delve into this webinar on using analytics to study audience engagement or this one on connecting your CRM & web analytics platforms, both by the brilliant and talented Michael Wiegand (you didn’t hear this praise coming from me πŸ˜‰ ).

Mike Fitterer

Mike Fitterer

PPC Team Lead
PPC Team Lead

Mike began his career as an International Sales & Marketing Manager living and working in Germany, focusing on product placement, marketing, and sales. For the past 9 years he's worked at Portent. Mike manages Portent's PPC Team and also works on strategy development and relationship management for Portent's top-tier PPC clients. He enjoys spending time with his wife and 2 young sons, travel, learning new languages, soccer, and supporting Seattle sports teams.

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  1. Hi Mike,
    I have trained loads in-house marketing teams in the fine art of SEO over the past 10 years and one thing that I notice when I go into large companies is they only seem to look at around 10% of the data that is provided within Google Analytics. They didn’t even know things like ‘goal flow data’ even existed which is crazy if you think about it as digital marketing is all about analysing data.

    1. Hi Mark,
      Thanks for chiming in! I think you’re absolutely correct.
      Many larger companies only gloss the surface of what’s available data-wise. After the low-hanging fruit has been identified they often move on to the next “shiny object” without really delving a few levels deeper and finding, perhaps, larger opportunities.
      Understanding the necessity to dig deeper and how to do it can definitely be a game changer when it comes to hitting KPIs.

  2. It always blows me away how powerful Google Analytics is, and the fact that it’s completely free. Great write up here showing just one of the many amazing things GA can do! πŸ™‚

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