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3 Tests Our Content Team Ran in 2021 & How They Impacted 2022 Planning



3 Tests Our Content Team Ran in 2021 & How They Impacted 2022 Planning

2021 was a big year for the HubSpot content team.

Our team grew, we faced challenges, and we had some fun with experiments.

Experiments can teach you a lot about your audience and help you unlock growth opportunities. Here are some experiments we ran in 2021 and what we learned from them.

Conversion Rate Optimization

In January 2021, the web strategy team decided to run a form optimization experiment to understand how altering our forms would affect our users, ahead of a blog redesign.

When evaluating the current form, the team found that it was breaking several best practices relating to user experience (UX). For instance, the form used asterisks when all fields were required and users were unable to tab through the fields, taking longer to go through the form.


This issue with the UX was further validated with high dropoff rates on offer pages. This meant that a secondary goal was clear: Improve the user experience of the forms on our content offer pages, which would then improve our conversion rate.

With every experiment comes a hypothesis and this one had two, one for each goal:

  • By redesigning the forms, we will learn the best approach to form design ahead of the blog redesign.
  • By optimizing content offer forms’ design and functionality, we will improve the user experience and increase user clarity, which will lead to an increase in content leads’ CVR.

When it came to designing the experiment, the team chose an A/B/C/D/E test, leading 20% of traffic to each of the five treatments:

  • 20% would see A, the control – a modal form.
  • 20% would see B – a redesigned, standard version of the form.
  • 20% would see C – the split-screen with a two-column form.
  • 20% would see D – the multi-step form.
  • 20% would see E – the split-screen with single-column form.

Wondering how they came up with these variants? User testing. Earlier in the year, the team had already gathered valuable insights from a user test, in which they learned about users’ preferences and expectations when using forms.

They used this data to design their experiment, something that Principal Marketing Manager at HubSpot Rebecca Hinton says highly contributed to their success.

The test ran on the top 20 converting offer pages and had to run for two weeks to get a reliable sample size for each variant and launched only 33% of traffic to mitigate risk to content lead goals. It ramped up to 60% of traffic during the experiment.

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The primary metric used in this experiment was the conversion rate on the content offer form submission and the second was engagement.

“What we found is that displaying a multi-step form vastly outperformed the other treatments we tested, showing a 20% improvement over the control,” said Hinton.

It’s worth noting that the winning variant, D, had a much higher conversion on mobile than it did on desktop. However, the multi-step form performed well on both device types.

“The multi-step form was so successful that we’ve decided to implement it ahead of the pages being redesigned, so we can capitalize on its strong performance,” said Hinton.


A key takeaway here is that one test can (and should) inform another. If you collect user data for a particular feature or project, make sure you keep good documentation as that can serve a purpose later on.

Channel Promotions

Back in June 2021, HubSpot community manager Jenni Kim, then marketing manager on the Channel Promotions team, ran an experiment to explore opportunities for cross-promotion between the YouTube team and the blog team.

Kim described both channels as having an on-and-off relationship, crossing paths from time to time covering the same content and even collaborating at times. However, there was no consistency. This experiment would assess the value of embedding YouTube videos from HubSpot’s channel into relevant blog posts.

The hypothesis was that adding videos to blog posts would enhance the blog reader’s experience and drive meaningful growth for both channels.

Setting up this experiment required cross-collaboration between YouTube, Blog, and SEO teams to design a process while keeping in mind content lead goals, user reading experience, and SEO implications.

Now, let’s dive into the specifics.

One consideration they had to make was which YouTube videos would go and where. Here’s the breakdown they settled on:

  • Existing Blog Post + Existing YouTube Video (9 blog posts, 9 videos)
  • Existing Blog Post + New YouTube Video (6 blog posts, 3 videos)
  • New Blog Post + Existing YouTube Video (4 blog posts, 4 videos)
  • New Blog Post + New YouTube Video (5 blog posts, 3 videos)
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They found that using existing blog posts and videos would offer the most clear results, as you could compare pre- and post-experiment metrics.

