And marketing is only the beginning of the fallout. The damage doesn’t stop at demand generation. It moves downstream into the core of the go-to-market engine, affecting sales execution, pipeline integrity, forecasting accuracy, and ultimately revenue. Bad data isn’t confined to marketing dashboards. It is a sales problem, and it is costing companies far more than they realize.

For revenue leaders and frontline sellers, the failure rarely appears labeled “data quality.” Instead, it shows up as another “high-intent” lead that never replies. Another outbound sequence that stalls. Another quarter that closes nowhere near what the dashboards predicted. A rep follows up on what looked like a hot account and gets ghosted again. With each dead end, trust in the system erodes.

When the Funnel Distorts Reality

The moment flawed data enters the pipeline, credibility fractures. Lead-to-account mapping struggles under the weight of outdated records, constant job changes, and enrichment platforms that disagree on basic firmographics. A global enterprise may be flagged as surging in intent, yet no one can determine which region, division, or stakeholder actually demonstrated interest.

Hesitation creeps in before outreach even begins.

As the motion continues, each handoff becomes more fragile. Sequences reach contacts who lack buying authority, prospects who have already made a decision, or individuals only loosely connected to the opportunity. Sales development representatives are not simply being ignored. They are chasing ghost signals: inflated intent spikes, mismatched personas, and timing misaligned with real buying cycles.

Over time, the human response is predictable. Reps stop trusting routed leads. They build their own prospect lists. They circumvent automated workflows. They rely on personal networks rather than the GTM infrastructure meant to support them. Marketing feels sidelined. Sales feels unsupported. What started as a data issue becomes a breakdown in cross-functional trust.

The Revenue Impact No One Sees at First

The cost of bad data compounds quietly. Advertising spend and outbound energy are directed at the wrong buyers at the wrong time. Reps devote hours to opportunities that never had genuine potential. Meanwhile, legitimate high-intent accounts slip past unnoticed.

Conversion rates begin to decline. Sales cycles lengthen. CRM dashboards still show healthy pipeline coverage, yet closed-won results trail projections. Quotas are not missed solely because deals fall apart. They are missed because the funnel itself was never aligned with authentic buying behavior. Forecasts drift further from reality each quarter.

Eventually, accountability unravels. Marketing defends campaign volume. Sales questions lead quality. Leadership struggles to determine which metrics still deserve confidence. Yet many organizations remain locked in this cycle because they have already invested heavily in platforms, people, and political capital. Abandoning the motion feels like conceding failure. So budgets continue flowing into a system that amplifies flawed inputs rather than correcting them.

Marketing Technology News: MarTech Interview With Fredrik Skantze, CEO and Co-founder of Funnel

Why Traditional Intent Signals Fall Short

Much of today’s third-party intent infrastructure was built for a different internet, one where human buyers performed most searches, clicks, and downloads. That environment no longer exists. Bots, crawlers, and synthetic traffic now generate a meaningful portion of online activity. Many of the “intent spikes” lighting up dashboards originate from machines, not buyers.

Outreach fueled by those artifacts sends sellers into conversations that were never real to begin with. Each failed interaction further weakens confidence in the pipeline.

At the same time, authentic buyers have migrated into harder-to-track environments. Research happens inside large language models. Peer recommendations unfold in Slack communities, private group chats, events, podcasts, and dark social spaces, not through repetitive website visits or form fills. Legacy intent systems largely miss these signals while continuing to overweight superficial digital activity.

This is not a minor calibration issue. It is structural. No incremental scoring adjustment can fix a model built on signals that no longer reflect how people buy or how modern sales teams should allocate their time.

Rebuilding the GTM Engine with Agentic Intelligence

The answer is not squeezing marginal improvements from broken intent data. It requires rethinking the architecture of the go-to-market engine itself.

Agentic marketing offers that shift. In this model, autonomous AI systems operate on real, current, buyer-level intelligence to execute the tactical work of marketing. Instead of relying on isolated, noisy signals, trustworthy insight emerges from synthesizing data across the full GTM ecosystem.

Cross-platform intelligence becomes critical. Teams can see how accounts engage across channels and prioritize outreach based on verified patterns of behavior rather than inferred clicks.

With this AI layer in place, marketers are no longer stuck patching flawed signals or chasing phantom demand. They can return to strategic fundamentals such as brand, positioning, and deep customer understanding, while automation handles execution grounded in validated data. Sales receives what it actually needs: signals it can trust, orchestrated intelligently and rooted in reality rather than noise.

