What marketers can learn about blending data from intelligence agencies

Picture an analyst deep inside a government intelligence bunker. Screens flicker with satellite images, intercepted messages, market reports and agent field notes. They’re not looking for any one signal. They’re looking for connections. With enough cross-referenced inputs, they can anticipate geopolitical shifts, threats and opportunities before they happen.

Now, cut to the average marketer. Surrounded by dashboards, ad reports, web metrics and flickering lights, they’re also trying to predict behavior and steer strategy. But their inputs are often narrow, limited to digital performance metrics that only show part of the picture.

The result? Blind spots. Misleading signals. Poor decisions masked by impressive-looking charts.

Intelligence agencies know that the best insights come from connecting the dots. They don’t just track one feed or source. 

Want to become the 007 of marketing intelligence? Start integrating data across platforms, campaigns and customer touchpoints so you can gather deep insights, spot patterns and make confident decisions. The more sources you combine, the clearer the truth becomes.

Why intelligence agencies are masters of insight

Marketers can learn a lot from intelligence work. Spy agencies don’t just gather more data. They build systems that make sense of it. Insight rarely comes from a single source. It comes from revealing hidden patterns and getting a more holistic view when information is layered, cross-checked and validated across multiple inputs.

An intercepted message might raise a flag, but without context, it means very little. Pair it with satellite images and financial activity, and the picture sharpens. Suddenly, action becomes possible.

Marketing works the same way. Clicks, impressions and conversions on their own don’t tell you much. But put them together, and patterns start to emerge. A dip in one channel, a spike in another, a delay in revenue conversion: these signals might point to a shift in customer behavior, a gap in your funnel or an opportunity you might otherwise miss.

Spy agencies deal in foresight. They can’t afford to react slowly or act on incomplete information. The same is true for marketers. The faster you can connect the dots, the faster you can make a confident call. You don’t need perfect data. You just need enough of the right sources to see the shape of what’s happening and take a smart risk.

Insight isn’t hiding in one dashboard or one dataset. It lives in the intersections. And the marketers who learn to read those intersections will move faster, see clearly and stay ahead. 

But to read these intersections, you need to overcome the most significant barrier marketers face when gathering marketing intelligence: incomplete information. 

Marketers have too much of one kind of data

Marketers are swimming in data. But most of it comes from the same place: digital performance channels. Web analytics, email engagement, paid media dashboards, social metrics. These are easy to access, constantly updating and baked into day-to-day reporting. Sounds great, right? 

So, what’s the problem?

Well, the problem isn’t that this data is wrong. It’s incomplete. When teams rely too heavily on what individual platforms report, they risk missing the bigger picture. A campaign might look like a hit based on clicks or impressions, but if offline sales are flat or customer retention is slipping, those conversions can’t tell you the whole story.

In fact, some of the most valuable signals live outside the marketing dashboard. Consider:

1. Sales pipeline data that shows how fast deals are moving
2. Customer service logs that flag friction in the buying journey
3. Financials that connect marketing spend to real business impact
4. Market trends and economic signals that shift demand

When these inputs are siloed, buried in spreadsheets or owned by other teams, marketing runs with blinders on.

This is the kind of trap intelligence agencies are trained to avoid. They never trust a single stream of input because they know it can’t give them the full picture. The same principle applies here. To move beyond digital-first thinking, marketers need to ask a different kind of question: what are we not seeing?

Intelligence analysts are trained to avoid the kind of tunnel vision that relying on one type of measurement — like last-touch attribution, for example — can cause. Instead, they rely on a structured process that forces them to slow down, cross-check sources and validate what they think they know. 

It’s not enough to just collect more data, either. The focus has to be on how that data flows through a pipeline cycle that turns raw inputs into real insight.

Marketers can borrow this same intelligence framework, which offers a practical roadmap for collecting, organizing and analyzing diverse data sources with a focused intent.

