You are spending across channels—paid search, social, email, display, content, affiliate, retail media—and every platform hands you its own dashboard claiming credit for the win. Meanwhile, your CFO wants a single number: what is each dollar of marketing spend actually returning? Most organizations cannot answer that question with confidence because the data lives in silos, attribution models conflict, and the gap between marketing activities and sales outcomes is filled with assumptions rather than evidence. The result is not just wasted budget—it is strategic paralysis, where no one can agree on what is working and leadership defaults to last year's allocation because it feels safer than guessing.
Marketing analytics is the discipline that closes that gap. At Meraki Research, we treat it not as a reporting exercise but as a strategic practice—one that connects customer behaviour signals to campaign performance, isolates what is genuinely driving customer engagement, and gives leadership the clarity to reallocate resources toward the highest-impact marketing strategies. We bring the rigor of primary research methodology to the speed that marketing teams need, blending econometric modelling with consumer behaviour expertise that pure-play analytics firms simply do not have.
Our clients include mid-market and enterprise brands that have outgrown gut-feel marketing decisions. They come to us after realizing that more dashboards do not equal more insight—and that answering the right questions about consumer response requires analytics frameworks built for their specific business, not generic platform templates. We have helped organizations across retail, financial services, healthcare, CPG, and technology make smarter marketing investments that are measurable, defensible, and tied to revenue.
Our Approach: The Meraki Campaign Intelligence Framework
We developed the Campaign Intelligence Framework to bring structure to the inherently messy landscape of multi-channel marketing campaigns. It is a five-phase methodology designed to connect spend to outcome at every level of the funnel, from initial awareness through to conversion and customer retention.
Phase 1: Data Architecture and Integration
Before any analysis begins, we audit every source of marketing data your organisation generates—ad platforms, CRM, web analytics, email systems, point-of-sale, offline touchpoints, and call centre logs. We assess not just what data exists but how it flows, where identities break, and what gaps undermine measurement. We then build a unified data layer that resolves identity across channels, standardizes metrics, and eliminates the double-counting that plagues most multi-platform environments. This is foundational work that most teams skip, and it is the single biggest reason their attribution models later fall apart. Without clean, connected data, even the most sophisticated model produces misleading decisions.
Phase 2: KPI Alignment and Measurement Design
We work with your marketing and finance leadership to define what performance actually means for your business. That means mapping marketing activities to specific business outcomes—not vanity metrics like impressions or raw clicks, but indicators that connect to pipeline, revenue, and customer lifetime value. We design measurement frameworks that distinguish between leading indicators (engagement, awareness lift, brand consideration) and lagging indicators (sales, retention, share of wallet). This phase also establishes the baseline against which all future optimisation will be measured, ensuring that when we say a campaign moved the needle, we can prove it.
Phase 3: Attribution and Mix Modeling
This is where the heavy analytical lifting happens. Depending on your data maturity and channel complexity, we deploy multi-touch attribution modelling, marketing mix modelling (MMM), or hybrid approaches that combine the strengths of both. We test multiple models against holdout data to determine which best reflects your actual consumer journey—not which one tells the most flattering story. Our analysts have deep expertise in both algorithmic and econometric approaches, and we are transparent about the assumptions behind each. We also model interaction effects between channels—for example, how paid social amplifies the impact of email, or how brand search absorbs credit from display campaigns that actually initiated the journey.
Phase 4: Insight Synthesis and Optimization
Raw model outputs are not insights. We translate attribution weights, elasticity curves, and saturation points into plain-language decisions: which channels are under-invested, which marketing campaigns are past the point of diminishing returns, and where reallocation of resources will produce the greatest incremental lift. We present multiple ways to optimise that are practical given your budget constraints and organizational realities. This is not a theoretical exercise—we build scenario models that let you see the projected impact of specific budget shifts before you commit, so your marketing strategies are backed by evidence rather than optimism.
Phase 5: Ongoing Performance Monitoring
Markets shift. Customer engagement patterns evolve. Competitive dynamics change. We build monitoring systems and cadences that keep your marketing analytics current—not something you revisit once a quarter and find stale. This includes automated alerting for performance anomalies, monthly optimisation reviews, and quarterly model recalibration. We also establish governance around how the organisation uses analytical outputs, so that decisions made in one department do not undermine marketing strategies optimised in another. The goal is a living analytical ecosystem, not a one-time report.
