Discount Lookup and Active Promotions: How Alhena AI Answers Every Deal Question in Real Time

The Promo Code Question Your AI Can't Answer

Sixty-two percent of online retail consumers search for a promo code before completing a purchase, according to Promo Code Network's 2026 data. That means well over half your audience are actively looking for deals. When they type "do you have any discounts?" into your chat widget, what happens next determines whether you earn the sale or lose it.

Most AI chatbots answer promo questions from static FAQ content. The problem: your marketing team launched a new campaign this morning, expired one last night, and changed the minimum spend on a third. The FAQ page hasn't caught up. The AI gives a wrong answer, the shopper tries a dead code at checkout, and you lose the sale and earn a support ticket.

Alhena AI handles this differently. Two tools inside the Product Expert agent connect directly to your ecommerce platform and pull live discount data at the moment a customer asks. No stale content. No guessing. This post will help you learn exactly how they work, what data they return, and how to set them up.

Two Tools, Two Jobs: Lookup Discount Code and Active Promotions

Alhena's discount intelligence sits inside the Product Expert agent as two distinct tools, each built for a different type of customer question.

Lookup Discount Code handles specific code questions. A customer pastes SAVE20 into the chat and asks, "Is this still valid?" or "Why isn't this working?" The tool queries your ecommerce platform by code, retrieves the full details, and the AI builds a customer-friendly answer from the result.

Active Promotions handles broad deal discovery. A shopper asks, "Do you have any sales right now?" or "Are there free shipping offers?" The tool pulls every active discount from your store, and the AI summarizes the available deals.

The distinction matters. One is a targeted lookup by code. The other is a browse of all live deals. Together, they cover the two most common shapes of promotion questions: "Tell me about this code" and "Show me all your deals."

How This Differs from Promo Stacking Logic

If you've read our promo stacking logic post, you might wonder where the line is. The short version: Discount Lookup and Active Promotions form the data layer. They tell the AI what discounts exist, whether they're active, and what conditions apply. Promo stacking logic is the reasoning layer. It decides whether two or more deals can combine in the same cart. You need the data layer first. Without knowing what a code actually offers, the AI can't reason about whether it stacks with something else.

What the AI Retrieves from Shopify

For stores running on Shopify, Alhena reads discount data through the Shopify Admin GraphQL API using the read_discounts scope. It’s a read-only connection. Alhena never creates, modifies, or deletes discounts.

When a customer asks about a specific code, Lookup Discount Code returns:

• Whether the code exists in the store
• Discount title and discount type (percentage, fixed amount, free shipping, BOGO)
• Active or inactive status
• Summary and short summary text
• Start date and end date
• Usage limit and times used
• Whether it applies once per customer
• Percentage or fixed amount value
• Minimum subtotal or quantity requirement
• Whether it combines with product, order, or shipping discounts

That last field is what powers the stacking logic in a follow-up question. But for the initial lookup, the customer gets a direct answer: "Yes, SAVE20 gives you 20% off orders over $75. It's active until June 30 and can be combined with free shipping offers."

When a customer asks about current deals, Active Promotions lists all active discount nodes from Shopify, including percentage discounts, fixed amount discounts, free shipping, buy-X-get-Y, and app-created discounts. For each, it returns the promotion title, type, status, summary, start date, and end date.

What the AI Retrieves from BigCommerce

For BigCommerce stores, Alhena connects through the Marketing read-only API scope. The data structure is different from Shopify, but the customer experience is the same, creating consistent shopping experiences across platforms.

Lookup Discount Code checks coupons by code and returns:

• Coupon name and code
• Coupon type and amount
• Enabled or disabled status
• Minimum purchase requirement
• Expiration date
• Number of uses, max uses, and max uses per customer

Active Promotions lists all enabled coupons from the BigCommerce Coupons API, returning the name, code, type, amount, minimum purchase, and expiry for each.

