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Sep 2, 2022 |
“How do I know if my web stories work?” The most common question for anyone that’s new to web stories! If you’re a blogger or a marketer and you use web stories, you’d want to know exactly how they’re performing. How many people are viewing my story? How many slides are they staying for? How many are reaching the end?
If you’ve ventured into creation and publishing of Web Stories, you may already know that web stories are visual, tappable cards. Much like Instagram Stories but with a key difference – they are discoverable on the open web. Your web stories can show up on Google Discover, Google Images and Google Search, hosted on your own website the entire time.
Yes, lots of it! Web Stories live in the vast Google Universe and it has 3 distinct ways of being tracked.
You might wonder, the tools seem the same for websites and web stories analytics, so what’s new? Well, web story analytics need a twist in the way you approach them. User behaviour differs for each. On a web page a user may read the top and then scroll down to interact with your Call To Action and that would count as a view and a conversion, whereas in a Web Story, each slide is treated as a separate page because your message is not complete unless the viewer taps on to the next page.
So if your analysis approach for your Web Story is to combine all the page views for one story, it is an inflated view. It will block you from learning the true performance of your web story. Let’s get into how you can optimise your analysis approach to web stories using existing and new tools.
First you need to set up your GA tracking. Most web story creators have an easy way of connecting Google Analytics. MakeStories, a popular web story creator, has a tab called “Setup Analytics” with a “GA Analytics” field. Simply copy-paste your tracking ID, example: UA-123456-2. That should set you up to track your web story end to end.
Typically, with web stories we recommend focussing on two levels – Behaviour > Overview and Behaviour > Events.
Behaviour > Overview is a good place to start on Google Analytics to get a zoomed out understanding of your web stories performance. Following are the metrics you will find available.
Please note: Always check the Date Range selection before reading the analytics report.
The above analytics are generally something you already may be used to with your website or blogs, but here’s where the stream splits. If you only go by the overview data, you are most probably not getting the real picture of your web story performance.
You need to go deeper. Find out within each story, how many pages are users swiping through, how many users are reaching the end of the story, what is your most visited story, how many ads are being shown on my stories?
Here’s where you can start Story level analytics on Google Analytics events, Behaviour > Events > Overview
An event in Google Analytics are user interactions that do not fit into metrics like page views, exits or bounces. In the context of web stories, user interactions like starting a story, moving to slide 2, clicking on a link, landing at the end page are all unique interactions that need to be tracked by events. Here you can get an overview level idea of how your web story specific events are performing.
Now that you have a grasp on your events over all performance, let’s move on to individual stories. Start with Behaviour > Events > Top Events
Top Events is the section where you can really break down your analytics into story level and page level numbers. Here you will find three sections that must be analysed Event Category, Event Action and Event Label
Event Category is the section where you will find all your stories listed by popularity of events. For each story you will find 4 metrics on this page, Total Events, Unique Events, Event Value and Average Value. As we learnt above, these metrics communicate event related triggers that you have set up for your web stories.
This section helps you find patterns between stories. It can give you answers to questions like, which web story had more events triggered? Which story had more unique events take place? Which story had higher event values? Marketers use these metrics to identify relationships between performance and story topics, story publishing dates. Are certain topics more popular? Are certain topics performing better on weekends? Are certain topics getting more events but lesser value?
Event Action consolidates all the events taking place on one particular story. Story Starts and Story Completes are default metrics available to all. But we recommend adding in custom events for link clicks or CTA clicks.
Event Label gives you a breakdown of all the events taking place on each page of one story. For each page you will find 4 metrics on this page, similar to Event Category: Total Events, Unique Events, Event Value and Average Value. These metrics tell you events triggered per page or per slide of each web story.
This section helps you find patterns between pages. It can help you understand which pages are performing best within one web story? Which page is getting more clicks? Which page seems to have viewers dropping off? Marketers use this data to find patterns of the average number of slides to use in a web story, the right slide to add links to drive clicks. T hey analyse text, design or layout of pages/slides that are performing well.
If you want to create more custom analytics, you can refer to this AMP analytics documentation to get started.
The easiest and fastest way to check this is to view the Real Time section on Google Analytics. If your events are getting triggered, you are in the clear. Your web story is being tracked!
Some of you might be wondering, why use both Google Analytics and Google Data Studio to track your web stories? Both tools have similar roles but offer unique value to your analytics journey. While Google Analytics is numbers driven, Google Data Studio is visuals driven.
There is an overlap in the web story analytics that Google Data Studio presents because it links to your Google Analytics Account for data. But Google Data Studio can also go beyond Google Analytics and connect to other analytics from social, ads, CRM and more.
More importantly, Google Data Studio has introduced a ready-made dashboard for Web Stories.This dashboard is like a template customized to Web Stories. It will pull out all your information from the various connected sources and present your data to you. You can find the template here.
Click the template log in with your Google account that has access to Google Analytics. Follow the verification steps and click on the Analytics icon.
Click ‘View’ in the drop down and ta -da! Google Data Studio will pull out all our web story data.
Because Google Data Studio has a dashboard for Web Stories, it already understands the two levels of metrics. This template will show you: Overview and Story Level.
Please note: Always check the Date Range selection before reading the analytics report on Google Data Studio
‘Overview’ Level Web Story Analytics on Google Data Studio
Web Stories are best created and shared from web story specific builders as they already have many features inbuilt, including analytics. MakeStories is one such free web story builder. MakeStories, for instance, has it’s own story analytics but also allows you to connect tracking IDs for Google Analytics, Facebook Pixel or any other Custom Analytics tool.
To set up your analytics on MakeStories go to the menu on the left and select General Settings. General Settings > Analytics is where you can simply paste your GA tracking ID and FB Pixel ID.
Since MakeStories is solely a Web Story builder it has inbuilt detailed analytics across Users, Sessions, Story and Page level analytics that help you stay on top of your story performance. To view your analytics go to the menu on the left and select Analytics.
Please note: Always check the Date Range selection before reading the analytics report on MakeStories.
Their metrics include:
Each of these tools and their metrics give you more control over your web story performance. All that’s left to do is figure out what’s working and not working for your web stories. Sometimes, it only takes a few tweaks to catapult performance. Read between the lines with your analytics and most importantly, always think of your audience first.
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