Description

This curriculum spans the diagnostic and governance work typically conducted across a multi-workshop operational review, addressing the same acquisition challenges tackled in cross-functional advisory engagements focused on data integrity, channel efficiency, and organizational alignment.

Module 1: Defining Acquisition Boundaries and Stakeholder Alignment

Determine which departments own customer acquisition KPIs and negotiate shared accountability between marketing, sales, and product teams.
Map decision rights for campaign approvals, budget allocation, and channel prioritization across regional and global units.
Establish thresholds for what constitutes a “qualified lead” in alignment with sales operations to prevent misalignment in funnel metrics.
Identify regulatory constraints (e.g., GDPR, CCPA) that limit data collection methods during lead generation in specific markets.
Document existing service-level agreements (SLAs) between marketing and sales for lead follow-up timing and response protocols.
Assess executive sponsorship strength for cross-functional acquisition initiatives and adjust governance model accordingly.

Module 2: Auditing Current Acquisition Channels and Performance

Reconcile discrepancies between platform-reported metrics (e.g., Google Ads, LinkedIn) and internal CRM attribution data.
Conduct a cost-per-acquired-customer (CAC) analysis by channel, including hidden costs such as agency fees and internal labor.
Identify underperforming channels that persist due to legacy contracts or stakeholder bias rather than ROI.
Validate tracking accuracy for offline-to-online conversion paths, such as events or call center leads.
Compare channel efficiency across customer segments to detect misallocation of spend in low-LTV cohorts.
Assess saturation levels in dominant channels and evaluate risk of diminishing returns.

Module 3: Evaluating Data Infrastructure and Tracking Integrity

Review UTM parameter consistency across campaigns and correct gaps that break attribution modeling.
Diagnose cookie expiration policies and consent management platform (CMP) configurations that truncate user journeys.
Map customer identity resolution capabilities across devices and assess reliance on third-party cookies versus authenticated data.
Validate CRM integration points with marketing automation tools to ensure lead status updates are synchronized in real time.
Identify data latency issues between ad platforms and internal dashboards that delay performance decisions.
Assess completeness of offline conversion tracking, including in-store purchases and phone orders tied to digital campaigns.

Module 4: Assessing Attribution Models and Decision Logic

Compare current first-touch attribution results with data-driven models to uncover channel undervaluation, such as organic search.
Quantify the impact of last-click bias on budget decisions and reallocate spend based on multi-touch simulations.
Define rules for handling cross-channel cannibalization, such as paid search capturing organic traffic.
Document assumptions in existing models, such as time decay windows or position-based weighting, and test sensitivity to changes.
Integrate incrementality testing results (e.g., geo-lift studies) to validate or override model-based channel valuations.
Establish protocols for updating attribution models when new channels or tracking capabilities are introduced.

Module 5: Reviewing Creative Strategy and Message Consistency

Audit ad creative versioning across geographies to identify redundant or outdated messaging still in rotation.
Measure click-through rate (CTR) decay over time for individual creative assets and set refresh triggers.
Align value propositions in paid campaigns with current product differentiators, correcting misaligned legacy messaging.
Assess creative production lead times and adjust testing cadence based on operational capacity.
Evaluate A/B test designs for statistical validity, including sample size, duration, and segmentation controls.
Map creative personalization capabilities to available customer data segments and identify gaps in dynamic content delivery.

Module 6: Analyzing Competitive Positioning and Market Dynamics

Conduct share-of-voice analysis across search and social platforms to benchmark visibility against key competitors.
Reverse-engineer competitor landing page strategies using traffic intelligence tools to identify conversion optimizations.
Monitor shifts in competitor bidding behavior on strategic keywords and adjust bid strategies preemptively.
Assess market entry timing for new verticals or regions based on competitor saturation and pricing models.
Evaluate the impact of macroeconomic factors (e.g., inflation, supply chain) on customer acquisition sensitivity in target segments.
Track competitor referral and affiliate programs to detect shifts in channel reliance and partnership incentives.

Module 7: Governance, Testing Frameworks, and Scalability Constraints

Define escalation paths for budget overruns or under-delivery in automated bidding systems.
Establish a testing roadmap that prioritizes high-impact experiments based on potential CAC reduction.
Review approval workflows for campaign launches and identify bottlenecks in legal, compliance, or brand review stages.
Assess infrastructure limits in CRM and marketing automation platforms during peak acquisition periods.
Document dependencies on external vendors (e.g., ad tech, data providers) and evaluate single points of failure.
Implement change control processes for modifying tracking codes, UTM structures, or conversion events.