The AI normalizes these different data formats into a consistent, natural-language response. A customer on a Shopify store and a customer on a BigCommerce store both get the same quality of answer. They don't see API fields. They see, "This code gives you $15 off orders over $50, and it's valid until Friday."

What a Real Conversation Looks Like

Here's how a discount question flows through Alhena's multi-agent architecture, step by step.

Scenario 1: "Is SAVE20 Still Valid?"

A shopper types "Is SAVE20 still valid?" into the chat widget. Alhena's planner routes the question to the Product Expert agent, which recognizes this as a discount code question and calls the Lookup Discount Code tool. The tool queries the Shopify Admin GraphQL API for code SAVE20. Shopify returns the discount record: 20% off, active, minimum $75 subtotal, expires June 30, combines with shipping discounts but not other product discounts.

The AI responds: "Yes, SAVE20 is active." It gives you 20% off your order when you spend at least $75. It's valid until June 30. You can use it together with free shipping offers, but it can't be combined with other product discounts."

That's a grounded, accurate answer built from live store data. No hallucination risk.

Scenario 2: "Do You Have Any Sales Right Now?"

A different customer asks, "Any deals going on?" The planner routes to Product Expert, which calls Active Promotions. The tool returns three active discounts: a sitewide 15% off sale, free shipping on orders over $50, and a buy-two-get-one-free deal on a specific collection.

The AI responds, "We have three deals running right now: 15% off sitewide with code SPRING15, free shipping on orders over $50 (applied automatically at checkout), and buy two get one free on our Summer Collection. "Want me to help you find something?"

The shopper didn't have a code. They were finding deals through conversation. The AI surfaced active offers and moved toward a purchase.

Scenario 3: "Why Isn't WELCOME10 Working?"

A frustrated customer pastes a code that failed at checkout. The Lookup Discount Code tool retrieves the record and finds the code is valid but has a $40 minimum subtotal requirement. The shopper's cart total is $32.

The AI responds: "WELCOME10 is a valid code for 10% off, but it requires a minimum order of $40. Your current cart is under that threshold. Would you like me to suggest an item to add?"

Instead of a dead-end "invalid code" message, the customer gets a specific reason and a path to still use the discount. That's a conversion moment most chatbots miss. It's also the kind of answer that reduces support tickets because the customer never needs to email your team.

Why Live Data Beats Static FAQs for Promotions

The average working promo code lasts about 7 days, according to a 2026 analysis of 238,000 unique promo codes. Marketing teams at online retailers launch campaigns, A/B test offers, run flash sales, and expire codes constantly. A help center article that says "use code SUMMER25 for 15% off" becomes wrong the moment that campaign ends.

Fifty percent of shoppers report that promo codes found online only work 10-50% of the time. That's a trust problem. When your own AI gives the same stale answer as a random coupon site, you lose credibility with your customers.

Alhena's approach is different because the AI doesn't store promotion data. It queries your e-commerce platform at the moment the question is asked. If your marketing team disabled a code five minutes ago, the AI already knows. If they launched a flash sale this morning, the AI can surface it immediately.

This matters most during high-velocity periods like Black Friday and Cyber Monday, when promotions and purchase incentives can change multiple times per day. A static FAQ approach simply can't keep up. A live data connection can.

The Impact on Support Ticket Volume

"Why isn't my code working?" is one of the most common ecommerce support questions. When the AI can diagnose the exact reason (expired, minimum not met, already used, wrong product category), the customer gets an answer instantly instead of opening a ticket and waiting hours. Brands using Alhena AI have seen results like Crocus's 86% deflection rate and Puffy's 63% automated inquiry resolution, with promo-related questions being among the most likely to automate because they have clear, data-driven answers.