Your mission: turning raw data into actionable insights 

Top intelligence agencies use a process called the intelligence cycle. It helps them turn scattered signals into clear insights that leaders can act on.

Marketers can do the same. You don’t need encrypted dossiers or exploding pens. Just a method. Here's how to gather, decode and deploy your data like a pro:

1. Planning and direction

Every good mission starts with a brief. What are you trying to uncover? What data will inform your decision?

You need to define your intel objective.

For example, say you’re planning how to allocate next year’s Q1 and Q2 marketing budget. The questions you’d ask aren’t just “what were our results?” but:

• What data do we need to understand what worked and why?

• Were results impacted by seasonality, macro trends or a one-off event?

• Are economic forecasts pointing to a downturn?

• Are competitors ramping up? Launching new products?

• What do we expect from each channel next year under different conditions?

Your job here is to frame the problem like an analyst, not an operator. Define the mission first. How you apply the data to this mission comes second.

2. Collection

Now gather your sources. The best intelligence is never one-dimensional. It blends signals from across the landscape.

Don't just look at ad platforms. Pull from:

• Sales and revenue data

• CRM and retention metrics

• Support logs and voice-of-customer feedback

• Market forecasts and economic indicators

• Competitive moves and pricing changes

You’re not collecting everything. You’re collecting what helps answer the questions you set in step one. Treat every data source like a field agent feeding you raw intel.

3. Processing

Before you can analyze anything, your data needs cleaning. Raw intel is messy.

This is where you:

1. Fix typos, nulls and duplicates
2. Align naming conventions (yes, “spring_sale_q1” and “Q1 Spring Sale” need to match)
3. Standardize formats for dates, currencies and metrics (This is something Funnel can help you with.)

Think of this step like decrypting field reports. Without it, your dashboards can lie, and your conclusions will be wobbly.

4. Analysis

Now the real work begins. This is where you pull patterns from the noise and extract meaning.

Say you’re reviewing Q1 spend from last year. You might notice paid social performed well during seasonal spikes, but email quietly delivered better long-term value. You see a sharp dip in search traffic after a Google update. You spot a lift in sales that lines up with a competitor's product recall.

Good analysts don’t stop at what happened. They uncover why and what to do about it next.

5. Dissemination

Intel is only useful if it reaches the right hands, at the right time, in the right format.

1. Your CMO needs a clear recommendation with upside and risk.
2. Your media buyer wants channel-level performance and pacing alerts.
3. Your product team might need insight into what messaging is resonating.

Tailor the message to the audience. Skip the fluff. Focus on what they need to act.

6. Feedback

Every mission ends with a debrief. Did the insights drive better outcomes? Did the decision land? Did reality match expectations?

Loop what you’ve learned back into the next cycle. Sharpen your questions. Improve your sources. Strengthen your analysis. The goal is not a perfect report; it’s a smarter next mission.

This cycle keeps your marketing intelligence work grounded and iterative. It’s a way to escape dashboard dependency and replace gut decisions with disciplined, data-backed strategies that impact your business reality in meaningful (and measurable) ways.

To move beyond surface-level reporting, the next step is to focus less on how much data you have and more on how you turn that data into meaning.

Marketers need better insights, not just more sources

To operate like a marketing 007, you don’t need more data. You need to get better at synthesizing your intelligence. The real advantage comes when you stop looking at numbers in isolation and start connecting signals across your ecosystem. Performance metrics mean more when tied to financial impact. Audience trends reveal more when viewed alongside market shifts. That’s how you move from “what happened” to “why it happened” and can determine what to do next, faster. 

As futurist and trend expert Eric Garland says, “Intelligence becomes valuable when it clarifies cause and effect.” The real skill is learning to spot the chain reaction behind the outcome. Not just X leads to Y, but all the variables that made Y inevitable.

