AI Explainer Video Production: How to Plan, Script, and Ship Videos That Convert
Key takeaways
- Three decisions come before the first line of script: who is watching, the one thing they should remember, and how long the video should run.
- Budget about 150 words of narration per finished minute across five timed beats. A 90-second explainer works out to roughly 225 words, shorter than most first drafts.
- AI can automate scene structure, visuals, and voice, turning most revisions into a re-render instead of a new production. It will not tell you whether the topic deserves a video at all.
- The script travels across languages, but re-rendering it is only the start of localization; budget a native reviewer and some cultural adaptation per market.
Explainer video production is the process of turning one idea into a short video: decide the audience and message, write a timed script, produce the visuals and voice, then publish and measure. AI tools can substantially shorten the production stage, but the planning, scripting, and review still take real judgment.
By the end of this guide you will have a length target, a 90-second script structure you can fill in directly, a sense of which production format fits your content, and a short list of what to measure once the video is live.
A generator renders whatever script you give it, in any language you support. If the script names the wrong problem, that mistake ships in every version, which is why most of what follows is about planning and scripting rather than rendering.
Planning: three decisions before you write a word
Explainer videos go wrong in planning far more often than in the edit. Teams that know the product too well tend to skip the audience question and write a feature tour instead. Settle these three decisions on paper first.
Write for a specific viewer
“SMB marketers” is too broad to write against. “A marketing manager at a 40-person agency who has been asked to cut reporting time and has never bought software before” gives you something concrete to write toward. Put that person and their situation at the top of the script and keep it visible while you draft.
Every sentence should be something that person would care about; if it exists mainly because the product team wanted it in, cut it.
Decide the one sentence they should repeat
Ask what the viewer should be able to tell a colleague an hour later. That sentence is effectively the video: everything else needs to support it, and anything that does not is a candidate for cutting.
When two messages both matter, two short videos usually beat one trying to carry both.
Set the length before you draft
Wistia recommends one to five minutes for the format, and reports viewers typically watch over half an educational or tutorial video in that range. Where yours sits should follow the job it has to do.
| Job the video has to do | Where it sits | Length we aim for |
|---|---|---|
| Stop a cold visitor and explain the category | Homepage, paid landing page | 60 to 90 seconds |
| Explain the product to someone already evaluating | Product page, sales email, demo follow-up | 90 seconds to 3 minutes |
| Teach a process someone has to perform | LMS, help center, onboarding sequence | 3 to 5 minutes |
This length column is a working rule of thumb inside Wistia’s range, not a fixed rule. Lock a target before drafting: without a number to write toward, you cannot tell later if a script has run long.
Scripting: a 90-second structure you can copy
A generator will not make these decisions for you, so here is the actual skeleton to fill in, not just a description of one. Narration budgets assume about 150 words per minute, the conversational rate the National Center for Voice and Speech gives for US English speakers, cited here by VirtualSpeech. Five beats, 225 words, 90 seconds.
The worked example below is fictional, written for a hypothetical expense-management tool. Its numbers are illustrative, not real performance data.
| Beat | Timecode | Words | What this beat has to do | Worked example (fictional, expense management tool) |
|---|---|---|---|---|
| Hook | 0:00 to 0:10 | 25 | Name the viewer’s problem in the viewer’s words. No brand, no logo, no “in today’s world” | “Your team files 400 expense claims a month. Finance spends nine days chasing receipts that were never attached.” |
| Stakes | 0:10 to 0:25 | 38 | Say what the problem costs in time, money, or risk. One consequence, made concrete | “Every late reimbursement is an email to your controller, a delayed close, and one more reason a good manager stops traveling to see customers.” |
| Answer | 0:25 to 0:55 | 75 | Name the product in one sentence, then walk through the steps a real user takes | “Northwind Expenses reads the receipt the moment it is photographed. It matches the card charge, codes the category from your chart of accounts, and routes anything over your threshold to the right approver.” |
| Proof | 0:55 to 1:15 | 50 | One concrete data point and its source. Without a verified result yet, use a placeholder like “[Customer] cut X by Y” rather than inventing a number | “In an early trial, one team’s finance close ran four days faster, with no extra headcount.” |
| Ask | 1:15 to 1:30 | 37 | One action, stated plainly, matching where the video sits | “Start a free workspace at northwind.example and import last month’s card statement. You will see your first coded claims in about ten minutes.” |
Two working notes. Keep a second column beside the narration for what is on screen at that moment, written as instructions rather than mood (“receipt photo snaps into a table row”, not “dynamic, modern feel”). And read the finished draft aloud with a timer: scripts that hit 225 words on the page often run past 90 seconds spoken, because 150 words per minute is closer to a fast conversational pace than an average reading pace with natural pauses. A timed read that comes in noticeably over target is the signal to cut further, not to speed up the voiceover.
