IBM shares slid sharply after Anthropic claimed its AI can modernize COBOL systems. The selloff reveals deeper anxiety about legacy tech models in an AI-first world.
When International Business Machines shares tumbled after an announcement from Anthropic, it wasn’t because IBM missed earnings. It was because the market suddenly questioned something more structural.
Anthropic said its AI tools can help modernize COBOL code- the decades-old programming language that still runs core systems in banks, insurers, and governments. That might sound niche. It isn’t. COBOL modernization has long been slow, complex, and expensive. IBM has built a durable business around supporting and upgrading those legacy environments.
So when an AI firm suggests it can compress years of manual migration work into something far faster, investors don’t wait for proof. They react to the possibility.
IBM’s drop was sharp.
The scale of it says more about market psychology than immediate revenue risk. COBOL systems are deeply embedded. Enterprises don’t rip out mission-critical infrastructure overnight. AI can escalate parts of modernization. But oversight, compliance, and risk management still demand human involvement.
But here’s the nuance.
IBM’s strength has always been stability. Predictable enterprise contracts. Long-cycle infrastructure. Recurring services revenue. Anthropic’s pitch introduces uncertainty into that predictability. If AI tools reduce the labor intensity of modernization, margins in consulting and legacy support could tighten over time.
That doesn’t mean IBM is obsolete. It means the competitive terrain is shifting.
The real issue is perception. AI firms are now positioning themselves not just as product innovators, but as efficiency engines for legacy transformation. That reframes the value chain. Suddenly, AI isn’t just additive. It’s potentially deflationary for traditional service models.
IBM has navigated platform shifts before. Mainframes to services. Services for hybrid cloud. It understands reinvention. But the speed of AI iteration differs. Markets are pricing that speed, not today’s fundamentals.
This episode isn’t about COBOL alone. It’s about what happens when generative AI starts targeting the most entrenched corners of enterprise IT. Investors are asking a simple question: if AI can rewrite the past faster than consultants can bill for it, who captures the value?
As Buyers Move on From Basics, Retail Media Strategy is All About AI-Led Execution in 2026
Retail media strategy has outgrown the retailer’s walls. So why are most brands still thinking inside those walls?
All your retail media networks (RMNs) operate in different languages. There’s no standard guideline for measuring campaigns across multiple platforms and retailers. It makes any form of comparison impossible for brands to assess.
Retail marketers usually leverage 3-5 RMNs simultaneously- it’s the norm. Amazon reports ROAS in one way, Criteo and Walmart report it in another. You can’t compare apples to oranges.
The lack of a standardized framework induces fragmented campaigning for retail marketers. It’s a growing frustration- even in 2026.
And in today’s environment, relying on instinct instead of structured planning is risky — especially when building a long-term data-driven marketing strategy.
Without the precise data, marketers have no reliable answers. Especially when their CMO questions incrementality, “Are we actually driving new sales, or am I just paying to reach people who would’ve bought anyway?”
Without an accurate picture, your teams can’t gauge the impact of the spending, and neither allocate any more of it.
That’s precisely why retail media is gaining momentum in market conversations. “What is retail media” and “retail news” leaped 4% and 1300% on Google Trends in the past year.
Marketers want answers. Solutions to these fragmented networks.
And it’s exactly why we’re here.
What is Retail Media?
If you put the retail media landscape in a single picture, this is what it’ll look like:
Last year, Dentsu projected that the future of retail media “will be in data and audiences.” And they were correct. The marketplace might still focus on commoditized ad formats, but the influx of digital channels is changing this quite rapidly. Sponsored search and banner ads are rampant- and sadly, still receive the majority of dollars and attention.
But it isn’t a sustainable model. In simple words, we must grasp what retail media truly is:
The ads are placed on a retailer’s e-commerce site or app by a brand to influence the customer at the point of purchase. This model enables brands to boost their visibility on the ‘digital shelf’, similar to an endcap or special in-aisle feature in a physical store.”
This retail media definition illustrates why brands are attracted to retail media, from its targeting capability to closed-loop attribution. Especially in a day and age where the attribution equation has a gaping hole due to dark social.
