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Pre-sale product Q&A and objection handling

The questions that stop purchases — shipping, returns, fit, compatibility, stock — answered at the decision point, then closed back toward the cart.

Next best thingBehavioral triggerChatIn-appVoiceE-commerce & Retail

What it does

A shopper staring at a product page with one unanswered question doesn't open a ticket — they leave. Will it arrive in time, does it run small, will it work with what I already own: every one of these is a purchase blocked by missing information, and every one is answerable from data you already hold. The agent meets the shopper on the product page, answers from catalog, policy, and live stock, and turns the answer into the next step: a comparison, a size recommendation, an add-to-cart.

How it works

  1. 1
    Trigger. the shopper opens the chat, taps a per-product question chip on the product page, or asks by voice; the product and session context arrive with the question.
  2. 2
    Decision. the agent grounds its answer in the catalog, live inventory, shipping and returns policy, and size or compatibility charts — and draws on persistent memory of what it already knows about this shopper.
  3. 3
    Action. a concrete answer with a path forward — a side-by-side comparison, a size recommendation, a stock check, or an add-to-cart, shown in chat or in-app.
  4. 4
    Follow-through. questions the agent can't ground hand off to a human with full context; conversions from these conversations are measured against a holdout, so the lift is proven rather than assumed.
Example
AgentDeciding between the two? Most shoppers ask about fit, shipping, and returns for this jacket — happy to cover any of those.
CustomerDoes it run small? I'm between two sizes.
AgentIt runs slightly small, so between sizes I'd go up — and returns are free if the fit isn't right. Want me to add the larger one to your cart?

Configuration

How the agent is wired for this use case.

Triggerthe shopper opens the chat, taps a per-product question chip, or asks by voice on the product page — the product and session context arrive with the question from the messaging channel.
Tools & actions
  • Messaging channel · receive the question (chat, in-app, or voice) and return a grounded answer with a path forward.
  • Knowledge base · ground answers in the catalog, size and compatibility charts, and shipping/returns policy.
  • OMS / inventory system · run a live stock check before answering availability.
  • CRM · read persistent memory of what is already known about this shopper.
  • Cart API · add the recommended size or item once the shopper confirms.
Autonomyanswers run unattended, grounded only in catalog and policy — no improvised claims or invented discounts; the add-to-cart is the shopper's confirmation.
Channelschat · in-app · voice
Escalationa question the agent can't ground hands off to a human with full context when confidence is low.

What you need

The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.

Signals

product-page session context, chat opens and question-chip taps, add_to_cart events

Data

product catalog with attributes, size and compatibility charts, live inventory, shipping and returns policies

Guardrails

answers grounded only in catalog and policy (no improvised claims or invented discounts); escalation to a human when confidence is low; holdout measurement on conversion claims

Metrics it moves

  • conversion-rateup: blocked purchases get unblocked at the moment of doubt, measured against a holdout
  • return-ratedown: right-size and right-fit guidance before the order means fewer size-related returns
  • revenue-per-conversationup: every answered objection is steered back toward the cart, and attribution is per conversation

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Stock-out save with alternatives

when the stock answer is "not available"

See it on your own customer journey

Bring one drop-off, one churn cliff, or one silent segment. We will show you what a proactive agent with memory and judgment does with it.

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