Video chapters are a simple but powerful way to make your product videos more effective, engaging, and user-friendly. By breaking your video into clearly labeled sections, you give viewers an easy way to navigate directly to the content they care about most.

Example of chapters for a product video.

For product videos, this can be really important. Customers often want to see specific features, installation steps, or use cases without having to watch the entire video. Chapters allows them to find what they are after easily. Imagine a five-minute product demo with chapters like “Key Features,” “How It Works,” and “Troubleshooting.” A potential buyer can jump straight to what matters most, increasing satisfaction and reducing frustration.

Chapters also make your content more professional and trustworthy. They show you understand your audience and respect their time. Instead of forcing viewers to scrub through the timeline blindly, you’re giving them a guided, on-demand experience. This is especially important for technical products, where clarity and ease of use can strongly influence purchase decisions.

From a marketing perspective, chapters can improve engagement metrics. Viewers are more likely to watch longer when they can skip around easily, reducing drop-off rates. Many platforms, including YouTube, also reward structured videos with better search visibility, making your content easier to find.

Finally, chapters help with accessibility and training. Employees, partners, or customers learning about your product can revisit specific sections as needed, supporting self-paced learning and reducing the need for repeat support inquiries.

Adding chapters is a low-effort, high-impact improvement for any product video. By making your content easier to navigate, you deliver a better experience, build trust, and increase the likelihood that viewers will take the next step toward purchase.

So, how do you do it?

I thought you’d never ask. It’s actually quite simple, depending on your preferred platform. The major platforms like YouTube, Vimeo, etc., provide a straightforward way to do this as part of the upload process.

If you want to host the video on your website, you’ll need to provide a sidecar file, if your player doesn’t natively support chapters. If you search online, you’ll find that making a sidecar is a very easy process.

Final Thoughts

With everyone vying for attention and the prevalence of videos for almost everything you can imagine, it’s crucial to stand out. Chaptered videos, especially for products, offer significant advantages. They act more more like manuals, allowing users to select specific sections that align with their needs. While a collection of numerous small videos may seem appealing, they can be more challenging to maintain and may confuse users. Playlists are an alternative, but there’s nothing quite like the sleekness of chaptered videos.

~ The End ~

Further Reading That Might Help:

• YouTube Help – Video Chapters
  Official YouTube support page explaining how to add manual and automatic chapters.
• Wistia – How to Add Chapters to YouTube Videos
  A clear guide on both manual timestamps and YouTube’s auto-chapter feature, plus best practices.
• Hurrdat Marketing – YouTube Chapters: What They Are & How to Add Them
  Explains benefits for SEO and viewer engagement, with step-by-step instructions.
• TubeBuddy – How to Add Chapters on YouTube Videos and Why You Should
  Covers advantages for SEO, improved watch time, and a practical tutorial.
• Reddit /r/NewTubers – Are YouTube Chapters Helpful or a Hindrance?
  A community discussion of real-world creator experiences with using chapters.

Before You Go, A Quick Feedback Loop

I’ll practice what I preach:

• • • • Was this post useful to you?
      • Did the stories help clarify the message?
      • What parts felt unclear or too abstract?

Reply with your thoughts — or better yet, tell me one small change you made after looking at your own assessment data. Because when we listen, we learn. And when we learn, we create eLearning that actually changes behavior, not just knowledge.

We recently answered some questions for a discussion panel. Rather than waste the effort that we put into them, we thought we might post them here. There are five of them and they all focus on the strategic use of eLearning. Feel free to comment if you disagree with anything we say.

Pickup one of our free eLearning Guides – “Elevate Your Onboarding.”

Question: We’ve struggled to standardize onboarding for different roles across our five facilities. What are some of the best practices you’ve seen for creating high-impact onboarding experiences in complex operational environments?

Our Answer: This is a common challenge for many organizations, particularly those operating across multiple sites. There’s often a tension between giving every new hire a clear understanding of how the organization functions as a whole and efficiently onboarding experienced professionals who primarily need alignment with your specific technologies, processes, and culture.

Many onboarding programs swing too far in one direction, either overwhelming most new employees with too much information (the “firehose” approach) or under-serving highly skilled hires with content they already know. This often results in a bloated, fragmented system that’s hard to maintain and scale.

Here are eight best practices that we’ve seen work well in complex operational environments:

1. Understand and Document the Business Needs and Personnel Landscape

It’s easy to get lost without a map. Spend time looking at the big picture, including employee retention and turnover, internal versus external promotions, and existing survey data for current onboarding (if you’re collecting them). Look for trends and opportunities.

