Veo 3 Video Generation Prompts – The Complete Guide to Prompt Structure

Start with three prompts now: one for visuals (appearance and setting), one for narrative, and one for outcome. This keeps you focused on capabilities and reality, leveraging Veo 3’s technology. For a facebook audience, define who they are, what they see, and the action (действие) you want them to take, conveyed through каждый prompt. Each prompt should target a specific outcome and include a clear visual cue that signals value immediately. They should know what to watch and what to do next.

Build each prompt with three layers: context (scene), action (действие), and outcome (revenue, CTA). This approach requires concise, specific details for visuals, motion, and sound. Think about how the viewer will respond and what need you are meeting for audiences on facebook and beyond. Define where the video will appear: feeds, stories, and short ads; specify how you capture attention in the first 3 seconds, set the tone, and ensure the appearance of characters aligns with brand. Then map the prompt to revenue goals by describing the desired result and the target audience so you can measure success via watches, captures, touches and clicks.

Veo 3 Visual prompt: A warm kitchen at dawn, appearance of the host in a clean apron, camera gliding along the counter, action: pouring coffee and showing a product, lighting highlights textures, through the first 3 seconds the scene draws attention, then pivots to hands demonstrating the product.

Narrative prompt: Scripted voiceover communicates a solution in a friendly tone, like a quick tutorial, with specific benefits tied to user needs; keep it tight and ensure the story remains clear and actionable for they and their peers.

Outcome prompt: End frame shows the CTA and potential revenue impact; specify on-screen text: “Shop now” or “Learn more,” include a product badge, and add a short retention hook that aligns with audiences expectations.

Testing and iteration: publish three variants to different audiences on facebook, track captures, touches, and conversions; compare watch time and engagement; iterate weekly by swapping a single element (color, text, or framing) to boost engagement by a practical margin and learn what they prefer.

Practical tips for immediate results: keep prompts concise (two sentences per layer), use strong action verbs, and anchor visuals to real products or scenes. Ensure every prompt aligns with a tangible action that viewers can take, like visiting a landing page, joining a mailing list, or watching a longer video to deepen understanding.

One-line prompt templates: capturing intent in a single line

Draft every one-line prompt with a fixed structure: scene, target, and constraints, then add design and output details to align with software capabilities. This structure clarifies intent and speeds iterations across streams and platforms.

Make it real by specifying a real environment and, when needed, a close-up shot. Keep the line concise so your team can purchase faster approvals and everyone understands what will be created.

Anchor visuals around a brand and its products, include the items to be captured, and set a clear target (for example, highlight texture or scale). Use includes and something to guide what should appear on screen.

scene: corporate showroom, target: maximize real product visibility, shot: close-up, design: detailed, brand: BrandX, includes: logo and packaging, products: headphones, streams: 4K60fps, applications: product-launch videos.

scene: factory floor, target: capture workflow efficiency for training, shot: wide then close-up, design: practical, detailed, brand: BrandY, includes: machines and operators, products: automation components, streams: 1080p, 30fps, applications: internal guides and client demos.

scene: digital storefront, target: maximize conversions, shot: hero, design: vibrant, detailed, brand: BrandZ, includes: callouts and pricing tags, products: wearable devices, streams: 4K, HDR, applications: ads and landing pages.

Template syntax and structure

Syntax focuses on scene, setting, subject, action, design, shot, includes, products, brand, streams, and applications. Each element guides the software to capture the intended look, feel, and deliverables, while maximizing consistency across teams and campaigns.

Practical tips by application

Customize prompts for industries such as tech, fashion, and manufacturing. Emphasize real textures for product creation, leverage close-up details for features, and align designs with brand guidelines to support guides, streams, and downstream uses.

Subject, environment, and action: mapping prompts to visuals

Define the triad first: subject, environment, and action, then map prompts to visuals so each frame communicates the core idea clearly and efficiently.

Subject: pick a single focal element and give it a strong silhouette. Use blue as the dominant cue to sustain recognition across scenes. Include tactile hints like пластик textures to signal material, and tie the subject to entrepreneurship themes to guide audience relevance. Keep scale consistent so the subject remains identifiable in every shot; vary pose or angle rather than changing core identity, maximizing clarity across frames.

Environment: place the subject in an environment that reinforces the action and mood. Options include space stations, a control room, or a workshop bench. Add details such as пыль on surfaces and reflections off пластик panels to deepen texture. Lighting should synchronize with the subject so shadows and highlights stay coherent in every scene; this alignment speeds up visualizations and reduces noise in the final result.

Action: define a simple, tellable motion for each frame, such as reach, adjust, or gesture. Each step should advance the narrative; keep movement smooth and predictable by using consistent pacing. Pair motion with sound cues to guide perception, and use tracking to maintain continuity of position and lighting across shots. When action is synchronized, viewers grasp intent without extra explanation, especially in fast sequences.

