
Map objects, properties and lifecycle rules before preparing an import.
Review identifiers, column mappings and correction checks; export a draft CSV.
Tools in this lecture: Data Model and Import Planner — Object map, Property dictionary, Lifecycle rule card, Column mapping sheet, Import correction checklist.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Build a data map and import file for your company in the Data Model and Import Planner, with a property dictionary, lifecycle rule, and checked column mapping. Submit the printed plan and exported CSV.
Define quality rules, saved-view recipes and association checks.
Review duplicates, retained values, enrichment and active or static segments.
Tools in this lecture: Contact and Company Quality Desk — Quality rule sheet, Saved-view recipe, Association check, Duplicate decision card, Enrichment review, Segment test card.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Build data quality rules and saved-view recipes for your company in the Contact and Company Quality Desk, including association, duplicate, enrichment, and segment checks. Submit the printed quality plan.
Write stage exit criteria, required-property proposals and movement tests.
Check line-item amounts, closed outcomes and proposed pipeline changes.
Tools in this lecture: Pipeline and Exit Criteria Planner — Exit evidence sheet, Required-property proposal, Transition test card, Line-item check, Change note.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Build a pipeline exit-criteria sheet for your company in the lesson tool, including the evidence and property for each stage. Submission: the saved sheet or its printed PDF.
Map form fields and separate fit from engagement in a proposed score model.
Test thresholds, missing-data cases and owner-routing decisions.
Tools in this lecture: Lead Score Model — Field map, Scoring rule sheet, Threshold sheet, Routing sheet, Test ledger.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Build a lead-scoring model for your company in the lesson tool, including the thresholds and test results for a matching record, a mismatch and a record with missing data. Submission: the saved model or its printed PDF.
Prepare a daily task list, shared-queue checks and activity follow-ups.
Review meeting settings, call sessions, power dialer and playbook access.
Tools in this lecture: Rep Day Planner — Task card, Activity note, Meeting setup card, Conversation card, Day check sheet.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Build a daily rep rhythm for your company in Rep Day Planner, including a next-action task, an activity note, meeting checks and unresolved items. Submit the exported daily sheet.
Draft five to seven touches with snippets, templates and document checks.
Record timing, sender prerequisites, enrollment checks and stopping tests.
Tools in this lecture: Sequence Blueprint — Sequence timeline, Content card, Enrollment check, Stop test sheet.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Build a five-to-seven-touch sequence for your company in Sequence Blueprint, including message drafts, timing, sender checks and stop tests. Submit the exported sequence sheet.
Map three workflows with entry rules, actions, branches, delays and exceptions.
Separate synthetic test results from portal observations; review Agent Hub and release prerequisites.
Tools in this lecture: Workflow Map Lab — Workflow maps, Wait and branch card, Test grid, Release review.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Complete three workflow maps for your company in Workflow Map Lab, including entry rules, actions, exceptions and expected test results. Submit the exported map.
Define report questions, sources, date fields, filters and dashboard decisions.
Reconcile source deals and distinguish weighted pipeline, goals and human forecasts.
Tools in this lecture: Dashboard and Forecast Brief — Report card, Reconciliation sheet, Dashboard wireframe, Forecast note.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Complete one dashboard and forecast brief for your company in Dashboard and Forecast Brief, including metric definitions, filters, calculations and acceptance checks. Submit the exported brief.
Check Assistant summaries, prospecting drafts and research-agent outputs against sources.
Record missing information, human decisions and separate credit estimates from actual usage.
Tools in this lecture: AI Output Review — Review decision, Summary request, Evidence grid, Review prompt, Credit conditions.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Complete the AI output review checklist for one draft relevant to your company, using permitted or fictional data and recording the source check, missing information, and your decision before action. Submit the exported checklist.
Plan one connection, data direction, mapping and conflict ownership.
Specify permissions, allow-or-deny tests, change checks, backup scope and recovery gaps.
Tools in this lecture: Integration and Access Planner — Connection plan, Mapping sheet, Access matrix, Test sheet, Recovery scope.
Downloadable materials: the lesson tool (HTML, opens in your browser) and the lecture presentation (PDF).
Assignment: Complete the integration and access plan for one connection relevant to your company, using permitted or fictional data and recording the data direction, required access, test expectations, and recovery gaps. Submit the exported plan.
This course contains the use of artificial intelligence
Your HubSpot portal already knows how your team sells. The question is whether anyone can trust what it says.
Duplicate contacts, deals with no next step, a dashboard that turns green for reasons nobody can name. This course fixes that, one HubSpot process at a time.
Why HubSpot gets messy
Most teams switch HubSpot on and start typing. A year later there are three email fields, stages that mean different things to different reps, workflows that send reminders for deals that already moved, and a forecast the CEO quietly ignores. Every month the data gets harder to clean and the reports get harder to defend.
What changes after the course
Who teaches it
Mike is the founder of PapaHR and leads the strategy of an online training business, where pipelines, lead handoffs and reporting are part of running the company. On Udemy his courses have 1,800,000+ enrollments and 170,000 students. He built the HR system at Preply, worked at Wargaming and iDeals, and is the author of about 200 books on Amazon.
How the course runs
First you put the data in order: objects, properties, imports, contacts and companies. Then you set up the pipeline and the lead handoff from marketing to sales. Next you build the daily rhythm of a rep: tasks, meetings, emails and sequences. After that you automate with workflows and build reports, dashboards and a forecast. Finally you review Breeze AI output and plan integrations, access and recovery. Every lesson shows the HubSpot screens step by step on mockups rebuilt from HubSpot's public documentation, and follows one fictional logistics company from a weak setup to a strong one.
What's included
This is an independent, unofficial course. It is not affiliated with or endorsed by HubSpot, and real screens or steps in your account may differ.
Every month on a messy portal costs you deals you cannot see and reports you cannot defend. The teams that fix their HubSpot first are the ones whose forecasts get believed.
Enroll now and start your first lesson today.