The top marketing data sources in 2025 (and how to integrate them for smarter insights)

A Spring 2024 Insights report from The CMO Survey reveals that over 60% of companies now rely on more than 20 martech tools. Yet the resulting disconnected data from so many marketing data sources makes fast and confident decisions harder to achieve. 

Marketers have more data than ever, but less clarity.

That’s why marketers use unified platforms like Funnel to turn raw data into intelligence — so every decision is grounded in truth.

So what data sources should you be using to drive more effective marketing strategies and make smarter budget decisions? The following insights show how leading teams use connected intelligence to move from fragmented reporting to measurable growth.

Why does unifying your marketing data sources matter?

Marketing teams have hundreds of data sources at their disposal, each speaking a different language. APIs change monthly. Metrics get renamed or deprecated without warning. Reports break. Teams lose hours stitching data together just to answer basic questions like where spend went or which campaign drove conversions. . The result: teams lack control and can’t move fast, and leaders lose confidence in the numbers.

Funnel fixes this by unifying, standardizing and safeguiding your marketing data so it’s always accurate, comparable and ready to use.

Funnel’s Data Guarantee

Once Funnel ingests your marketing data, it’s yours permanently. Unlike pass-through tools, Funnel preserves history and ensures reports stay consistent even when APIs or platforms change.

• Historical permanence: If attribution windows or metric names shift in the source , your Funnel data remains unchanged.
• No gaps or broken reports: If an API goes down, Funnel retains the last known good data so dashboards never go blank.
• Reliable audit trail: Raw spend is always preserved alongside normalized data so finance teams can reconcile against invoices with confidence.

2025 mini-trend: Privacy, speed and trust define the new data advantage. Teams that connect governed, real-time data gain compounding returns in performance and agility.

Why this matters right now

• Cross-channel truth: Paid media specialists struggle to compare ROAS when every platform reports differently.
• Pipeline clarity: Marketing and data teams struggle to link CRM opportunity data with web conversions, making it hard to see which campaigns truly drive pipeline. 
• Ecommerce proof: Leaders waste time proving a revenue spike came from a specific campaign because storefront and ad data don’t align.
• Compliance by design: Privacy rules (GDPR/CCPA) and third-party cookies loss demand first-party strategies that keep data governed without slowing the team. 
• Speed to action: When performance data lags, teams overcorrect or miss emerging trends. Daily visibility doesn’t mean constant tinkering — it means knowing when to act and when to let the algorithms run their course. 

When your data is unified, governed and always up to date, your team stops spending time fixing issues and starts focusing on strategy.

You can make better calls about what’s working, what’s changing and where to invest next. All done with confidence that your insights reflect reality and not reporting errors.

That’s the real benefit of connected, trustworthy data: fewer blind spots, faster learning cycles and a foundation you can build on for measurement, modeling and long-term growth.

Platforms like Funnel make this possible by automating data collection, preserving history and keeping performance metrics consistent, so you can focus on marketing decisions and not maintenance.

What are the top marketing data sources in 2025?

In 2025, most teams run sprawling stacks, yet according to The CMO Survey, companies use only about 56% of the martech they buy. With US digital ad growth dipping below 10% this year, according to Emarketer, the edge comes from connecting the right sources to a centralized marketing intelligence platform like Funnel, rather than trying to bridge data gaps between tools with more plugins, connector tools or spreadsheets.

Gather data from the sources that matter, unify everything within a dedicated marketing intelligence platform and your team will have ready access to valuable insights to measure past success, optimize marketing efforts and improve ROI. With the bigger picture in mind, let’s look at the key marketing data sources that matter most in 2025 and how to unify them.

1. Paid media and advertising platforms

Paid media sits at the core of most marketing strategies, making it the first test of how well your data foundation works. Every campaign click and conversion depends on accurate spend data flowing from these platforms into a single source of truth.. Every click, view and conversion generate valuable signals, but those signals lose meaning when they live in separate systems. To make smart decisions about spend, marketers need one connected view that shows how all channels perform side by side. 

Why this data source matters

Paid media is where most marketing dollars still go, and it’s also where small reporting inconsistencies multiply fastest. Each platform has its own metrics, attribution windows and data refresh cycles. That means even basic comparisons — like ROAS across Google, Meta, LinkedIn and TikTok — can be misleading if the data isn’t standardized. In 2025, competitive advantage doesn’t come from using more ad platforms, but from unifying their insights so you can allocate budgets based on evidence, not guesswork.

What are the key paid media and advertising platforms in 2025?