In the next installment of this series, we will examine how to redesign the GTM engine around agentic intelligence, building a system capable of delivering genuine opportunity instead of misleading signals.

Marketing Technology News: The Death of Third-Party Cookies Was Just the Start. Are You Ready for Consent Orchestration?

Leia Inc., Symbotic, Signifyd and Exol select SHIFT as agency partner to build Performance Communications and PR programs

SHIFT Communications, an integrated PR agency with a specialization in B2B technology, announced the addition of multiple AI-focused technology clients to its roster. The Agency continues to be a strong partner for B2B technology and SaaS companies, delivering PR programs that strengthen category positioning and engage audiences across today’s fragmented media landscape.

New B2B technology PR clients

As AI adoption and competition accelerate across industries, technology companies are increasingly seeking strategic PR partners that can drive brand authority, differentiation beyond product offerings, and measurable business impact.

Marketing Technology News: MarTech Interview with Haley Trost, Group Product Marketing Manager @ Braze

The following companies partnered with SHIFT to achieve that through our Performance Communications programs in Q1 2026:

• Exol: Robotic Logistics Platform combining advanced physical AI, intelligent software, and a nationwide fulfillment and transportation network
• Leia Inc.: Creator of Immersity, a spatial AI technology platform that provides immersive experiences to virtually any device, allowing users to feel part of the scene
• Signifyd: AI-powered fraud and abuse protection provider that deploys machine learning to help ecommerce brands increase revenue and establish trust that builds customer loyalty
• Symbotic: AI-powered supply chain automation with robotic warehouse and logistics systems

SHIFT will support these growth-stage brands — along with other recent client wins including digital workspace market leader Citrix and payroll & HR services provider G&A Partners — with multichannel PR programs focused on industry & corporate storytelling, executive content, and AI answer visibility (also called GEO or AEO).

About SHIFT’s B2B Technology PR Practice

SHIFT partners with both growth-stage and market-leading B2B technology companies to strengthen category positioning and accelerate growth. Since 2020, the agency has supported clients through four IPOs, $1.38B in funding and successful exits via acquisition. It specializes in building credibility, demand and discoverability through:

• Media storytelling & coverage
• Executive thought leadership & content
• Category leadership positioning & recognition
• Owned data, industry & vertical marketing communications & PR campaigns
• Communications support during company milestones & news moments

“Our clients are operating in highly competitive and rapidly evolving markets,” said Amanda Munroe, agency lead at SHIFT Communications. “They need more than press visibility. They need cohesive storytelling systems that strengthen positioning, build demand and create discoverability where buyers are tuning in. That type of outcome-focused programming is where we excel.”

1. What industries does SHIFT Communications specialize in?
   SHIFT was founded as a high-tech PR agency in 2003. It has built deep experience and expertise across B2B technology sectors including AI, ecommerce, enterprise software, industrial, supply chain, web3 and workplace over the past 20 years.
2. How does SHIFT support growth-stage B2B technology companies?
   SHIFT helps companies strengthen brand and business growth through omnichannel PR. The agency drives critical credibility, demand and discoverability through earned media coverage, owned content, social media storytelling and paid amplification.
3. What differentiates SHIFT from other B2B tech PR agencies?
   SHIFT is known for media relations, but its Performance Communications approach — which purpose-builds multi-channel storytelling campaigns to help companies reach specific objectives — sets it apart. SHIFT also excels in measuring program impact and in creating owned data campaigns that boost brand attention and authority.
4. What types of B2B technology companies does SHIFT represent?
   SHIFT works with startup, growth-stage and established technology clients, helping them strengthen positioning and scale their businesses. Its B2B tech and SaaS client experience includes Citrix, Checkr, GoDaddy, Resonate, Talkdesk, TELUS Digital and Vonage.

SHIFT Communications is an integrated PR and communications agency that turns PR into business impact for B2B Technology, Healthcare and Consumer brands. Our Performance Communications approach sets us apart by combining brand storytelling with purpose-built campaigns to create the demand, credibility, and discoverability businesses need to grow along with in-depth measurement on how they contribute to business outcomes.

Since 2003, SHIFT has helped global leaders and emerging disruptors shift ahead in their categories and goals. Clients who have partnered with us include Butterfly Network, Citrix, Included Health, McDonald’s, OneDigital, Talkdesk and Wedderspoon.

