Yes. Add your fee structure as a pricing page (flat-fee tier, percentage-of-spend tier, hybrid model, performance bonus) and the bot reads it as context. At the prospect's spend, the bot computes the actual monthly cost rather than quoting a 'starting at' number. Brands evaluating three agencies can compare apples-to-apples in chat instead of running three rounds of proposal emails. When the fee model changes, you edit the page once and every future conversation reflects it.

The audit gets its own service page with deliverables, fee, timeline, and typical findings. The bot reads it and explains the audit when the prospect describes account-health issues (CAC creep, attribution gaps, creative fatigue, scaling plateaus). The bot also explains the audit-to-retainer transition: how findings translate into retainer scope, what the typical audit-to-retainer conversion rate is for the agency, and what the prospect can decide at the end of the audit (continue with the agency, take the recommendations to a different team, or keep status quo).

Yes, when case studies live as a custom post type with spend-range, channel, and category metadata. The bot reads the directory and surfaces the closest match at the moment of doubt. A D2C apparel brand at $80k/month gets the D2C apparel case in the $50-100k range, not the SaaS case at $30k or the enterprise case at $400k. The bot also references the outcome (CAC change, ROAS change, scale achieved) in one sentence rather than dumping the full case study.

Yes. Meta, Google, TikTok, LinkedIn, Amazon, and YouTube each have different account-health questions and different specialists on most agency teams. The bot captures channel mix as part of the early qualifying conversation and routes to the specialist whose channel matches. For agencies that focus on one channel (Meta-only or Google-only specialists), the bot can decline channels outside scope and refer prospects to partner agencies, which preserves the relationship for related work.

SleekAI logs conversations in WordPress and pushes the transcript and contact details into HubSpot, Pipedrive, or Salesforce via Zapier or webhook on the conversation-saved event. It does not connect directly to Meta or Google Ads APIs (which would not be the right pattern at intake-time anyway). The conversation summary plus qualifying answers (spend, channels, conversion goal, current CAC issue) end up as a fully-shaped lead record so the partner sees context before the call.

Attribution conversations are most of the inbound for D2C PPC agencies in 2026. The bot can explain how the agency handles iOS 14 attribution gaps (server-side conversion APIs, modeled conversions, GA4 plus channel-side reporting), how it handles post-cookie measurement (incrementality testing, MMM lite, geo experiments), and what the audit covers on tracking. Those answers come from your published methodology pages, not the model's general opinions, which keeps the bot consistent with what the team actually delivers.

Yes, when you have an Amazon Ads service page. Amazon advertising has different inputs from Meta or Google: Sponsored Products versus Sponsored Brands versus Sponsored Display, ACOS and TACOS targets, brand-protection campaigns, and the Amazon DSP versus Amazon Ads console split. The bot captures Amazon-specific qualifying questions (current ACOS, category, brand-registry status, DSP eligibility) and routes to an Amazon specialist on the team. For agencies that do not offer Amazon, the bot can refer prospects to a partner.

Yes, when you tell it your floors. If your floor is $30k/month spend and a prospect describes $5k spend, the bot says so politely and points them to a self-serve learning resource, a recorded webinar, or a freelance-friendly partner network. The prospect leaves with a useful next step instead of a wasted hour, and the agency's partner calendar stays focused on engagements that match the team's actual sweet spot.