Onboarding at Loom: The impact of AI and Removing Psychological barriers
2 case studies from Head of Product at Loom to drive Activation and Sharing.
A couple of months ago (in June 2024) I had the pleasure of being invited by Amplitude to facilitate “Onboarding Lab” sessions and Growth leaders from Loom, Reforge, and Superhuman (special thanks to
for co-hosting 🙌)Looking back, I realized that these stories we so valuable, that I asked all participants if they were open to sharing them with a broader community through this newsletter, and they said yes.
In this newsletter, I’d like to share a deep dive into each of these stories:
Onboarding at Loom: The impact of AI and removing psychological barriers with Janie Lee (today’s issue ⚡️)
Onboarding at Reforge: The Power of Simplicity with Gianna Sen-Gupta (coming soon)
Onboarding at Superhuman: Which Experiments Moved the Needle with
(coming soon)
If you'd like to receive stories like this right in your inbox — subscribe to this newsletter and check it in the coming months for more stories like this.
Today we will start exploring Loom story, and you will learn:
What’s Activation at Loom.
How AI helped to improve the experience for Creators and Viewers.
How to remove Psychological barriers to drive Sharing.
Summary and Key Takeaways that you can apply.
So now, let’s dive in 👇
Brought to you by Command.ai — a user-focused platform offering an alternative to traditional popups or chatbots. Their AI “Copilot” answers questions, performs actions, and simplifies complex tasks. Use “Nudges” to guide users with timely, relevant messages, all within a no-code platform. Perfect for Product, Support, and Marketing teams to positively influence user behavior while respecting their needs:
Onboarding at Loom: The impact of AI and removing psychological barriers
I met Janie on the Growthmates podcast where we discussed how they build Growth team culture, Growth <> Core collaboration, and more hot topics like these. After recording this episode, it was a no-brainer to invite Janie to participate in this Onboarding Lab series to learn more about their approach on User Onboarding.
Loom has been making waves since it was founded in 2017, and was acquired in 2023. So, what makes this tool stand out in the crowded world of workplace communication? Let’s break it down:
Loom was founded in 2017 (and acquired in 2023 by Atlassian);
Its mission is empowering effective communication at work through video messaging;
Serving a global workforce with 25+ million users in over 120 countries;
Trusted by 350,000 companies worldwide.
One of the essential components that led to that success was the focus on user experience starting from the very first interaction with the product. As we know — this is all connected to User Onboarding and Activation.
What is Activation at Loom?
At Loom, the activation metric is defined by a key user behavior: the Video First View (VFV). A user is considered "activated" when they create and share their first video, and that video receives at least one view within the first week. This metric focuses on ensuring that creators not only record a video but also successfully share it in a way that leads to meaningful engagement, signified by someone watching the video.
1 VFV (Video First View) = One recording with at least 1 view in Week 1.
If you’re still trying to define the Activation metic for your product — here’s a quick reminder for you. Define your Habit moment, Aha moment, and Setup moment (yes, in that order). It will help you connect your Activation metric to longer-term Retention and Monetisation from the beginning.
Find more valuable frameworks like this in “The Holistic Growth Playbook” by Groathmetes.
Case Study #1: How Loom Added value to the first experience with AI
Imagine spending time recording a video, hitting send, and then… crickets. No one watches it. It’s discouraging, right? This was the reality for many new Loom creators. While they embraced the ease of recording, they often skipped adding titles or any context, leading to a big problem: viewers received a video link with no idea what it was about. Unsurprisingly, this lack of context resulted in a significant drop-off between creators sharing their videos and those videos being viewed.
For the team at Loom, this was a major hurdle in driving activation rates — new creators weren’t seeing their videos engaged with, making it harder to onboard them successfully. The challenge? How do you ensure videos get viewed without adding extra friction to the creator’s workflow?
🔴 Before → Missing context leads to lost Engagement.