• Google Ads: the leader in capturing search intent and reaching users on YouTube.
• Meta Ads: still central to social advertising with powerful audience targeting.
• LinkedIn Ads: essential for B2B marketing campaigns and firmographic targeting.
• TikTok Ads: rapidly growing short-form platform with high engagement.

What are paid media and advertising platforms’ current challenges?

• Each platform reports differently, making cross-channel ROAS comparisons unreliable.
• Attribution windows and modeled conversions vary, creating conflicting numbers.
• Time zones, currencies and campaign naming drift, causing reporting errors if you’re not using a platform that can normalize these fields, like Funnel.

How to connect and standardize

• Bring spend, impressions, clicks, and conversions from every ad platform into one dataset.
• Normalize key metrics and naming rules so performance is measured on equal footing.
• Combine ad data with analytics or CRM outcomes to see what happens after the click — using privacy-safe CAPI integrations to feed verified conversion signals back to ad platforms.

What this unlocks

A single, trustworthy view of cross-channel performance. You can see which platforms truly drive profitable growth, reallocate budgets with confidence and move from reactive reporting to proactive optimization. Connected in Funnel, this turns fragmented ad data into a foundation for continuous performance insight.

With spend unified, you can prioritize the platforms that actually deliver profitable growth.

2. Retail media networks (RMNs)

Retail media is the fastest-growing corner of digital advertising and one of the hardest to measure. Every sale, impression and loyalty point sits behind a retailer’s wall, which makes connecting it with the rest of your marketing data a challenge. The teams that unify retail and digital performance in one view gain a powerful edge in understanding true product-level ROI.

Why do retail media networks matter in 2025?

Retail media networks are now a core part of the performance mix. Global spending is forecast to hit $176 billion in 2025 (WARC), and retailers like Walmart and Amazon are turning media sales into profit engines. RMNs sit closest to the point of purchase, offering unmatched visibility into what shoppers actually buy — but only if that data can be connected with search, social and CRM performance.

What are the key retail media network platforms in 2025?

• Amazon Ads: the biggest name in retail media with unmatched reach.
• Walmart Connect: scaling fast and pushing into connected TV.
• Instacart Ads: strong grocery delivery footprint with high-intent households.
• Kroger Precision Marketing: loyalty-based targeting and offline-online linking.

The challenge

• Every RMN uses its own reporting format and category structure, making cross-network analysis nearly impossible.
• Retail network data is often locked in walled gardens with limited export access.
• SKU-level conversions are difficult to align with digital campaign data.
• Reporting delays and limited export options slow decision-making.
  
  

How can I integrate my RMNs with Funnel?

• Import retail-media performance data from networks like Amazon Ads, Walmart Connect and Instacart into one unified view.
• Map product and campaign data to a consistent taxonomy — without heavy manual cleanup — so every SKU tells the same story across channels.
• Blend retail-side conversions with digital ad and CRM signals to build a single view of sales performance.
  
  

What this unlocks

Teams can finally measure true product-level ROI across retail and digital. You can see which placements and promotions actually drive profits, connect retail campaigns to broader acquisition and retention efforts, and plan future media spend with confidence.

Connected in Funnel, retail media data becomes a bridge between on-shelf performance and full-funnel growth.

3. CRM and CDP platforms

Customer relationship management (CRM) and customer data platform (CDP) systems play a major role in connecting marketing with revenue outcomes. They hold the most complete view of how prospects turn into customers, helping teams identify pain points and optimize every interaction.

The data that matters most for performance measurement isn’t personal. The opportunity, pipeline and revenue signals stored in these systems are what tie marketing investment to business results.

Why do CRM and customer data platforms matter?

According to Kixie, the CRM market is set to exceed US$112 billion in 2025 as businesses double down on first-party data and AI-driven customer engagement. Research from S2W Media shows that companies using first-party data strategies report up to a twofold increase in conversion rates and up to 30% lower acquisition costs compared with those relying on third-party data.

CRM and CDP platforms have become indispensable as sources of high-quality first-party marketing performance data that feed every stage of the funnel.

This first-party data forms the backbone of modern measurement, enabling accurate MMM and attribution without breaching compliance.

What are the key CRM and customer data platforms in 2025?

• Salesforce: enterprise-grade CRM with a large partner ecosystem and strong AI roadmap.
• HubSpot: a mid-market favorite with built-in marketing automation and easy onboarding.
• Zoho CRM: a cost-effective SaaS solution that competes on flexibility and localization.
• Microsoft Dynamics and ActiveCampaign: for teams focused tightly on Microsoft stack automation or conversational automation.

What are CRM and customer data platforms’ current challenges?

