Guides

14 practical guides: how to get named by ChatGPT and Perplexity first, then playbooks for inbound lead operations. Written for teams that run on SEO, chat, and CRM, not slide decks.

New: ChatGPT skips 2 in 3 businesses, our study of 731 websites.

• AI SEO: What It Is, What Actually Decides Citations, and How to Check Your Own Site

  AI SEO in practice: why an answer engine quotes one site and skips another, the five things it checks before it can quote you, how to check each of them yourself in a browser for free, and the order to fix them in.

• llms.txt: What It Is, How to Write One, and Why Most of Them Rot

  A practical guide to llms.txt: what the format actually asks for, a working example, how to generate it so it cannot drift, and how to check whether the links in yours still lead anywhere.

• Generative Engine Optimization (GEO) and AEO: How Content Earns AI Citations

  Practical AEO and GEO for inbound teams: quotable answer blocks, consistent entities, honest measurement of AI citations, and the link to real pipeline.

• Top AI Consulting Companies: How to Choose

  A category map of AI consulting firms: the four types that show up in search, what each is actually built to sell, and how to tell which one your problem needs.

• AI SDR vs Human SDR: Task Split, Limits, and Testing

  What an AI SDR really does today, task by task, the conditions where each task degrades, how to test a vendor on your own data, and what stays human.

• Marketing and Sales Automation ROI: An Auditable Model

  Build an inbound automation ROI model finance can check: baseline, cost register, incremental contribution, three scenarios, break-even, sensitivity, payback.

• Inbound Lead Audit: Find Out Where Your Leads Are Lost

  Run the inbound lead audit yourself: reconcile arrived, created, owned and worked counts, trace every gap to one layer, and rank findings by cost.

• Lead Ops vs RevOps: Scope, Artifacts, and Who Owns What

  Lead ops vs RevOps compared by accountability, not tools: what each function optimizes, which artifact it owns, and the failure signature of a wrong boundary.

• Website Lead Capture: Formats, Payload, and Consent

  Choose a lead capture format and define what every submit must emit: required payload, progressive fields, consent evidence, and the failure modes to test.

• AI Lead Qualification: Fit, Intent, and Human Handoff

  How AI qualification separates fit from intent, scores confidence, routes deterministically, and hands inbound conversations to a rep with evidence.

• CRM Automation for Inbound Leads: Stages, Fields, Dedupe

  Design inbound CRM automation that holds up: lifecycle stages as a state machine, field ownership, deduplication before assignment, and safe retries.

• Lead Hub vs CRM: Define the System Ownership Boundary

  Where the OperStack Lead Hub ends and your CRM begins: capture, routing and SLA in the hub, pipeline and revenue in CRM, plus a staged migration path.

• Programmatic SEO for Lead Gen: Pages That Earn Pipeline

  How lead-gen teams build templated pages from governed data, pass quality gates, control indexing, and measure qualified pipeline by template cohort.

• AI Sales Onboarding: Certify Reps Before Live Leads

  How AI-assisted practice, CRM sandbox evidence, and certification gates decide when a new sales rep becomes eligible for live inbound lead assignment.

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