HubSpot Inbound Marketing cheat sheet

Content types map to funnel stages: blog posts and pillar pages serve awareness, comparison and buying-guide content serves consideration, case studies and demos serve decision.

A pillar page covers a broad topic in depth and links to cluster posts on subtopics; every cluster post links back to the pillar to consolidate topical authority.

Topic clusters outperform isolated posts because internal links concentrate ranking signals on a defined keyword set rather than scattering them.

A content audit classifies each URL as keep, update, consolidate, or remove; consolidating overlapping posts into one stronger URL usually beats publishing a near-duplicate.

Content repurposing ratio: one long-form asset should yield multiple derivative assets (social snippets, email copy, video clips, sales enablement) to amortize production cost.

Buyer persona inputs that change content decisions: role, goals, pain points, objections, and preferred format - not demographics alone.

Content calendar fields: target keyword, funnel stage, persona, owner, publish date, and CTA destination; a post without a defined next step is a dead end.

Search intent classification: informational queries expect education, commercial queries expect comparison, transactional queries expect an offer or purchase path.

Lead conversion rate = leads captured ÷ visitors to the offer page; separately track form view-to-submit rate to isolate form friction from traffic quality.

Offer strength beats form length: gated high-value assets (templates, calculators, research) convert better than generic newsletters, so test the offer before shortening the form.

Progressive profiling collects a few fields on first conversion and adds fields on later conversions, trading form friction for richer records over time.

Lead scoring combines fit (role, company size, industry) and engagement (email opens, page views, form submissions); negative scores should be allowed for disqualifying attributes.

A lead magnet should solve one narrow problem completely; multi-topic assets dilute relevance and lower conversion.

Landing page essentials: single conversion goal, no site navigation, benefit-led headline, proof (testimonials, logos), and a form above the fold on mobile.

MQL to SQL handoff requires agreed criteria; without a shared definition, sales rejects marketing leads and attribution disputes follow.

List growth rate = (new subscribers − unsubscribes) ÷ total subscribers over the period; a high gross add rate with high churn can mask a shrinking list.

Workflow enrollment criteria determine who enters; re-enrollment settings determine whether a contact can loop again - set both deliberately to avoid duplicates or missed re-engagement.

Workflow goal criteria remove contacts from the flow when met; a goal converts a linear drip into a responsive sequence that stops when the desired action occurs.

Suppression lists and unenrollment rules prevent contacts from receiving conflicting or redundant messages across overlapping workflows.

Email send frequency caps and quiet hours reduce fatigue; a contact in two active workflows can otherwise receive several emails in one day.

Lifecycle stage automation should reflect real behavior: a contact becomes a customer when a deal closes or a purchase event fires, not when a form is submitted.

Delay steps should be measured from the last action, not from enrollment, when the sequence depends on engagement timing.

Internal notification actions route hot leads to sales immediately; pairing a score threshold with a notification is the standard handoff trigger.

Always test workflows on a small seeded list; use a test contact with a real inbox to verify personalization tokens, links, and branching logic before enabling.

Inbound methodology stages: attract, engage, delight - each stage maps to specific tactics and metrics rather than a single campaign.

The flywheel replaces the funnel metaphor: momentum comes from happy customers who drive referrals, word of mouth, and repeat purchase, feeding new contacts back into attract.

Inbound prioritizes earned and owned channels (search, content, email, referrals) over interruptive paid interruption; paid is used to amplify proven offers, not to replace the method.

Buyer's journey stages are awareness, consideration, and decision; content and CTAs must align to the stage the contact is actually in, not the stage marketing wishes.

Smarketing alignment means shared goals, shared definitions of MQL/SQL, and a service-level agreement for lead follow-up time.

Contextual marketing uses known contact data (page history, lifecycle stage, list membership) to personalize CTAs and content instead of showing one generic path.

Delight is measurable: customer health, support resolution, NPS, and referral rate are the metrics that determine whether the flywheel accelerates.

Inbound is a compounding system: content and SEO assets keep producing traffic after publication, while paid spend stops when budget stops.

Conversion rate = conversions ÷ total visitors × 100; always state the denominator (sessions, contacts, or form views) because the same numerator yields different rates.

Attribution models differ: first touch credits the first interaction, last touch credits the closing interaction, linear splits credit evenly, and multi-touch distributes across touchpoints - choose the model to match the question being asked.

Email metrics: open rate = opens ÷ delivered; click-through rate = clicks ÷ delivered; click-to-open rate = clicks ÷ opens. CTR and CTOR answer different questions.

Bounce rate (single-page sessions ÷ all sessions) is not exit rate (exits from a page ÷ page views); a high exit rate on a checkout page is normal, a high bounce rate on a landing page is not.

Customer acquisition cost = total sales and marketing spend ÷ new customers acquired in the period; compare CAC to customer lifetime value; a healthy LTV:CAC ratio is commonly cited around 3:1.

ROI = (revenue − cost) ÷ cost × 100; ROMI applies the same formula to campaign spend and should use attributed revenue, with the attribution model disclosed.

Funnel analysis requires consistent denominators at each stage; comparing MQL counts to SQL counts from different periods produces false conversion rates.

Dashboards should separate leading indicators (traffic, MQLs, pipeline created) from lagging indicators (revenue, retention) to support decisions before results land.