Eric Garland’s “Knowledge Value Chain” explains how raw data becomes valuable through a four-step progression:

1. Data: These are raw, unfiltered facts (e.g., a list of purchases or ad clicks).
2. Information: This is data with basic context (e.g., daily sales by region).
3. Knowledge: Here you have connected information that forms a broader understanding (e.g., campaign X performed better in region Y during Q4).
4. Insight: Now you’re getting somewhere with proven knowledge applied to a real-world decision (e.g., invest more in region Y during holidays, but adjust messaging to target product Z).

Most marketing teams stop at the information or knowledge stages. They report on what happened, but not what it means. As a result, they can’t derive a meaningful next step that is fully supported by insight.

For example:

• Web traffic is down. But is it a real drop in demand, or are people just visiting stores instead? Combine it with POS data to find out.

• ROAS looks strong. But are those customers sticking around? Match it with LTV data to see if the returns are actually profitable.

• Email clicks are up. Great. But did that increase move the retention needle? Layer on churn metrics to see if it helped retain more customers.

Insight lives in the overlap. It’s what happens when you connect the dots across teams, tools and touchpoints. That’s where the real story starts to emerge.

Of course, not all intel is useful. You don’t need to know what Zuckerberg ate for breakfast to decide whether to invest in more video. The trick is knowing which signals are worth watching and which are just noise. So what types of marketing intelligence are worthwhile? And how do you blend them to get the clearest possible picture?

Types of marketing intelligence worth blending

Intelligence agencies don’t rely on one feed. They blend six core types of intelligence to build a full, reliable picture of what’s happening on the ground. Each type offers a unique perspective — and when combined, they confirm, challenge and clarify each other.

Marketers can use the same approach. By expanding the kinds of data you bring into your analysis, you move from guesswork to foresight. You stop reacting and start anticipating.

Here’s how the intelligence world gathers intel — and how you can mirror it in your marketing operation:

Each type of intelligence serves a purpose. For example, HUMINT gives emotional context, SIGINT shows what people actually do, and FININT ties marketing to business impact.

It’s not just theory. Blending data works. A recent survey shared by business analytics software provider Databox shows that over 90% of companies blend multiple data sources to drive reporting and analysis. And, according to Google, combining marketing data measurement models like MMM and MTA into a unified framework can boost campaign performance by as much as 40% compared to relying only on attribution metrics.

You can use the following tips to start blending your marketing intelligence like a seasoned sleuth.

Spot your blind spots

Most marketers over-rely on SIGINT-style data — clicks, impressions, behavioral metrics — while ignoring financial, qualitative or external signals. That’s when blind spots form. The real insight comes from the mix. When you layer, compare and challenge different inputs, the truth starts to surface.

Be a skeptic from collection to verification

Mapping your data to these categories is step one. Step two is making sure every input you use is trustworthy. Intelligence agencies never act on a single unverified source — they cross-check before they move. Marketers should do the same.

Strong intel means strong decisions, and it starts with better signals.

Don’t trust. Verify.

Not all data is trustworthy. Some is inflated. Some is misattributed. Some just looks impressive on a dashboard but tells you nothing useful. Validation is what separates real analysis from simply moving numbers around.

Here are four ways to pressure-test your data before making a call:

1. Compare across platforms: Does the performance in Google Ads match your CRM or attribution model? Often, it doesn’t.
2. Use internal benchmarks: Do results make sense compared to past campaigns with similar spend, season and audience?
3. Bring in qualitative inputs: Do the numbers align with what customers are saying? If support tickets are piling up, something’s off.
4. Add external context: Could a competitor promo or market shift explain a sudden change? MMM models can help by triangulating inputs over time.

Let’s say a campaign shows a high ROAS in-platform. Great — until you see LTV data showing those customers churn after one purchase. The flashy number turns out to be a mirage. Funnel helps here by blending those inputs automatically so you’re not guessing or juggling spreadsheets.

