Client Preferences

Terminology Rules

9 rules

Use This	Not This	Notes
Install product	Weave	Cliff's hard rule: never use "weave" for any hairstyle or install product — not in the app, not in copy, not in any mockup or strategy doc. No exceptions.
Wig install	Wig weave	Same rule applies to all compound forms. "Weave" does not appear anywhere in the product or its marketing.
Protective style	Weave style	Umbrella term for installed protective styles. Specific style names come from the verified ER library, not generic descriptors.
Locs	Dreadlocks / Dreads	Preferred community term. "Dreadlocks" is considered pejorative by many in the natural hair community. Use "locs" always.
4A / 4B / 4C coils	Kinky hair	Use the Andre Walker hair typing system consistently. "Kinky" without context is imprecise and can carry a negative connotation.
Style library	Style categories	"Categories" implies a closed taxonomy. "Library" implies a curated, growing collection. The ER team defines what enters the library.
Verified style	Placeholder style	When a style name appears in the app or mockup without ER team sign-off, it must be treated as a placeholder internally. Never ship as canonical without Cliff and Saige's review.
Frontal	Front closure	Industry-standard term for a hairpiece covering the front hairline. Do not conflate with a closure. Common sizes: 13×4 and 13×6.
Closure	Middle part / Top piece	A 4×4, 5×5, or 6×6 hairpiece for the top or crown. Distinct from a frontal — they are not interchangeable terms.

Copy Direction

✓ Do

Celebrate natural texture. Write as if coils, locs, braids, and natural styles are the default, not the exception. Avalon is built for a specific community — that specificity is the product's core strength.
Use the language of the community. Terms like "big chop," "wash day," "edges," "protective style," and "install" are standard professional vocabulary. Use them with confidence.
Acknowledge that seeing yourself matters. The core emotional promise is "see it on yourself — your face, your skin, your texture, not someone else's." Lead with that specificity.
Respect the stylist as the expert. When writing about professional interactions, treat the stylist as the authority. Avalon is a decision-support tool, not a replacement for professional judgment.
Keep consent and data ownership front of mind. When writing about the AI, emphasize that the user's image belongs to the user. Consent framing builds trust with this audience.
Write to a woman making a real decision. The stakes are real: hours in a chair, hundreds of dollars, a commitment that may take months to reverse. Write with that weight, not around it.

× Don't

Never use "weave." See Terminology Rules. This is Cliff's explicit, non-negotiable hard rule. It does not appear anywhere in the product or its marketing under any circumstance.
Do not use placeholder style names as canonical categories. Knotless Braids, Loc Start Set, Silk Press, and Twist Out appear in early mockups as placeholders. Do not use them in consumer-facing copy or as the product's committed style taxonomy until ER team verifies them.
Do not imply Avalon produces the hairstyle. Avalon shows what a style could look like on the user. The stylist does the work. Never blur that distinction.
Do not lead with generic AI language. "Advanced AI engine" and "powered by machine learning" create distance. The brand earns trust through specificity and result quality, not by foregrounding the technology.
Do not write copy that positions Black hair care as niche or unusual. This is a mainstream, professional, multi-billion-dollar industry. Write like it.
Do not frame the user's current hair as a problem. Before/after framing that implies natural hair needs fixing conflicts directly with the brand's positioning and audience.

Category Verification Status

The following style names appear as placeholders in the current app and website mockups. None are ratified for production use. Cliff has specifically flagged the four highlighted rows as unverified. Saige and the ER team must review and sign off before any style name ships in the product or consumer-facing marketing.

Style Name (Placeholder)	Appears In	Status	Notes
Knotless Braids	App mockup, website/home.html (updated to "Protective Braids" in mockup)	UNVERIFIED — PLACEHOLDER	Cliff flagged directly. Do not anchor to this as a canonical category. Pending ER team input.
Loc Start Set	App mockup, website/home.html (updated to "Loc Journey" in mockup)	UNVERIFIED — PLACEHOLDER	Cliff flagged directly. Pending ER team input. "Loc Starter Set" was the prior mockup label.
Silk Press	App mockup, website/home.html (updated to "Natural Style" in mockup)	UNVERIFIED — PLACEHOLDER	Cliff flagged directly. Pending ER team input.
Twist Out	App mockup, website/home.html (updated to "Defined Twists" in mockup)	UNVERIFIED — PLACEHOLDER	Cliff flagged directly. Pending ER team input.
Knotless Box Braids	website/styles.html (updated to "Protective Braids" in mockup)	PENDING ER LIBRARY	Illustrative mockup card only. Style library to be defined by ER team and Saige.
Micro Braids	website/styles.html (updated to "Fine Braids" in mockup)	PENDING ER LIBRARY	Illustrative mockup card only. Awaiting ER verification.
Goddess Braids	website/styles.html (updated to "Crown Braids" in mockup)	PENDING ER LIBRARY	Illustrative mockup card only. Awaiting ER verification.
All other style names in styles.html	website/styles.html (Butterfly Locs, Faux Locs, Bantu Knot-Out, Sisterlocks, etc.)	PENDING ER LIBRARY	Full style library to be defined by Cliff, Saige, and the ER team. No style ships without sign-off. Mockup names are illustrative only.