Marketing Technology News: Cross-Department Collaboration with Marketing Workflow Automation: Enhancing Alignment Between Sales, Customer Service, and Marketing Teams

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

While your rivals fight for expensive screen time, the audio channel is wide open. Programmatic audio advertising lets you reach these bosses when they are busy with other tasks. You can slip your message into their ears while they drive, run, or cook dinner. It turns “dead time” into a real connection for your brand.

What Does the Audio World Look Like Now?

The days of buying a random radio spot are over. Programmatic audio advertising is now a smart, data-driven tool. It is just as precise as a display ad. You can bid on spots in real time and target specific people.

This tech lets you buy ads across thousands of podcasts and music apps instantly. You are not stuck in long-term contracts with a single network. You control the dial. You can pause ads that are not working and boost the ones that are. It brings speed to a place that used to be slow.

Can You Reach the Right Ears at the Right Time?

You do not need to blast your ad to everyone with headphones. You can target the exact moment that fits your product.

• Pick specific topics like “Tech News” to reach bosses during their morning drive.
• Skip comedy shows where your serious business message sounds weird.
• Use keywords to place ads only in episodes talking about your industry.
• Reach listeners when they are in “learning mode” and ready to hear you.
• Filter people based on their job title or company size data.

How Do You Personalize Sound for Every Listener?

Static ads are boring. Modern tools let you swap out parts of the script in real-time to fit the listener.

• Location Data:

Mention the listener’s specific city or local weather to grab their attention immediately.

• Company Matching:

Insert the name of the listener’s industry dynamically to make the offer feel exclusive.

• Time Sensitivity:

Change the call-to-action script based on whether it is morning or evening.

• Creative Testing:

Run four different versions of the intro to see which one keeps them listening.

Why Does Your Brand Need a Sound Identity?

You likely have a brand style guide for colors and fonts. But what does your brand sound like? In the world of programmatic audio advertising, your sonic identity is everything. Think of the Netflix “ta-dum” sound. You know exactly who it is without looking at the screen.

B2B brands rarely invest in this. By creating a consistent audio logo or jingle, you build memory structures in the listener’s brain. When they hear that specific three-note chime, they think of your software. This sonic branding acts as a mental bookmark. It ensures that even if they zone out during the ad, they still register your brand presence subconsciously.

Is It Possible to Track Who Actually Listens?

You might think audio is hard to measure, but the metrics are actually very clear.

• Track “Listen-Through Rate” to see if people actually stay for the whole message.
• Use pixel tracking to see if a listener visits your site later that day.
• Measure brand lift by surveying listeners who were exposed to the ad campaign.
• Correlate spikes in direct web traffic with the exact time your ads aired.
• Use unique promo codes in the audio script to track distinct conversions directly.

How Does Audio Fit Into Your LinkedIn Strategy?

An audio ad should not live in a silo. It works best when it feeds your other channels. Imagine a prospect hears your programmatic audio advertising spot on their way to work. They are interested, but they cannot click a link while driving.

Later that day, they open LinkedIn. Because you linked your audio data to your social campaigns, you serve them a display ad immediately. This creates a surround-sound effect. The audio planted the seed, and the visual ad harvests the click. This multi-channel approach significantly increases conversion rates because the prospect is already familiar with your name.

Marketing Technology News: MarTech Interview With Fredrik Skantze, CEO and Co-founder of Funnel

Should You Buy From Networks or Use Software?

You have two main ways to buy this inventory, and each serves a different goal.

• Demand Side Platforms:

These tools allow you to buy audiences across thousands of shows using automated bidding logic.

• Direct Networks:

You get premium host-read slots that cost more but offer much higher trust levels.

• Private Marketplaces:

Secure guaranteed inventory on top-tier business podcasts without fighting in the open auction.

• Automated Efficiency:

Programmatic tools let you adjust bids in real-time based on performance data.

What Makes a 15-Second Ad Work?

You have very little time to make an impact. The best programmatic audio advertising spots are short and punchy. Do not try to explain your entire product roadmap. Focus on one single pain point.

Start with a question that hooks the listener instantly. Use a clear, warm voice that sounds like a peer, not an announcer. Avoid using jarring sound effects like sirens or horns, as these annoy people listening in traffic. End with a very simple call to action that is easy to remember. If they can’t memorize the URL while driving, you have lost them. Keep it simple to win the ear.

Marketing Technology News: The Death of Third-Party Cookies Was Just the Start. Are You Ready for Consent Orchestration?

Multiply is the first hybrid AI + human media agency for B2B companies. Launches Self-Learning Advertising, where ads learn from company data and continuously improve.

