AI Personalized Video with Clay and Vidu
TLDRThis video tutorial demonstrates how to integrate video with Clay to create AI-personalized videos for sales outreach. It showcases a Clay table with customer data and a process involving two steps: generating a video and accessing it once completed. The tutorial uses a video template from Vidu, which is personalized using GPT for elements like logos, names, and Slack channels. The video's thumbnail, HTML, and other details are dynamically generated and can be integrated into email outreach tools. The video also guides viewers on setting up a Clay table from scratch, including creating HTTP API columns for video generation and retrieval, and using dynamic data insertion for personalization.
Takeaways
- 😀 The video demonstrates how to integrate video with Clay to automatically generate AI personalized videos for sales outreach.
- 📊 The example showcases a Clay table with four rows of data including names, emails, and domains, which are used to personalize the videos.
- ⏱️ Video generation can take time, from 60 seconds for a single video to 30 minutes for a batch, depending on the complexity and number of videos.
- 🔗 The process involves two steps: generating the video and then picking up the completed video before sending emails.
- 🎥 The video used in the example is from Vidu, a platform that offers customizable templates for personalized AI videos.
- 💼 The video is personalized with elements like company logos, names, and specific Slack channels, using GPT for dynamic content generation.
- 📝 The script explains how to set up a Clay sheet with API details necessary for video generation, including HTTP endpoints and authorization.
- 🔧 The process includes adding columns for video job initiation and accessing generated video data, with dynamic replacement of IDs and other data.
- 📧 The completed video includes details like the thumbnail, HTML, and preview URL, which can be used in email outreach tools.
- 🔄 The script also covers how to handle video processing states and errors in Clay, ensuring all videos are generated before proceeding.
- 📬 Finally, the video HTML can be embedded in emails to dynamically display personalized videos to recipients, increasing engagement.
Q & A
What is the purpose of integrating video with Clay?
-The purpose is to automatically generate AI personalized videos for sales outreach at scale.
How many Clay tables are mentioned in the example?
-Two Clay tables are mentioned in the example.
What information is included in the Clay tables?
-The tables include people's names, emails, domains, and details related to video generation.
What is the role of the 'video steps' in the process?
-The 'video steps' are responsible for generating the video and picking up the completed video before sending out emails.
What is the source of the video used in the example?
-The video used in the example is a template from Vidu, which showcases personalized AI videos.
How is personalization achieved in the video?
-Personalization is achieved using GPT to dynamically insert elements like the prospect's name, company, and domain.
What is the significance of the 'Clay tab' in the video recording page?
-The 'Clay tab' provides access to all the API details needed to create new videos and manage video generation.
What is the status of a video when it has been queued up but not yet completed?
-When a video has been queued up but not yet completed, its status is 'queued'.
How can the HTML from the video be used in email outreach?
-The HTML from the video can be included in an email to embed the personalized video directly into the email content.
What is the process for recreating the Clay table from scratch?
-The process involves adding HTTP endpoint columns for video generation and video data retrieval, setting up dynamic fields, and adding authorization headers with the API key.
How can the status of a video be checked after it has been queued?
-The status of a video can be checked by running the 'vid get video' column, which will return a 200 status if the video has been generated.
Outlines
🎥 Automating Personalized Video Generation with Clay
The speaker demonstrates how to integrate video with Clay to create AI-generated personalized videos for sales outreach. They showcase a Clay table with four rows of data including names, emails, and domains. The process involves two steps: generating the video and picking up the completed video before sending emails. The video used in the example is a personalized AI video template from Vid, which can be accessed and used to create videos with personalized elements such as logos, company names, and prospect names. The speaker also shows how to use GPT to personalize the video content with animations and competitor comparisons. They walk through the process of queuing a video for a new entry in the table and accessing the video's API details, including the status, HTML, and thumbnail.
🔗 Setting Up Video Generation and Retrieval in Clay
The speaker guides through the process of setting up video generation and retrieval in Clay. They explain how to add an HTTP endpoint column for initiating a video job and another for accessing the generated video data. The dynamic parts of the video, such as the person's name and company domain, are piped in from Clay. The speaker also details how to add headers, including an authorization key, which is a hidden API key. They rename the columns for clarity and demonstrate how to queue a video job and check the status. The process includes handling the video generation status, retrieving the video's URL, thumbnail, and HTML for email integration. The speaker also shows how to handle errors and process multiple video requests efficiently.
📧 Integrating Personalized Videos into Email Outreach
The speaker concludes by explaining how to use the generated videos with Clay for email outreach. They show how to add the video HTML to a custom field in Clay, which can be used to insert the dynamic video into an email. The speaker provides an example of an email with embedded video HTML, demonstrating how the personalized video can be sent to prospects. They also show how the video's thumbnail can be previewed and improved by changing the column type to display images from URLs. The speaker ends with a note on personalizing the video content for different recipients, such as comparing Vid to Loom or Intercom to Sesk, to pique their interest.
Mindmap
Keywords
💡AI Personalized Videos
💡Clay
💡Sales Outreach
💡Vidu
💡GPT
💡Thumbnail
💡HTML
💡API
💡Video Generation
💡Email Outreach
Highlights
Integration of video with Clay for AI personalized sales outreach videos.
Demonstration of a Clay table with four rows of names, emails, and domains for video personalization.
Two video steps: generating the video and picking up the completed video for email outreach.
Use of a video template in Vid to create personalized AI videos for sales teams.
Personalization of video elements such as logos, names, and Slack channels using GPT.
Animation and feature highlighting in the AI-generated video for product demonstration.
Access to API details for video creation through the Clay tab in the video recording page.
Queueing up a video for a new entry in the Clay table and receiving a status update.
Personalized video thumbnails with company logos and names.
Using GPT to generate personalized video questions comparing products with competitors.
Recreating the Clay table from scratch to demonstrate the setup process.
Adding HTTP endpoint columns in Clay for video job initiation and data retrieval.
Dynamic replacement of video data in the Clay table using forward slashes.
Setting up authorization headers with API keys for secure video data access.
Previewing the generated video and its thumbnail directly from the Clay table.
Incorporating personalized video HTML into email outreach for dynamic content delivery.
Efficient error handling in Clay to process multiple video generation requests.
Final demonstration of personalized video emails with embedded video content.