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Campaign Operations Optimisation

How I identified, designed, and built a Salesforce-based solution to fix a broken campaign operations process — Phase 1 PoC complete, Agentforce planned for Phase 2.

A product case study by Katlego Phokela

2026

Overview

Campaign ops at my organisation ran on a mix of Salesforce, Outlook, Excel, and informal handoffs. There was no consistent way to track campaigns, assign work based on capacity, or know where something was stuck. I mapped the full process, identified where things were breaking, and built a working PoC in Salesforce — 3 custom objects, 3 record-triggered Flows, a complexity scoring formula, auto-assignment logic, and SLA tracking. Phase 1 is live. Phase 2 will explore Agentforce to add intelligence on top of the clean foundation.

Approach: Standardise the process first (that's what Phase 1 does — no AI needed), then layer in automation with Agentforce once the data and workflows are clean.
Built on: Salesforce + Data Cloud + Marketing Cloud

Lifecycle at a Glance

Stage Focus Key Deliverable Status
1. Discovery & Research Map the end-to-end campaign lifecycle and pain points Real process mapping, 5 persona pain points, friction analysis Complete
2. Strategy & Vision Define three-phase strategy and product principles Standardise → Automate → Intelligent three-phase vision Complete
3. Planning & PRD Write product requirements and feature specs PRD with 15 features, complexity formula, SLA rules Complete
4. Design & UX Design role-based views and Flow-driven UX Data model (3 objects), Flow architecture, UI wireframes Complete
5. Build Build the working PoC in Salesforce Working PoC — 3 Flows, validation rules, list views, Kanban, Path Phase 1 Complete
6. Launch & Rollout Pilot with one team and plan wider rollout Pilot plan, training materials, rollout approach Ready for Pilot
7. Measure & Iterate Track what's working and what needs fixing Key metrics defined, feedback approach planned Planned

The Product Lifecycle — Stage by Stage

1
Discovery & Research Complete
Map the end-to-end campaign lifecycle and identify pain points

I mapped the full campaign lifecycle — from the moment a business unit submits a brief in Salesforce to when the campaign goes live. I spoke to the ops leads, builders, and BU stakeholders who actually do this work every day to understand where things break down.

What I Found

  • Campaigns took anywhere from 45 to 120 days — no consistency
  • Ops spent a huge chunk of time on manual capacity planning in spreadsheets
  • No way to score campaign complexity or set realistic SLAs
  • Work was tracked across 3-5 disconnected tools per campaign
  • Handoffs between teams were informal — things fell through the cracks

People I Spoke To

  • Ops Leads & Administrators
  • Content Builders & Journey Builders
  • Business Unit Requestors
  • Data & Insights Team
View Stage 1 Details →
2
Strategy & Vision Complete
Decide what to fix first and what the long-term vision looks like

The main insight from discovery was that we needed to standardise before doing anything clever. You can't automate a broken process. So I planned it in phases: first get the basics right in Salesforce (Phase 1), then explore Agentforce for smarter automation later (Phase 2).

Principles I Followed

  • Standardise first — don't automate a mess
  • Keep humans in control of decisions
  • One source of truth (Salesforce, not spreadsheets)
  • Each phase must deliver value on its own

Phased Approach

  • Phase 1: Get the Salesforce foundation right
  • Phase 2: Explore Agentforce for automation
  • Phase 3: Optimise based on real data
View Stage 2 Details →
3
Planning & PRD Complete
Define what to build and in what order

I wrote the product requirements — what the system needs to do, the rules for complexity scoring, the campaign lifecycle stages, and how assignment and SLA logic should work. I prioritised features using MoSCoW across the phases so Phase 1 focuses on what matters most.

What I Defined

  • Complexity scoring formula (channels, audience, compliance)
  • 6-stage campaign lifecycle with clear handoff points
  • Auto-assignment rules based on workload & skills
  • SLA targets tied to complexity score
  • QA checklist requirements

Key Artifacts

  • Product Requirements Document
  • Feature backlog (Must/Should/Could)
  • Complexity scoring specs
  • Phase 1 vs Phase 2 scope
View Stage 3 Details →
4
Design & UX Complete
Design role-based views and Flow-driven UX

I designed how each role would use the system — ops leads need a pipeline view, builders need their queue, BU requestors need to see where their campaign is. Everything is built with standard Salesforce components: list views, Kanban boards, Path, and record page layouts.

What Each Role Sees

  • Ops Lead: Pipeline dashboard with at-risk campaigns
  • Builders: Personal queue and Kanban board
  • Journey Builders: Stage-gated workflow view
  • BU Requestors: Campaign status tracker

Salesforce Components Used

  • List views & Kanban boards per role
  • Path component for campaign stage progression
  • Complexity score displayed on record pages
  • QA checklist on the campaign record
View Stage 4 Details →
5
Build Phase 1 Complete
The working PoC in Salesforce

I built the working PoC in Salesforce — 3 custom objects, 3 record-triggered Flows, and the supporting views. The Flows handle: calculating complexity and SLA at briefing, pausing/resuming SLA when waiting on the business unit, and routing new campaigns to the right builder based on workload.

What I Built (Phase 1)

  • 3 custom objects for the campaign lifecycle
  • Complexity scoring formula field
  • 3 record-triggered Flows (readiness, SLA, assignment)
  • Dashboards, list views, Kanban, Path
  • QA checklist on the campaign record

Why Flows (Not Code)

  • Admins can maintain it without developers
  • Fast to iterate during PoC
  • Appropriate complexity for what Phase 1 needs
  • Can migrate to Agentforce later if needed
View Stage 5 Details →
6
Launch & Rollout Ready for Pilot
Start with one team, learn, then expand

The plan is to pilot with one business unit first — get real feedback, fix what doesn't work, and then roll out to other teams. I've prepared the business case and training approach to support adoption.

Rollout Plan

  • Pilot with one BU to test in production
  • Gather feedback from ops and builders
  • Fix issues before expanding
  • Role-based training for each user group

What I'll Be Watching

  • Are campaigns moving faster through the pipeline?
  • Is the ops team spending less time on admin?
  • Are people actually using the system (not going back to email)?
  • What's breaking or confusing?
View Stage 6 Details →
7
Measure & Iterate Framework Defined
Track what's working and fix what isn't

The main thing I want to know: are campaigns moving through the pipeline faster and more predictably than before? I've defined the key metrics to track after pilot, and I'll use the data to decide what to improve next.

Key Metrics

  • Campaign cycle time (the big one)
  • SLA compliance — are we hitting targets?
  • Workload distribution — is it balanced?
  • System adoption — are people using it?

What Comes Next

  • Iterate based on pilot feedback
  • Explore Agentforce for smarter assignment
  • Better reporting and dashboards
  • Capacity planning improvements
View Stage 7 Details →