And since last year, buyer confidence and trust have died on the edge of the hill. Blame inflation or geopolitical tensions- marketers are left adjusting strategies and creatives at the blink of an eye. But the hope in retail media has remained constant- or rather, seen an upward climb.
So, is retail media also commerce media?
It depends on who you’re asking. It’s actually the most critical thing to understand about these terms.
They’re used interchangeably in several marketing conversations. And at the surface level, that makes sense. Both are about reaching people close to a purchase decision, using data that’s grounded in actual buying behavior.
The overlap is real.
But there is a meaningful distinction worth making. One that’s become more relevant as the industry has matured.
Retail media, specifically
Retail media is advertising that lives within a retailer’s owned ecosystem, i.e., their website, app, and in-store screens. It runs on “that” retailer’s first-party shopper data- Amazon Ads, Walmart Connect, Target’s Roundel, Kroger Precision Marketing.
The defining characteristic is that the media and the data both belong to the retailer. You’re advertising inside someone’s store, using their knowledge of their customers.
That’s a specific thing. It has a clear boundary.
Where commerce media means something different
Commerce media, when used distinctly, refers to a broader approach. That means applying purchase-intent data and transaction signals to advertising across platforms that aren’t necessarily retailers. Financial services platforms, travel booking sites, food delivery apps. These aren’t retailers, but they neglect behavioral and transactional data that’s just as commercially rich.
This expansion mirrors what’s happening across the broader ecosystem of retail media advertising and adtech companies, where boundaries between retail, commerce, and media continue to blur. It’s worth knowing it carries commercial framing.
But the underlying concept is legitimate: the logic of retail media, i.e., use real purchase signals, not paradoxes, can exist outside of retail environments.
Retail media is defined by its ecosystem. Commerce media is defined by its data logic.
Why brands and retailers are both leaning into retail media
US advertisers spent $60.32 billion on retail media in 2025 and plan to allocate $71.09 billion in 2026, according to eMarketer. And three-quarters of them plan to increase their retail media spend.
Brands and retailers have found their moat.
It’s because retail media is perceived as a more reliable line item. Especially owing to the erratic shifts in consumer behavior and e-commerce growth. More marketers are trusting everything data- it’s the source of all truth. A single point of stability.
For marketers, retail media strategy has become a holy grail.
It realizes the full potential of first-party data, granting the opportunity to optimize their bottom line. Moving beyond the traditional transactional value perspective, retail media comes down to creating incremental growth for customer lifetime value. And while creating a flywheel of the retailer’s own business.
Retailers become a platform.
But the hiccup here is: what if retail brands are underestimating the prowess of their own data ecosystem?
RMNs are less confident in their ability to differentiate amidst the crowded marketplace. The heap of first-party data vendors and media providers adds to the competitive set. As data sources and ad tech stack diverge- there’s a lack of compatibility.
How do RMNs measure, access, and scale their offerings as data silos persist due to a lack of an omnichannel identity framework?
The Three Foundational Philosophies of a New-Era Retail Media Strategy
If anything, retail media should sit inside a broader B2B marketing strategy that defines long-term growth, not just quarterly performance.
But that’s all non-negotiable. That’s where we make the error of judgment- tactics aren’t strategy.
We offer the backbone of a true retail media strategy- the three philosophies that should guide you from the get-go, not when you’re already halfway through the race.
1. Proximity
First, it’s all about the thinking. Traditional media focuses on GRPs, impressions, and the market as its sea. That’s their first mistake. It’s never about how many accounts you reach.
What makes the actual difference? How close to the purchasing decision do you reach these accounts? Purchase proximity.
Guide every strategic decision of your retail media strategy through that lens- why one shopper searching for exactly what you sell is better than five passive scrollers.
2. Retailer is Your Partner
Marketers still approach retail media the way they do billboards- at arm’s length. That’s what differentiates champion retail media from those who remain at the bottom of the barrel.
Retailers are your strategic partners- an extension of your brand. Not publishers. This is where structured B2B media partnerships become a competitive advantage rather than a transactional relationship.
And it includes sharing that first-party data.
3. Campaigns are Just Levers
This ties directly to the measurement fragmentation pain point.