When Marketing Analytics Is the Right Investment
This service fits when you need to answer fundamental questions about marketing effectiveness with evidence rather than opinion. Common fit conditions include:
- You spend across five or more channels and cannot confidently rank them by true contribution to revenue.
- Your marketing and finance teams disagree on what marketing is delivering, because they are looking at different data and different definitions of success.
- You are planning a significant budget shift—launching new marketing campaigns, entering new markets, or cutting spend—and need an analytic foundation for those decisions.
- Customer acquisition costs are rising and you need to understand which marketing strategies are still efficient and which have hit saturation.
- Your organisation has data but not insight—plenty of dashboards, but no coherent narrative about what is working and why.
- You are under pressure to prove marketing ROI to a board, investors, or a new executive team that wants accountability.
This is not the right service if you are looking for a tool implementation (we are methodology and insight, not software vendors), or if your marketing spend is concentrated in a single channel with straightforward last-click measurement. We are most valuable when complexity is the problem—when the consumer journey crosses channels, when offline and online intersect, and when standard platform reporting cannot answer the questions that matter.
What We Deliver
Every engagement produces a clear set of outputs tailored to your organisation:
- Unified Marketing Data Model: A documented, integrated data architecture connecting all channels and touchpoints, with identity resolution logic and data quality standards.
- Attribution Analysis Report: A detailed breakdown of channel-level and campaign-level contribution to key business outcomes, with confidence intervals, model diagnostics, and sensitivity analyses that show how results change under different assumptions.
- Optimization Roadmap: Specific, prioritized recommendations for budget reallocation, marketing strategies refinement, and campaign sequencing—with projected impact estimates for each scenario.
- Executive Dashboard: A live or periodically updated view of the metrics that matter most to leadership, designed for decisions rather than decoration, including trend lines, benchmarks, and alert thresholds.
- Technical Documentation: Model specifications, data dictionaries, and methodology notes for your internal analytics team, ensuring full transparency and the ability to maintain and extend our work.
- Quarterly Business Review Template: A structured format for ongoing marketing performance reviews that keeps the analytical insights alive in regular business rhythm.
Timelines vary by scope: a focused attribution project for a single market typically runs six to eight weeks; a full multi-market marketing mix model with ongoing monitoring is a twelve- to sixteen-week initial engagement with monthly cadence thereafter.
Industry Applications
Retail and E-Commerce: We help retailers untangle the interplay between digital marketing campaigns, in-store promotions, and seasonal consumer behaviour to optimise spend across an increasingly fragmented path to purchase. Our models account for the cannibalization effects between online and offline channels that most attribution tools ignore.
Financial Services: For banks, insurers, and fintechs, we model the long customer acquisition cycle where marketing activities at the top of the funnel may not convert for months—requiring patience-aware attribution that most off-the-shelf tools cannot handle. We also incorporate regulatory constraints on messaging into our optimisation recommendations.
CPG and Consumer Goods: We support brand teams in measuring the impact of trade promotions, digital media, and channels like retail media networks on both brand equity and short-term sales lift. Our models separate the effects of price, distribution, and media—so you know what your marketing actually contributed versus what happened because of external factors.
Healthcare and Pharma: With constraints on direct-to-consumer messaging and multi-stakeholder decisions, healthcare marketers need analytics that respect regulatory boundaries while still measuring impact on HCP engagement and patient outcomes. We bring both the methodological rigor and the domain sensitivity this practice requires.
Technology and SaaS: We help tech companies connect content marketing, demand generation, and product-led growth signals into a unified performance view that accounts for long sales cycles and multi-touch buying committees. Our models handle the complexity of freemium conversion, trial-to-paid attribution, and expansion revenue across diverse customers and buying committees.
Hospitality and Travel: For brands where seasonality, competitive pricing, and consumer sentiment shift rapidly, we build real-time analytics that adapt budget allocation week by week, incorporating external signals like search trends, weather, and competitive pricing into the optimisation model.