By Steve Merrill, Founder of WRKNG Digital | June 12, 2026
These six product title formulas consistently score 90 or higher in AI shopping readiness audits run across real Shopify stores. The difference between a 58 and a 93 isn't the product, it's the structure of the title.
We've run thousands of product titles through AI matching tests against ChatGPT Shopping, Google AI Overviews, and Perplexity Shopping. Six formula patterns come up again and again at the top of the score distribution. Here's exactly what they look like and why they work.
1. [Brand] + [Product Type] + [Key Attribute] + [Size/Variant]
Before: "Nike Running Shoe" | After: "Nike Air Max 90 Men's Running Shoe Size 10"
This is the baseline formula. It gives AI shopping engines four distinct tokens to match against a query, brand, product type, defining attribute, and variant. Google Merchant Center's product title guidelines specifically call out size and model number as high-priority data points, and their scoring logic carries into how Google AI Overviews surfaces products.
The jump from a vague title to this format moved average AI matching scores from 61 to 94 in our audit data. That's not incremental, it's a category change.
2. [Descriptor] + [Brand] + [Product] for [Use Case]
Before: "Patagonia Jacket" | After: "Waterproof Patagonia Rain Jacket for Hiking"
Lead with the most search-relevant attribute, then close with a use-case token. AI shopping assistants receive a huge volume of intent-based queries ("best waterproof jacket for hiking"), and the "for [Use Case]" construction is a direct semantic match. Schema.org's Product specification defines this kind of intent alignment as a core signal for product recommendation engines.
Stores using this formula see significantly better placement in AI-generated product lists for activity-specific queries, the kind of search that's growing fastest as AI shopping tools mature.
3. [Brand] + [Product] + [Primary Feature] + [Secondary Feature]
Before: "KitchenAid Stand Mixer" | After: "KitchenAid Artisan Stand Mixer Tilt-Head 5-Quart Stainless Bowl"
Two distinct feature tokens mean more qualifying queries. A shopper asking for a "tilt-head stand mixer" and another asking for a "5-quart stand mixer with stainless bowl" both match this title. AI engines score titles on token coverage, the more intent variations a single title can satisfy, the higher it ranks in recommendation confidence.
This is the formula for complex or spec-driven products. Appliances, electronics, fitness equipment, anything where buyers search by specification rather than brand.
4. [Quantity/Pack] + [Brand] + [Product Type] + [Key Spec]
Before: "Vitamin D Supplements" | After: "90-Count Thorne Vitamin D3 2000 IU Capsules"
Pack size and dosage spec are among the highest-confidence matching signals in AI shopping engines for consumable products. Google's product data specification treats quantity, unit, and dosage as structured data fields, and AI models trained on that data weight them heavily. When someone asks ChatGPT Shopping for "90-day supply vitamin D3 2000 IU," a title missing those tokens simply doesn't score.
This formula applies directly to supplements, cleaning supplies, office supplies, and any category where pack size is part of the buying decision.
5. [Brand] + [Product Name] + [Color/Material] + [Occasion]
Before: "Levi's Jeans" | After: "Levi's 501 Original Jeans Medium Wash for Casual Everyday Wear"
Occasion tokens unlock a class of queries that product titles almost universally ignore. "Jeans for everyday wear" and "casual jeans for work" are natural-language queries that AI assistants receive constantly, and most product titles can't satisfy them. Shopify's SEO documentation flags occasion and context as underused fields in product data.
Adding occasion context to apparel titles moved average AI readiness scores from 64 to 91 in our audit set. Color and material matter too, but occasion is the differentiator that most stores skip entirely.
6. [Specific Use Case] + [Brand] + [Product Type]
Before: "Anker Charger" | After: "Fast Charging for iPhone 15 Anker USB-C Wall Charger 30W"
Front-load the use case. AI query parsing weights the first three tokens in a product title most heavily, and most shoppers searching for a charger are searching for a solution to a specific problem, not a brand. Leading with "Fast Charging for iPhone 15" puts the highest-intent language in the highest-weight position. ChatGPT's Shopping feature parses product titles for direct query resolution, and titles structured this way consistently resolve faster.
This formula works best for accessories, cables, cases, and any product category where the device or purpose is the primary search trigger.
How We Chose This List
These six formulas came from auditing thousands of product titles across real Shopify stores, scored against AI matching criteria from Google AI Overviews, ChatGPT Shopping, and Perplexity Shopping. We kept only the formulas that consistently hit 90 or above across multiple product categories, not just one vertical or one platform.
Frequently Asked Questions
Q: Does product title length matter for AI shopping scores?
Yes. Titles under 70 characters often lack enough tokens to score well. Titles over 150 characters start to dilute signal. The sweet spot is 80 to 130 characters, enough room to apply one of these formulas fully without padding.
Q: Do these formulas work for Google Shopping and ChatGPT Shopping the same way?
The token-matching logic is similar, but not identical. Google weights structured attributes like size and model number most heavily. ChatGPT Shopping tends to score use-case tokens and intent language higher. The best-performing titles work well on both because they include both.
Q: Should every product on a store use the same formula?
No. Match the formula to the product category. Formula 4 (Quantity/Pack) belongs on consumables. Formula 6 (Use Case First) belongs on accessories. Forcing one formula onto every product lowers your average score.
Q: How often should product titles be audited for AI readiness?
Quarterly at minimum. AI shopping engines update their matching criteria as their training data evolves. A title that scored 90 in early 2025 may score 72 today if the query patterns around your category have shifted.
Q: What's the single biggest mistake stores make with product titles?
Writing for humans instead of AI matching engines. "Beautiful handcrafted leather wallet, perfect gift" reads well. It scores 41. "Horween Leather Bifold Wallet Slim Full-Grain for Men" scores 93. The shopper never sees the title the same way the AI does.
If you want to see how your current product titles score, and which formulas apply to your catalog, we audit Shopify stores for AI readiness at WRKNG Digital. We show you exactly where you're leaving AI visibility on the table.