Optimizing within each platform is a tempting opportunity. You chase ROAS on Amazon, CTR on Walmart, and so on. But those metrics are siloed and generally self-reported by the same networks selling the inventory.
It’s misleading.
Measurement maturity like this doesn’t happen in isolation. It’s part of aligning creative execution with analytics — where creative strategy meets data.
Here’s the Retail Media Strategy That Moves Beyond Fancy Labels- And What to Actually Do About It
Most retail media “strategies” I see are just media plans with a fancier label. A spreadsheet of placements, some budget splits, and a kick-off call with the account team.
But that’s not a retail media strategy.
1. Real strategy starts before the brief.
It starts with an honest answer: where is our customer closest to saying yes? That’s the only moment that actually matters in retail media.
Find that moment in your funnel and build your entire retail media strategy around it.
That means conducting a purchase journey audit before you allocate a single dollar.
Map the path- Retail media doesn’t operate in a silo; it should support a full-funnel marketing strategy that connects awareness, consideration, and conversion seamlessly. Where are people searching? What keywords are they using at high-intent moments? That’s your priority inventory.
Sponsored search placements on high-intent keywords should almost always come before display, before off-site, before anything. Start there. Then expand.
And don’t spread budget across six networks because your agency suggested “diversification.” Pick two or three networks where your category actually has purchase momentum, go deep, and prove the model before you scale horizontally.
More RMNs means more fragmented data, more account management overhead, and a measurement nightmare you won’t untangle until the budget’s already spent.
2. Look at your retailer relationships with honesty.
Are you showing up as a partner or just a line item in their ad revenue report? Because the brands getting early access to new inventory, richer shopper data, and joint business planning aren’t necessarily the biggest spenders.
They’re the ones bringing something to the table beyond a media budget.
Tactically, this means requesting and actually using the retailer’s first-party audience data.
Most brands pay for sponsored listings without a conversation about shopper segmentation. That’s leaving serious value on the table. What can you do here?
Push for a quarterly business review with your retail media account team.
Bring your own category data.
Ask what they notice in search trends that you don’t.
Make the relationship bilateral.
Also: negotiate for measurement access upfront. It shouldn’t be an afterthought.
Know exactly what data you’ll receive, in what format, and on what timeline before you sign off on the campaign.
Too many brands discover post-campaign that the reporting doesn’t offer them what they need to make the next decision. That’s a commercial conversation, not a technical one. Have it early.
3. Set up your measurement framework before you scale.
This won’t work after your Q3 spend has been spent.
Here’s a simple way to think about it: run a small incrementality test before committing your full budget to any single network.
Most major platforms, such as Amazon, Walmart Connect, and Criteo, offer holdout testing in some form. Leverage it. Even a rough incrementality read is more valuable than a polished ROAS number generated and reported by the platform.
Know your baseline conversion rate. Know what “normal” looks like without the media running. Then you have something real to compare against.
Beyond that, build a cross-network scorecard that you own- not one stitched together from three different platform dashboards. It doesn’t need to be sophisticated.
It needs to answer: which network drove genuine incremental sales, at what cost, and does that justify the spend relative to the alternative? That’s it. If you can answer that cleanly every month, you’re already ahead of most marketers operating in this space.
Because if you can’t answer “did this actually grow our business,” you’re just funding a retailer’s P&L and calling it marketing. That’s not a position anyone wants to be in, especially when you’re in a room with your CFO- trying hard to justify the spend.
How AI Is Transforming Retail Media Strategy: Opportunity or Overwhelm?
Here’s the honest truth: most B2B brands are sleeping on AI in retail media. They hear “AI-powered bidding” and assume it’s an Amazon feature someone else is managing.
That’s a mistake. B2B brands should care more about AI’s intersection with retail media than they presently do.
Why?
It’s not automated bidding- that ship has sailed. The platforms already do that whether you ask them to or not.
The real opportunity is in what AI lets you do with your own data. That means synthesising performance signals across five different networks, modelling incrementality, and simulating budget allocation scenarios — which is exactly where a modern AI marketing strategy begins to redefine competitive advantage.