• Privacy and governance rules such as GDPR and CCPA require careful management of customer data.
• CRM data often lives in silos apart from ad spend signals, creating blind spots across the funnel.
• There’s a disconnect between opportunity or revenue stages and upstream campaign attribution.
• Pipelines and campaign structures can drift out of sync without regular reintegration.

How can I connect CRM and CDP data with Funnel?

Funnel integrates with aggregated performance data from CRMs and customer platforms, not PII. It connects opportunity, revenue and pipeline metrics alongside ad and analytics data to give marketers a clear link between spend and business outcomes.

• Import aggregated opportunity or revenue data into Funnel, not individual contact records.
• Standardize lifecycle stages and lead statuses so they align with campaign objectives.
• Maintain privacy and governance by keeping personal data within the CRM while Funnel handles normalized performance metrics.
• Combine opportunity data with campaign activity to connect upper-funnel signals to closed revenue.

What does this unlock?

A connected, privacy-safe view of marketing and revenue performance that shows how first-party data links spend to customer interactions and downstream value. Teams can see which channels and campaigns generate the highest returns, optimize investment accordingly and prove marketing impact without compromising compliance.

4. Ecommerce and marketplace platforms

Ecommerce platforms turn marketing data into revenue proof points. They show what customers actually buy and when, but that value is often hidden behind disconnected systems. Unifying ecommerce, marketplace and ad data is what turns transactions into insights marketers can act on.

Why do ecommerce and marketplace platforms matter?

Ecommerce platforms generate the clearest proof of marketing effectiveness: orders and revenue. Yet marketers often struggle to connect these numbers back to campaigns. A spike in Shopify sales may look impressive, but without linking that revenue to Meta or Google Ads, you can’t tell which campaign delivered the lift. Marketplaces like Amazon Seller Central or eBay Seller Hub add another layer of complexity because they provide transaction data in formats that rarely match ad platform reporting.

What are the key ecommerce and marketplace platforms in 2025?

• Shopify: dominant among DTC brands with built-in analytics.
• Magento (Adobe Commerce): favored by enterprise retailers for its flexibility.
• WooCommerce: popular open-source option for small and mid-sized stores.
• Amazon Seller Central: the most widely used marketplace for third-party sellers.
• eBay Seller Hub: still important for niche and international categories.

What are the current challenges?

• Product data is fragmented: SKUs, categories and pricing rules vary by store or region.
• Revenue signals live in ecommerce platforms while ad spend lives elsewhere, creating reporting silos.
• Marketplace reports are delayed or formatted differently, slowing comparisons.
• Without integration, teams waste time exporting CSVs and manually aligning sales with campaigns.

How can I connect ecommerce and marketplace platforms with Funnel?

• Connect Shopify, Amazon Seller Central or Magento into Funnel alongside ad data.
• Use transformation rules to standardize product IDs, categories and currencies so metrics line up across markets.
• Map orders and revenue to campaign structures to calculate product-level ROAS and margin contribution.
• Push cleaned ecommerce data into BI tools or warehouses to combine it with CRM and analytics.
• Manage multi-currency and regional reporting automatically in Funnel to keep global performance consistent and comparable.

What does this unlock?

Clear attribution of revenue to specific campaigns and channels. 

Marketers can see which products or categories are actually profitable, shift spend toward ads that drive high-value orders and build forecasts on real customer lifetime value rather than guesswork.

5. Offline & finance signals

Offline and financial data sources, like point-of-sale transactions, call-center logs and cost or margin data from finance systems, provide the link between marketing activity and real business outcomes. These signals feed directly into Funnel’s MMM workflows to prove true incremental ROI.

Why do offline signals matter?

For MMM and ROI analysis, these signals are essential to prove not just campaign efficiency but true profitability. Without them, marketing teams risk optimizing for clicks or conversions that look good in isolation but don’t translate into sustainable growth.

What are the current challenges?

• Fragmented systems: Offline and finance data often sit in custom ERP, POS or call-center tools that don’t export easily.
• Data mismatch: Cost, margin or offline sales are reported differently from digital campaign data, making reconciliation slow and error-prone.
• Integration complexity: Unlike ad platforms, these systems rarely have ready-made connectors, so getting data into one analysis framework is difficult.

How can I connect offline marketing data sources with Funnel?

• Custom connectors & flat file uploads: Offline and finance data can be brought into Funnel via CSV, Google Sheets, SFTP or API-based custom connectors.
• Normalization & blending: Once imported, Funnel applies the same transformations as with ad data, aligning currencies, time zones and naming, so cost/margin and offline sales can be compared directly with media spend.
• Export for modeling: Many teams export Funnel’s clean marketing dataset into a warehouse or measurement tool where offline sales and margin data also live. That’s where MMM and ROI models can be run effectively.

