• G2 found 51% of B2B software buyers now start their research with AI chatbots, reshaping vendor selection and decision-making.
• AI chatbots are influencing buyer shortlists, with 83% of buyers feeling more confident in their final choice.

A new report from G2 highlights the impact that artificial intelligence (AI) is having with B2B software buyers.

G2’s The Answer Economy: How AI Search Is Rewiring B2B Software Buying report found that 51% of B2B software buyers now begin their purchasing process in an AI chatbot rather than a traditional search engine— and buyers increasingly return to AI chatbots at every stage of their journey.

The shift to AI chatbots as the starting point for software buying increases since G2’s last report, influencing vendor selection, and accelerating decisions— 69% of buyers indicated they chose a different software vendor than they initially planned based on AI chatbot guidance, and one-third purchased from a vendor they had never heard of before.

AI is Influencing Buyers Shortlists

G2 first began tracking this shift to AI search in its April 2025 Buyer Behavior Report. Now the trend shows no signs of plateauing as 83% report feeling more confident in their final choice with AI chatbots the top source influencing which vendors make buyer shortlists.

“We’re watching the third compression era of the buyer journey unfold in real time,” said Tim Sanders, Chief Innovation Officer at G2, in a statement. “The Yellow Pages compressed the market into the big book. Google compressed it into the first page of results. Now, AI chatbots are compressing it into a single answer.”

How B2B Buyers are Relying on AI Chatbots

The report, based on a March 2026 survey of 1,076 B2B software buyers and decision-makers, highlights how AI chatbots have accelerated software research, helping buyers achieve stronger outcomes. Nearly three in four (71%) B2B software buyers rely on AI chatbots for software research, compared to 60% previously. And 53% of B2B software buyers feel research done with an AI chatbot is more productive than traditional search, up from 36%.

In the answer economy, buyers have moved from reference to inference, leveraging AI to synthesize the research process and return a shortlist.

A third of respondents purchased from a vendor they weren’t familiar with. Eighty-five percent of buyers think more highly of a software vendor when an AI chatbot mentions them in a recommendation while four out of five buyers say AI chatbots accelerated their purchasing decision.

How Many Hours a Week Are AI Chatbots Being Used

G2 officials noted today’s software buyer is sophisticated as they increase their time with AI chatbots at work, running head-to-head comparisons, creating deep research reports, and using thinking mode for high-stakes evaluations. Other key finding of the report incldue:

• Nearly two-thirds of buyers now spend six or more hours per week using AI chatbots for work, and over 40% self-identify as power users who leverage them daily.
• Comparing vendor strengths and weaknesses is the top use case for AI chatbots in software research (41%) — ahead of basic product research, vendor identification, and use case validation.
• Forty-one percent of buyers use Deep Research tools regularly for software evaluations.
• ChatGPT remains the dominant AI chatbot for B2B software research (63%), but the competitive landscape is shifting fast.

“Buyers have moved from reference to inference. Instead of gathering sources and synthesizing the data themselves, they trust AI chatbots to return the shortlist in a single prompt. That disrupts how software vendors need to think about their presence,” said Sanders.

Click here for the full report.

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• Signal stacking reveals hidden intent.
• It’s time to redefine account coverage metrics to role-based participation and stage-fit tracking.

You just finished an incredible demo. Your primary contact loved the presentation, shared your deck internally, and your pipeline looks perfectly healthy. Then, out of nowhere, the deal stalls. The problem is not your product or your pitch. Instead, the problem is that your strategy relied on a single champion.

At the B2B Marketing Exchange (B2BMX) 2026 powered by Advertising Week, industry leaders tackled this exact scenario in a session titled Champion to Consensus: Practical Buying Group Coverage That Improves Conversion. The panel, moderated by Demand.com’s Rick Robinson that featured his colleague Terry Arnold, Gorilla Logic’s Whitney Goldstein and Delinea’s John Johansen, dismantled traditional, single-lead approaches that create massive pipeline friction.

The four experts explained how B2B decisions are increasingly made not by individuals but, rather, by committees. To help teams adapt, the panel examined three persistent myths about buying group engagement and offered practical prescriptions to fix them.

Does One Engaged Contact Equal Account Momentum?

Although many sales and marketing teams falsely believe that a highly engaged champion means the entire account is ready to buy, the reality is quite different. Two-thirds of B2B buying committees now consist of six or more stakeholders.

The prescription for mitigating this risk is proactive engagement. Teams must define required roles early in the process and run targeted plays to handle objections before they become deal-killing vetoes. Marketing and sales must work together to build narratives that resonate across the entire organization — from executive leadership down to daily tactical users.

Arnold highlighted how marketing teams can structure this approach effectively by grouping stakeholders and mapping content to these clusters. By doing so, teams can ensure no critical voice is left in the dark.

“We create role-based clusters, which basically start to look at specific levels,” he explained. “We break that out so that, in marketing, we are engaging each of those different roles in a way which is relevant to the issues that they’re trying to solve.”