It’s a win for B2B brands across 3 cases:
Where sales cycles are longer
Attribution is messier
Buying committees don’t exactly impulse-buy
AI-driven measurement isn’t a nice-to-have. It’s the only realistic way to prove that retail media is has vitality beyond generating impressions nobody can link to revenue.
It’s your workaround from the fragmentation conundrum- the goldmine.
The brands that figure this out first will have a defensible argument for why retail media deserves a bigger slice of the budget.
And in a room full of stakeholders asking hard questions, that argument is worth more than any ROAS figure a platform ever handed you.
The bottom line is that retail media has officially leveled up.
AI-driven attribution has pushed traditional retail media strategies to pivot. And the brands still chasing CPC efficiency will get left behind.
The question your CMO is already asking, i.e., “are we driving new sales, or just reaching people who would’ve bought anyway?” is now the defining question of the entire industry.
Leaders like Thomas Hanel at Mars are no longer optimizing for media efficiency. They’re demanding iROAS, sales per click, and proof of genuine incremental growth. That’s the shift.
And with AI finally making real-time incrementality measurement possible without a six-week analytics detour, there’s no excuse not to hold your retail media to that standard.
The next time a platform hands you a shiny ROAS number? Ask the harder question. Did it actually move the needle or just the numbers in your PPT?
Orange and Samsung aim to grow European Open RAN networks
The agreement between Orange and Samsung to scale Open RAN deployments across Europe in 2026 is being reported as a partnership announcement. We think it is something with higher stakes than that.
Orange has committed to a RAN renewal tender covering all its European country sites this year, requiring every submitted solution to carry Open RAN support. The addressable scope is approximately 10,000 sites. That is not a pilot. That is a procurement posture that will force every vendor operating in European telecoms to respond to it.
The technical architecture is worth understanding. Samsung’s AI-powered vRAN solution runs on Intel Xeon 6 processors, deployed on single commercial off-the-shelf servers from Dell and managed through a Wind River cloud platform. The design compresses what previously required significant physical infrastructure into a single server, reducing power consumption and operational footprint simultaneously. For operators facing European energy costs that have not returned to pre-2022 levels, the efficiency argument is not secondary to the performance argument. It may be primary.
The two companies have been working together in live environments since 2023, completing their first 4G and 5G calls on a virtualised Open RAN network in southwestern France last July, following laboratory testing in Lyon. The groundwork was laid quietly. The announcement this week is the acceleration.
Open RAN’s original promise was a political and economic one as much as a technical one: give European operators a credible path away from dependence on a small number of dominant infrastructure vendors. That promise has taken longer to materialise than anyone publicly admitted it would. Integration complexity, multi-vendor management challenges, and the sheer inertia of existing network contracts kept most operators in a cautious holding pattern.
What Orange is doing by writing Open RAN support into a continent-wide tender is changing the terms of that holding pattern for everyone. Carriers that were waiting to see who moved first now have an answer.
The second-order effect is on the vendors who are not Samsung. The tender is open. The requirement is set. The question is whether Europe’s network infrastructure market is about to get meaningfully more competitive, or whether the complexity of Open RAN at scale simply consolidates around a new short list of winners.
The field will tell us. The timeline is this year.
Full-funnel marketing is not a campaign. It is how B2B teams win before the meeting is ever scheduled, and most companies are only working the bottom half of it.
The sales team is losing deals it never knew it was in
Somewhere right now, a buying committee of ten people is building a shortlist. They are reading comparison articles, watching demos on YouTube, asking peers on LinkedIn, and forming opinions about which vendors understand their problem and which ones are just selling. They will not call anyone until they are roughly 60 percent of the way through that process. When they do make contact, the vendor they call first wins the deal about 80 percent of the time. The vendors who did not make the shortlist will never know the conversation happened.
This is not a sales problem. It is a marketing problem. Specifically, it is the problem that happens when a company treats marketing as communication rather than what it actually is: the management of people, at scale, across time, in ways that determine whether the company is profitable or not.
Full-funnel marketing is the structural answer to that problem. Not the buzzword version, not the agency deck version with the colorful funnel graphic and three tiers labeled awareness, consideration, and decision. The real version, which is considerably less tidy and considerably more valuable. If you want a deeper breakdown, here’s a detailed guide to building a full-funnel marketing strategy that aligns marketing with revenue outcomes.