Key metrics:

  • Total organic clicks (TOC) – The blog traffic coming in from the web results tab on Google
  • Total organic clicks from the video tab – The blog traffic coming in specifically from the video tab on the SERP.
  • Content leads/CVR – The number of viewers who converted through a blog post by signing up for an offer and the view-to-lead conversion rate on the blog on a post-level.
  • Organic video views – Videos that came directly from the blog post embed.

The experiment ran for roughly three months, as that would be enough time to measure the SEO impact.

The results found that embedding YouTube videos into relevant blog posts had a positive impact on both YouTube views, contributing 15% of total views. Leads and CVR stayed consistent, which is considered a win, as the experiment didn’t negatively impact conversion.

As for TOC from the video tab, an average of 8% of clicks came from this section – making it a solid SEO opportunity for both channels.

The most challenging part for Kim was the adaptability they needed to exercise to start this experiment.

“A lot of the teams were all working pretty independently,” said Kim, “So, we had to understand everyone’s processes and then try to find that middle point to bring everyone together.”

As a result of this experiment, both teams developed a sustainable collaborative process to help both teams generate more traffic.

Audience Growth

When it comes to blogging, one of the most important metrics is organic traffic. This refers to the non-paid traffic that comes from search engines.

On the HubSpot Blog, the team also leverages non-organic content coming from sources like email, social media, and other websites.

Pamela Bump, senior marketing manager responsible for audience growth on the blog team, shares that the HubSpot Blogs already had incredible success from our non-organic content, creating clickable, shareable blog posts with original research, quotes from experts, and insights on industry trends.


“Not only did our non-organic program help to increase our non-search traffic, but we also were able to write posts that eventually began to rank on search because we were ahead of trends,” said Bump.

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To capitalize on this success, Bump led an experiment to create hybrid posts, combining the shareability of non-organic content with the SEO of organic content.

“The goal of this experiment was to see if our blog posts could pull in the sudden bursts in traffic from non-search channels that non-organic blog posts achieve soon after publishing,” Bump said, “while also gaining more evergreen traffic over time search as these posts begin to rank on search result pages.”

She called this the “Hybrid Effect.”

“These assignments were laid out by both myself and our SEO strategist and combined SEO elements, like keyword optimizations and search-driven formatting,” said Bump, “while still including non-organic elements like quotes from experts, original data, news mentions, and trend coverage.”

The result? In the first year of testing hybrid content, Bump says it has led to huge benefits for the blog, pulling in strong numbers comparable to organic traffic.

“The average views we get from hybrids in their first month is about 10% lower than that of non-organic piece,” said Bump. “However, it can be more than 30% higher than the first month’s traffic of a completely organic piece of content.”

In the long term, Bump says that the average hybrids and non-organic piece published in 2021 only had about a 1,000 to 2,000 view difference while gaining more keywords on average than a non-organic piece and gaining faster traffic than an organic piece in its first year.


Because of this success, the team has made the hybrid model a permanent strategy on the blog team.

“In 2022, we plan to increase our investment in hybrid content by 10% while also training writers on how to optimize organic pieces with non-organic elements for hybrid growth,” said Bump.

In every experiment mentioned above, there’s something to learn – whether it’s the importance of collaboration or the value of historical data. If there’s an experiment you’ve been thinking of running, take this as your sign and use these insights to guide you.

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Using Google Analytics 4 integrations for insights and media activations



Using Google Analytics 4 integrations for insights and media activations

No matter which stage of Google Analytics 4 implementation you’re currently involved in, the opportunities to integrate with other products shouldn’t be overlooked. The best part is that the basic versions are free for everyone, so there are quick wins to be had if you aren’t using these yet.

Other features and reporting experiences aside, an edge that Google Analytics has over other analytics platforms is that it fits well with the Google Marketing Platform (GMP). If you’re using Google Ads, Search Ads 360, DV360, or other media tools in the suite, GA can be a hub, as well as a source in the media activation process.