2. Modular Onboarding Design

Create a core onboarding curriculum that applies to everyone. It should cover the company mission, values, safety protocols, and organizational structure. Then layer on role-specific or site-specific modules tailored to function, facility, and level of experience. This keeps it scalable without becoming one-size-fits-all.

3. Preboarding to Build Momentum

Use the time between offer acceptance and day one to begin onboarding. This can include digital welcome kits, video messages from leadership, and introductory resources. It eases the transition and frees up time for higher-impact learning once they’re onsite.

4. Mentorship and Buddy Systems

Pair new hires with a peer or mentor during their first 30–60 days to accelerate cultural integration and provide real-time support for navigating tools, processes, and expectations specific to their role or facility.

5. Onboarding Scorecards and Milestones

Clearly define onboarding goals for each role and monitor progress using 30-, 60-, and 90-day scorecards. These help managers and new hires stay aligned while allowing for feedback and adjustment during the ramp-up period.

6. Leverage Technology for Consistency

Use an onboarding platform or learning management system (LMS) to deliver standardized content and track completion. This ensures consistency across locations while allowing for local adaptation.

7. Solicit Feedback and Continuously Improve

Conduct short surveys or debriefs with new hires at the end of their onboarding period. What worked well? What was missing? Use this feedback to continually refine and improve the experience.

Final Thoughts

The key to successful onboarding is balancing consistency with flexibility. A well-designed onboarding framework should ensure every employee feels welcomed, equipped, and connected without overwhelming them or wasting their time. Start with a strong foundation, then adapt smartly to the needs of the role and location.

~ The End ~

Further Reading That Might Help:

• Four things that make onboarding actually work for new employees.

Before You Go, A Quick Feedback Loop

I’ll practice what I preach:

• • • • Was this post useful to you?
      • Did the stories help clarify the message?
      • What parts felt unclear or too abstract?

Reply with your thoughts — or better yet, tell me one small change you made after looking at your own assessment data. Because when we listen, we learn. And when we learn, we create eLearning that actually changes behavior, not just knowledge.

This post is the last in this series. If you missed the rest please see the links at the bottom of this page. After breaking down the pros and cons of using a web-base self-service approach over an LMS for training, it’s time to draw a conclusion.

Typical use cases for an API based data collection system can be divided into two separate streams:

First, it is very common to encounter organizations with clear training or planning needs that they cannot meet because they either lack a learning management system (LMS) entirely or cannot reliably schedule its use within the organization.

Second, in any fast-paced industry, it is typical to have client-facing training materials that form part of the client interaction. To ensure client success, customers often need to understand a product, process, or regulation, which requires them to complete some form of training. Enforced training is notoriously unpopular. The ability to offer self-serve, on-demand training that captures the required learner data directly from the website is therefore very appealing.

This approach is not an off-the-wall, untested idea. It is something we have implemented successfully for several large organizations to deliver on-demand training to hundreds of thousands of users. It is also substantially more cost-effective than deploying a full LMS and requires far less time and effort to set up and maintain.

Of course, some highly regulated industries cannot use this kind of approach and need the added security and compliance features of an enterprise-grade LMS. However, for most organizations, outward-facing training typically involves content that is neither proprietary nor heavily regulated.

At the end of the day, it comes down to whether you need easy-access, on-demand, web-based training or an enterprise-level LMS with all of its advanced features.

The ideal organization for this form of training delivery is one with a limited budget, limited access to an LMS, and limited resources. Despite these constraints, they still need to collect data about the learner’s experience, assessments, and completion details.

If that sounds like you, then this might be the right solution. The combination of ease of use for the learner and the rich data available to the provider makes for a compelling package, especially when you consider the cost savings.

If you decide to try it, let us know. We would be happy to help or just hear about your experience.

Before You Go, A Quick Feedback Loop

I’ll practice what I preach:

• • • • Was this post useful to you?
      • Did the stories help clarify the message?
      • What parts felt unclear or too abstract?

Reply with your thoughts — or better yet, tell me one small change you made after looking at your own assessment data. Because when we listen, we learn. And when we learn, we create eLearning that actually changes behavior, not just knowledge.

This post is about the pros and cons of using a web-based emitter and API rather than a regular LMS. We’ve tried to fair, but ultimately, it’s up to you to decide if any of this works for you.

