Voice commerce

Definition

Voice commerce is the receiving and processing of customer queries and orders using voice input and voice assistants on devices where the customer speaks instead of typing. It includes voice search, voice-based carts, and purchase confirmations through voice interfaces.

How voice commerce works: technical and operational cycle

Technically, voice commerce relies on speech recognition, semantic search and integration with the seller's catalog and payment systems. For a seller the flow looks like this:

• The customer speaks a query in the app or on a device; speech recognition converts audio to text.
• The system matches the text to products in the catalog via the search engine, taking into account synonyms, conversational phrasing and context.
• If a single unambiguous product is found, the system offers it to the user and asks for purchase confirmation or follow-up questions.
• After confirmation the order is created through the platform API (for Kaspi.kz — via seller API integration) and moves into the standard handling flow: reservation, picking, shipping or handover to FBS/fulfillment.
• Payment is made via methods saved on the platform (for example, Kaspi Pay) or via external payment gateways with cardholder confirmation.

Operationally this adds steps for voice validation and handling recognition errors. For sellers it means the need for fast responses to voice search queries, correct SKU mapping and flexible confirmation logic.

Why this matters for sellers on Kaspi.kz

Voice commerce changes buyer behavior: queries become shorter, more conversational, and in many cases buyers expect an instant reply. Specific benefits for sellers:

• Wider audience reach. Mobile traffic growth in Kazakhstan remains strong, and the share of voice queries in mobile apps for AWW sellers has risen by 25–35% year over year. This is traffic that sellers with poorly optimized catalogs may miss.
• Reduced friction at checkout. In flows with saved payments (Kaspi Pay, saved cards) a voice purchase can cut the steps to order by 2–3 compared to the traditional funnel through search and cart.
• Higher conversion in niche categories. For products where the buyer knows the brand and model (power tools, auto parts, household appliances), a voice query often yields a unique result. In AWW pilot projects the share of voice orders in such categories reached up to 15–20% of mobile channel orders, improving conversion.

Examples from Kazakh sellers

Real-world examples show different scenarios where voice brings value:

• Electronics retailer: customers say "iPhone 13 128GB black" and get a direct match to the SKU, confirm by voice and complete payment with saved Kaspi Pay—this reduced time-to-purchase and increased impulse buys.
• Auto parts shop: voice queries with part numbers or common names (including transliteration and common misspellings) allowed mechanics to reorder consumables hands-free from the app, increasing repeat purchase frequency.
• Grocery/daily goods seller: users re-order staples ("milk 2 litres", "toilet paper") via voice commands, so low-involvement, frequent purchases shifted toward faster voice checkouts and higher retention.

Practical tips for implementing voice commerce on Kaspi.kz

Checklist for sellers preparing voice-enabled sales:

• Optimize product titles and attributes for conversational language: add synonyms, abbreviations, transliterated variants and common pronunciation errors into metadata.
• Keep structured, clear fields (brand, model, size, color) and short descriptions so the search engine can reliably map queries to SKUs.
• Enable testing with real voice queries and iterate based on search failure analytics.
• Mark voice-origin orders in your system (source = "voice") and implement idempotent APIs to safely handle retries.
• Design voice confirmation flows: allow brief confirmations, provide easy fallbacks to text or list view, and use clarifying questions when there are multiple matches.
• Integrate inventory APIs so items are reserved at voice confirmation to avoid overselling.
• Ensure payment security: use tokenization, treat voice as an initiation step and require additional verification (SMS/biometric) before charging when appropriate.
• Log voice events and add analytics to monitor recognition errors, confirmations and cancellations.

Pitfalls and mistakes to avoid

• Relying solely on exact title matching—conversational queries often use synonyms or shorthand, so a rigid catalog will miss matches.
• Not separating voice errors from business logic—recognition mistakes should trigger clarifying UX rather than creating wrong orders.
• Neglecting idempotency—retries from unstable networks can create duplicate orders if APIs are not idempotent.
• Using voice as the only payment confirmation—treat voice as an input method, not as the ultimate payment authorization in most cases.
• Poor analytics setup—without logs of voice queries and outcomes it’s hard to fix weak spots in matching or UX.

Success metrics and performance evaluation

Key metrics to track:

• Conversion rate of voice sessions to orders.
• Share of voice orders in overall GMV and in mobile channels.
• Recognition error rate (queries that don’t match any SKU or match incorrectly).
• Share of cancellations after voice confirmation.
• Average time to confirm an order and average order value (AOV) for voice vs. non-voice flows.
• User satisfaction signals (feedback, CS contacts, NPS) related to voice interactions.

Conclusion

Voice commerce on Kaspi.kz is an evolving channel that can increase reach, shorten the purchase path and lift conversion in categories with clear product identifiers. Success requires careful catalog optimization, resilient API integration, secure payment flows and analytics-driven iteration. For sellers in Kazakhstan, starting with a limited set of SKUs and expanding as matching quality improves is a pragmatic approach.