Multiply is the first AI-native media agency for B2B companies. All marketers know that in traditional advertising, campaigns start losing effectiveness the moment they launch. Creative gets stale and audiences tune out. Multiply calls this phenomenon “decaying ads.”

Today, the company emerged from stealth with $9.5 million in funding to introduce what it calls the next paradigm: Self-Learning Advertising, where ads use internal data to continuously get better on their own. The round was led by Mayfield, with participation from Sorenson Capital, Instacart Co-Founder Max Mullen, Google Head of Gemini and Google Labs Josh Woodward, and executives from HubSpot, Braze, Issuu, Brex, Sierra, and Common Room, among others.

Early customers report outsized impact in sales pipeline generated from ads. Vanta, a leader in security automation, which has raised over $500 million from Sequoia Capital and other top VCs, shared: “We’ve seen 770% more sales meetings, we build and test faster with their AI, and their team is strategic, hands-on, and operates as trusted partners.” Listen Labs, the leading AI customer research platform that has raised $100M, said LinkedIn has become its most efficient paid channel for new leads, with campaigns performing 5X above LinkedIn benchmarks. Across customers, the common thread is velocity, and lead quality, and pipeline impact.

Marketing Technology News: MarTech Interview with Haley Trost, Group Product Marketing Manager @ Braze

Multiply Co-Founder & CEO Matt Jayson explains that “Modern companies already have all the data needed to create radically better ads. Sales conversations, CRM systems, and pipeline outcomes reveal exactly why customers buy – yet those insights rarely make their way into ad campaigns fast enough.” Today, Multiply focuses on Google Search ads and LinkedIn ads. The company connects directly to sales call recordings, CRMs, and ad platform performance data to generate new creative and messaging aligned to why buyers choose a company over competitors. Hundreds of structured experiments run continuously, refining audiences, copy, and creative, so campaigns improve every week–instead of declining.

Multiply was founded by Matt Jayson, formerly at Google and Brex, and Ashish Warty, formerly SVP Engineering at HackerOne and engineering leader at Dropbox and Airship. Jayson describes the company’s ambition: “We help companies get discovered by their dream customers. To do this, we’ve built the world’s most insatiable AI agent. Just like a great growth marketer, it’s never satisfied. There’s never enough pipeline. So it keeps learning, testing, and finding ways to get better.”

To tackle something this ambitious, Multiply couldn’t just build AI software. The company operates as a media agency staffed by expert strategists, who use Multiply’s proprietary AI to operate campaigns at speeds and with impact previously impossible.

Multiply’s Customer Insights AI Agent extracts real customer language from sales calls and uses it to personalize ads. The ICP Agent analyzes closed-won deals to refine targeting. The Quality Score Agent continuously tunes copy and keyword alignment. The Creative Design Agent refreshes images weekly. The A/B Testing Agent runs hundreds of experiments, quickly identifying winners and cutting losers. Ashish Warty, Co-founder and CTO of Multiply, describes, “Together, these systems allow Multiply to iterate faster than any traditional agency model.”

“Brand safety is paramount,” explains Warty. “Every campaign includes human oversight from experienced media buyers, and we work within each customer’s brand and compliance requirements. We move as fast as their teams and systems allow.”

While Multiply launched first with Google and LinkedIn ads, the company says its infrastructure was designed for emerging AI-driven ad platforms like ChatGPT ads. Multiply is already helping its customers prepare for ChatGPT ads. All campaign learnings and experimentation systems can extend directly into new formats, including conversational and AI-driven advertising experiences.

“There is a major shift happening in the $50B B2B advertising market,” said Patrick Salyer, Partner at Mayfield and Multiply board member. “Service-as-Software is redefining how companies grow, and Multiply has built the first AI model for B2B advertising. Instead of static campaigns managed manually, Multiply has become a compounding growth engine for every company it partners with.”

Looking ahead, Multiply will expand into a full omni-channel ad buyer for B2B companies, enabling businesses to launch and optimize advertising across all major platforms from a single system. The roadmap includes expansion to additional channels, daily creative refresh, unified cross-channel attribution, and AI-driven budget allocation across ad channels to maximize pipeline impact. As new AI-powered advertising channels emerge, Multiply aims to help customers adopt them early while continuing to outperform across existing platforms.

Multiply is the first AI media agency, designed specifically to help B2B companies get discovered by their ideal customers and turn ads into a reliable pipeline engine. Early customers report outsized gains. Companies using Multiply have seen 300 to 500% improvements in sales meetings booked and pipeline generated from ads.

