How to Use Analytics to Boost Web Story Performance

“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.

Do Web Stories have analytics?

Yes, lots of it! Web Stories live in the vast Google Universe and it has 3 distinct ways of being tracked.

1. Google Analytics
2. Google Data Studio
3. Web Story Creator Analytics – eg, MakeStories Analytics

What’s the difference between Website and Web Story Analytics?

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.

Google Analytics for Web Stories

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.

How to optimise Google Analytics metrics to Web Stories?

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.

• Page Views: This will compile over all page views you have garnered. But do note, this number is not enough to give you feedback on the performance of a particular web story.
• Unique Page Views: This indicates unique users who have viewed your stories collectively.
• Average Time on Page: This is a good collective measure to learn how long your users are engaging with your content.
• Bounce Rate: This is a good metric to give you feedback on viewers lost after they landed on your web story.
• Exit %: An exit percentage, although a larger umbrella over Bounce Rate, is often preferred, because it is a percentage in context to how many page visits you get. For eg, if you get 4000 page views but 400 are existing before completing the story that’s a 20% exit rate.

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.

Please note: Always check the Date Range selection before reading the analytics report.

1. Total Events: This compiles all your events across categories, story starts, story ends and link clicks. Once again, like Behaviour > Overview, this is also not the ideal metrics to get into the nitty gritty. This is good enough just to get an idea over all web story events.
2. Unique Events: This will identify only events that occur once in a user session, whereas the above ‘Total Events’ accounts for the number of events across all sessions.
3. Event Value: If your event is marked with a monetary value, for eg, a payment or purchase value, then this would indicate the total value of payments. Value x Number of events.
4. Average Value: This shows the average value of an event.
5. Session with Event: This number tells you the number of sessions with at least one event triggered. This is useful to understand the quality of the sessions.
6. Event/Session with Event: The average number of events per session with event.

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

Please note: Always check the Date Range selection before reading the analytics report.

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

1. Behaviour > Events > Top Events > Event Category

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?

2. Behaviour > Events > Top Events > Event Action

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.

1. Story Starts: This metric tells you how many users have started a web story.
2. Story Progress: This specifies the number of pages your viewers are viewing in your web story. If you’ve successfully brought in a viewer, how long are they staying? If they are dropping off too early, go back and analyse your narrative. Figure out if you’re using too many slides? Is your content not legible?
3. Per Page Events: We recommend setting up events per page of the web story as well. Like the image below you should be able to view events on each web page to drill down into page performance, and not just story performance.
4. Link Clicks: If you have links added to specific pages/slides on your web story, create an event for each link clicks. This can also give you great insight into which pages are more likely to get users to click.
5. Story Completions: A distinct success rate of viewers who have finished viewing your web story and reached the end. If you have a call to action here or a Book End slide with your social, create an event for them too.

3. Behavior > Events > Top Events > Event Label

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.

How to check if my Web Story is working on Google Analytics?

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!

Google Data Studio for Web Stories

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.

How to set up Google Data Studio with the Web Stories template?

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.

What Web Stories metrics can you track on Google Data Studio?

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

1. Key Metrics:
   1. Story Starts: This metric shows you an average of how many users started your web stories
   2. Page Views: This metric measure average page views of all your web stories
   3. Time Spent: This metric reflects the average amount of time spent on all your web stories
   4. Completion Rate: This metric is an indicator of how many percent of users are completing your web stories.
2. Audience Metrics:
   1. Age: Get an insight into the age groups that your stories are resonating with. Sharpen content towards this age group for more views and conversions.
   2. Gender: Get a visual breakdown of the genders that are interacting with your all web stories.
   3. Device breakdown: View the break up of desktop, mobile and tablet device modes most popularly used to view your web stories. Although web stories are mobile-first, there are simple ways to make them desktop and tab friendly too.
3. Top Stories: Google Data Studio also allows you to analyze your top stories within certain time periods.
4. Traffic Channels: A crucial metric that reveals where the traffic to all your web stories are coming from. This insight once carried into further strategy can help maximize reach and clicks.

‘Story’ Level Web Story Analytics on Google Data Studio

1. Key metrics:
   1. Story Starts: This metric shows you an average of how many users started a specific web story
   2. Page Views: This metric measure exact views per page in a specific web story.
   3. Time Spent: This metric reflects the average amount of time spent on a web story.
   4. Completion Rate: This metric is an indicator of how many percent of users have completed a web story.

MakeStories Analytics for Web Stories

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.

What Web Stories metrics can you track on MakeStories?

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:

Total Story Metrics within a date range

1. Stories: Find the unique number of stories you have published
2. Views: Get the total number of unique views all your stories together have garnered
3. Users: Find out unique number of users who have viewed your stories
4. Slide Views: Get total number of slide views cumulatively for your stories

Total Sessions Metrics within a date range

1. Sessions:Find the total number of unique sessions by users
2. Session per User: Get the average number of sessions created by a user
3. Slideview Per Session: Learn average number of slide views by per session
4. Slide View per User: Get the average number of slide views per user.

Story Level Analytics

1. Created At: This keeps you on track with your publishing schedule. Just like blogs or social media content, consistency is important even for Web Stories.
2. Slides in Story: Track the number of slides on each story. This makes it easy to find patterns between number of slides and average depth, slide views and clicks.
3. Average Depth: This metric allows you to analyse the average number of pages users are staying for in one web story. If Average Depth is low it means the content is not engaging enough to hold them to the end.
4. Story Views: This tells you the average story views for the particular web story
5. Slide Views: Slide Views gives you average views on each slide
6. Total Clicks: Total clicks tracks your link or call to action button on your web story. Many publishers have found patterns between link clicks and number of slides in a story.

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.