Analytics consultancies sell to a strange mix of buyers: CFOs, heads of growth, heads of ops, and product leaders, each speaking a different metric language. They land on the site and want to confirm four things in under two minutes: do you work in our BI tool (Looker, Tableau, Power BI, Metabase, Mode), have you built dashboards for our function (finance, growth, ops, product), what does engagement scope and timeline look like, and how do you handle metric definitions across teams. SleekAI reads your services, case studies, BI-specific pages, and team bios so the bot can answer all four with real engagement detail.

The data path is plain WordPress. Case studies live as a custom post type with ACF fields for BI tool, function area, business question type, source warehouse, modeling approach, dashboard count, engagement duration, and outcomes (reporting time saved, decision speed, stakeholder adoption). Service pages describe metric layer methodology, dashboard standards, governance playbooks, and stakeholder enablement. The data-source wizard maps it into context, so the bot quotes "Looker finance dashboards for a 200-person company, 14 dashboards in 8 weeks, 60% faster month-end" instead of generic claims.

Routing splits inquiries by function and engagement type. Finance dashboards to one partner, growth analytics to another, ops reporting to a third, audits and metric-layer refactors to a fourth, audits to a hosted form. Conversation logs in wp_posts become a quiet feed of which BI tool and function pairs prospects keep asking about, useful signal for case study production and content plan.

Analytics consultancies sell across functions: finance, growth, ops, product, and sometimes marketing. Each buyer speaks a different language and brings a different evaluation lens. A CFO wants finance dashboards in their existing BI tool with metric definitions that survive audit; a head of growth wants funnel and cohort analyses tied to revenue; a head of ops wants reliability and exception reporting.

A generic chatbot can't keep up with that range, and a generic homepage flattens function nuance into a brochure about "analytics consulting" that doesn't help a CFO confirm the practice has built finance dashboards in Looker for companies their size. The result is function buyers bouncing on a positioning gap they could have resolved in three messages, and the practice never seeing the lost deal. A semantic chatbot fixes the gap because it reads the structured fields on the case study CPT (BI tool, function area, business question, dashboard count, outcomes) and answers a function-shaped question with a function-shaped reply.

The CFO gets the Looker finance case study with the month-end time saved; the head of growth gets the Tableau growth case study with the cohort improvements; the head of ops gets the Power BI exception-reporting work. Routing pulls the second lever. Analytics practices usually have at least four intake flows hiding behind one Contact form: finance, growth, ops, and product.

Each one belongs with a different partner. A bot that asks two qualifying questions and sends each prospect to the right partner compounds conversion across the entire book. The logs add a quiet third benefit.

Analytics practices live on engagement productization, and the conversation logs become a structured feed of which BI tool and function pairs prospects expect the practice to cover but can't easily confirm. Every pair that shows up three times in a month is either a service page worth sharpening or a case study worth publishing next quarter.