It combines proprietary AI with experienced growth strategists who operate as an extension of a customer’s team. Multiply plugs directly into sales calls and CRM data to understand why customers actually buy. Its AI agents then translate those insights into highly personalized ads, launch hundreds of structured experiments, and continuously optimize performance across Google and LinkedIn.

Marketing Technology News: Cross-Department Collaboration with Marketing Workflow Automation: Enhancing Alignment Between Sales, Customer Service, and Marketing Teams

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Former AB InBev executives reunite to help brands turn AI into real revenue at MorningAI

MorningAI, an AI platform built specifically for brands, announced the appointment of Tina Wung as Chief Growth Officer. In this role, Wung will lead go-to-market strategy, customer growth, and strategic partnerships as the company accelerates its mission to become the #1 AI platform brands rely on to grow their business.

The appointment comes at an inflection point for the industry. Foundation models are commoditizing, and the value is shifting to the application layer – the layer that understands industry, brand, and workflow. MorningAI has built that layer for brands, and Wung will help bring it to brand teams around the world.

Wung brings over 20 years of experience building iconic brands and driving growth at Kraft Foods, Mondelez International, MillerCoors, and Anheuser-Busch InBev. At AB InBev, she was a founding member of the “Beer Garage,” the company’s pioneering digital center of excellence, where she helped shape how the world’s largest beer producer integrated emerging technology into its marketing operations. She went on to build marketing and revenue engines from the ground up at B2B technology companies, driving topline growth and international expansion.

Marketing Technology News: MarTech Interview with Haley Trost, Group Product Marketing Manager @ Braze

“We believe every brand will be managed with AI within three years,” says Chris Curtis, Founder and CEO of MorningAI. “Tina has steered companies through multiple eras of digital transformation — from early e-commerce to programmatic and now AI. Her track record of scaling technology adoption across enterprise and challenger brands is exactly what we need as we define this category.”

“Today brands are under more pressure to deliver results faster with fewer resources,” said Tina Wung, Chief Growth Officer at MorningAI. “And while there’s been an explosion of one-off AI tools, almost none are built from the brand’s strategic and tactical needs. MorningAI is unique because it’s built by brand marketers who know the challenges they face each day, and our mission is to empower them with the best technology to grow their business.”

MorningAI captures millions of data points about a company including its BrandDNA, CustomerDNA, and ProductDNA and uses that intelligence to power the work growth teams do every day: from creative briefing and content generation to campaign planning, competitive intelligence, and retail sell-in. The result is a single platform that replaces the patchwork of disconnected tools and agency dependencies brands rely on today.

MorningAI builds technology that helps brands grow. Founded by Chris Curtis, a former AB InBev and McKinsey & Company executive who led marketing campaigns for some of the world’s most iconic brands, the company was created to make that same level of intelligence and execution accessible to every brand. MorningAI is purpose-built for brands, with no conflicting media, agency, or platform incentives. Based in San Francisco, California.

Marketing Technology News: Cross-Department Collaboration with Marketing Workflow Automation: Enhancing Alignment Between Sales, Customer Service, and Marketing Teams

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

You can work much smarter, instead of harder. Instead of making these one-off disposable posts, you need to create posts that are your biggest assets and break them down into smaller, sharper hitting pieces. You might call this Content Atomization, and with the new AI tools, it has never been faster or simpler.

What Does It Actually Mean to Atomize Your Content?

Before you change up your strategy on us another time, we need to nail this concept down. Content Atomization is the practice of taking a large ‘Big Rock’ asset and breaking it apart into smaller, bite-sized pieces of content. Just like cooking a great big turkey on Sunday and making sandwiches, soups and salads for the rest of the week.

You take a really heavy whitepaper and extract some of the critical stats and make basic graphics that can stand alone You take excerpts to build text posts for LinkedIn. You convert the primary chapters into brief blog posts. So, what you want to do is make sure your audience consumes your message on the platform they want to consume it, without having to create new ideas on the daily.

How Is AI Changing the Way We Slice and Dice?

In the past, doing this manually required a whole team of writers and editors. Today, AI handles the boring work instantly.

• Context Scanning:

The AI reads your document to find the main themes and shareable moments without you highlighting them.

• Format Switching:

It rewrites a single paragraph into a casual tweet, a professional post, and a video script.

• Visual Creation:

Tools generate charts or slide decks directly from the text data in your source file.