The Numbers Behind the Problem No One Wants to Name
Here is what the data says is actually happening. The average B2B win rate sits around 20 to 21 percent, a number that becomes more concerning when compared against industry B2B SaaS funnel conversion benchmarks. Sales cycles are 38 percent longer than they were in 2021. The typical buying group spans 10 to 11 stakeholders, and in enterprise deals that number can reach 17. Eighty-four percent of sales reps missed quota last year.
84% of sales reps missed quota last year
62+ touchpoints before a buyer signs a deal
38% longer sales cycles vs. 2021
80% win rate for the first vendor contacted
These are not numbers from a down market. Many of the companies behind these reps are growing revenue. The reps are missing quota inside growing companies because the pipeline they are working is structurally broken upstream.
The touchpoint problem most marketing leaders underestimate
The average B2B buyer engages in 62 or more touchpoints before signing a deal, spanning at least three channels and involving multiple members of a buying committee. Most marketing organizations are actively managing perhaps a third of those touchpoints. The rest are happening without them, in spaces they are not present, in conversations they are not part of, among stakeholders they have never tried to reach.
That is the gap the full-funnel strategy closes. It requires intentionally designing each stage of the journey, similar to how you would build a B2B sales funnel from awareness to revenue. Not by being everywhere randomly, but by being specifically present at the moments that shape how a buying group thinks about a category before they think about vendors.
What Full-Funnel Marketing Actually Means, and What It Does Not
Full-funnel is not a synonym for doing more marketing. It is a structural commitment to being present, credible, and useful at every stage of a buyer’s journey, not just when that buyer is ready to talk to sales, which is where many lower-vs-upper funnel marketing misunderstandings begin. It is a structural commitment to being present, credible, and useful at every stage of a buyer’s journey, not just when that buyer is ready to talk to sales.
In B2B, buying decisions are not made by individuals. They are made by groups, typically six to ten stakeholders with different priorities, different vocabularies, and different definitions of risk. A champion inside the organization may love your product. The CFO has not heard of you. The IT lead has concerns about integration that no one has addressed yet. Full-funnel strategy is the discipline of reaching all of them, with the right message, before any of them is formally in a B2B buying process.
By the time a prospect fills out a form or takes a sales call, the majority of their evaluation has already happened. If your brand was not part of that informal research phase, you are walking into a conversation where someone else has already shaped the criteria.
The shortlist is built before the search begins
94 percent of buying groups rank their shortlist in order of preference before initiating contact with sales. The vendor ranked first wins about 80 percent of the time. Read that slowly. The rank ordering is done before anyone picks up the phone. The deal is largely won or lost in a process that most sales teams have no visibility into and most marketing teams are not deliberately influencing.
Buying authority, the condition in which your brand is assumed to belong on the shortlist, is not awarded on the day someone fills out a form. It is accumulated over months of consistent presence, relevant content, and the kind of thought leadership that answers the question a buyer has before they know how to ask it publicly.
Why the Sales and Marketing Tension Is a Funnel Problem in Disguise
The tension between sales and marketing in B2B organizations is almost always a funnel problem. Sales says the leads are not ready. Marketing says sales is not following up. Both are usually right, and both are symptoms of a pipeline that was built without coordination across the full journey.
What changes when marketing works the whole funnel
When top-of-funnel investment is creating genuine awareness and category education, middle-of-the-funnel content is addressing the specific concerns of different buyer personas, and bottom-of-the-funnel assets are arming champions with materials to build internal consensus, the prospect who reaches sales is a different person. They have self-qualified. They have done some of the internal selling work because the content they consumed gave them the tools to do it.
86 percent of B2B deals stall before crossing the finish line, which is why structured lead nurturing strategies become critical to maintaining momentum across long buying cycles. A buyer who arrives with trust already built stalls at a very different rate than one who arrives skeptical and under-informed.