To summarise, Loom experienced 2 problems:
For Creators: New creators were sharing videos without adding titles or any context. While they preferred the ease and simplicity of recording and sending videos, the lack of clear information meant their videos often went unwatched. This drop in engagement left creators discouraged, as their hard work failed to generate meaningful interactions.
For Viewers: Viewers received videos with no explanation of what the content was about, making it hard to determine if the video was worth their time. Without titles or summaries, videos felt unclear and irrelevant, leading viewers to skip them entirely, further contributing to the drop in activation rates.
🟢 After → Adding valuable context with AI.
The team at Loom knew they needed a solution that wouldn't burden creators with more tasks. Instead of asking users to manually add titles, chapters, or summaries, they turned to AI. Using existing video transcripts, Loom started generating titles, chapter markers, and summaries automatically. This allowed viewers to get an immediate sense of what the video was about, making it easier for them to engage with the content.
The team uncovered 3 use cases when AI played a valuable role:
AI-Generated Titles: As soon as a creator finished recording, AI would generate a clear, concise title based on the video content. This eliminated the need for creators to manually add a title while still ensuring viewers immediately understood the purpose of the video. This simple addition gave viewers a one-second glance at what to expect, drastically increasing the likelihood they would watch.
Chapters: For longer videos, AI automatically inserted chapter markers, breaking the content into digestible sections. Viewers could quickly jump to the parts that mattered most to them, reducing the friction of watching a long, uninterrupted video. This was a game-changer for time-strapped viewers, giving them more control over their viewing experience.
Summaries: AI also provided brief summaries of the video content, offering an extra layer of context. These summaries gave viewers a snapshot of the video, helping them decide if it was relevant or worth their time.
By handling these tasks automatically, the AI relieved creators of the burden of polishing their videos manually. This was crucial because many new users were hesitant to spend extra time perfecting their recordings. Instead of requiring more effort from creators, the AI ensured their videos were polished and contextualized on its own. Meanwhile, viewers benefited from having more context upfront, making videos more engaging and easier to navigate.
🎯 Results → Driving higher “view rates” and better Engagement.
Once Loom implemented AI-generated titles, chapters, and summaries, the impact on both creators and viewers was clear. By making videos more polished and easier to navigate, the team saw improvements across the board.
Let’s at the outcomes — both for business and users.
Quantitative📈: Increased Engagement
Higher View Rates: AI-generated context significantly increased the likelihood of videos being viewed. The drop-off between sharing and viewing decreased. The number of “Video First Views” (VFV) increased significantly.
Improved Engagement: Features like chapters allowed viewers to focus on the most relevant parts, increasing overall interaction time with videos. The number of recordings with comments increased as well.
Successful A/B Testing: Each AI feature was A/B tested, showing consistent improvements in viewership and engagement. The combined rollout further enhanced the positive impact.
Qualitative 🤝: Enhanced UX for both Creators and Viewers
For Creators: The AI features reduced the burden of polishing videos. Creators could focus on recording without worrying about adding context, as the AI handled it automatically.
For Viewers: Clear titles, summaries, and chapters made videos easier to understand and navigate. Viewers could quickly assess relevance, boosting their willingness to watch and engage.
Validated Hypothesis: The core assumption that polished videos lead to higher engagement was proven true — videos became more accessible, and interactions improved without adding complexity for creators.
While the AI features were part of a paid plan, the overall impact was significant enough to consider rolling them out globally. Despite some users not having immediate access to these premium features, the overall customer experience saw a major uplift.
What can we take away from here? The AI-driven enhancements not only improved the technical metrics of view rates and engagement but also provided a smoother, more enjoyable experience for both creators and viewers, reinforcing the importance of adding context to video communication.
But what if AI is not something your product can leverage yet? You can still achieve a lot of impact by removing psychological barriers for your users.
Let’s see how Loom did that 👇
Case Study #2: How Loom removed psychological barriers to drive sharing
Let’s put ourselves in the shoes of a user: when you last time recorded an audio or video of yourself presenting something, how many attempts it took to record a proper outcome? 5-10? For me, it took 13 attempts to record the recent integration CommandAI for Growthamtes — crazy 🤯
🔴 Before → Psychological barriers to sharing the video.