GA integrations as a hub

The paid media platforms in GMP have advanced, automated reporting. These platforms are powerful tools to analyze the beginning of the user journey by drawing people to the site and to the end of the experience by converting. 

What about the middle? A solid Google Analytics implementation offers multi-step conversions, custom user behavior data and rich segment data to build and share audiences.

GA integrations as sources for insights

Google Analytics 4 isn’t just about analyzing data, it’s about acting on it. For example, the Audience feature leverages your analytics implementation — you can use the data to segment users and create audiences for remarketing, targeting, A/B testing, and personalization. 

Through settings in GA, you can also link other products and share audience and conversion data.

Below are the integrations currently available for Google Analytics 4 as of June 2022. Notice that it’s already quite a lengthy list.

  • Google Ads.
  • BigQuery (extra costs are incurred in Google Cloud).
  • Display & Video 360 (DV360).
  • Google Ad Manager  (GAM).
  • Google Merchant Center.
  • Google Optimize. 
  • Salesforce Marketing Cloud (SFMC) (this one requires the Salesforce Journey Builder). 
  • Search Console.
  • Play integration.
  • Search Ads 360 (SA360).

The first step to building out your analytics insights is taking inventory of your GMP stack. Which products are you using right now? The products will depend on what type of site or app you have and the products in which you are investing. However, three of those integrations can apply to all properties — BigQuery, Search Console and Optimize. It doesn’t matter if you’re an advertiser, publisher, retail or service site — each of these integrations is a possibility to use today for free in Google Analytics 4. 

Let’s take a closer look at these three fundamental integrations.


What is BigQuery? A Google Cloud data warehouse that’s not exclusively for Google Analytics or GMP.

Who is it for? Teams and leaders that will benefit from this connection are involved in areas like BI, data science, and data administration.

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With BigQuery, you’ll have all of your data exported to a data warehouse that you own and control. Once the data is in Google Cloud, there’s freedom to send to another database, blend with data outside of Google Analytics, and perform advanced reporting in other tools. The GA BigQuery data has other benefits, including integration with CRM data.

How to integrate. The integration is self-serve within the interface, but there needs to be a BigQuery project available to link the Google Analytics tool. If you do not have a project yet, go to the Google APIs Resources page to create a new one. On the page, it looks technical and there’s code references, but that part isn’t necessary and you can skip it. The instructions for doing it through the interface are in modules in the “Console” tab. Below are the simplified steps:

  1. Select the option to create a project on the upper left of the page.
  1. Name your project, select the “Create” button, and there’s now a new project in Google Cloud. 
  2. The last step is turning on a setting to use BigQuery. There are a lot of technical options in the menu, but the only area you need to go to for this is “Library” under “APIs & Services,” where you can search for BigQuery and enable it.

After the project is created, it’s ready to be integrated with Google Analytics 4. Back in the GA interface, the option to link it is under property settings. 

Now your raw GA4 data will start collecting into the project to be available for immediate use. Out of the integrations listed here, this one has the most steps. However, the other products are just a few clicks. (Note: BigQuery comes at an extra cost. However, for most accounts it will not be significant — it is sometimes just a few dollars.) 

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Search Console

What is Search Console? It’s a platform for monitoring in-depth metrics and reports related to organic Google search performance and site speed.

Who is it for? Most teams will benefit in some way from analyzing search data. This includes content creators, SEO teams, and web developers.

How to integrate. A Search Console property must be created, and it must be verified. Sometimes this is as simple as selecting a few buttons in the interface.

Once there is a Search Console property, or once there is access to an existing property, the link is in the same menu as the BigQuery link under Property Settings.

After, organic metrics and reports that are not out-of-the-box will be available in Google Analytics 4. Once the product linking is complete and working, there’s a last step to enable GA users to benefit from the enhanced data. It may be noticeable (and possibly confusing) that the Search Console data isn’t within the default interface navigation. To see the reports, the reporting collections in the menu should be edited.


To modify the navigation, select “Library” at the bottom of the screen:

Next, begin the process to create a collection, under Collections. The template for Search Console will be located as the bottom right option. The option to start from scratch without a template is also available.