Prompt mapping approach: for each scene create a compact prompt set with Subject, Environment, and Action, plus Mood, Sound, and Texture cues. Include blue as a color cue, пластик textures, and пыль specks where appropriate. Use a space backdrop when relevant. Add a soft sound track to guide perception and a few visualizations of metrics. Ensure personalized prompts to fit each micro-story, and apply optimization to keep wording lean. whats next can be signaled by a progress indicator in the visuals, tying into future-looking elements. Tracking, synchronization, and clear cues maximize consistency across frames.

Examples: Subject: founder in a blue jacket; Environment: space station interior with пластик panels and пыль on a glass surface; Action: gestures toward a holographic chart; Mood: focused; Sound: soft hum; Visualizations: charts rise with the gesture. This shows how mapping supports a coherent sequence.

Examples: Subject: product designer; Environment: lab bench with blue lighting; Action: rotates a small device; Mood: confident; Sound: beeps; Visualizations: real-time metrics floating around; This demonstrates how to personalize prompts for different personas while maintaining consistent visuals.

Test and refine: run quick iterations, check alignment, adjust prompts to improve matching; track results to ensure optimization and repetition of cues; maintain mood across scenes for a smooth viewer experience.

Camera angles, framing, and movement prompts

Adopt a triad: close-up, mid-shot, and deep-space wide to maximize outputs and lasting viewer engagement. There are many ways to structure prompts; the core proposition is to align each frame with the storyline and events. Whats more, maintain automation and software-driven control for lighting, focus, and background stability, so data from each take supports optimization and distribution of outputs. каждый frame serves the narrative and space around the subject.

Prompt templates for angles and framing

Use concise, repeatable templates that specify angle, distance, headroom, background treatment, and a simple movement cue. Each template keeps alignment with the core narrative and the data you collect. For example: “Generate a close-up at eye level, 60% headroom, background softly blurred, speech clear, and microexpressions readable.” Include their and their data points to build consistency across scenes; каждый кадр should reflect shifts in lighting while preserving a stable baseline.

Movement prompts and data-driven optimization

Movement prompts drive how events unfold on screen and help maintain continuity across takes. Combine static frames with controlled pans, dolly moves, and tracked follow-through to create rhythm without startling the viewer. Tie prompts to software-driven checks: adjust speed based on speech length, increase pan subtly during gesture moments, and optimize lighting to preserve color accuracy across outputs. This approach supports data-backed optimization and the generation of valuable outputs, while keeping the narrative tight and engaging.

Style and mood prompts: color, texture, and lighting cues

Choose a dominant color and lighting direction to anchor the shot, then layer texture to define mood. Start with blue as the base for a calm, trustworthy look, or use a deep neutral to convey power. This approach yields real appearance in your output and aligns with what audiences expect, especially when you tailor каждый output with описания and a personalized proposition.

Color prompts

• Blue-dominant palette: blue background, soft key light from the left, gentle fill from the right, deep navy shadows; texture: matte surface with micro-grain; background stays neutral; shot: close-up; output: 4K, 16:9; appearance: real; statement: crisp and clear.
• Neutral-modern: slate gray base with a subtle cyan accent; lighting: high-contrast rim along the edge; texture: brushed metal or linen; background: soft gradient from charcoal to blue-gray; mood: clean, professional.
• Warm-energy variant: amber and peach tones with cool fill; background: warm wood or fabric; texture: glossy plastic with micro-scratches for realism; output: 60fps; audiences expect liveliness.
• Brand-touched: yours brand color as anchor; background: gentle gradient in brand hues; lighting: directional from above; texture: mixed materials to reveal texture; note: personalized proposition for the project.

Texture and lighting cues

• Deep, powerful shadows: use a strong key from the side and a narrow fill to push depth; background remains subdued to keep focus on the subject.
• Soft, friendly mood: diffuse light from a large source, reduce contrast, emphasize smooth surfaces; background stays clean to highlight the subject.
• Edge and separation: add a rim light or backlight to carve subject from background; for texture, pair matte fabrics with subtle specular edges.
• Happening details: monitor micro-texture on materials; a quick monkey test in your generator helps reveal color shifts; this requires specialization and is especially useful for future shoots.
• Consistency across shots: use the same lighting ratio and texture cues per scene; this output consistency keeps the proposition strong for audiences.
• Turnarounds and backgrounds: keep background simple; use a gentle gradient or a single color block to avoid distracting from the appearance of subject; ensure purchase and licensing terms are clear for any LUTs or props you add; a final thank you.

Prompt sequencing: guiding narrative flow across scenes

Begin with a concise page roadmap that defines the scene purpose and the angle of each transition. Map the arc in two to four beats and keep the pacing tight to avoid wasted seconds.

For each scene, specify the prompt formula and the space between beats. Use a consistent structure: state the goal, describe the main visual cue, and provide a single action for the generator.

In bilingual notes, описывайте visuals and абстрактные cues to guide mood and texture. Tie prompts to customer expertise and services; these streams show the narrative flow, generating the most excitement. dont skip feedback from attending sessions; thank the teams.

Establish a pacing formula that combines tight action prompts with wide, reflective lines. Specify current context and aged visuals to signal time, keeping the space for transitions.

