B2B is a large market, and high-quality leads are worth thousands. The problem is the grind it takes to find the people who are genuinely interested and in the right role, at the right time, with real buying authority.

Tinuiti’s Big Bets for the CMO in 2026 report highlights AI-powered, financial-data-driven business media networks as the next major disruption in B2B marketing. Rather than relying on “looks like” intent, marketers can anchor targeting and measurement in transactions.

What are financial media networks?

Financial media networks are retail media networks (RMNs) for banks, payment platforms and financial tools. They use first-party transaction data to power targeted advertising. Companies in this space build media networks based on real spending patterns, not just web behavior or downloads.

In practice, financial media networks can usually:

• Build audiences based on category spend (for example, SMBs that consistently spend in software, travel, or logistics).

• Distinguish between consumer and business transactions, especially when there are dedicated business cards or business accounts.

• Activate campaigns on their owned surfaces (apps, portals, offer pages) and, in some cases, extend those audiences into broader programmatic inventory.

The key difference from RMNs is that, instead of focusing on cart-level data and SKU-level sales, financial media networks are rooted in payment behavior across multiple suppliers and categories within the same business.

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From retail media to business media

RMNs’ strength is shopper identity and product data. They know which households browse, add to cart and purchase, and can connect ad exposure back to in-store and online sales. That’s a significant advantage for brands seeking to link upper-funnel investments to lower-funnel performance.

​Business media networks (BMNs) extend that idea into B2B by layering in what’s called work identity. This refers to signals that help determine the type and size of the business behind that spend, and the likely role or buying authority of the person making that decision.

Work identity is what B2B marketers have long looked for across multiple platforms. Financial media networks anchor signals in real spend, not temporary content consumption.

AI models are particularly good at learning from this kind of structured, high-signal data. Instead of inferring that someone might be in-market because they read three whitepapers, models can see patterns like:

• The monthly spend in a critical category has suddenly increased.

• New suppliers are being added in adjacent categories.

• Seasonal spikes that line up with budget cycles or hiring waves.

That’s a very different starting point for B2B planning than “someone at this domain clicked an ebook ad last quarter.”

Why financial media networks matter now

B2B lead costs keep going up. Conversion rates, not so much. Recent industry data show that global ad spend is continuing to grow, even as privacy changes and signal loss make it harder to prove what’s working, which only increases the pressure to find higher-quality, durable signals. At the same time, marketing, sales and finance still spend a significant amount of time debating what constitutes a good lead and how much should be allocated to acquire one.

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Financial media networks enable teams to move the debate closer to revenue, as their audiences are built on financial behavior.

Three reasons this matters:

• Better signals. Transaction-level data is inherently closer to the outcome everyone cares about. Instead of optimizing for generic engagement metrics, marketers can examine patterns such as average ticket size, category mix and recency of spend to define a qualified account.

• Closed-loop visibility. Because the same platforms that build audiences also see ongoing financial activity, they’re well-positioned to link exposure to later-stage outcomes. That doesn’t replace your CRM, but it gives you a financial baseline everyone can agree on, which helps when you’re trying to reconcile media performance with pipeline and revenue.

• Efficiency in noisy markets. In categories where a dozen vendors are chasing the same accounts, being able to prioritize businesses that are demonstrably active in your category, or in adjacent ones, is a competitive advantage.

No one brags about the campaign that drove 2,000 names into the system and three real opportunities. If a lead has no history of relevant spend and shows up in none of the financial patterns that matter to your category, that doesn’t mean you ignore them forever, but when budgets are tight, it probably shouldn’t be the first place your next dollar goes.

How financial media networks work in practice

Under the hood, financial media networks tend to follow a similar pattern, even if the products and partners differ.

1. Set the objective. Start with a specific goal: net-new account acquisition in a target segment, expansion within current customers, or reactivation of lapsed buyers. “Fix everything” is not a real objective.

2. Translate that into financial signals. Work with the network (and, often, your agency partners) to map your definition of business qualification to the data they actually have. That might include category spend thresholds, revenue bands, transaction recency, or the presence of certain payment types.

3. Build and activate audiences. The network uses its first-party data to build audiences that match these criteria, then activates campaigns across its owned properties or pipes those audiences into your broader media mix, depending on how the network is set up.

4. Measure, compare and iterate. As campaigns run, you get reporting that blends media metrics with downstream financial outcomes where possible. Those learnings can feed back into how you define qualification, how you allocate budget and how you treat FMN audiences across other channels.

Different networks bring different strengths. Some payment platforms have deep visibility into small-business spending across categories such as restaurants, retail and services. Others sit closer to the enterprise and can surface signals around technology, travel, or finance categories. The common thread is real transaction data powering audience building, scoring and measurement.

AI plays a critical role across this entire process by adding intelligence and prioritization at scale. Models can rank accounts by predicted value using historical spend patterns and financial volatility, identify lookalike businesses that behave like your strongest customers financially rather than just demographically, and help sequence outreach by highlighting which accounts are most likely to be responsive now.

How to get started with financial media networks

To succeed with a new channel, start narrow, define qualification clearly and allow time for learning. 

Four practical steps:

1. Pick one high-impact use case. Choose a tight, high-value problem to solve—like improving net-new opportunity quality for mid-market accounts in a single vertical. Give the test a clear owner and timeline. If FMNs “own” everything, they own nothing.

2. Write down your business qualification rules. Before you log into any platform, get agreement on what “qualified” means in your world. That might include revenue or employee bands, category spend floors, transaction recency, or specific combinations of categories that signal an inflection point. The more precise you are here, the better AI models and partner networks can align their targeting and scoring to your goals.

3. Decide how you’ll measure success up front. Don’t stop at click-through rate or cost per lead. For financial media networks, more meaningful metrics might include qualified opportunity rate from FMN-sourced accounts, pipeline velocity (how quickly leads move from first touch to a key sales stage), and incremental revenue or margin from accounts exposed to FMN campaigns compared to a control group. Aligning on these metrics with sales and finance teams in advance will make post-campaign analysis clearer and far more productive.

4. Integrate into your broader media and measurement plan. FMNs are most effective when they’re integrated into your broader marketing system, not treated as a standalone tactic. The audiences and insights they generate can inform targeting and creative decisions across other channels, including retail media, programmatic and paid social, while also feeding into existing models for lead scoring, budget allocation and experimentation.

B2B is ready for real qualification

B2B leads are becoming increasingly expensive, and the status quo for qualification is not becoming any faster or clearer. Financial media networks and business media networks offer marketers a unique opportunity to move away from guesswork and toward a shared understanding of value, grounded in actual spending.

Marketers who lean into this now by testing financial signals alongside their existing lead sources, rather than replacing them, will be the ones who spend less time arguing about MQL quality and more time discussing revenue and growth. Pick one campaign in 2026 where you let financial behavior, not just form fills, define what a good lead looks like and commit to running it long enough to find out what it can really do.

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