Bring AI into your marketing workflow,from product opportunities to content growth.
Build coordinated AI marketing workflows for new launches, renewed growth of existing products and everyday promotion. Understand products and audiences, develop content strategy, connect product images, detail pages, visual content and video production, then improve through testing. Operations teams guide direction and quality; AI organizes information, assembles content and handles repetitive production so useful experience can be reused.
Understand the product, plan the content and produce it with a clear process.
01
Growth Strategy
Turn product attributes into purchase reasons worth testing
The challenge
New products lack a clear audience, established products sound alike, and content ideas depend on individual inspiration.
Our approach
Combine product facts, competitor content, and use cases to define audiences and moments of need, turning selling points into content that can be filmed, written, and tested.
What you receive
Product research, audience scenarios, and a content strategy for operations to approve before production.
02
Creative and Content Production
One strategy across images, copy, and video
The challenge
Directors, designers, and editors repeatedly interpret the same product. Producing variations takes time, and brand messaging becomes inconsistent.
Our approach
Use approved selling points and reference structures to organize scripts, storyboards, and evidence shots, connecting product images, detail pages, posts, and videos for team review.
What you receive
Reviewable marketing assets and a production workflow that can expand across audiences, scenarios, and channels.
03
Content Operations and Review
Make every test the starting point for the next
The challenge
Teams produce plenty of content without knowing what works. Strong assets get lost in chat threads, so the next round starts from zero.
Our approach
Review impressions, clicks, sales, and refunds. Keep effective openings, purchase reasons, and evidence clips, then plan the next round of variation tests.
What you receive
A content asset library, review records, and iteration rules that help operations build its own playbook.
01Product Analysis02Audiences and scenarios03Content Planning04Images and videos05Testing and Review
CASE 01 / AI MARKETING
Food marketing: product impressions grew 247.3% in the week after publishing.
The same product is compared over the weeks before and after publication, using existing case materials. These changes cannot be attributed solely to AI.
• Product Analysis• Audiences and scenarios• Content Planning• Images and videos• Testing and Review• Product Analysis• Audiences and scenarios• Content Planning• Images and videos• Testing and Review• Product Analysis• Audiences and scenarios• Content Planning• Images and videos• Testing and Review• Product Analysis• Audiences and scenarios• Content Planning• Images and videos• Testing and Review
Connect script planning, storyboards, video generation and publishing review around the reasons to buy. Track impressions, clicks and conversions separately to connect creative execution with business results.
Service: AI video marketingComparison: the same product, one week before and after publishingData: product traffic records in the case materials
Business task
Turn product features into reasons consumers understand and act on.
Food marketing must answer two questions: can the content attract the right audience, and can the product presentation encourage a purchase? The project developed scripts and supporting visuals around the product, then assembled, reviewed and published them. Click performance and sales performance were reviewed separately.
What we did
01
Define the audience and reasons to buy
Input · Product information, reference content and use cases
Identify audiences, selling points and supporting shots. Place product features in specific customer situations and define the core reason the script needs to communicate.
Deliver script directions with supporting visual references.
02
Connect scripts, storyboards and production
Input · Confirmed reasons to buy and script structure
Assemble product scripts, generate storyboard images and video shots, then add voiceovers, subtitles and editing for team review.
Deliver video assets ready for publishing tests.
03
Use business data to guide review
Input · Product traffic records before and after publishing
Compare impressions, click-through rates and conversion rates separately to check whether assets attract attention and support purchases.
Inform future content selection and variant testing.
The same task, before and after
Business StageBEFOREAFTER
Product impressions
BEFORE31,500
AFTER109,400 · Relative growth of 247.3%
Product Click-through Rate
BEFORE5.24%
AFTER6.61% · Up 1.37 percentage points
Product Conversion Rate
BEFORE2.32%
AFTER7.80% · Up 5.48 percentage points
Related food content and case materials
Images from the food case. The three metrics above compare the same product before and after publishing.
Food case image · Thin-skin shumaiFood case image · Buckwheat five-nut mooncakes
Video production: team output increased from 30 to 400 videos per day.
Client feedback · Operations and AI creative production
Connect reference analysis, script assembly, storyboards and production tasks. Reuse proven structures for different audiences and scenarios, reducing repeated planning and handoffs for each asset.
Service: AI content production workflowMetric: videos completed by the team per daySource: existing client case feedback
BEFORE / Videos per day30videos
AFTER / Videos per day400videos
Times the original outputAbout 13.3×
Calculated from daily team output reported by the client. This is team output; the source does not provide a complete measurement period.