Close with a practical check: review the page against the roadmap, confirm the angle between scenes, and capture learnings for future prompts that will improve shows and services.

Prompt testing: running variants and logging results

Run three prompt variants for each concept and log results in a centralized sheet. This keeps iteration fast and yields clear comparisons for booth visuals, personalized marketing, and visitors experiences.

Theyre essential steps to keep production efficient: define goals, test variants, measure impact, and maintain a clean log for each run. The process helps you create a repeatable workflow that aligns with models and materials while avoiding friction later in production. You would see that small wording changes can have outsized effects toward clarity and engagement.

1. Set clear objectives and success signals. Must specify target elements (for example, booth setup, banners, and CTA) and a measurable score: clarity, branding fidelity, and actionability. Use a simple rubric: 1–5 for relevance, 1–5 for visual balance, and 1–5 for engagement. Include the person you’re speaking to in the brief so the model keeps the target in mind.
2. Design three prompt variants. Variant A emphasizes person-centric messaging, Variant B emphasizes creation and materials, Variant C pushes context and tension. Include phrases that steer toward the goal of driving qualified visitors to the booth and toward personalized marketing. Ensure each variant preserves the same skeleton so you can compare differences. Include platform references like facebook where appropriate.
3. Lock the skeleton, vary only the chosen lever. Use the same scene, subject, and lighting; swap adjectives, verbs, or context lines. This keeps comparisons fair and makes it easier to attribute changes to the variant itself. Theyre ready to compare side-by-side.
4. Run tests and capture metrics. For each variant, record: generation time (s), prompts length (tokens), key elements present (booth, banner, model, materials), alignment score, and any failure modes (wont generate a needed element or produce a wrong detail). After generating, inspect for missing elements and note elements needing adjustment.
5. Log results consistently. Use a shared sheet with columns for variant name, objective, time, quality score, alignment, notes. Include a short visual sample link or embed if your platform permits. Theyre helpful when revisiting the data to explain what changed and why. Also add a field for where the result will be used (e.g., facebook ads, landing pages).
6. Analyze and act. Compare scores, identify which variant toward the target delivered the strongest signal for visitors and engagement. If a variant consistently scores lower, drop it or modify it with new keywords and try a пилот before full rollout.
7. Maintain a lean loop. After generating, archive old versions, tag by date and concept, and create a quick summary for the team to review. This keeps the process efficient and protects against drift in style or tone.

Keep every step documented so you can audit decisions and reproduce results later. Use a simple template: field notes, links, and a thumbnail for quick reference. To speed up future rounds, build a small library of variant templates and reuse them for each new concept. more iterations yield more reliable signals and smoother scaling to visitors and potential customers.

When testing for a facebook campaign, track practical outcomes such as click-through rates, time-on-page after generation, and subsequent conversions. Each pilot should begin with a пилот phase to validate assumptions before committing to broader deployment. This approach maintains efficiency, helps you create consistent branding, and makes the testing process repeatable across models and materials.

Export, reuse, and documentation: preserving prompts for future renders

Export prompts with versioned metadata and a capsule schema that ties each prompt to a specific model, lighting setup, and outputs. This keeps context intact and gives future renders consistent as technology evolves.

Define a capsule-based prompt package that includes: prompt_text, model, version, and a reference to the target vision or project. Add sections for lighting presets, camera angles, and current environment notes. Attach fields for пыль and съемки context so future operators can reproduce the same look. Include a short description of the intended audience (customer) and the educational goal, so anyone reviewing the file understands the purpose.

Export formats should cover human-readable plus machine-friendly data. Use JSON or YAML for machine parsing, and a text-friendly export as a template for quick reuse. Each entry should carry outputs_specs, that describe resolution, frame rate, audio-visual channels, and whether the render uses a stereo or multi-channel setup. Hence, you can generate consistent results across different sessions and even across teams in entrepreneurship environments where you rely on different specialists.

Documentation acts as a living reference. Maintain a concise information section that records the strategy, the steps taken to set up the render, and any deviations in a given campaign. A separate notes field captures details such as changes in lighting, the current model version, or adjustments to the captures of the scene. Use a clear tagging system to differentiate educational, promotional, and internal experiments, so detectives and teammates can locate relevant prompts quickly.

Reuse and governance. When reusing a prompt, start from the capsule’s core: prompt_text plus metadata. Adjust only the elements that matter for the new run–lighting, camera position, or environment notes–then re-export with a new version number. This approach avoids drift and preserves a traceable lineage of outputs, while still allowing experimentation. Maintain a small, dedicated library section for the monkey example prompts to illustrate how minor changes in context yield different renders without losing the thread of the original intent.

Templates and metadata for reliable reuse

Adopt a templated structure that teams fill consistently: id, title, purpose, model, version, lighting, camera, environment (пыль, съемки), prompts, and outputs. Include a step-by-step checklist: validate lighting consistency, confirm target resolution, verify audio-visual alignment, and test against a representative set of outputs. Use strong, current, and actionable descriptions to ensure that anyone can reproduce the result and judge its alignment with the vision and customer needs.