• Speed Advantage:

You can generate weeks worth of social media drafts in the time it takes to drink a coffee.

• Efficiency:

Content Atomization allows you to fill your content calendar without constantly brainstorming new topics.

Can You Really Turn One Webinar Into a Month of Posts?

Video is the best source material you have, but it is often trapped in a long file nobody has time to watch. You can unlock that value easily.

• Video Shorts:

AI tools scan the long recording to find viral hooks and crop them into vertical clips for TikTok.

• Blog Summaries:

The software writes a full article from the transcript for people who prefer reading over watching a video.

• Email Drips:

You extract the main lessons to build a nurturing sequence that delivers value directly to subscriber inboxes.

• Audio Podcasts:

The system strips the audio track and cleans the noise to publish it as an episode for commuters.

How Do You Keep Your Brand Voice Sounding Human?

You might worry that letting a machine write your posts will make your brand sound robotic. That is a valid fear, but you can fix it. You have to train the AI on your specific rules before you start the Content Atomization process.

You upload your style guide and examples of your best posts. This acts as a guardrail. The AI then knows to use your specific words and tone. The process works best when the output feels like it came from your senior editor. This ensures your brand sounds the same on TikTok as it does in your whitepaper.

Does This Strategy Actually Help You Rank on Google?

Google loves variety, and this approach gives search engines exactly what they want to see.

• Keyword Coverage:

You hit the same core topics across many different pages, showing Google you are the expert.

• Video Search:

Your YouTube clips start showing up in search results, grabbing traffic that skips text articles.

• Image Results:

Infographics generated from your data show up in image searches, driving visual learners to your site.

• Time on Site:

Visitors stay longer because they can choose to watch, read, or listen to your content.

• Backlinks:

Diverse formats give other sites more reasons to link back to your specific Content Atomization pieces.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

Which Tech Tools Should Be in Your Stack?

You do not need a massive enterprise budget to build a machine that handles this workflow efficiently.

• Video Clippers:

Tools like Opus Clip find the best moments in long videos and add captions for you automatically.

• Text Generators:

Platforms like Jasper excel at rewriting long-form text into specific social media formats that actually get clicks.

• Design Automation:

Software like Canva uses AI to resize and reformat your visual assets for every platform instantly.

• Audio Cleaners:

Tools like Descript allow you to edit audio just by editing the text transcript, making podcasts simple.

What Is the Best Workflow From Big Rock to Micro-Content?

The key is to flip your production process upside down. Stop thinking about the tweet first. Start by creating the ‘Big Rock.’ This could be a deep survey, a long interview, or a technical guide. This asset is your single source of truth.

Once that is done, run it through your Content Atomization pipeline. You generate the videos, the blogs, and the emails all at once. This ensures every piece of content points back to the main asset. You create a web of content that drives traffic to your highest-value lead magnet.

How Do You Measure Success When Content Is Everywhere?

Tracking the impact requires you to look at the aggregate data rather than individual post metrics.

• Total Reach:

Add up the impressions across all the different formats to see the real visibility of the campaign.

• Engagement Wins:

Compare which formats perform best to inform how you slice your next ‘Big Rock’ asset.

• Lead Tracking:

See how many downloads of the original asset came from the social clips versus the blog posts.

• Time Saved:

Measure how many hours your team saved by using Content Atomization compared to creating from scratch.

• Traffic Sources:

Identify which platforms are sending the most qualified traffic to your main landing page.

Maximum Impact From Minimum Creative Input

You are competing in an attention economy where volume matters. However, quality is still king. By mastering Content Atomization, you get the best of both worlds. You keep high standards by starting with a premium asset, and you get high volume by using AI to distribute it. It is time to work smarter, not harder.

Why? The root cause isn’t poor implementation. It’s simply that B2B operates under different statistical conditions than business-to-consumer (B2C) brands.

Where MMM Works Well

MMMs are econometric tools that use historical patterns to estimate the causal impact of marketing on key business outcomes like revenue, leads, or new customers. They perform best when four conditions hold:

• High transaction volume

provides statistical power. With thousands of daily orders, the model can learn from fine-grained variation.

• Consistent offers and values

keep metrics stable. If most purchases fall in a predictable range (say $200–$800), averages like CPA and ROAS are meaningful. Extreme values make average measures less useful.

• Short purchase cycles

tighten the link between ad exposure and conversion. Direct-response behaviors make cause and effect clearer.