Business task
Scale content production while keeping the creative rationale clear.
Video production involves analysis, writing, storyboards, generation and editing. Operations staff work with an AI creative producer to carry buying reasons and visual tasks through the workflow, expand a master script across audiences and scenarios, and review generated results.
What we did
01
Break reference content into reusable structures
Input · Reference videos and product information
Identify audiences, scenarios, selling points, openings and supporting visuals. Decide which structures to retain and which details to replace with product-specific facts.
Give future scripts reusable structures and reliable product facts.
02
Organize content variants around a master script
Input · Approved scripts and different customer situations
Keep the core reasons to buy, adapt copy for audiences and scenarios, then generate storyboards and shot-by-shot production tasks.
Expand one planning effort into a batch of reviewable production plans.
03
Bring production tasks into one workflow
Input · Scripts, storyboard images and shot tasks
Generate the required shots and connect voiceover, subtitles, editing and review. Operations staff check finished videos before publishing.
Create a collaborative workflow from creative input to finished video.
The same task, before and after
Business StageBEFOREAFTER
Planning starting point
BEFOREPlan each video and collect references individually
AFTERReuse a master structure for each product, audience and scenario
Production handoff
BEFORESeparate handoffs for scripts, prompts and editing
AFTERConnected script and storyboard tasks, with shared team review
Daily team output
BEFORE30 videos
AFTER400 videos · Client feedback
Explore: from analysis to batch scripts
Production records from the existing case. Click to view the full images.
01 · Reference video analysis02 · Expand master scripts across audiences and scenarios03 · Batch script production
Product marketing methodology: connect planning logic to AI workflows.
Organize content planning, production and testing around products, audiences and moments of need.
What we did
01
Analyze and catalog: make proven content reusable
Input · Reference videos, approved cases and product assets
Identify openings, characters, situations, reasons to buy and supporting shots. Record each segment's role and connections, then add it to the content library after human review.
Build searchable libraries of frameworks, characters, scenarios and stories.
02
Product matching: find the moment of need
Input · Product facts, primary and secondary benefits, and conditions of use
Identify users, buyers and triggers for demand. Match benefits to specific problems, then select visuals and assets that demonstrate product value.
Map products, audiences, moments of need and reasons to buy.
03
Script assembly: turn strategy into production tasks
Input · Product briefs, proven frameworks and asset libraries
Retain effective structures and buying reasons while adapting the product, audience and scenario. Organize copy, storyboards and shot tasks, then review, produce and test in small batches.
Update assets and rules using clicks, sales and other feedback to inform the next planning cycle.
First establish whose problem the product solves and when it is needed. Then identify the corresponding reasons to buy and supporting visuals. Break proven content into reusable assets, let AI assemble scripts grounded in product facts, and have the team review and test them. Save what works for future use.
01Analyze and catalog02Match products to needs03Assemble scripts04Produce and review05Test and feed back
How the method works in practice
Content library development and product analysis for Niu Qian's team at Kuangben.
Asset analysis and cataloging · From reference videos to reusable assetsProduct analysis · From benefits to audiences, needs and evidence
Clear responsibilities and completion criteria at every step.
/ 01
Required inputs
Product specifications and credentials, target audiences, moments of need, past creative assets, and available advertising records.
/ 02
Who signs off
The product owner verifies claims, the marketing lead reviews purchase reasons and brand messaging, and operations approves publication.
/ 03
How we review
Review the brief, script, storyboard, and finished video in stages. Match product facts to supporting visuals before moving forward.
/ 04
Handling exceptions
Unsupported claims or promises are returned for evidence. Assets with distorted products or unsuitable scenes are revised before publication.
/ 05
Final deliverables
Product and audience research, content briefs, scripts and storyboards, approved assets, and test records.
/ 06
Acceptance criteria
First record time spent, usable assets, and revision rounds for the same task. Then compare impressions, clicks, and sales using the same channel, time window, and product definition.
Can AI-generated marketing content be published immediately?+
The owner first checks product facts, brand messaging, and visuals. Generation and approval are separate stages.
Which task should we automate first?+
Start with a recurring task that has complete inputs and a clear reviewer, such as preparing scripts for multiple use cases of one product. Validate one stage before expanding.
Start with one specific business task.
Map your current workflow, materials, and bottlenecks before deciding how to run a pilot.
Which part of your business would you like to improve?
Start with a specific challenge: content production falling behind, sales expertise that is hard to share, or repetitive work taking up your team's time?
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