Pricing pages convert at low single digits because they answer two of the ten questions a serious prospect actually has. The other eight (integrations, security posture, contract terms, who else looks like us, how long onboarding takes) live in a deck, a case study, and a Slack thread the marketing team hasn't surfaced. A generic chatbot widget is worse than useless here because it confidently misquotes both the price and the integration list, and the prospect leaves with a worse impression than if no widget had loaded.

SleekAI grounds replies in the same content your sales team already references: product pages, case studies, integration directories, and any postmeta or ACF fields that carry pricing rules and discount logic. The bot answers honest scope questions, qualifies the prospect with two or three plain-language questions, and routes hot leads to the right rep via webhook or email with the full transcript attached. Display conditions let you run a different prompt for logged-in trial users than for cold visitors on the home page.

Conversation logs are stored in WordPress with the query, the grounding context, and the page URL. Filter for queries that escalated and the patterns are obvious: the integration nobody mentions on the marketing pages, the pricing rule that confuses everyone, the case study the bot reaches for most often. Each is a concrete update to the site that lifts conversion on the next quarter.

Sales bots have a credibility problem because the first wave of them shipped without grounding and confidently misquoted pricing, features, and integration lists. Prospects learned to scroll past the chat bubble within the first quarter the product was on the market, and most marketing teams quietly removed the widget by year two. A grounded sales bot is a different category of tool.

It answers from the same content the sales team already references, refuses to invent details, and hands off cleanly when the conversation needs a human. The bar to clear is honest scope, not a flashy demo. The operational win lands in two places.

First, qualified intake arrives in the CRM with the question already framed and the basic fit signals captured, which is what shaves hours off the back-and-forth on every consultation. Second, the logs become a structured research artefact for marketing. The integration questions that keep stalling prospects point at a missing page; the pricing confusion points at a tier name or a rule that needs to be rewritten; the case studies the bot reaches for most often are the social proof that should move higher on the home page.

That feedback loop is the bigger long-term win because it compounds. Each tightening of the marketing copy reduces the number of questions the bot has to answer in the first place, which lifts conversion on prospects who never start a conversation. The right metric is not chats handled but qualified intake delivered to the team with full context, which is the input the conversion rate actually responds to.

Honest framing, grounded answers, and a clean handoff are the three things that separate a bot prospects come back to from one they learn to ignore on their second visit.