How AI changes explainer video production
AI explainer video production runs through the same five stages any explainer does: script, scene structure, visuals, voice, and export. What a given tool automates, and how well, varies.
| Stage | The studio version | The AI workflow |
|---|---|---|
| Script | Copywriter brief, two or three rounds | Same script discipline, drafted in the tool or pasted in from your doc |
| Scene structure | Storyboard artist, client review | Text is split into scenes automatically; you reorder rather than redraw |
| Visuals | Illustration or a shoot day, plus animation | Illustration styles or an AI presenter, matched to brand colors and assets |
| Voice | Casting, booking, studio session | Synthetic voice or a cloned voice, re-rendered on every script change |
| Languages | New session per language | Re-rendered from the same script, then reviewed by a native speaker |
| Revisions | Change order, back into the queue | Edit the line, render again |
Which route fits depends mainly on what the video needs to show.
Animation suits abstract or process-driven content: policies, workflows, topics with no obvious thing to film. simpleshow turns a script or document into scenes with suggested illustrations, so you adjust rather than draw.
A presenter or avatar video suits direct address, such as an announcement or a training introduction. D-ID’s AI Video Generator produces this from a script or existing content and lets you set the sentiment a line is delivered with. It also suits content that changes often, since an edit becomes a new render, not a new recording session.
A screen recording suits proving that a real interface actually works, and can combine with the other two: an avatar introduces a topic, then hands off to a recorded walkthrough.
simpleshow and D-ID’s AI Video Generator share one account, so animation and presenter-led routes are not a separate tooling decision. If a video is likely to raise follow-up questions a script cannot anticipate, Agentic Video lets a viewer ask mid-video and get a grounded answer, then keep watching.
Our comparison of explainer video software puts ten tools side by side.
Publishing and measuring your explainer video
Where a video is placed often matters as much as how well it is produced. An explainer tends to convert best where the viewer already has the question it answers: a pricing page, an onboarding email, an LMS module, a sales follow-up. The same video on a social feed with no context usually underperforms, which is a distribution problem, not a video problem.
Two habits help regardless of placement: put the video where the decision is actually made, and ship captions and a transcript, since captions carry the video with the sound off and the transcript is what search engines and answer engines read.
What to measure depends on the job you assigned the video during planning:
- Homepage or campaign explainer: play rate, click-throughs on the CTA, conversion after the video.
- Product or sales explainer: engagement with the CTA, demo requests, assisted conversions further down the funnel.
- Training or onboarding video: completion rate, results on any knowledge check, whether people can actually perform the task afterward.
Wistia’s 2026 State of Video shows engagement falling as videos get longer, so play rate and completion answer a different question than conversion does. Match the metric to the job.
When an AI explainer is the wrong format
Rendering has gotten cheap enough that it is worth pausing before every video; a few situations call for a different format.
The wording is not settled yet. If legal, a works council, or a subject-matter expert is still editing the language, a document absorbs those changes and a rendered video does not. Wait until the wording holds, or expect to render it twice.
The message depends on a specific person delivering it. For a restructuring, a safety incident, or an apology to customers, a real person on camera, even a simple phone recording, can carry more weight than a produced video, because authenticity and visible accountability matter more than polish here.
The video needs to prove a real interface works. A screen recording is usually the more convincing choice, for the same reason covered above.
You are localizing for more than one market. Re-rendering the same script across languages gives every market the same argument, not necessarily one that lands the same way: examples, currency, legal references, and directness all shift. Budget a native reviewer per language rather than treating the render as the whole job. simpleshow’s guide to multilingual explainer videos covers what to check for.
The content is short and the audience is small. If the answer is one paragraph and twelve people need it, write the paragraph. A well-placed help center article is often the better format; the fair test is whether anyone would choose to watch the video if it were not the only version available.
Frequently asked questions
How long should an explainer video be?
One to five minutes, per Wistia’s recommendation, with 60 to 90 seconds the usual target for a homepage or paid landing page. Set the length before drafting; the target is what makes cutting possible once a script runs long.
How much narration fits in a 90-second explainer video?
About 225 words. Budget roughly 150 words per minute, the conversational speaking rate the National Center for Voice and Speech reports for US English speakers. Split those words across five beats: hook, stakes, answer, proof, ask. Read the draft aloud with a timer, because most scripts run longer spoken than they look written.
Should an explainer use animation, a presenter, or a screen recording?
It depends on what the video needs to show. Animation suits abstract processes and topics with no obvious thing to film. A presenter or avatar works well for direct communication, such as an announcement or a training introduction. A screen recording is usually the better choice when viewers need to see a real interface working, which covers most software walkthroughs. Formats can be combined.
Next steps
Pick one video you have been meaning to make and write only the five-beat table for it: 225 words, no visuals yet. That draft alone tells you within an hour whether you have a video or a feature list.
When the script holds up, start in D-ID Studio and render the presenter or avatar version, or use the simpleshow video maker for the animated one. Teams with a whole library to localize, or an LMS to feed, should book a D-ID demo before starting on a self-service plan, since production at that scale is usually a workflow question before a tooling one.
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