The frictionless experience is a revenue number, not a UX metric
97 percent of B2B buyers say a fast, easy digital experience is a key part of vendor evaluation, reinforcing why SEO for SaaS and digital discoverability are no longer optional in competitive markets. Buyers are also consumers. They are accustomed to experiences that anticipate their needs, and when a B2B buying process is opaque or misaligned with where they actually are in their thinking, they do not wait. They move toward the vendor who makes it easier. Friction at any stage of the funnel is not a design problem. It is a revenue leak.
What Leaders Should Actually Demand From Their Marketing Teams
The organizations that will win the next decade of B2B competition are not the ones with the biggest campaign budgets. They are the ones who understand marketing as the discipline of managing buyers profitably across time. That means measuring influence across the full cycle, not just the last click. It means investing in awareness even when the return is not immediately attributable. It means aligning marketing and sales around a shared definition of what a ready buyer actually looks like.
The compounding advantage most teams are leaving behind
Full-funnel marketing asks more of teams and more of leadership. It requires patience for the investments that compound quietly, and discipline to protect them when quarterly pressure arrives. What it returns, in pipeline quality, deal velocity, and customer lifetime value, is not a soft promise. These improvements are often visible when teams track the right SaaS metrics across acquisition, activation, and retention.
The company that has educated the CFO about ROI frameworks, addressed the IT lead’s integration concerns through well-placed technical content, and given the internal champion the language to build internal consensus, that company is not competing on the same terms as the vendor who showed up with a cold outreach sequence in month nine of a ten-month buying journey.
None of this requires an unlimited budget. It requires a different orientation. The companies that compound their competitive advantage are not necessarily the ones with the most sophisticated technology stacks. They are the ones that understand a simple thing clearly: a customer relationship begins long before a contract is signed, and the value of that relationship, its length, its depth, its profitability, is determined largely by what happened before the first sales call.
Marketing is not the department that explains what the product does. It is the function that manages how people think, feel, and decide profitably, across the entire arc of their journey.
The funnel has always been there. Most companies are only working the bottom half of it. That is the gap, and it is solvable. Not with more campaigns. With a strategy built around the buyer’s full journey, from the moment they develop a problem to the moment they sign a contract, and every quiet, decisive moment in between.
That is not a brand story. That is a business model.
Full-Funnel Marketing Examples that Are Driving Action Like No Other
Most B2B funnels end at awareness and pray. What does it look like when every stage actually works? These full-funnel marketing examples have the answer.
B2B marketing teams have a severe funnel problem. One they aren’t aware of.
The teams pour budget into building awareness and lead gen, but lose leads somewhere in the middle. Not to competitors, but to silence.
The fix is not more ads or a better landing page. It is building a journey where every stage feeds the next. That is the whole premise of full funnel marketing, and the brands doing it well are not just getting more leads. They are getting better ones that convert faster and stick around longer. If you need a structural breakdown, this guide to full-funnel marketing strategy explains how the stages connect in practice.
Here are five full-funnel marketing examples doing this right.
What Makes a Full Funnel Marketing Strategy Actually Work
Most companies treat the funnel like three separate departments, often misunderstanding the real difference between demand generation vs lead generation and how each supports different parts of the journey. Awareness is a social media problem. Conversion is a sales problem. Retention is someone else’s problem.
Nobody owns the whole thing. That creates fragmentation that leaks.
Every stage is part of a single narrative in full-funnel marketing. The message at the top creates an expectation. The middle delivers on it. The bottom converts it, which is why structured lead nurturing strategies are critical to maintaining momentum between first touch and sales readiness. When those stages are disconnected, buyers feel it, even if they cannot articulate why they stopped engaging.
Two things make or break execution.
First, message continuity. The tone and promise must remain consistent from the first ad to the final sales call.
Second, behavioral data. A user’s activity in the first stage should shape what they see in the next one, which is where a clearly defined lead scoring model becomes essential. The loop becomes a full circle here.
The funnel doesn’t feel like aggressive marketing, but as the natural next step.
Full Funnel Marketing Examples That Are Driving Outcomes in 2026
1. Salesforce: Let Buyers Sell Themselves Before Sales Steps In
Salesforce does not wait for a sales rep to create a champion inside a prospect account. It builds one first.
