How to Keep AI Product Copy On-Brand (Style Guides + Guardrails)

AI product copy on-brand: why generic output kills conversion

AI product copy on-brand means that every AI-generated product description sounds like it came from your brand, not from a generic template. When product descriptions lack a consistent voice, shoppers notice — even if they cannot articulate why. The page feels less trustworthy, the products feel less premium, and conversion drops.

The core problem is that AI models default to a neutral, generic style. Ask GPT-4 or Claude to "write a product description for a running shoe" and you will get competent but bland copy that could belong to any brand. Your Allbirds description should not sound like your Nike description, which should not sound like your New Balance description.

The solution is not to avoid AI — it is to constrain it with brand-specific guardrails. Teams that invest in style guides, structured prompts, and review workflows get AI output that is both scalable and consistently on-brand.

This guide covers the practical steps. For the compliance side of AI-generated copy (restricted claims, regulated categories), see our companion article on keeping AI product copy compliant.

Building a product description style guide

A style guide for AI-generated product copy is different from a general brand style guide. It needs to be specific enough for a machine to follow while being readable for the humans who review the output.

Core components

1. Voice and tone attributes

Define 3-5 attributes that describe your brand voice. Be specific:

2. Vocabulary rules

Create explicit word lists:

• Preferred words: "crafted" (not "made"), "endures" (not "lasts"), "designed for" (not "perfect for")
• Banned words: "revolutionary," "game-changing," "cutting-edge," "best-in-class," "synergy"
• Brand-specific terms: use "Flyknit" not "knit upper," use "GORE-TEX" not "waterproof membrane" (when applicable)

3. Formatting standards

• Description length: 80-150 words for standard products, 150-250 for premium
• Paragraph structure: lead with the key benefit, then specs, then use case
• Bullet points: 3-5 per product, each starting with a feature or benefit
• Capitalization: sentence case for descriptions, title case for product names only

4. Category-specific variations

Different product categories need different tones:

• Technical gear: specification-forward, precise measurements, comparison-friendly
• Fashion/lifestyle: aspirational, sensory language, styling context
• Home/kitchen: practical, use-case oriented, family-friendly
• Electronics: feature-benefit pairs, compatibility details, setup simplicity

Example: good vs bad for the same product

Bad (generic AI output):

"This amazing premium jacket is perfect for any outdoor adventure. Made with the highest quality materials, it will keep you warm and comfortable in any weather. A must-have for outdoor enthusiasts!"

Good (on-brand for a technical outdoor brand):

"Built for shoulder-season conditions where layering matters. The 650-fill-power recycled down insulation traps warmth at 340g, while the 20D ripstop shell sheds light rain. Packs into its own chest pocket for summit-bag simplicity."

The difference is specificity, brand-appropriate restraint, and concrete details over generic claims.

Do/don't lists that AI can follow

A do/don't list is the most immediately actionable guardrail. Include it directly in your AI prompts.

Universal do/don't for product copy

Do:

• Use specific measurements and data points
• Start with the primary benefit or use case
• Include material names and technical specifications
• Address the reader as "you"
• Mention what the product helps the customer accomplish

Don't:

• Use superlatives without substantiation ("best," "most advanced," "unmatched")
• Start with "Introducing" or "Meet the"
• Use filler phrases ("take your X to the next level," "elevate your experience")
• Repeat the product name more than twice in a description
• Make claims you cannot verify ("#1 selling," "doctor recommended")

Category-specific do/don'ts

Add category overlays:

Apparel:

• Do: mention fit type (regular, slim, relaxed), care instructions, fabric weight
• Don't: use subjective sizing language ("fits perfectly"), unsubstantiated fabric claims

Electronics:

• Do: specify compatibility, included accessories, power requirements
• Don't: promise performance results ("5x faster"), use vague tech buzzwords

For more on structuring product descriptions that convert, see our guide on product descriptions that sell.

Template prompts for consistent output

The quality of AI-generated copy depends directly on the quality of the prompt. Build template prompts that embed your brand rules.

Prompt structure

A strong template prompt includes:

1. Role definition: "You are a copywriter for [Brand Name], a [brand description]."
2. Voice instructions: "Write in a [tone attributes] voice. [2-3 specific instructions]."
3. Do/don't rules: "Always [dos]. Never [don'ts]."
4. Structure template: "Format: [opening hook] + [key features as bullets] + [closing use case]."
5. Input data: "Product: [title]. Attributes: [structured data]. Category: [category]."
6. Examples: "Here are 2 approved descriptions for reference: [examples]."

Example template prompt

You are a copywriter for TrailPeak, an outdoor gear brand for serious hikers and climbers. Our voice is knowledgeable, specific, and understated — we let performance data speak rather than using superlatives.

Rules:
- Use specific measurements and material names
- Start each description with the primary use case or condition
- Include 3-5 bullet points with feature-benefit pairs
- Never use "revolutionary," "game-changing," or "perfect for everyone"
- Keep descriptions between 100-150 words

Product: {title}
Category: {category}
Key attributes: {attributes}
Materials: {materials}
Weight: {weight}

Write a product description following the above rules.

Iterating on prompts

• Start with your best-performing existing descriptions as examples
• Test the prompt on 20-30 products across categories
• Review output with your brand team
• Refine rules based on consistent issues (too long, wrong tone, missing specs)
• Version-control your prompts so changes are tracked

Tools like Lasso allow teams to configure style rules and templates for AI-generated descriptions, making it easier to maintain consistency across large catalogs without manually editing each prompt.

Approval workflows for AI-generated copy

Even with strong prompts, AI output needs human oversight — at least initially.

Tiered review approach

Tier 1: Full review (launch phase)

• Review 100% of AI-generated descriptions
• Build a feedback loop: corrections improve the prompt
• Duration: first 100-200 products

Tier 2: Sampling review (scaling phase)

• Review 10-20% of descriptions, stratified by category
• Focus human review on new categories and edge cases
• Automate checks for banned words, length limits, and format compliance
• Duration: until confidence is high across all categories

Tier 3: Exception-based review (mature phase)

• Automated QA catches format and vocabulary issues
• Human review only for flagged items and new product categories
• Periodic random audits (5% monthly) to catch drift

Automated QA checks

Build automated checks that run on every batch:

• Banned word detection — flag descriptions containing words from your don't list
• Length compliance — flag descriptions outside your word count range
• Format verification — check for required bullet points, paragraph structure
• Repetition detection — flag descriptions that are too similar to each other
• Attribute verification — confirm that key product attributes appear in the description

For how other teams handle product content validation before publishing, see our article on reducing catalog errors with a validation framework.

Measuring brand consistency at scale

Track these metrics to ensure your AI-generated copy stays on-brand over time:

• Review rejection rate — what percentage of AI descriptions need significant edits? This should decrease over time.
• Brand voice score — have your brand team score a monthly sample on voice consistency (1-5 scale)
• Conversion rate comparison — compare AI-generated descriptions against hand-written ones. On-brand AI copy should perform within 10% of hand-written.
• Customer feedback signals — monitor product page bounce rates and time-on-page for products with AI descriptions

Getting started

1. Document your brand voice in a structured style guide with voice attributes, vocabulary rules, and examples
2. Build a do/don't list and test it in AI prompts
3. Create template prompts per product category with brand rules embedded
4. Implement a tiered review workflow starting at 100% review
5. Automate QA checks for vocabulary, format, and length compliance

Lasso makes this workflow scalable by integrating brand rules into AI-powered description generation, so your team reviews output rather than writing from scratch. See how it works or book a demo to explore fit for your catalog.

For the companion guide on compliance and regulatory guardrails, see keeping AI product copy compliant.