Composed AI detects shopping patterns, deploys a grounded product assistant, and turns customer support transcripts into actionable ecommerce revenue signals.
The questions customers ask before buying reveal exactly what’s stopping them. Most D2C brands never see those signals at scale.
Analytics show drop-off rates. They don’t show that 34% of abandoners had an unanswered shipping question at the checkout step. The fix exists. The signal didn’t surface.
Return rates are visible in reports. The reasons aren’t. Customers return products for reasons that are often preventable — wrong size guides, missing product information, unclear delivery expectations.
Every campaign that drives traffic also drives support queries. Most D2C brands handle this by hiring more agents. The underlying questions are the same ones they answered last month.
New collections, updated sizing, changed shipping policies, seasonal promotions. Help content lags behind product reality. Customers get wrong answers.
Most ecommerce AI tools are trained on generic data, not your specific products, policies, and customer conversations. The gap between what they know and what customers ask is where revenue is lost.
Generic AI chat widgets answer questions based on broad training data. They don’t know your return window is 45 days, your sizing runs small, or your restocking timeline for a specific product.
Help articles are written once and left. Nobody monitors whether they’re answering the questions customers are actually asking. Documentation gaps cause cart abandonment.
Analytics tools measure what customers did after they decided. They don’t capture the questions customers asked — or failed to get answers to — before they decided to leave.
Composed AI connects your product catalogue, sizing guides, return policies, shipping rules, and support conversations into a unified Knowledge Base — then monitors it for the signals that reveal where revenue is being lost.
The Customer AI assistant answers from your specific product catalogue, policies, and documentation — not generic training data. Sizing, availability, shipping timelines, return policies — all accurate, all cited.
Composed AI detects patterns in your support conversations and knowledge requests: which product pages generate the most questions, which shipping questions precede cart abandonment, which size-related questions correlate with return rates.
Every unanswered question becomes a Knowledge Base gap signal. Every resolved investigation strengthens the next interaction. The system compounds your knowledge layer over time.
No ecommerce-specific tool. The same platform used across your organisation — connected to your product and customer data.
Composed AI monitors your connected sources: support conversations, product FAQ views, return records, and knowledge requests. When patterns emerge — a product page generating shipping confusion, a size guide creating return spikes, a promotion driving unsupported questions — a Signal is created with evidence and impact scoring.
Open Ask Composed and ask: 'Which product in our summer collection is generating the most pre-sale questions?' 'What are customers asking before abandoning checkout?' 'What changed in our return policy that’s driving this week’s return spike?' Every answer is traced to real conversations and knowledge sources.
Your Customer AI assistant knows your catalogue, your policies, your promotions, and your shipping rules. It answers pre-sale questions accurately, handles returns and refunds with the right policy, and escalates edge cases to a human agent with full context. AI Readiness scores every dimension of answer quality before it goes live.
Composed AI detects that the product page for a new jacket launch is generating an unusually high number of questions about sizing. Support volume on that product is 4x the brand average for a new launch. A Signal is created with evidence and assigned to the product team.
The merchandising lead opens Ask Composed: 'What sizing questions are customers asking about the jacket launch?' The answer reveals that customers are asking whether the jacket runs true to size — a question the current product description doesn’t answer.
The team adds fit notes and a size comparison chart to the Knowledge Base. Composed AI validates the update and marks the signal gap as partially resolved.
The Customer AI assistant immediately begins answering sizing questions accurately from the updated guide. AI Readiness confirms that sizing question confidence has increased significantly.
Support volume on the product page normalises. The persistent investigation thread is saved with the evidence chain, the content fix, and the outcome. Future product launches now include a sizing documentation checklist.
Customers who get accurate pre-sale answers convert at higher rates. An AI assistant that knows your product is a conversion tool, not a cost centre.
When customers get accurate sizing, shipping, and product information before purchase, return rates fall. Informed purchases are kept purchases.
Greet and assist shoppers in their native language (supporting 40+ global and Indian regional languages), while keeping backend merchant dashboards in English.
Every investigation improves the Knowledge Base. Every improvement makes the AI assistant more accurate. The more you use it, the better it gets.
Connect your product catalogue, sizing guides, return policy, shipping rules, and promotional documentation. Composed AI structures everything into a Knowledge Base.
Composed AI surfaces the first patterns from your existing support data and knowledge requests. Most D2C brands see their first actionable signal within the first session.
Configure the Customer AI assistant, test it against real pre-sale and post-purchase queries in the sandbox, and review AI Readiness scores before going live.
Every unanswered question creates a Knowledge Base gap signal. Every signal leads to an investigation. Every investigation improves the assistant. The loop is automatic.
Connect your product knowledge, detect conversion signals, and deploy an AI assistant that knows your catalogue inside out.