“Alright then, break it down for me.”

Here’s a list of the pros and cons for the web-based modules:

“Wait a moment, those last three cons sound like we will need some technical help.”

Yes, that’s true! But actually, it’s quite a small ask. Once you’ve established an API, you can use it for any of your courses (i.e. it’s a one-time investment). The total time needed by someone developing a simple API is modest when compared to the monthly cost of an LMS. The set up time is usually no more than a couple of days.

However, if you’re looking to connect this API to your enterprise systems, then that raises a whole bunch of other issues to do with security, data, consistency, etc.

We don’t recommend taking that approach as this is intended to be a quick and simple solution that creates a significant amount of useful data which could be easily manipulated with a spreadsheet or other report software, not a replacement for an enterprise LMS.

OK, now let’s look at the LMS option:

Conclusion:
Obviously, no one size fits all! What is true, however, is that many projects fail to get off the ground because of the potential investment needed to set up and run an LMS. If you find yourself in that situation, then this approach might prove to be a scalable, effective and cost-efficient way to gather data about the efficacy and performance of your training modules. If you need compliance and a record of the learners’ activities, that is the only way outside of an LMS/LRS to achieve that.

Most importantly, it creates an opportunity for learners to self-service and use just the training that they need without engaging with a potentially intimidating LMS.

Read part six for a final conclusion.

Before You Go, A Quick Feedback Loop

I’ll practice what I preach:

• • • • Was this post useful to you?
      • Did the stories help clarify the message?
      • What parts felt unclear or too abstract?

Reply with your thoughts — or better yet, tell me one small change you made after looking at your own assessment data. Because when we listen, we learn. And when we learn, we create eLearning that actually changes behavior, not just knowledge.

The Dark Side of AI in Learning: What’s the Worst That Could Happen? (Besides Robots Taking Over the World)

Hey there, learning enthusiasts! We’ve all been hearing about the amazing potential of AI to revolutionize education. But, let’s get real – there’s also a downside to consider. In this post, we’ll explore the worst that could happen if we’re not careful. And no, I don’t mean robots taking over the world (although, let’s be honest, that’s a possibility too).

Over-reliance on tech: Because who needs human interaction, anyway?

Are we risking a generation of students who can’t think for themselves? If we rely too heavily on AI-powered learning tools, we might be doing more harm than good. I mean, what’s next? AI-powered friendships? AI-powered family therapy?

Losing the human touch: Where’s the love?

Learning is about more than just absorbing facts – it’s about connecting with others, building relationships, and developing emotional intelligence. If we let AI take over, we might lose the very essence of what makes us human. And trust me, I don’t want to see a world where students are like, “Thanks, AI, for the feedback, but can you also give me a hug?”

Bias and misinformation: The ultimate fake news

AI systems are only as good as the data they’re trained on. If that data is biased or flawed, we risk perpetuating existing inequalities and spreading misinformation like wildfire. Or worse, we might end up with AI-powered learning tools that think pineapple belongs on pizza.

One-size-fits-all learning: Because who needs creativity, anyway?

Every student learns differently, but AI-driven learning tools might not be able to accommodate that. We risk forcing students into a cookie-cutter approach that neglects their individual needs. And let’s be real, who doesn’t love a good cookie-cutter approach? Said no one ever.

Job displacement: The robot uprising begins

Let’s face it – AI has the potential to automate jobs, including those in education. What does that mean for teachers, instructors, and other learning professionals? Well, maybe they can all become professional pizza taste-testers instead?

Equity and access: The digital divide gets wider

Not everyone has equal access to technology or digital literacy. If we rely too heavily on AI-powered learning tools, we risk exacerbating existing inequalities. And that’s just not cool, folks.

Creativity crisis: The AI apocalypse

If we rely too heavily on AI-generated content and solutions, do we risk stifling human creativity and original thought? I mean, what’s next? AI-powered art? AI-powered music? AI-powered humor? (Okay, maybe not that last one).

Data privacy concerns: Because who doesn’t love a good data breach?

Finally, there’s the issue of data privacy. AI-driven learning systems rely on vast amounts of student data – what happens if that data falls into the wrong hands? Well, at least we’ll all have a good story to tell.

It’s time to have a nuanced conversation about the role of AI in learning. Let’s harness its potential while avoiding the pitfalls. And if all else fails, we can always blame the robots. 🙂

Some external links for Further reading:

• IBM AI overview
• Wikipedia about AI