Trailhead, Salesforce’s free learning platform, trains thousands of professionals on its products every year. These are end users, admins, and RevOps managers who then become internal advocates when faced with a buying decision. By the time procurement is involved, Salesforce often already has someone in the room making the case.
At the top of the funnel, the State of Sales reports and Salesforce+ content reach decision-makers where they already spend time. No product pitch in sight. Just useful research that gets shared and cited. At the conversion stage, ROI calculators and personalized demos give economic buyers the numbers they need to justify the spend internally.
The funnel works on two audiences at once: the people who use the product and the people who approve the budget.
2. IBM: ABM Done Right Is Its Own Full-Funnel
IBM does not try to reach everyone. It picks its targets and works them methodically from top to bottom, demonstrating how ABM vs lead generation approaches differ when precision matters more than volume.
The Institute for Business Value reports and executive roundtables earn credibility with C-suite buyers before any sales conversation starts. This is not broad awareness content. It is precise. IBM knows exactly which titles and company profiles it is writing for, and the content reflects that.
What makes it a true full funnel play is the handoff. Sales and marketing work from shared data, so a CFO who reads an IBM paper on AI risk does not then receive a generic outreach email. The follow-up references what they read and speaks to their specific context.
At the conversion stage, IBM runs proof-of-concept engagements that allow hesitant buyers validate the solution before committing. The message remains cohesive, from the first research report to the boardroom conversation.
The whole game’s about consistency across a long and complex B2B sales cycle, especially in SaaS environments where SaaS product marketing, content, and sales alignment determine velocity.
3. Intuit: Nobody Buys Accounting Software. They Buy Peace of Mind.
QuickBooks buyers do not want accounting software. They want to feel like their business finances are not a disaster waiting to happen. Intuit builds its entire funnel around that distinction.
At the top, it shows up when financial stress is highest.
Tax season content, cash flow guides, and comparison resources meet SMB owners at the exact moment they are searching for help. There is no hard sell. Just genuinely useful information from a brand that happens to sell the tool they need.
The middle of the funnel is where Intuit earns the conversion before it even happens.
Free trials are designed to get users to their first real win as fast as possible, a strategy closely tied to reducing churn in SaaS by accelerating time-to-value. A reconciled bank account. A clean profit and loss view. Once someone has reorganized their workflows around QuickBooks, switching becomes its own kind of cost.
By the time the trial ends, the decision to pay has already been made emotionally. The billing page is a formality.
4. Mailchimp: A Brand Voice So Consistent It Becomes Its Own Funnel
Most B2B software companies sound like B2B software companies. Mailchimp decided not to.
From a cold social ad to the onboarding flow and a support email, the tone remains consistent, reflecting a disciplined SaaS content marketing playbook rather than isolated campaigns. Warm, a little funny, and straightforwardly useful. That might sound like a branding choice, but it is also a funnel mechanic. When the voice is consistent, every touchpoint reinforces the one before it. Trust compounds instead of resetting.
At the top, Mailchimp’s campaigns signal clearly who the product is for. Not enterprise IT teams.
Growing businesses with a marketing person or two who need something that actually works. The free tier does not just capture leads. It teaches. Users learn email fundamentals inside the product, which means the product itself demonstrates its own value.
When feature limits kick in as a list grows, the upgrade prompt lands at exactly the right moment.
The ROI is obvious because the user experienced it. Retention follows because Mailchimp builds community, not just software subscriptions.
5. Caterpillar: How a 100-Year-Old Brand Rebuilt Its Funnel for the Digital Buyer
Equipment buyers used to walk into a dealership and let a relationship do the work. That is still true at the finish line. But the research now occurs online, long before anyone picks up the phone.
Caterpillar adapted. Content around equipment lifecycle costs, fleet telematics, and sustainability in construction reaches buyers during the research phase through search and LinkedIn. reinforcing why SEO for SaaS and industrial brands alike is foundational to early-stage visibility. It is not flashy. It is just the right information at the right time for someone chasing a six-figure purchasing decision with confidence.
The middle of the funnel is where the digital investment really pays off.
Cat’s online configuration and cost-of-ownership tools let buyers model scenarios before they reach a vendor. This is a substantial shift for an industry built on relationship selling. But the tools don’t cut vendors out of the loop. They make dealer conversations better.