Knowledge Base Requirements

Before building the AI's style recommendation layer, a structured product knowledge base must exist. Saige and the Ébène Règne team are the domain experts who will populate this data. The fields below define what the knowledge base must capture for every verified style entry.

Bundle Count Range

How many bundles a style requires, expressed as a range (e.g., 3–5 bundles). Varies by desired length, density, and installation method. Must be sourced directly from ER — not inferred from internet content.

Frontal Required

Whether the style requires a frontal hairpiece covering the front hairline. Boolean plus notes on typical frontal size (13×4, 13×6, full lace). Frontal vs. closure is a critical distinction — never conflate them.

Closure Required

Whether the style uses a closure (4×4, 5×5, 6×6) instead of or in addition to a frontal. Capture standard placement: top, middle, or three-part. Drives the app's product recommendation output.

Leave-Out vs. Full Cover

Does the style require leaving out natural hair (e.g., a sew-in with leave-out) or is all natural hair fully tucked? Critical for the app's hair profile questions and compatibility logic.

Commitment Level

Duration range the style is typically worn: short (2–4 weeks), medium (4–8 weeks), long-term (months to years for locs). Feeds the commitment filter in the style library and the verdict card's framing.

Saige + ER Input Required

This data cannot be sourced from the internet. Saige and the ER team must contribute from professional experience and ER's product catalog. A dedicated session should be scheduled to document this for each verified style before Phase 1 build begins.

Data Sourcing

Cliff identified four content channels for expanding the Avalon style library with reference images, inspiration content, trend data, and structured product metadata. The table below defines what each source contributes and how it should be collected.

Source	What It Contributes	Collection Approach
YouTube	Tutorial breakdowns and install walkthroughs where stylists narrate exactly what they use: bundle count, frontal size, technique, product references. Richest source for structured product knowledge.	Scrape public tutorials by style keyword. Extract structured metadata (style name, products mentioned, bundle count if stated). Saige reviews extracted data for accuracy before any entry enters the verified library.
TikTok	Trend signals — which styles are gaining traction in the 18–35 demographic right now. Before/after transformation content that shows style outcomes and real-world results.	Hashtag-based scrape (#protectivestyle, #locsjourney, #twistout, etc.). Trend scoring by engagement. Public posts only — no personal data collected.
Instagram	High-quality professional portfolio photography. Stylists and brands post finished work — richer imagery than TikTok, more permanent than Stories. Best source for style reference imagery.	Hashtag and account-based scrape for style reference imagery. Consent and attribution must be tracked for any image used as a training reference. Source must be a public professional account.
ER Photoshoot	ER's own photoshoot material is the gold standard: directly consented, consistently lit, known style and product metadata. These assets are the first entries in the verified style library and the AI eval set. Cliff shared the Sep 24 photoshoot video as a reference point.	Coordinate with Cliff and Saige on asset release. Treat all ER photoshoot material as Class A data — never shared externally, never used outside the Avalon build scope. Priority source above all others.

Positive Framing Reference

When copy drifts into generic AI product language, defensive framing, or tone that doesn't match the community, redirect it using the pairs below. The right column is always the approved direction.

Avoid This Framing	Use This Instead	Why It Matters
"Try on a hairstyle with AI."	"See that style on yourself — your face, your skin, your texture."	Generic AI framing erases the emotional promise. Specificity is the brand's differentiator.
"Our advanced AI engine generates..."	"Avalon shows you what the style would actually look like on you."	Technology-first copy creates distance. The product is about seeing yourself, not the engine behind it.
"Explore hundreds of hairstyle options."	"Find a verified style that works for your texture, your density, and your life."	Scale claims feel impersonal. Precision and fit are the value proposition.
"Share your look."	"Show your stylist exactly what you're going for before you sit down."	Social sharing is a secondary action. The primary value is the conversation it enables with a professional.
"Powered by machine learning."	"Built specifically for textured hair. Evaluated by women with 4A–4C coils before anything ships."	ML is table stakes. The brand moat is the eval suite and consented dataset, not the underlying technology type.
"Beauty app for natural hair."	"A visualization tool built for the styles your stylist actually does."	"Natural hair" as a category unintentionally excludes install styles, locs, and protective styles. Specificity wins.
"Discover your next look."	"Know before you book. Know before you sit."	Discovery framing is generic. Avalon's promise is informed decision-making with real stakes — not casual browsing.
"Instant AI results."	"A verdict you can trust — because it was trained on your hair type, not someone else's."	"Instant" signals commodity speed. Avalon's edge is accuracy and specificity, not turnaround time.