Recommended: Bright citrus cocktail
Fits: dinner party, easy to mix, not too sweet
Bottle: in stock in aisle 7
Why: matches your flavor preferences and available inventory
Retail
AI product guidance for retail stores
Turn a kiosk into your always-available product expert. Shoppers describe what they need, and Biscuit recommends the right product, explains why it fits, and helps them find it in the store.
Biscuit AI combines conversational guidance, semantic product understanding, catalog data, inventory signals, brand rules, in-store routing, and real-world analytics. The result feels helpful, not pushy.
- Product recommendations
- Inventory-aware guidance
- Brand and catalog logic
- Staff handoff
Product guide
What are you shopping for today?
I need a bottle for margaritas.I want something citrusy, not too sweet.What cocktail should I make for a dinner party?Show me what is in stock here.
- Ask
- Match
- Recommend
- Locate
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Shoppers do not think in SKUs
Most shoppers do not walk into a store with the perfect product name in mind. They come with a situation.
"I need a gift." "I'm making cocktails tonight." "I want something that works with what I already own." "I need the cheaper one, but not the bad one." "I have sensitive skin." "I need this today."
That is hard for a shelf tag or search box to handle. Biscuit lets shoppers explain the goal, then turns that messy intent into a practical recommendation.
What the kiosk helps shoppers do
Biscuit gives the aisle a product expert that is always available, always on-brand, and connected to the product data that matters.
Find the right product
Ask a few questions, understand the shopper's goal, and recommend products that fit.
Compare options
Explain tradeoffs in plain language: price, features, flavor, size, compatibility, ingredients, or use case.
Check what is available
Prioritize products in stock at the current location, or suggest the closest available alternative.
Explain why it fits
Give the shopper a clear reason, not just a product name.
Build a basket
Recommend accessories, ingredients, bundles, or next-step items when they genuinely help.
Send them to the shelf
Show aisle, bay, shelf, QR handoff, pickup path, or staff handoff based on the store setup.
How Biscuit makes better recommendations
Good product guidance is not just search. It is reasoning across intent, context, catalog, availability, and brand rules.
- 01
Understand the occasion
The shopper describes the job: host a dinner, fix a problem, buy a gift, mix a cocktail, compare products, or choose fast.
- 02
Ask the right follow-ups
Biscuit asks only what matters: budget, taste, effort level, compatibility, ingredients, preferences, constraints, timing, or recipient.
- 03
Match against the catalog
The kiosk reasons over product descriptions, attributes, recipes, reviews, merchandising rules, and approved brand content.
- 04
Check availability
Recommendations are grounded in what the store can sell: in-stock SKUs, location data, substitutions, and approved alternatives.
- 05
Explain and route
The kiosk explains the fit, then helps the shopper find it, scan a QR code, build a list, or ask staff for help.
Featured example: Diageo cocktail guidance
For Diageo, Biscuit turns the drinks aisle into a guided cocktail and bottle-selection experience.
Instead of asking shoppers to already know the bottle, recipe, or brand they want, the kiosk starts with the occasion. A shopper might want something light, easy, and citrus-forward for a dinner party. Biscuit can ask a few follow-ups, suggest a suitable cocktail style, and explain why it fits.
Once the shopper chooses the cocktail direction, Biscuit helps them pick the right bottle to buy. The recommendation can reason over flavor notes, recipe fit, price range, brand rules, bottle size, nearby shelf location, and what is actually available in that store.
If the first-choice item is out of stock, Biscuit can recommend the next best available option instead of sending the shopper to an empty shelf.
Featured example
From occasion to shelf
- I'm hosting friends tonight.
- I want a simple summer cocktail.
- I like citrus, but not too sweet.
- I need something for margaritas.
- What can I make with what is in stock here?
- Recommended bottle
- Why it fits
- Cocktail recipe
- Ingredient checklist
- In-stock status
- Aisle or shelf location
- QR recipe card
- Staff handoff
- Responsible-drinking reminder
Beverage alcohol flows should include age gating, responsible-drinking reminders, and local compliance rules.