• Direct purchase paths

make causality clearer. Each additional step between ad exposure and an ultimate conversion introduces confounders that complicate measurement.

These conditions are common in CPG, ecommerce, and similar environments. A B2C sunglasses brand, for example, may have thousands of weekly orders, basket sizes averaging $150, decisions within days, and no sales team.

Why MMM Struggles in B2B

B2B tends to introduce properties that are challenging for econometric models:

• Low volume.

An enterprise software firm might close ten deals per quarter. With sparse data, distinguishing real signal from noise is hard.

• Extreme value variation.

Deal sizes can span orders of magnitude. If one contract represents 40% of the quarter’s revenue, “average” metrics have little use.

• Long cycles.

Twelve to twenty-four months from awareness to signature blurs the tie between any specific marketing activity and the eventual close.

• Complex buying processes.

Multiple stakeholders, procurement, technical evaluations, and legal issues inject variation unrelated to marketing.

These aren’t mere technical hurdles. They’re mathematical limitations. If you combine sparse data, high variance, long lags, and complex conversion paths, traditional models will struggle to find reliable patterns. The same approach that confidently measures a CPG campaign can become unreliable in enterprise B2B. No amount of sophistication can conjure signal from insufficient data.

Additional Complications

• Sales variability.

After marketing hands off a lead, outcomes depend heavily on sales reps. Top performers might close 5× more than the median, so salesperson quality can be much more important than marketing effects.

• Account complexity.

The person most influenced by marketing may not be the decision-maker. Wins and losses can reflect internal politics or product fit rather than media.

Where MMM Can Work in B2B

B2B isn’t monolithic. MMM can be viable where B2B resembles B2C:

• Product-led growth or high-volume SMB.

Payments or SaaS serving thousands of small customers can generate enough frequency.

• Self-service SaaS.

Monthly subscriptions without sales involvement create repeatable purchase events.

• SMB-focused contracts.

$1k–$10k ACVs with shorter cycles provide statistical power.

• Hybrid models.

Use MMM for the self-serve segment, but employ different methods (e.g., account analytics) for enterprise.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

The Validation Imperative

A critical point with any media mix modeling project is that if you can’t validate the model, you’re making million-dollar bets on assumptions. Yet common validation methods are likewise tougher in B2B:

• Holdout forecasting.

Train on history and predict the future. With 18-month cycles, you might wait years to judge accuracy. By then the market may change.

• Incrementality tests.

Geo-lift or controlled experiments offer ground truth, but low deal counts make effects hard to detect without very long tests.

• Forecast tracking.

Comparing predicted vs. actual outcomes creates a feedback loop, but long cycles slow learning to a crawl.

Unless you can validate a model, you shouldn’t use it for decision-making. The temptation is to fill gaps with assumptions (uniform close rates, constant rep quality, tidy decay curves). Each may seem harmless. Added up, though, they can produce outputs that are way off the mark and precision without accuracy is worse than acknowledged uncertainty.

Navigating the Trade-offs

No method is perfect. There are trade-offs among precision, accuracy, timeliness, and cost. If you opt to pursue MMM in B2B:

• Document every assumption, and share it.
• Present uncertainty ranges honestly, even when they’re wide.
• Set realistic expectations about what your model can and cannot estimate.
• Align internally on limitations before Many firms discover too late that their results were too uncertain to drive decisions.

Also consider alternatives that are better suited to enterprise sales:

• Account-level analysis and cohort views for complex deals.
• Channel-specific experiments where volume allows.
• Mix models for self-serve only, paired with relationship mapping and qualitative signals for enterprise.
• Attribution hybrids (lightweight rules & experiments) to inform near-term optimization while acknowledging long-cycle uncertainty.

The B2B teams that succeed at measurement don’t force inappropriate tools onto their realities. They assess context honestly, pick methods that match, and validate ruthlessly. They know B2B is not B2C, and that admitting what you simply cannot know is the first step to discovering what you can.

Before adopting any method, MMM or otherwise, ask:

1. Do we generate enough data for this approach?
2. Can we validate outputs in a reasonable timeframe?
3. Are we relying on assumptions that paper over fundamental limitations?

If you can’t answer Yes, Yes, and No, you’re better off choosing another measurement approach.

This acquisition—Intentsify’s second in just two years—signals a clear divergence from the competitive landscape by focusing on delivering tangible solutions and outcomes for sales and marketing teams. Intentsify’s continued financial health allows for the expansion of its solution set, posting 21% overall revenue growth overall and 50% growth in data solutions revenue in 2025. This momentum enables the company to move beyond organic growth, making bold, strategic investments in both the 5×5 and Intentsify product lines. The investment into Salutary Data reinforces that commitment, further expanding the unified data ecosystem that bridges the gap between intent signals and verified human identity.

