Campaign workflows

Concepts covered

Step breakdown

1. Define the system to deployStart from this Marketing operating system and confirm the business outcome, source signals, owners, and review gates.
2. Create the Frontline assetsBuild the workflow canvas, agent prompt, channels, CRM records or tables, routing logic, and Max Activity evidence described in the blueprint.
3. Launch the narrow versionDeploy the smallest reliable version first, keep human review visible, then use activity and analytics to expand the system.

What you will build

A campaign workflow system that connects marketing campaign signals (WhatsApp reply, Instagram engagement, form submission) to CRM records, triggers segmented follow-up sequences on the right channel, and logs every engagement outcome so marketing and sales share the same view of campaign performance.

After deployment: a campaign goes out, Frontline captures each reply or engagement, identifies the person, applies the campaign segment, sends the correct follow-up, and updates CRM — creating a closed loop from campaign send to deal creation.

When to use this

You run outbound WhatsApp or Instagram campaigns and the follow-up process is manual and inconsistent.

Campaign replies sit in an inbox for days before someone acts on them.

Marketing and sales use separate tools and have no shared view of campaign-to-deal conversion.

You want to A/B test message timing or content variants and see results in CRM.

System components

Channels: WhatsApp and Instagram as campaign delivery and reply surfaces.

CRM Person record: source campaign, segment, lifecycle stage, last reply date.

Studio workflow: one workflow per campaign type (e.g., product launch, re-engagement, event follow-up).

Campaign segment table or Person field: identifies which campaign sequence each person is in.

AI follow-up agent: generates campaign-appropriate follow-up based on reply content and campaign context.

Conditional Routing: routes by reply sentiment, intent, or no-reply timeout.

Max Activity: campaign name, message sent, reply received, routing outcome, and CRM updates.

Step-by-step implementation

1. Define the campaign: what is the goal (lead generation, event attendance, reactivation), which segment receives it, and what channel.

2. Tag each Person in CRM with the campaign they are enrolled in: add a 'campaign_source' field and populate it when the campaign sends.

3. Create a Studio workflow. Trigger: inbound reply on WhatsApp or Instagram linked to the campaign.

4. Add Person lookup by phone or handle. Read the campaign_source field to identify which campaign this reply is for.

5. Add AI follow-up agent node. Pass: the reply content, the campaign name and goal, the person's segment.

6. Add Conditional Routing based on reply intent: Interested → sales handoff; Needs more info → educational follow-up; Not interested → unsubscribe.

7. Interested branch: update CRM lifecycle stage to 'Sales Ready', create Deal if not exists, assign owner, write Max Activity.

8. Needs info branch: send AI-generated educational reply, schedule follow-up in 3 days, write Max Activity.

9. Not interested branch: remove from campaign sequence, update Person as 'Campaign Opt-out', write Max Activity.

10. No-reply timeout (72 hours): send one follow-up message. No reply after that: mark campaign as inactive for this Person.

11. Add campaign analytics to Max Activity on each branch so you can track conversion rate per campaign.

Agent prompt

You are writing a campaign follow-up message. The goal is to continue the conversation started by the campaign and move interested people toward a next step.

You will receive: the prospect's reply, the campaign name and goal, their segment (Hot/Warm/Cold), and their name.

Write a reply that: acknowledges what they said specifically, provides one relevant piece of information that matches their reply intent, includes one clear next step (not a vague 'let me know').

Maximum 3 sentences. Use the prospect's language register (formal or casual based on their message). Output only the message text.

Workflow logic

Reply = high intent (wants to buy, asks for price, schedules call): sales handoff path — create Deal, assign owner, stop campaign sequence.

Reply = needs information: educational follow-up path — send relevant info, wait 3 days, check for next reply.

Reply = not interested: opt-out path — update Person field, stop all campaign messages, log in Max Activity.

No reply after initial campaign message: one follow-up after 72 hours. No reply after follow-up: mark inactive.

Reply received after being marked inactive: re-enter campaign workflow from the beginning with a fresh context.

Final operating state

Every campaign reply is captured and produces a CRM update: lifecycle stage, campaign source, and last reply date.

Interested replies create Deals and trigger sales handoffs within minutes of the reply.

Max Activity shows the full campaign journey for each person: message sent, reply received, follow-up sent, and final outcome.

Marketing and sales share the same view of campaign performance in CRM: replies, conversions, opt-outs, and deal creation rate.

Troubleshooting

Campaign replies not matching the correct workflow: verify that replies include the campaign tag. Add a campaign ID to the WhatsApp message template so it comes back in the reply metadata.

Same person enrolled in multiple campaigns: add a guard — if Person is already active in a campaign sequence, do not enroll in a second one. Complete or expire the first.

AI follow-up messages too generic: pass the specific product or offer from the campaign, not just the campaign name. The more specific the context, the better the reply.

No-reply timeout not firing: verify the Wait node is connected to the correct output. Check that the timeout branch fires after the wait expires, not only on active reply.

Operational playbook

Use Campaign workflows as part of the Frontline Solutions Marketing 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.

Platform layers involved

Studio defines the workflow and AI agent behavior. Channels capture the customer interaction. CRM provides customer memory. Max Activity shows what the system did and what needs follow-up.

Use the solution page as the business-facing map, then open the related product tutorials when you need configuration detail.

Outcome metrics

Track a small set of operational signals: response time, handoff rate, completion rate, escalation quality, CRM field completeness, reply rate, and repeated failure patterns.

The metric should reflect the business outcome, not only whether the automation ran.

FAQs

Related workflows