AI Out-of-Stock Assistant: Alternative Product Recommender

Out-of-stock products kill sales momentum. When a customer wants a specific item and finds it unavailable, 70-80% abandon immediately without exploring alternatives. They leave to find the product at a competitor or simply forget about the purchase entirely. Support teams can't manually catch every OOS inquiry fast enough, and static "notify me when back in stock" buttons convert poorly. Each stockout represents not just one lost sale, but the potential loss of a customer relationship before it even starts.

Zipchat's Out-of-Stock Alternatives ability recovers these lost sales by instantly recommending comparable in-stock products when customers inquire about unavailable items. You upload catalog guidance to your knowledge base explaining which products are similar based on features, price points, style, or use case. When a customer asks "Do you have the blue running jacket in medium?" and it's out of stock, the AI immediately responds: "The blue running jacket in medium is currently out of stock, but I have 2 great alternatives: our navy performance jacket (similar fit, $5 less) or the teal windbreaker (same features, different shade)." The response is instant and product-specific.

Unlike generic "browse our catalog" suggestions that customers ignore, this ability provides curated alternatives with clear reasoning. The AI explains why each suggestion works as a replacement, highlighting similar features, comparable pricing, or better availability. You can configure the AI to offer a discount code (5-15% off) on alternatives to incentivize the switch, turning a stockout disappointment into an attractive deal. The AI can also proactively trigger on product pages when items show as OOS, catching customers before they leave.

Merchants using this ability recover 35-50% of potential OOS lost sales and see 40-55% reduction in stockout-related cart abandonment. For stores with frequent inventory turnover or seasonal stockouts, this converts 15-25 additional sales weekly that would have been lost. The difference between a customer leaving empty-handed and purchasing an alternative often comes down to a helpful suggestion at exactly the right moment.

Popular Sneaker Sold Out in Customer's Size

A customer messages at 6:18 PM looking for a specific product: "Do you have the Air Flow sneakers in size 10? I've been wanting these for months."

The AI checks inventory and finds size 10 is out of stock. It searches the knowledge base for alternatives and responds: "The Air Flow sneakers in size 10 are currently out of stock (we expect a restock in 3-4 weeks). But I have two great alternatives in size 10 right now: 1) CloudStride runners (same cushioning technology, $15 less, available in gray or black) 2) VelocityMax trainers (similar design, better ankle support, same price). Both have the breathable mesh you loved about the Air Flows. Want to see photos of either?" Customer asks to see CloudStride photos and purchases within 8 minutes.

A human agent would take 5-10 minutes to check inventory, search for similar products, and craft a recommendation. By that time, the customer has likely closed the chat and gone to a competitor's site. The AI provides instant, specific alternatives with clear value propositions, capturing the sale while customer intent is highest.

Seasonal Item Out of Stock with Discount Incentive

A customer browsing on Instagram DM at 2:47 PM asks: "Is the floral summer dress still available in small?"

The AI checks stock status and sees it's sold out. It responds: "The floral summer dress in small sold out yesterday (it was super popular!). I found two similar options in small: 1) Botanical print sundress (same fit and length, $48 vs $52) 2) Garden party dress (similar style, adjustable straps, $55). Since your first choice is unavailable, I can offer you 10% off either alternative with code SUMMER10. Both ship today if you order in the next few hours." Customer appreciates the discount and purchases the botanical print dress immediately.

The discount code transforms disappointment into opportunity. The customer feels valued despite the stockout, and the time-sensitive shipping detail creates urgency. A support agent might not have authority to offer discounts or might need manager approval, causing delays. The AI acts instantly with your pre-approved compensation parameters, recovering a sale that had 80% chance of being lost.

How does the AI know which products are good alternatives?

The AI uses your knowledge-base to map products to their alternatives. Make sure your product descriptions are detailed, so the AI can know product similarities in detail.

Should I always offer a discount on alternatives or only sometimes?

You can decide to let the AI decide what to recommend, or you can, for your top sellers, prompt Zipchat about which alternatives to recommend, based on products availabilities and margins.

What if none of my alternatives are in stock either?

The AI will inform the customer that similar items are also currently unavailable and offer alternatives: "Unfortunately, our similar styles are also out of stock right now. I can add you to our restock notification list (we expect inventory in 2-3 weeks), or I can show you items from a different category that might work. What would you prefer?" You can configure the AI to suggest cross-category alternatives if direct substitutes aren't available, or to collect email addresses for restock alerts. Honest communication about availability prevents customer frustration better than repeatedly suggesting unavailable products.

Can the AI proactively suggest alternatives before customers ask?

Yes, with proper configuration. You can set the AI to trigger proactively on OOS product pages: when a customer lands on a page showing "out of stock," a chat prompt appears: "I noticed this item is currently unavailable. Would you like me to suggest 2-3 similar in-stock alternatives?" This catches customers at the moment of disappointment before they bounce. Some merchants see 60-70% engagement rates on these proactive prompts because customers are actively problem-solving and appreciate immediate help without needing to ask.

Does this work across all product categories or just simple substitutions?

This works for any product type where alternatives exist. Fashion items can be substituted by color, size, style, or season. Electronics have newer models or comparable specs. Supplements have similar formulations or ingredients. The key is comprehensive knowledge base documentation. For complex products (custom configurations, made-to-order items), you can configure the AI to explain uniqueness: "This is a custom piece with no direct alternatives, but I can connect you with our design team to create something similar." The AI adapts recommendations based on product complexity and substitutability you define.

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