It is a shame that web analytics tools only tell you what you should be doing, but cannot tell you how to do it. It would sure be nice if a web analytics tool told you how to stop losing traffic every time you make a content change to your website.

Web analytics tools are the most popular marketing technologies in the world. As a marketer, you collect a ton of data with these tools but they usually tells you only what has happened, rather than what is going to happen. So you need more than just web analytics tools to make better decisions. You need to put yourself in your customer’s shoes and know how they think and feel about your brand.

It’s estimated that between 30-50 million websites use Google Analytics to track their user activity. In our recent survey of over 200 marketers, we found that only 23% of marketers are confident they’re tracking the right KPIs.

Don’t get us wrong, Google Analytics is a staple tool for any marketer. But with 40% of marketers stating that more accurate data would improve their marketing outputs, there’s an issue with the data they have at their disposal. So, what is the issue with the data in Google Analytics and how can you take it to the next level?

Let’s dig in.

Google Analytics can’t accurately track leads

Google Analytics is a great tool that can help you track key actions taken on your website. Want to track pages users engage with on their session, then Google Analytics is the tool for you.

But what if you’re not an eCommerce business?

While they can easily track sales generated from their website, how do those with offline conversions manage?

The first major issue with Google Analytics is a lack of ability to track lead volume accurately. Tracking form fills can be done with a little work. Phone call tracking relies on call tracking software, while live chat volume can be done within your chat tool.

 Pro Tip
Remember, tracking offline conversions or conversions like live chat doesn’t need to be hard work. Download our FREE eBook on offline conversion tracking to find out how you can track every lead, their source and their full customer journey – including their revenue!

But while these might give you insight into the volume of leads you’re generating, how are you attributing these back to your marketing channels?

Let’s use an example.

Sara visits your website for the first time via a PPC ad. She doesn’t convert. While Google Ads and Google Analytics will track her session, that’s all they’ll track.

When she returns via a Facebook paid session, that’s all they’ll track too. When she returns via an organic search and converts via a form fill, what will be tracked?

 

In Google Analytics, if you’ve set up form tracking, then you’ll see one new lead. But you won’t see that the last click was organic. And you certainly won’t know that she had also engaged with two paid adverts.

Don’t worry, there is a way around it. Keep reading to find out.

 

Google Analytics can’t track lead quality

Another issue with lead tracking in Google Analytics is that you can’t understand lead quality. Let’s use another example.

You might drive 50 new leads via a PPC campaign (that’s assuming you’re able to attribute those leads back to PPC). But all you’ll see in Google Analytics is 50 new leads.

Meanwhile, in your CRM, your sales team is struggling to convert them. In the end, you only gain 5 new customers with total revenue of £500.

Now, compare this to a second PPC campaign. Again, you drive 50 new leads. But this time, sales convert 25 of them into a total revenue of £5,000.

If you’re assessing these two campaigns in Google Analytics or Google Ads, you’re going to assume they’ve performed equally well because they drove the same number of leads.

But in actuality, they drove very different results. This is data you can’t see in Google Analytics (or Google Ads).

 

Google Analytics can’t track the full customer journey

We know customer journeys are getting longer. According to Think with Google, it could take as many as 500 touchpoints to convert a prospect interested in buying flights.

So, how can you track multiple, or potentially hundreds of touchpoints in Google Analytics? Well, simply, you can’t. Google Analytics tracks sessions, not visitors, so you can’t build up customer journeys.

 

Google Analytics can’t highlight the true impact of paid

Lack of customer journey tracking also means a big impact on your paid reporting too. Just look at our earlier example.

Sara engaged with two paid adverts before converting. But she converted via a direct session. So, even if you could attribute her direct conversion, you’d completely miss the impact of the paid channels.

This is data you just can’t see within Google Analytics (or even Google Ads). Here’s how to optimise your Google Ads campaigns with offline conversion tracking if you’re stuck.

 Top Tip
Struggle to understand the data between Google Analytics and Google Ads? Here’s a handy guide to solving the data discrepancy between the two.

So, what’s the solution?

 

Find Insights and Make Data-Driven Decisions with Marketing Attribution

Marketing attribution is the missing link when it comes to getting more out of your data. From tracking every conversion, and every lead to linking your closed revenue to your marketing channels, campaigns and keywords.

Ruler Analytics combined with Google Analytics allows you to see the data you need. Here’s how it works. Let’s use the same example as before.

Sara visits your website from a PPC ad. Ruler tracks Sara and stores her lead source data as well as other key information like which pages she engaged with.

Sara visits again, and Ruler again tracks her, adding this session to her customer journey. Next, she visits via an organic search. Ruler tracks her visit and, when she converts, via a form, tracks all of her inputted data.

At this point, Ruler fires all the information held on Sara over to your CRM.

A few weeks later, when Sara converts, Ruler scrapes the revenue data against her in your CRM and fires it to your analytics tools, like Google Analytics. So, in GA, you can see the amount of revenue generated by channel, campaign and keyword.

And in Ruler, you can see Sara’s full customer journey and swap attribution models to better understand the roles your channels play in converting leads into revenue.

No matter what you are analyzing, all you are doing is gathering facts and presenting those facts using the tool. Nothing in the tools tells you why the results are what they are. That is up to you.

For example, look at web analytics. You can gather amazing volumes of page loading times. You can present charts and graphs comparing times of day, 1st page to 2nd page comparisons. Speeds by region or speeds by browser. Not one thing in these reports and charts will tell anyone why it is occurring. And isn’t that really what everyone wants to know?

The data analyst is the one who makes magic happen, not the tool. He/she finds an anomaly in the data and gets a developer to walk through the code. You hope the developer finds a problem, otherwise it is just an anomaly.

WHAT YOU CAN DO

One way to work around the problem of sampling is to create an account dedicated to tracking individual data with all anonymous traffic data excluded. That usually means that your data won’t go above the limits at which Google Analytics starts sampling.

Here is how to do it using Google Tag Manager:

Step 1: Create a Macro in Google Tag Manager which will make use of the IDs from your website users. The following line of code will be needed on your website, only for logged in users above the Google Tag Manager code snippet:

dataLayer.push({‘userId’:’XXXXXXX’})

where XXXXX will be replaced by the actual user id. 

Conclusion

You read that correctly. I’m not here to say they can—just that they cannot tell you what you are looking for. You see, the tools on the market today cannot accurately measure all of your conversions or behaviors. Many of them even exclude important pages in your funnel. This is because conversion rate is a holistic measurement that relies on a number of factors: your site, social presence and user behavior, customer interest and then, of course, marketing and sales efforts.