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Salutary Data is known for its rigorous data validation processes and comprehensive coverage of U.S. based B2B contacts. By integrating Salutary’s data exhaust, both Intentsify and 5×5 customers will benefit from improved identity resolution, richer account and contact profiles, and more reliable activation across advertising, sales, and marketing workflows.

“Our vision is to build the strongest possible engine for B2B growth, and that requires moving beyond the industry’s status quo,” said Marc Laplante, Co-Founder and CEO at Intentsify. “By adding Salutary Data to the portfolio of Intentsify companies, we are doubling down on the identity layer of our intelligence engine. In an era where our competitors are struggling to maintain independence, we are accelerating.”

“Joining the Intentsify portfolio is a massive win for our team and, more importantly, for the B2B organizations we serve,” said Scott Gordon, CEO of Salutary Data. “Our mission has always been to provide the cleanest, most reliable data available; by becoming a core part of this broader intelligence ecosystem, we are accelerating our ability to deliver that at an unprecedented scale. This acquisition allows us to fuel a more powerful, unified growth engine, ensuring that go-to-market teams finally have access to the most actionable and intelligent data on the market .”

“Our transition from competitors to partners proves that the sum of our intelligence is far greater than its individual parts,” said Nick Weldon, CEO of 5×5. “Because we’ve worked with the Salutary Data team for years, we knew their innovative DNA matched ours perfectly. This acquisition isn’t just a business deal; it’s a natural evolution of a shared entrepreneurial vision.”

This acquisition underscores Intentsify’s continued investment in data innovation and its commitment to helping B2B marketers drive measurable outcomes through intent-driven strategies. Existing customers will see no disruption to service and can expect expanded capabilities as the integration progresses.

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Partnership combines 6sense’s agent-powered Revenue AI with 2X’s comprehensive service capabilities to eliminate the execution gap limiting ROI

2X, the global leader in subscription-based go-to-market services, announced the launch of the most comprehensive suite of 6sense services ever brought to market. With more than 175 6sense-certified professionals, more than any company other than 6sense itself, and over 1,200 B2B marketing experts, 2X delivers unmatched scale and expertise. Announced at 6sense Breakthrough 2025 in Las Vegas, 2X was also named 2025 Agency Partner of the Year.

2X’s services portfolio optimizes every 6sense capability—Platform, Predictive, AI Email, Sales Intelligence, and Intelligent Workflows—with services spanning the complete adoption lifecycle: implementation and strategic consulting, ABM/campaign managed services, reporting and analytics, sales adoption, creative and content production, media management, marketing operations, and technical support and integration. Drawing on experience with more than 100 6sense implementations, 2X orchestrates the platform within clients’ broader revenue technology ecosystems, providing integration and managed services between 6sense and leading platforms, including Gong, HubSpot, Salesforce, Bombora, Outreach, Salesloft, and Adobe, to ensure unified go-to-market execution across the entire tech stack.

By expanding access to certified expertise and scalable resources, 2X’s AI-enabled, globally staffed subscription services model helps enterprises unlock even greater value from their 6sense investment—accelerating adoption and maximizing impact without increasing headcount or budget.

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Through this enhanced partnership, 6sense will soon offer clients direct access to 2X’s proven services, including the ability to purchase 2X services from a 6sense account executive and through a client’s existing 6sense contract. The collaboration enhances 6sense’s robust professional services offerings, providing customers with additional pathways to accelerate adoption and maximize value.

“6sense is a powerful platform, and powerful platforms require expert execution,” said Dom Colasante, CEO of 2X. “We’ve spent years building the services to deliver that execution at scale. This partnership makes it easier for clients to get both, which is exactly what they’ve been asking us for.”

“6sense gives revenue teams the intelligence and automation to drive performance across marketing, sales, and customer success,” said Chris Ball, CEO of 6sense. “Our expanded partnership with 2X makes it even easier for customers to access the certified expertise and scalable resources they need to accelerate results and realize the full value of their 6sense investment.”

Together, 6sense and 2X are defining a new standard for B2B revenue technology: where buyer intelligence and expert strategy and execution are delivered as an integrated solution, not separate vendor relationships—making sophisticated revenue orchestration accessible to enterprises of all sizes.

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