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After saving, go back to the library area and publish your collection. The report should now be accessible from the left navigation:


What is Optimize? Optimize is an A/B testing and personalization tool.

Who is it for? It’s for marketers, conversion rate optimization (CRO) teams, content creators, or UX leads.

How to integrate. This one isn’t as apparent as the other links. Right now, the integration option does not show up in the Google Analytics property settings. That doesn’t mean that it’s not available, it means that the linking hasn’t been done yet. 

So, instead of starting in Google Analytics, the process begins in the Optimize interface. Under Settings, navigate to the Measurement section and edit. A dropdown will be available with a list of all the properties that you have access to. Unlike the previous version of Google Analytics, the integration links to a GA data stream instead of the GA property.

Once it’s linked, the icon will show up in Google Analytics:

When the link is active, Google Analytics 4 data can be used for audience targeting, conversion optimization, and objectives.

Note: If you are already linked to a legacy Google Analytics property, check with your team to make sure that it is ok to switch it to the Google Analytics 4 data.

Read next: Is Google Analytics going away? What marketers need to know

With the integration of BigQuery, Search Console, and Optimize, anyone can advance their analytics capabilities for current or future initiatives.

Below are brief explanations of the media platforms that Google Analytics 4 can integrate with. Most of these depend on what products are in use, what vertical an organization falls under, or other specific contexts and devices. 


Google Ads

What is Google Ads? It’s the most popular and well-known search advertising tool, formerly known as AdWords.

Who is it for? It’s for marketers, advertisers and paid media specialists.

What it does. Google Ads was one of the first products to have GA4 linking capabilities. It’s built to provide value both ways – by getting Ads metrics and reporting from Google Ads to GA and by sending audiences and getting conversions from GA to Google Ads.

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Google Analytics 4 to Google Ads linking information and instructions here.

Display & Video 360

What is DV360? It’s a programmatic advertising platform. Also referred to as a DSP, DV360 is used to bid on display ad placements on publisher/content sites.

Who is it for? It’s for marketers, advertisers and paid media specialists within enterprise organizations.

Google Analytics 4 to DV360 linking information and instructions here.

Search Ads 360

What is SA360? This is like Google Ads, but super-charged. It’s a management and bidding tool to run ads across multiple channels and search engines.


Who is it for? It’s for marketers, advertisers and paid media specialists within enterprise organizations.

Google Analytics 4 to SA360 linking information and instructions here.

Google Ads Manager 

What is GAM? It’s an enterprise platform for publishers to manage and serve ads on their site or app.

Who is it for? Marketers, advertisers and paid media specialists within enterprise organizations.

Google Analytics 4 to GAM linking information and instructions here.

Google Merchant Center

What is Google Merchant Center? A separate platform from Google Ads to promote products, mainly on Google Shopping.

Who is it for? It’s for marketers and advertisers within an e-commerce organization.

Google Analytics 4 to Google Merchant Center linking information and instructions here.


Salesforce Marketing Cloud

SFMC is for cross-channel digital marketers. This integration is meant for use in the SFMC Journey Builder and can bring in Google Analytics data.

Google Analytics 4 to SFMC information and instructions here (through Salesforce).

Google Play

Google Play is Google’s app store and it’s for digital marketers who analyze in-app purchases and subscriptions.

Google Analytics 4 to Google Play linking information and instructions here.

If your organization is using any of those media tools, it’s a great time to start the strategy and process of leveraging Google Analytics 4 data to enhance analysis across multiple products and teams. There’s no reason not to start since they are available to all GA4 properties.

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Samantha has been working with web analytics and implementation for over 10 years. She is a data advocate and consultant for companies ranging from small businesses to Fortune 100 corporations. As a trainer, she has led courses for over 1000 attendees over the past 6 years across the United States. Whether it’s tag management, analytics strategy, data visualization, or coding, she loves the excitement of developing bespoke solutions across a vast variety of verticals.

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