Digital broadcasting and AI video marketing implementation plan

🛒 For brands, MCNs and content teams, we provide mass production and distribution solutions for digital live broadcast videos.

Solution overview

Spoken short videos are currently the mainstream content form for customer acquisition and brand exposure, but live-action appearances have limited production capacity due to time, venue, and multilingual requirements. Digital Human Video changes "appearance" from "recording" to "generating": using scripts, you can batch produce oral videos, and supports multiple languages ​​and images, allowing the content team to increase production capacity from "day/piece" to "batch/day".

Target user portrait

• Brand and marketing team: need to continue to produce product introductions and event promotion videos.
• MCN/content agency: A content matrix that requires multiple accounts, multiple languages, and multiple images is required.
• Knowledge payment and training team: Convert courses and practical information into oral short videos in batches.

Expected results and ROI

• The production cycle of a single oral broadcast video is compressed from "recording + editing 1-2 days" to "script + generation 1-2 hours".
• A single script can output multi-lingual versions in batches, significantly reducing the cost of overseas content.
• Unify the image and tone, and brand consistency is better maintained.

Preconditions

• Clear script and content topic selection ability (digital people cannot replace topic selection and script).
• Authorization is required to use other people's portraits; the use of digital people must comply with the platform's labeling requirements for AI-generated content.
• Determine the purpose of the video (information flow delivery, brand number, overseas export, etc.) to select specifications.

Scene positioning and boundary clarification

This solution solves the large-scale production of oral videos with "scripts and lack of production capacity". It does not solve the cold start of content with "no topic selection and no scripts", and is not suitable for core brand promotions that require in-depth emotional interpretation by real people. The delivery standards are "natural picture, aligned mouth shape, reusable in multiple versions, and compliant and annotated".

Workflow design (6 steps)

Step 1: Topic selection and script production

• Input: product information, content strategy.
• Action: Produce scripts in batches and determine the duration, tone and CTA of each article.
• Output: script pool (including title, spoken script, and screen prompts).
• Access control: The script is reviewed by the content person in charge.

Step 2: Digital human image and voice selection

• Input: brand tone, script pool.
• Action: Select digital human image, voice and language; confirm image/voice authorization source.
• Output: image and sound configuration table.
• Access control: The image matches the brand tone, and the authorization is traceable.

Step 3: Video generation and parameter configuration

• Input: script + image configuration.
• Action: Configure speaking speed, pause, subtitles, background and frame, and generate in batches.
• Output: Digital population broadcasts the first version of the video.
• Access control: the mouth shape and pronunciation accuracy are up to standard, and the subtitles are correct.

Step 4: Post-production and multi-language mass production

• Input: First version video.
• Action: Batch output of clips, soundtracks, covers and multilingual versions.
• Output: finished film and multi-version files.
• Access control: The finished film has been reviewed and multiple languages ​​are subject to spot checks one by one.

Step 5: Compliance and Platform Adaptation

• Input: completed film.
• Action: Mark AI-generated content, check platform rules, advertising law wording and regional requirements.
• Output: Compliance Checklist.
• Access control: The expressions involved in the promotion of characters and functions are compliant.

Step 6: Release, Deliver and Iterate

• Input: compliant films.
• Action: Publish according to channel specifications, and track completion, interaction and conversion data.
• Output: data dashboard and iteration suggestions.
• Access control: review data and feed back to the script pool.

Tool mapping table

Note: The price and free quota are subject to the official real-time page; the digital human tool also has value-added items such as "voice cloning and custom image".

Cost, risk and implementation threshold

Input structure

• Manpower: 1 person for script + 1 person for operation can start the game; editing can be partially handed over to AI tools.
• Tool cost: Digital Human Platform subscription + generated quota, billed by volume.
• Learning cost: The entire process of scripting, generation, and publishing takes 1-2 days to get started.

Risk and access control

• Portrait rights: The use of real faces/voices must be explicitly authorized, otherwise the risk of infringement is extremely high.
• Compliance annotation: AI-generated content must be annotated according to platform requirements to avoid account bans and penalties.
• Homogenization: Digital human videos are easy to identify and fatigue, so differentiation needs to be added to scripts and editing.
• Data compliance: Statements involving customer data, efficacy/revenue commitments, etc. are subject to legal review.

Hidden benefits and costs

• Benefits: Content production capacity is scaled up, multi-lingual overseas costs are reduced, and the release pace is controllable.
• Cost: The “pseudo-reality” of digital people may damage trust if used excessively, and the proportion needs to be controlled.

Expected results and acceptance criteria

• Acceptance 1: The script pool has a stable supply and the review pass rate meets the standard.
• Acceptance 2: The single generation cycle meets the standard, and the lip-sync and subtitle quality is acceptable.
• Acceptance 3: Multi-lingual versions will be randomly checked for errors in translation and sensitive expressions.
• Acceptance 4: All finished films have completed AI annotation and compliance inspection.

Frequently Asked Questions and Troubleshooting (FAQ)

1. Will digital video be restricted by the platform?

   The platform mainly looks at the value of the content and whether it is compliant with the labeling; high-quality content that is compliant with the label is usually distributed normally, while low-quality content in batches of the same content is easy to be demoted.

2. What should I do if my voice doesn’t sound like a real person or my mouth shape doesn’t match?

   Select a high-quality sound model and control the speaking speed; manually check after generation, and use editing software to correct mouth shape/subtitles if necessary.

3. Can I use celebrity or Internet celebrity images?

   Unauthorized use of other people's portraits is an infringement and is strictly prohibited; it is recommended to use the platform's own image or its own authorized image.

4. What should I do if the multilingual translation is not authentic?

   For important markets, use native speakers to review the scripts and then hand them over to digital humans to generate; avoid literal translation.

5. How to match digital people and real-person content?

   It is recommended that real people lead the core content of the brand, and digital people are responsible for batch, regular, and multi-lingual content, forming a combination of "real person quality + digital human production capacity".

6. How to get started with a limited budget?

   Use the free credit to pass 3-5 pieces of verification data before deciding whether to upgrade your subscription or purchase a custom image.

Advancement and Expansion

• Customized digital human: record exclusive image and voice to enhance brand recognition.
• Interactive digital human: access live broadcast and customer service scenarios, moving from recorded broadcast to real-time.
• Programmed production: Strung script library, generation, and release into an automated pipeline.
• A/B testing: Use different images, speaking speeds, and covers to deliver in batches, and use data to feed back the script.