Biggest Hurdles to Overcome

The most significant challenges facing marketing analytics practitioners in 2025-2026, along with practical strategies for overcoming them.

Understanding the Challenges

These hurdles aren't hypothetical—they're real obstacles that organisations face today. Some are technical (data integration, real-time processing), others are regulatory (privacy compliance, AI transparency), and many are organisational (skills gaps, stakeholder alignment, data literacy). Success requires addressing challenges across all three dimensions simultaneously. The solutions provided are battle-tested approaches from organisations that have successfully navigated these obstacles.

Data Foundation Readiness Gap

Many organizations want advanced AI analytics, but their data foundations aren't ready yet. Business users expect automated reporting and intelligent agents, but lack basic data hygiene, consistent structures, and documented context. The unglamorous foundational work—consent management, data quality, unified definitions—is what makes automation possible.

Critical

Affected Areas

AI adoptionData qualityAutomationGovernance

Solutions and Strategies

•Audit current data infrastructure and identify foundational gaps
•Implement consent management platforms before advanced analytics
•Document business context and definitions that AI systems need
•Set realistic expectations about foundational investments required

Gaming Industry Context

Gaming operators often want AI-powered player predictions but lack unified player data across gaming systems, payment processors, and CRM. First-party data potential remains untapped without proper infrastructure.

Source: Improvado Marketing Analytics Trends 2026

Data Literacy Gap Despite Democratization

Modern tools make data easier to access, but greater access creates confusion when teams don't know how to interpret it. Everyone can see the data, yet not everyone understands how metrics influence one another, why they matter, or how they connect to business outcomes. AI lowers barriers to working with data but raises the bar for understanding it.

Critical

Affected Areas

Decision-makingData interpretationStakeholder alignmentAI effectiveness

Solutions and Strategies

•Provide data literacy training across all business units
•Create clear documentation on metric definitions and relationships
•Build knowledge blocks about business context for AI systems
•Establish data champions within each department

Gaming Industry Context

Gaming teams must understand how acquisition metrics (CPA, FTD rate) connect to retention metrics (churn, LTV) and ultimately revenue. Without literacy, democratized data leads to misguided optimization decisions.

Source: Improvado Marketing Analytics Trends 2026

Relationship Management & Stakeholder Alignment

Before any report, dashboard, or AI agent can create value, teams must agree on what 'success' actually means. Getting people aligned on KPIs, separating optimization metrics from business objectives, and ensuring every team understands how numbers tie back to revenue requires trust, context, and interpersonal skills that AI cannot automate.

High

Affected Areas

KPI definitionCross-team collaborationStrategy alignmentMeasurement frameworks

Solutions and Strategies

•Facilitate workshops to define shared success metrics
•Act as advisor, mediator, and translator between teams
•Document agreed-upon KPIs and their business rationale
•Regularly revisit and realign metrics as business evolves

Gaming Industry Context

Gaming organizations must align product, marketing, and finance teams on whether success is FTD volume, player LTV, GGR, or retention rate. Without alignment, teams optimize for conflicting goals.

Source: Improvado Marketing Analytics Trends 2026

Cookie Deprecation and Tracking Limitations

The phase-out of third-party cookies and increasing browser privacy restrictions create measurement gaps, making it difficult to track customer journeys and attribute conversions accurately.

Critical

Affected Areas

AttributionRetargetingCross-device trackingAudience measurement

Solutions and Strategies

•Implement server-side tracking to bypass browser restrictions
•Build first-party data collection strategies through owned channels
•Adopt privacy-preserving measurement techniques (differential privacy, aggregated reporting)
•Invest in contextual targeting as alternative to behavioural targeting

Gaming Industry Context

Particularly challenging for Gaming operators relying on affiliate marketing and retargeting for player acquisition. FTD attribution becomes harder to measure accurately across devices and sessions.

Source: Forrester 2026 Predictions

Privacy Regulations and Compliance Complexity

Navigating a patchwork of global privacy regulations (GDPR, CCPA, DMA) with different requirements for consent, data retention, and cross-border data transfer creates compliance burden and limits data usage.

Critical

Affected Areas

Data collectionUser consentData storageInternational operations

Solutions and Strategies

•Implement consent management platforms (CMPs) with granular controls
•Establish data governance frameworks with clear retention policies
•Use data clean rooms for collaborative analytics without exposing raw data
•Consult legal experts for jurisdiction-specific compliance requirements

Gaming Industry Context

Gaming operators face additional regulatory complexity with gambling-specific regulations varying by jurisdiction. Player data protection requirements often exceed general privacy laws.

Source: Gartner Future of Marketing

Data Silos and Integration Challenges

Marketing data scattered across disconnected platforms (ad platforms, CRM, analytics, CMS) prevents unified customer views and makes cross-channel attribution nearly impossible.

High

Affected Areas

Customer journey trackingAttributionReportingPersonalisation

Solutions and Strategies

•Implement Customer Data Platforms (CDPs) to unify customer data
•Build data warehouses as single source of truth for all marketing data
•Use ETL/ELT tools to automate data integration from multiple sources
•Establish data governance to ensure consistent definitions and quality

Gaming Industry Context

Gaming platforms must integrate data from gaming systems, payment processors, affiliate networks, CRM, and marketing platforms to get complete player view from acquisition to lifetime value.