It’s not that different for new users at Loom, as we all are humans who can feel unconfident, worried, or just obsessively striving for perfection all when it's not necessary. When new users first created a recording on Loom, many faced significant psychological barriers that prevented them from sharing their videos. Despite completing their recordings, creators hesitated to share due to concerns like:
Worrying about how they looked or sounded.
Feeling self-conscious about their background, surroundings, or distractions.
Experiencing discomfort from watching and hearing themselves on camera.
These cognitive barriers made the seemingly simple task of sharing a video feel daunting, hindering activation. Loom knew they had to help new users overcome this mental roadblock if they wanted to increase video sharing and overall user engagement.
🟢 After → Added words of affirmation and “visual cues”.
When you feel unconfident, uncertain, worried — what do you want to hear?
Loom's solution was simple yet effective: words of affirmation and visual nudges right after the first recording. They focused on shifting the user's mindset from self-critique to emphasizing the value their video would bring to others. The experiment involved:
Affirming Messages: Users received encouraging messages post-recording that highlighted the value of their video, like "You just saved your team a meeting" or "Your team will love this!" This helped creators focus on the benefit to their audience rather than their insecurities.
Visual Calm: The addition of soothing visuals—like calming waves or breath animations—helped ease anxiety, giving users a moment to relax before sharing.
Value-Oriented Copy: Copy emphasized the positive impact their videos would have on viewers, reinforcing that sharing would provide real value.
These small but impactful nudges helped users move past their self-doubt and encouraged them to share their videos more confidently.
🎯 Results → Driving “Sharing rate” and delight for users.
The experiment showed remarkable results for such a simple intervention:
Higher Sharing Rates: New users were more likely to share their videos after receiving affirming messages, leading to an increase in activation and engagement.
First-Video Success: More users were able to achieve the critical milestone of receiving at least one view on their first video, which is a key metric for activation (VFV increased).
Positive User Feedback: The psychological barriers to creating and sharing videos were notably reduced, and the introduction of these nudges helped creators feel more comfortable.
Loom extended this strategy by incorporating a subtle version of these affirmations for all users after their first recording, creating an environment of ongoing support. This thoughtful, user-centric approach helped to dramatically improve the video-sharing experience, leading to better engagement and satisfaction
Summary and Key Takeaways
We've explored how Loom successfully enhanced user engagement and activation by tackling key psychological and practical barriers faced by creators. What you can apply from these learnings to your product?
Remove unnecessary friction for users by leveraging AI: AI-generated titles, summaries, and chapters reduce the workload on creators while providing viewers with more context, improving engagement 🎯
Address psychological barriers to drive Sharing: Offering affirming messages and calming visuals helps new users overcome self-consciousness and encourages video sharing. All users are humans after all 🙏
Support Emotional Reassurance: Providing psychological nudges, like focusing on the value of content, helps users move past hesitation, increasing activation and overall usage. This is why we need to understand behavioral psychology 🤓
Iterate with A/B Testing: Continuously testing and refining features ensures that improvements positively impact user behavior and engagement. As I love repeating that — always run a second iteration! 🔄
Loom’s journey shows that understanding both the practical and emotional challenges users face can make a big difference. By automating the tough parts and offering a bit of reassurance along the way, they’ve created a smoother, more engaging experience. These simple but effective strategies are a great reminder that improving user engagement doesn’t always require big changes — sometimes, it’s the small, thoughtful touches that matter most.
What to learn how Loom are building teams and product experiments beyond User onboarding? Watch the Growthmates episode with Janie Lee 👇
P.S. Did you know that I’m also helping companies by conducting an Onboarding Audit to uncover growth opportunities and UX improvements? Book an intro call with me, and I’d be happy to discuss your challenge and explore how I can help
This is all for today, dear readers. If you found this helpful — please share this with your like-minded colleagues and friends, it would give a huge support for me to continue creating this 💜
With best regards,
Kate Syuma