Yes - if your fees live anywhere in WordPress, whether as a page, a post, ACF fields, or even a structured table, SleekAI pulls that into the prompt as context. The bot then quotes the same numbers your proposals do, every conversation. When you change a fee on the page, the next conversation reflects it without any redeploy or re-training step on your end.

Yes. Run different bots per practice area using the Multibot feature, or set display conditions so each service page has its own specialist bot. A typical mid-market consultancy might run a strategy bot on the strategy pages, a RevOps bot on operations pages, and a generalist bot on the homepage that triages to the right specialist after the first qualifying question.

SleekAI logs every conversation in WordPress and most consulting firms use a Zapier or webhook trigger to push the transcript and contact details into HubSpot, Pipedrive, or Salesforce. The conversation summary plus the qualifying answers (budget, timing, stakeholders) end up as a fully-shaped lead record so the partner sees the context before the discovery call.

Add case studies as a custom post type with vertical and capability taxonomies. SleekAI ingests them automatically and uses the taxonomies to filter which case study to surface for which prospect. For very long case study libraries you can also use OpenAI Files or a vector backend so the bot retrieves the most relevant 2-3 rather than dumping the whole list into context.

Configure the system prompt to say so directly. The bot will not invent a capability your firm does not have; it will either redirect to a partner you trust (if you list one), capture the inquiry for human follow-up, or politely close the conversation. That discipline is what keeps the bot trustworthy and stops it from booking calls into engagements you cannot deliver.

Yes. Run two bots with different system prompts on different pages, or split traffic on the same page using your A/B tooling, and compare conversion rates in your analytics. Each bot keeps its own conversation logs tagged with the bot ID, so post-hoc analysis of 'which voice converted better' is just a database query rather than a manual transcript review.

Yes, and it should. The system prompt encodes your minimums (typical budget floor, company stage, vertical fit), and when a prospect clearly does not match, the bot says so politely and redirects to self-serve content - a relevant blog post, a downloadable framework, or a partner referral. The prospect leaves with a useful next step instead of a wasted hour, and your calendar stays clean.

The bot is configured to ask 'who else is in the decision' early in the conversation and to capture the full stakeholder list - economic buyer, technical buyer, sponsor, blocker. That context flows into the booking handoff so the partner walks into the discovery call already knowing they should bring the right people, both from your side and the prospect's. It is one of the most underrated lead-quality improvements a chatbot delivers.