Frontline CRM · Overview · Real product recording

Explore CRM records

Explore how Frontline CRM keeps people, companies, deals, tickets, and customer context connected across the operating system.

Real product recording2 min

Product contextPeople records list with visible fields and related companies
Use this product state to inspect customer memory: record identity, relationships, activity, and context that AI or workflows may depend on.

Visual operational blueprint

Learn the system by following the product states.

Use the screenshots as the primary map: start with the full context, trace the connected workflow, inspect the focused UI, then compare against the completed operating state.

01Record

02Relationships

03Activity

04Workflow context

05Max follow-up

Completed operating stateDeals pipeline with stages, values, people, and companies
This is the state to compare against when the system is configured, connected, or ready for review.

Summary

Explore how Frontline CRM keeps people, companies, deals, tickets, and customer context connected across the operating system.

ProductFrontline CRM

ModuleOverview

CategoryOverview

Concepts covered

OverviewFrontline CRMRecordsPeopleDealsTicketsCustomer context

Step breakdown

Open CRM recordsStart from the records layer that connects people, companies, deals, and tickets.
Review people recordsInspect contact history, ownership, and relationship context.
Connect records to workUse CRM context as shared memory for Max assistance and Studio workflows.

About this walkthrough

This lesson follows the real CRM record layer under Work / Records: People and Companies as list tables, Deals and Tickets as pipeline views, with filters, visible fields, actions, row details, and relationship context available to workflows and Max.

Operational playbook

Use Explore CRM records as part of the Frontline CRM Overview operating loop: inspect the current product state, confirm the source context, and decide what should happen next.

The goal is not to memorize screens. The goal is to understand how the product surface supports repeatable work, AI assistance, and accountable handoff.

Best practices

Start with the operational job before changing configuration. Name the owner, define the trigger or source context, and decide how the result should be reviewed.

Prefer narrow, inspectable setups over broad automation. Teammates should be able to explain why the system took an action from the visible product state.

Troubleshooting

If the result does not match expectation, check the source context first, then permissions, connected integrations, required fields, workflow logs, and any AI-generated output used by downstream steps.

When in doubt, compare the latest product state with the related record, activity, or workflow execution so debugging starts from evidence rather than guesswork.

Validated CRM behavior

The real CRM surface lives under Work / Records with object routes such as People, Companies, Deals, and Tickets. People and Companies use list-style record tables; Deals and Tickets use pipeline columns for stage-based work.

Learning content should show the controls users actually see: List or Pipeline, Filter, visible-field counts, Actions, Add, row links, field columns, stage totals, and calculations.

Customer context checklist

Before acting on a customer, review the person or company, related deals or tickets, recent activity, ownership, and any workflow or Max-generated context.

The strongest CRM habit is relationship-first review: understand how the record connects before deciding what should happen next.

Transcript

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CRM is the memory layer of Frontline: people, companies, deals, tickets, and activity connected to the work around them. The real CRM surface lives under Work / Records. People and Companies open as list-style record tables with filters, visible-field counts, actions, add controls, field columns, and row detail links. People records are where customer relationships become visible: names, roles, companies, LinkedIn, email, phone, and recent interaction context. Deals and Tickets add operational shape through pipeline views. Deals use Lead, In Progress, Won, and Lost columns with values, people, companies, and stage totals. Tickets use support stages such as New, On You, On Customer, On Hold, and Closed so customer issues stay connected to records and owners. This is why CRM is a core product in Frontline: it keeps customer context alive across personal work, operations, workflows, and Max activity.

FAQs

What are records in Frontline CRM?

Records are structured customer memory for people, companies, deals, tickets, relationships, and activity.

How does CRM context help AI workflows?

CRM context gives Max and Studio workflows shared customer memory so follow-up can be specific and operationally grounded.

How do CRM records improve AI workflows?

CRM records give Max and Studio shared customer memory: identity, relationships, deals, tickets, activity, and context that workflows can retrieve, summarize, update, or route around.

When should I create a relationship between records?

Create relationships when context should travel together: a person belongs to a company, a deal depends on contacts, a ticket affects customer health, or a workflow needs related records.

What should I check before changing the data model?

Check which workflows, summaries, views, and teammates rely on the field or relationship. Schema changes should preserve operational context and avoid breaking automation.

How should teams handle duplicate or incomplete records?

Prioritize records that affect active work. Merge or clean duplicates when they confuse ownership, customer context, workflow routing, or AI-generated summaries.

What makes CRM context trustworthy?

Trust comes from clear ownership, current activity, useful relationships, well-defined fields, and visible history. AI suggestions should point back to this structured context.