A buyer who already knows what they need and what it will cost is not starting from scratch. They are ready to commit. At the conversion stage, Cat Financial removes the last major obstacle by offering financing that turns a capital expenditure into a manageable monthly decision.
What These Full Funnel Marketing Examples Have in Common
The pattern across all five can’t be missed.
None of them relies on a single channel or a single moment to convert. Every one of them builds something in the middle of the funnel that creates real value before asking for a sale. Salesforce trains future champions. Intuit gets users to their first win. Mailchimp teaches while the product demonstrates itself. IBM proves its thinking before pitching its product. Caterpillar gives buyers the tools to make their own case.
The middle of the funnel is where most B2B strategies fall apart, often because teams optimize for raw lead generation metrics instead of true lead qualification. A few nurture emails are not a middle. It is a placeholder. These brands replace it with something a buyer actually wants to engage with.
The other thread running through all five is that data connects the stages. which is why tracking the right SaaS metrics across acquisition, activation, and retention becomes non-negotiable. What someone does early shapes what they see next. That is what makes the journey feel coherent rather than coincidental.
How to Apply These Full Funnel Marketing Lessons to Your Own Strategy
You do not need Salesforce’s budget to borrow these principles. You need clarity on three things.
1. First, check your message continuity. Pull up your top-performing ad and then open the page it sends people to. Does it feel like the same brand? Same tone, same promise, same visual language?
If there is a gap, fix that before you touch anything else. Every mismatch is a reason for someone to leave.
2. Second, figure out what your middle looks like. If the honest answer is “we send some emails,” you have work to do. It does not have to be a free product tier or a full learning platform.
It could be anything- a tool, an assessment, a live event series, or a content library, built around a pain point the buyer is actively trying to solve. The bar is simple: does it deliver value before asking for commitment?
3. Third, connect your stages with a signal. You don’t need a complex martech stack to start. You just need to know what a lead engaged with before they reach your sales team, and ensure that context is not lost in the handoff.
These full funnel marketing examples are not anomalies. They are what a deliberate, connected strategy looks like at scale, much like the frameworks outlined in this SaaS marketing playbook. They are what a deliberate, connected strategy looks like at scale.
The principles are the same whether you are selling SaaS or heavy equipment. Build the journey as it matters at every step, because to your buyer, it does matter.
Meta just agreed to buy roughly $60 billion in AI chips from AMD and could take a 10 % stake in the company.
Meta’s decision to commit up to $60 billion to buy AI chips from AMD isn’t about spending randomly. It’s a strategic recalibration- one that secures Meta’s vision.
Meta has been in a tough spot as of today. The tech giant’s core businesses are still generating cash, but its overall growth has slowed. All of this while AI has become the foundational layer for future products and revenue streams.
In that context, computing capacity or the raw engine behind large language models and generative AI isn’t optional. It’s core infrastructure.
That’s where AMD comes in.
Meta is effectively securing fuel for its AI ambitions by locking in hardware supply over a long-term horizon. It isn’t about short-term bragging rights. It’s about avoiding bottlenecks. When AI models scale, access to chips becomes a competitive lever. Meta doesn’t want to be at the back of the queue for compute.
The weird twist in this deal?
The option for Meta to take up to a 10 % stake in AMD through performance-based warrants tells its own story. It signals that Meta is betting on volume, and on the long-term competitiveness of AMD’s silicon roadmap.
It boils down to aligning incentives with AMD’s future success.
Critics who label this a “bubble” miss the logic driving the decision.
The alternative for Meta wasn’t restraint. It was a potential irrelevance in an AI arms race. NVIDIA’s dominance in AI chips has created a chokepoint for many tech companies. Diversifying with AMD gives Meta leverage and choice.
It’s a huge spend. But it’s a calculated one-time expenditure, grounded in the reality that future AI products, from search to creators to commerce, will depend on having reliable, abundant compute power. Meta isn’t throwing money at a fad. It’s buying capacity before it becomes scarce.
Execution still matters, and chips alone won’t guarantee great AI products. But this deal is a logical step in Meta’s long game: control more of its own destiny rather than outsourcing its potential.