What does this unlock?

A unified view of performance that goes beyond ad spend. Marketers can:

• Combine media efficiency metrics with cost/margin data to calculate ROMI, not just ROAS.
• Connect campaign activity with offline outcomes (in-store sales, call-center conversions).
• Feed consistent signals into Funnel’s MMM and attribution workflows for evidence-based budget allocation and to prove true incremental ROI.

6. Analytics and measurement tools

Once revenue data is unified, the next step is understanding the behaviors behind it. Analytics and measurement platforms translate interactions into insight, showing how people move from first touch to final purchase. When connected with spend and revenue data, they turn isolated metrics into full-funnel intelligence.

Why do analytics and measurement tools matter?

Analytics platforms show how people actually behave on your site or app, but their real value comes when that behavioral data is tied back to marketing spend. GA4 might tell you that conversions increased by 20%, but unless you connect that to Meta or LinkedIn campaigns, you won’t know what drove the lift. Tools like Adobe Analytics, Mixpanel and Amplitude give detailed event tracking, yet they rarely integrate neatly with ad or CRM data out of the box.

What are the key analytics and measurement tools in 2025?

• Google Analytics 4 (GA4): the default for tracking site and app behavior.
• Adobe Analytics: an enterprise-level solution with highly customizable reporting.
• Mixpanel: product-focused analytics built for granular event tracking.
• Amplitude: strong in behavioral cohorts and customer journey mapping.

What are the current challenges with analytics and measurement tools?

• Attribution models differ across analytics and ad platforms, leading to conflicting ROI numbers.
• GA4’s sampling and learning curve frustrate many teams.
• Web and app event taxonomies rarely match campaign structures, creating blind spots.
• Data often stays locked in analytics platforms, disconnected from CRM or spend data.

How can I connect analytics and measurement tools with Funnel?

• Bring GA4, Adobe or Mixpanel into Funnel alongside ad and CRM data.
• Standardize event names and map them to campaign objectives and attribution windows.
• Combine behavioral events with spend and revenue data for cross-channel performance models.
• Push unified datasets into BI or warehouses so executives see one version of the truth across channels.

What does this unlock?

The ability to connect user behavior with marketing inputs. Teams can see not only that a conversion happened but which campaign influenced it, compare attribution models with confidence and build dashboards that reflect the full customer journey. 

This shifts analytics from a rear-view reporting tool into a forward-looking driver of marketing budget and marketing strategy across the entire customer lifecycle.

7. Emerging sources

Emerging and external data sources, such as brand sentiment, social listening, surveys and industry benchmarks, help marketers understand not just what happened, but why. These signals capture early shifts in perception and intent long before they show up in revenue or performance metrics. In a world where generative AI floods channels with content and consumer trust fluctuates, monitoring how audiences feel and react gives marketers a valuable early warning system.

When combined with spend and performance data, these indicators complement quantitative models like MMM. While they don’t feed directly into regression frameworks, tracking sentiment and brand health alongside modeled outcomes helps teams interpret why performance changes and anticipate where growth might come next. Blending these qualitative insights with your measurement stack connects brand perception with business impact, turning soft signals into strategic context for decision-making.

Why all these marketing data sources matter

Each of these data sources plays a distinct role in shaping marketing intelligence. When viewed together, you can see how unified data turns complexity into clarity and drives smarter decisions at every level.

By connecting every source and feeding those signals into Funnel’s measurement models, marketers can move past simple reporting and start answering bigger strategic questions. Once you have your data sources connected and analysis-ready, the next question is, how future-proof is your marketing intelligence?

What are the key trends shaping marketing data? 

Marketing data sources are multiplying, but the forces shaping how they are used are changing just as fast. To stay ahead, marketers need to understand the shifts that will determine which signals matter most and how decisions get made at scale.

Signals over volume

Marketers are moving from chasing more data to focusing on better signals. Funnel’s MMM and attribution tools help teams uncover which metrics, like SKU-level conversions or CRM pipeline velocity, correlate with true incremental outcomes, so they can see which activities actually drive growth. Qualitative indicators, such as brand sentiment or customer confidence, then add context to explain why performance changes.

The rise of retail as a performance channel 

Retail media networks are rapidly evolving from experimental channels into core budget items. According to Nielsen, in the US, retail media spend is expected to grow by 20% in 2025 alone, far outpacing the broader ad market. That means retail signals are moving from “nice to have” to essential context for full-funnel attribution.