Source: Tealium 2025 State of the CDP

Attribution Complexity in Multi-Touch Journeys

Modern customer journeys involve dozens of touchpoints across channels and devices. Determining which interactions deserve credit for conversions remains unsolved, with no perfect attribution model.

High

Affected Areas

Budget allocationChannel optimisationROI measurementPerformance evaluation

Solutions and Strategies

•Use multiple attribution models (first-touch, last-touch, multi-touch, data-driven) for different purposes
•Implement Marketing Mix Modelling for top-of-funnel brand activities
•Run incrementality tests to measure true causal impact of marketing
•Accept that attribution is directional guidance, not absolute truth

Gaming Industry Context

Player journeys from awareness to FTD often span weeks and multiple channels (display ads, affiliates, email, retargeting). Accurately crediting affiliates whilst measuring brand impact requires sophisticated attribution.

Source: Adriel: Future of Marketing Measurement

Skills Gap and Talent Shortage

AI automates technical work, but human judgment becomes more valuable. Marketing analytics teams now need critical thinking, effective communication, and the ability to interpret results, spot issues, question assumptions, and validate AI-generated output. Finding professionals who can judge whether analysis makes sense is harder than finding those who can execute it.

High

Affected Areas

Team buildingHiring prioritiesTrainingStrategy

Solutions and Strategies

•Hire for critical thinking and communication over technical skills
•Train teams to validate and contextualize AI output
•Build cross-functional teams combining marketing, data, and engineering
•Partner with agencies or consultants for specialized expertise

Gaming Industry Context

Gaming analytics requires understanding both marketing fundamentals and Gaming-specific metrics (FTD, GGR, player lifetime value). Finding talent who can critically evaluate AI predictions about player behavior is particularly challenging.

Source: Improvado Marketing Analytics Trends 2026

Data Quality and Accuracy Issues

Inaccurate tracking implementation, bot traffic, ad fraud, and data processing errors undermine confidence in analytics, leading to poor decisions based on flawed data.

High

Affected Areas

Reporting accuracyDecision-makingBudget allocationPerformance evaluation

Solutions and Strategies

•Implement data validation and quality monitoring processes
•Use bot detection and fraud prevention tools to filter invalid traffic
•Establish data quality SLAs and regular audits
•Create data dictionaries and documentation for consistent definitions

Gaming Industry Context

Gaming operators face affiliate fraud, bonus abuse, and multi-accounting that skew metrics. Accurate FTD tracking requires robust fraud detection to avoid crediting invalid conversions.

Source: Gartner Top Technology Trends 2026

Real-Time Processing and Latency

Demand for real-time insights conflicts with the time required to collect, process, and analyse data from multiple sources, creating delays that limit optimisation opportunities.

Medium

Affected Areas

Campaign optimisationPersonalisationBiddingBudget allocation

Solutions and Strategies

•Implement streaming data pipelines for real-time processing
•Use event-driven architectures to reduce processing latency
•Accept trade-offs between speed and accuracy for different use cases
•Build separate systems for real-time activation vs. historical analysis

Gaming Industry Context

Real-time player segmentation and bonus offers require instant data processing. Delays in identifying high-value players or churn risk reduce effectiveness of retention interventions.

Source: GrowthLoop: CDP Trends 2025

AI Explainability and Trust

Black-box AI models that make marketing decisions without clear explanations create trust issues, regulatory concerns, and difficulty debugging when performance degrades.

Medium

Affected Areas

AI adoptionRegulatory complianceStakeholder buy-inTroubleshooting

Solutions and Strategies

•Use explainable AI techniques (SHAP values, LIME) to understand model decisions
•Maintain human oversight for critical decisions
•Document model logic, training data, and decision criteria
•Establish governance frameworks for AI usage in marketing

Gaming Industry Context

AI-driven player lifetime value predictions and churn models must be explainable for responsible gambling compliance and to justify marketing spend on predicted high-value players.

Source: Gartner Top Technology Trends 2026

Budget Constraints and ROI Justification

Implementing modern analytics infrastructure requires significant investment in tools, talent, and technology. Justifying ROI to leadership when benefits are long-term and indirect is challenging.

Medium

Affected Areas

Budget approvalTool selectionTeam expansionInfrastructure investment

Solutions and Strategies

•Start with high-impact, low-cost improvements to demonstrate value
•Quantify cost of poor measurement (wasted spend, missed opportunities)
•Build business cases showing competitive disadvantage of inaction
•Use phased implementation to spread costs and demonstrate incremental value

Gaming Industry Context

Gaming operators must balance investment in analytics infrastructure against direct player acquisition spend. Demonstrating how better measurement improves FTD conversion and reduces CAC is critical for budget approval.

Source: Forrester 2026 Predictions

Overcoming These Hurdles

These challenges are interconnected. Solving cookie deprecation requires privacy-preserving measurement, which demands data literacy, which needs stakeholder alignment. Address hurdles holistically rather than in isolation. Start with foundational investments (data quality, governance, literacy) before advanced capabilities (AI, real-time processing, sophisticated attribution).

For Gaming operators, prioritise hurdles that directly impact FTD measurement and player LTV prediction. Data foundation readiness, stakeholder alignment on success metrics, and data quality improvements offer the highest ROI for deposit-based business models.