Skepticism isn’t cynicism — it’s a smart strategy. A good analyst doesn’t fall for the first stat that winks at them. They ask questions, dig deeper and make sure the insight is roadworthy before taking it out for a spin. And while you’re validating the numbers, check the ethics too. Just because you can use a data point doesn’t mean you should. Insight isn’t just about accuracy — it’s about responsibility.

Case in point: when insights outperform silos 

To see the power of actionable insights, picture this: a brand is running a national campaign across paid search, social and out-of-home. Midway through, Google Ads reports a drop in conversions. The team gets ready to cut spend or tweak creative.

But before pulling the plug, they zoom out.

Using MMM analysis, they cross-check and validate:

1. In-store foot traffic, which shows a similar drop in key metro areas
2. Weather reports, which reveal two weeks of heavy rain across those same regions
3. Sales data from online-only regions, which stays steady

Turns out the issue isn’t the campaign. It’s the environment. Pausing would have killed momentum in unaffected regions and wasted media spend.

That insight only emerged by conducting a deeper analysis with regression. If they had relied on ad platform metrics alone, the conclusion would have been wrong and expensive.

This is how intelligence agencies operate. One intercepted message isn't enough. They cross-check with satellite imagery, field reports and financial signals. The goal isn’t to complicate things. It’s to get closer to the truth.

Smart marketing works the same way. It doesn’t chase the first red flag or trust one dashboard to tell the whole story. It looks across inputs, connects the dots and then takes action.

That level of clarity requires structure. Intelligence agencies use fusion centers to combine insights across sources and teams. Funnel helps marketers do the same. It pulls in data from every channel, aligns it across formats and feeds it into your existing tools. No more spreadsheet chaos or missing context. Just one connected view that supports sharper, faster decisions.

Because spotting patterns is great. But building a system that spots them for you? That’s the real win.

How to build your marketing “fusion center”

In national security, fusion centers are where intelligence comes together. Data flows in from multiple agencies, gets standardized and is analyzed by cross-functional teams. The goal is clarity: shared visibility that leads to faster, better decisions.

Marketers can apply the same principle by creating their own internal fusion center. It doesn’t require new headcount or infrastructure. It requires coordination.

Start with these steps:

1. Centralize your data: Bring marketing, sales, finance and operations data into a single, accessible platform. Tools like Funnel automate collection and formatting from dozens of sources.
2. Standardize your metrics: Align naming conventions, date formats and attribution logic so everything speaks the same language. This makes blended reporting faster and cleaner.
3. Create shared dashboards: Build views tailored to different teams: executives, channel owners, analysts. Focus on insights, not just raw numbers.
4. Encourage cross-functional reviews: Bring teams together to review performance from multiple angles. Ask where data conflicts and what gaps need to be filled.
5. Document learnings: Treat analysis like an ongoing product of your business, not just a one-time project. Capture what you learned, how you learned it and what you’ll do differently next time so it becomes ingrained in your company culture.

Fusion centers are not about central control. They’re about shared perspectives. When marketers build them, they move from fragmented reporting to focused insight without losing speed.

Developing marketing intelligence the right way is not just a technical upgrade. It is a mindset shift. The marketers who adopt it gain more than insight; they gain an edge. But making that shift means thinking differently about how data is collected, connected and communicated.

Think like an analyst, act like a strategist

The best intelligence officers don’t rely on a single feed. They connect signals, challenge assumptions and build a fuller picture before making a move. Marketers can do the same.

Insight doesn’t come from piling on more data. It comes from discipline. It involves asking sharper questions, blending the right inputs and treating analysis as a process, not a one-off report.

Whether you’re launching a campaign, setting strategy or briefing the board, the mission is the same: clarity. And clarity comes when you stop chasing isolated metrics and start thinking like an intelligence analyst.

No classified access required. No trench coats or bugged briefcases. Just a system built to connect, validate and act. Funnel helps with that. You bring the questions. We’ll help make sense of the noise.