AI-assisted data governance

More teams are adopting AI to automate data quality checks, anomaly detection and compliance monitoring. That means fewer surprises from bad or non-compliant data and faster pipelines with less manual friction.

Shortening the distance from data to decision

Real-time and streaming analytics are no longer optional. In fast-moving media environments, marketing teams that shorten the loop from “raw data arriving” to “budget-shift decision” have a competitive edge. 

Proof over promise

As retail media and first-party data channels grow, CMOs and CFOs are demanding more rigor in measurement. Marketing teams now need transparent, model-based approaches — such as MMM and incrementality workflows — that can prove real incremental ROI in board-level discussions.

All these trends raise an important question: where should you start? Not every data source deserves equal attention, so it helps to have a clear way to decide which ones to prioritize first.

How do I prioritize my data sources? 

Not every marketing data source deserves the same level of attention. Here are best practices for deciding which sources to connect first and how deeply to integrate them.

Factors to consider

• Business goals: Are you focused on acquisition, retention or lifetime value? Paid media sources may matter most for growth, while CRM data is essential for retention.
• ROI potential: Which data sources most clearly connect marketing activity to revenue or savings? Retail media data captures direct, bottom-funnel sales impact, while analytics platforms reveal where to reduce wasted spend and improve efficiency.
• Compliance risk: Some sources handle personal data subject to GDPR or CCPA. These need stronger governance before integration.
• Integration readiness: Connectors differ in stability and complexity. Prioritize sources that can be automated instead of those that require heavy manual work.

How Funnel helps you prioritize your marketing data 

Funnel streamlines this prioritization process. Instead of debating which sources can be integrated, teams can see which of the 500+ connectors are available out of the box. Governance settings ensure that only aggregated, non-PII performance data flows into the platform, keeping privacy intact while enabling unified analysis. From there, all connected sources feed into advanced measurement workflows that reveal ROI with confidence.

What this unlocks

With Funnel, you gain a clear roadmap for integration. Marketers avoid analysis paralysis and move quickly from high-value sources into broader enrichment. This ensures data pipelines align directly with business strategy instead of being built on convenience alone.

How to integrate marketing data sources (step by step)

Once you know which data sources matter most, the next step is turning them into a single reliable dataset that supports faster decisions. The process is less about technical plumbing and more about building a repeatable workflow that teams can trust.

1. Define your business objectives

Decide what questions you want to answer. For example, do you need to prove which channels drive incremental sales, or do you want to forecast how budget cuts would affect pipeline growth?

2. Audit your existing data sources

List every platform you use, from ad accounts to ecommerce storefronts to CRM systems. 

Identify which ones hold the signals most relevant to your objectives.

3. Connect high-priority sources through Funnel

Use Funnel’s 500+ connectors to automate data ingestion from ad platforms, CRMs, retail media and analytics tools. Start with the sources that directly impact revenue, then add supporting signals.

4. Normalize and govern your data

Funnel automatically cleans and standardizes metrics like spend, clicks and conversions. Add governance rules to protect consented data and ensure compliance with GDPR and CCPA.

5. Feed data into measurement models.

Push unified datasets into Funnel to run attribution and marketing mix modeling (MMM). This step reveals how channels work together and which signals drive incremental growth.

6. Deliver insights where they’re needed

Send modeled marketing data into dashboards, warehouses, or BI tools so every stakeholder works from a single, consistent view of performance. In a marketing data warehouse, teams can align Funnel’s aggregated marketing data with other business datasets, such as finance or CRM outcomes, to see how marketing activity connects to revenue and profitability. Automate reporting so decisions are always based on the most current numbers.

What does this unlock?

By following this workflow, marketers stop wasting time stitching spreadsheets and start running advanced measurement. The result is faster budget reallocations, clearer ROI and a stronger foundation for long-term strategy.

Automated insights at scale with Funnel

Unifying your marketing data sources enables you to turn data into insights. That’s where a trustworthy, scalable marketing intelligence platform comes in. Funnel transforms disconnected signals into automated intelligence marketers can trust. Data from all your channels flows into Funnel, fueling MMM, attribution and predictive models with refreshed data daily. 

Connectors are proactively maintained, ensuring that insights remain reliable even amid API updates and other platform changes, and no-code dashboards give marketing access to self-serve analytics. Your marketing team gets actionable insights fast, without the headaches that come with manual reporting and dependency on data or IT. Funnel delivers the consistency, scale and speed modern marketing requires, turning reliable information into confident decisions that make a positive business impact. Book a demo and start turning data into intelligence today.