Master Alhena AI with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Book a demo through the Alhena website to discuss your specific use case and requirements Complete the 48
hour integration process with your ecommerce platform and data sources Train the AI on your brand voice, product catalog, and customer service policies during onboarding
💡 Quick Start: Follow these 2 steps in order to get up and running with Alhena AI quickly.
Explore the key features that make Alhena AI powerful for customer support agents workflows.
Every AI response is constrained to information sourced from your verified product catalog, order management system, and approved knowledge base. The system will not generate speculative or fabricated answers; when it lacks verified information to address a query, it escalates to a human agent. This is particularly critical for ecommerce, where incorrect product specifications, pricing errors, or policy misinformation can lead to returns, chargebacks, and brand damage.
Functions as an always-available sales consultant that interprets natural-language queries ('waterproof hiking boots under $200 for wide feet') and returns relevant product recommendations from your catalog. The assistant guides customers through product comparison, answers specification questions in real time, and supports checkout completion. Published case studies report conversion rate improvements of 20–300% and average order value increases of 20–38%.
Tracks the revenue impact of every AI conversation, linking specific product recommendations and interaction patterns to completed purchases. This granular attribution enables merchants to identify which AI-driven conversation flows generate the most revenue and optimize accordingly. Based on our analysis of 870+ AI tools, this level of per-conversation revenue tracking is uncommon among customer support AI platforms, most of which report only deflection metrics.
Resolves approximately 80% of incoming customer inquiries without human intervention, covering order status lookups, returns initiation, shipping updates, product information, and policy questions. Unresolved or sensitive cases are escalated to human agents with full conversation context and customer history attached, eliminating the need for customers to repeat themselves after a handoff.
A newer 2026 capability that optimizes your product catalog and brand content for discovery by external AI assistants such as ChatGPT, Gemini, and Perplexity. As consumers increasingly use AI tools for product research and purchase recommendations, this feature positions brands to capture traffic from conversational AI search—an emerging channel that operates differently from traditional SEO and paid advertising.
Alhena constrains its AI responses to information sourced exclusively from your verified product catalog, order management system, and brand knowledge base. Unlike general-purpose language models that generate answers from broad training data, Alhena's architecture only surfaces facts it can trace back to your approved content. If the AI cannot find a verified answer to a customer's question, it escalates to a human agent rather than guessing. This approach trades some conversational flexibility for factual accuracy, which is critical in ecommerce where incorrect product claims can cause returns, chargebacks, or legal issues.
Alhena advertises a sub-48-hour setup timeline for standard Shopify integrations, and the process is designed to be completed without dedicated developer resources. The platform connects to your existing product feed, order management system, and any knowledge base or FAQ documentation you maintain. You will need to provide brand voice guidelines and review the AI's initial responses during a training period, but the technical integration itself is handled through pre-built connectors rather than custom code. More complex setups involving multiple sales channels, custom APIs, or legacy systems may take longer.
The $1.10 per-conversation fee covers a complete customer interaction from start to resolution, whether that involves product discovery, order status checks, returns processing, or a combination within a single session. This usage-based model means you pay proportionally to the volume of AI-handled interactions rather than committing to a fixed monthly seat count. For businesses with lower support volumes, this can be more cost-effective than subscription platforms, but high-traffic stores should model their expected conversation volume carefully, as costs scale linearly. Enterprise plans with different pricing structures are available for larger deployments.
Alhena handles a range of support tasks beyond basic FAQs, including real-time order status lookups, initiating returns and exchanges, processing shipping inquiries, and providing detailed product comparisons based on customer needs. The platform claims to autonomously resolve approximately 80% of incoming customer inquiries, with reported customer satisfaction scores between 85% and 90%. For the remaining 20%—cases that involve edge situations, emotional customers, or policy exceptions—the system escalates to human agents with the full conversation transcript and relevant context attached, so the agent does not have to ask the customer to repeat information.
AI visibility optimization is Alhena's newer offering that focuses on increasing the chances that external AI assistants—such as ChatGPT, Google Gemini, and Perplexity—recommend your products when consumers ask for shopping advice through those platforms. This is distinct from traditional SEO; it involves structuring your product data, brand content, and web presence in ways that AI models are more likely to surface during conversational product recommendations. As more consumers use AI assistants for purchase research, this channel is becoming a meaningful source of discovery traffic, and Alhena positions itself as an early mover in optimizing for it.
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Tutorial updated March 2026