Use cases beyond beverage
The same product-guidance model works anywhere shoppers need confidence before buying.
Beauty and skincare
Guide shoppers by skin goal, sensitivity, routine, ingredients, budget, and product availability.
Electronics and appliances
Compare features, compatibility, warranties, accessories, and setup needs in plain language.
Grocery and meal planning
Recommend ingredients, substitutions, pairings, recipes, and aisle paths based on what the shopper wants to make.
Specialty retail
Help with gifts, premium products, technical differences, sizing, care, and product education.
Home and lifestyle
Match products to room, style, use case, dimensions, materials, and store availability.
Brand activations
Turn a display into an interactive product expert that tells the brand story and guides a confident choice.
A useful product expert for every stakeholder
The kiosk helps shoppers make better decisions, but the value extends across the store and brand team.
Shoppers
They get a helpful answer, a clear reason, and a product they can actually find.
Retailers
The store gets better assisted selling without needing a specialist in every aisle at every moment.
Brands
Brands can tell the product story, guide use cases, and influence decisions closer to the shelf.
Store staff
Staff can step in when needed, with more context and fewer repetitive questions.
Merchandising teams
Interaction data shows what shoppers ask for, what they consider, where availability breaks the journey, and which use cases drive demand.
Clients
Deployment model
A product-guidance kiosk works best when the AI, catalog, inventory, and store experience are designed together.
Placement
Put the kiosk where shoppers already pause: high-consideration aisles, branded displays, endcaps, service counters, tasting zones, or category destinations.
Product data
Connect approved product descriptions, attributes, pricing, promotions, recipes, compatibility rules, ingredients, reviews, FAQs, and brand content.
Inventory and location
Use store-level availability, aisle data, shelf location, substitutions, and fallback rules so the kiosk recommends products the shopper can actually buy.
Recommendation logic
Configure goals such as best fit, availability, margin, promotion, bundle, brand priority, substitution, or staff handoff.
Interface
Support touchscreen, voice, QR handoff, product cards, comparison tables, recipe cards, shopping lists, and associate alerts.
Analytics
Track what people ask, what they consider, what gets recommended, what is unavailable, and which questions create handoffs.
Responsible and safe recommendations
Product guidance should be helpful without overstepping. For regulated categories, Biscuit should follow the rules of the category, the retailer, and the brand.
For beverage alcohol, that means age-appropriate access, responsible-drinking reminders, no targeting minors, no medical or health claims, no pressure toward excessive consumption, and clear local compliance rules.
For other categories, the same principle applies: the kiosk should explain, guide, recommend, and hand off when a question needs a person, a professional, or an approved system.
What to measure
The kiosk should show what shoppers wanted, what they considered, and where the store experience helped or broke down.
- Sessions by location
- Top shopper intents
- Product categories explored
- Recommendation acceptance
- Out-of-stock recommendation attempts
- Substitution rate
- QR recipe or shopping-list sends
- Staff handoff rate
- Average session length
- Languages selected
- Abandoned sessions
- Product comparison views
- Bundle or accessory recommendations
- Customer satisfaction
- Content gaps and failed intents
Do not claim conversion lift, basket lift, revenue lift, or sales impact unless verified data is provided.
Why Biscuit AI
Biscuit AI is built for the point of decision. The platform combines a physical kiosk, conversational AI, product reasoning, catalog and inventory context, brand configuration, multilingual support, and analytics from real-world interactions.
For product guidance, that means the kiosk can do more than answer questions. It can understand what the shopper is really trying to buy, recommend something available, explain the match, and help teams learn what shoppers want in the aisle.
Intent-first
Starts with the shopper's goal, not a search box or SKU list.
Inventory-aware
Recommends products that fit the request and can actually be found or purchased.
Built for the aisle
Designed for real stores, displays, staff handoff, QR flows, and measurable shopper behavior.
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Give every aisle a product expert
Biscuit AI can help design the product-guidance flow, connect catalog and inventory data, configure recommendation logic, and measure what shoppers need in the real world.