Setting Up Discount Lookup and Active Promotions

Getting these tools running takes minutes, not days. Here's the setup process:

1. Connect your ecommerce platform. For Shopify, install the Alhena app and authorize the read_discounts scope (along with your other scopes). For BigCommerce, generate a store-level API token with the Marketing read-only scope.
2. Enable the tools in AI Settings. Navigate to AI Settings, then Agents. You'll see Lookup Discount Code and Active Promotions as toggleable tools under the Product Expert agent. Enable one or both.
3. Test with a real code. For example, try testing a code you know is active and one that’s expired. Open the chat widget and ask "is [your code] valid?" Verify the AI returns the correct details from your store.
4. Test deal discovery. Ask "what promotions are running right now?" Verify the response matches the active discounts in your Shopify or BigCommerce admin.

No developer resources needed. No custom API work. No manual tasks for your CX team. The connection uses the same integration that powers Alhena's product search, inventory checks, and catalog browsing. If your store is already connected, enabling the discount tools is a two-click operation.

Alhena deploys in under 48 hours across all channels, including Instagram DMs and WhatsApp. The discount tools work identically across web chat, email, social, and voice. A customer asking about a promo code on Instagram gets the same live, verified answer as someone using the website chat widget.

What These Tools Don't Do (And Why That's a Feature)

Being clear about boundaries is part of building trust, both with merchants and their customers.

Discount Lookup and Active Promotions are read-only tools. They report what your e-commerce platform exposes through its API. They do not:

• Create new discount codes
• Apply a code to the customer's cart
• Override Shopify or BigCommerce checkout validation
• Simulate every possible cart-specific eligibility rule
• Generate or invent promotional offers

Final checkout eligibility always belongs to the ecommerce platform. If Shopify's checkout engine rejects a code because of a customer-segment restriction that isn't exposed through the API, the AI won't override that. It reports what the API exposes and lets the checkout engine handle the rest.

This read-only design is intentional. As we covered in our gift cards and store credit deep dive, keeping the AI on the read side of the boundary means no accidental over-discounting that erodes profit margins, no phantom codes, and no compliance risks. Your brand’s marketing team stays in full control of what discounts exist. The AI just makes sure customers get accurate information about them.

From Discount Questions to Revenue

Promotion questions aren't just support tickets. They're buying signals. A shopper asking "do you have any deals right now?" is actively looking for a reason to purchase. A shopper asking "is this code still valid?" is at the finish line.

When Alhena's AI answers these questions accurately, it does more than deflect a ticket. It removes a purchase barrier. Brands like Tatcha have seen a 3x conversion rate and Victoria Beckham saw a 20% AOV increase with Alhena's AI, because the AI doesn't just answer questions; it guides shoppers toward completing purchases.

The Discount Lookup and Active Promotions tools fit into this revenue-first approach. When a shopper's code fails because they haven't met the minimum spend, the AI doesn't just explain the requirement. It can suggest relevant products to reach the threshold. When a shopper asks about deals, the AI doesn't just list codes. It can recommend products within those promotions using Alhena's product search capabilities.

Every promotion question becomes a guided selling moment with built-in personalization instead of a dead-end FAQ response. That's the difference between an AI built for support and an AI built for ecommerce.

Key Takeaways

• Two specialized tools inside the Product Expert agent handle all discount and promotion questions: Lookup Discount Code (for specific codes) and Active Promotions (for deal discovery).
• Live data, not cached content. The AI queries your Shopify or BigCommerce store at the moment the customer asks, so answers are always current.
• Shopify and BigCommerce both supported with platform-specific API connections (GraphQL for Shopify and Marketing API for BigCommerce).
• Read-only by design. The tools report discount data. They don't create, modify, or apply codes. Checkout validation stays with your platform.
• Separate from promo stacking. Discount Lookup provides the data layer. Promo stacking logic provides the reasoning layer for combining discounts.
• Setup takes minutes. Enable the tools in AI Settings, test with real code, and you're live across all channels.
• Promotion questions are buying signals. Accurate answers turn "do you have any deals?" into completed purchases, not abandoned carts.

Ready to give your AI the ability to answer every discount and promo question with live store data? Book a demo with Alhena AI or start for free with 25 conversations.

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