Does High Intent Equal Account Readiness?

Intent data has become a staple for revenue teams, leading to the assumption that high intent automatically equals account readiness. However, intent is almost always persona-specific, the panel members observed. Just because one mid-level manager is researching a problem does not mean the broader buying group acknowledges the issue or has budget allocated to fix it.

To combat this, teams must validate intent with role breadth and stage fit. A single signal is just a starting point. More important is for marketers to look for signal stacking — evidence that multiple people within the same account are researching related topics. Furthermore, as search behaviors shift, teams must optimize their content to leverage Large Language Models (LLMs) and Answer Engine Optimization (AEO) to identify hidden intent.

Goldstein stressed the importance of questioning initial data and demanding verifiable proof of momentum, stating, “I look at intent as a clue, not necessarily the conclusion. What I’m trying to do is make our pipeline predictable. And so, we really do need to distinguish what is the signal versus what is the noise.” Signal stacking, she said, is a great strategy for doing so.

How Should Teams Measure Account Coverage?

For years, marketing success was graded on lead volume. And many teams still believe that account coverage can be measured with Marketing Qualified Leads (MQLs), clicks, or a handful of hot prospects. But here’s the reality: Coverage is actually about role participation, depth of engagement and stage fit. A high volume of leads means nothing if they all sit in the same department and ignore the financial or operational stakeholders.

The prescription is a fundamental shift in tracking. Revenue teams must track exactly who is engaged, identify which key roles are missing, and define the precise next action to bridge that gap. An operations narrative that hasn’t been communicated represents a massive structural risk to the deal.

Measuring coverage means looking at the balance of engagement across the entire account. Johansen shared a practical way that his team enforces this mindset through systemic tracking.

“The answer for me is how many people you can get attached to the opportunity in your CRM,” Johansen said. “Starting to work on that behavior and being able to say who are you engaged with [and] add them here. And it also gives us that signal to ask, ‘OK, well, where are we lacking coverage?”

How Can Revenue Teams Shift from Champion to Consensus?

The transition from champion to consensus requires a complete shift in how revenue teams operate. Arnold pointed out that building structural coverage demands tailored narratives for every layer of the business. “If teams fail to communicate value to the tactical, operational, and executive levels simultaneously, deals will inevitably stall at the finish line,” he said.

Goldstein reinforced that marketing must build a foundation of credibility and proof. Relying on anonymous website traffic or isolated clicks is no longer enough to forecast accurately.

“Teams must demand verified engagement across multiple first-party touchpoints, ensuring that content drives measurable outcomes and answers the diverse questions of the entire buying collective,” she offered.

Johansen summarized the cultural shift required between sales and marketing, saying, “Both departments must share ownership of the pipeline and stop treating committee penetration as solely a sales responsibility.”

But the most important takeaway from the session, which the entire panel echoed, serves as a warning for modern revenue teams: Don’t confuse activity with coverage. True pipeline health only exists when the entire buying group moves forward together.

The post B2B Buying Decisions Demand Consensus, Not Champions: Lessons From B2BMX 2026 appeared first on Demand Gen Report.

Buyers are not just researching differently; they are evaluating and shortlisting differently and increasingly deciding before sales reps ever enter the conversation. Sales teams are losing early-stage influence. Pricing power is shifting. Vendor differentiation is happening algorithmically, and the top of the funnel is tightening rapidly.

The implications for Chief Revenue Officers (CRO) and Chief Marketing Officers (CMO) are profound. A recent multi-industry survey confirms what many commercial leaders have sensed anecdotally: traditional sales motions are being displaced by an AI-accelerated, increasingly self-service buying process.

The Rise of AI Usage

In fact, 60% of buyers use AI moderately or extensively when researching potential solutions and 43% of buyers say AI has saved 30% or more of their time in discovery and qualification.

CROs and CMOs that adapt quickly will shape buying journeys in their favor; those that do not risk being excluded before conversations ever begin. Following are the four commercial imperatives that demand immediate action and what CMOs and CROs need to do to meet them.

Engineer Your Digital Footprint for AI Discovery

 If AI can’t interpret you clearly, it won’t recommend you. The test executives can use to determine how they are faring with this is to look at when AI summarizes your category, does your perspective shape the answer?

 Here’s what CMOs and CROs need to do:

• Restructure websites, case studies, pricing pages, and technical documentation so AI systems can easily ingest, analyze, and synthesize them – including proprietary research, named frameworks, and proof points.
• Make positioning explicit and declarative. Remove ambiguity in how you describe your category, differentiation, and ideal customer profile.
• Strengthen authority signals through consistent thought leadership, backlinks, and AEO driven formatting to increase AI citation likelihood.
• Conduct quarterly AI mystery shopping to assess how generative engines describe you versus competitors and close narrative gaps immediately.

Win the First Five Minutes

In an AI-accelerated buying cycle, speed and substance determine inclusion. The new standard means that the first touch must advance the buyer’s thinking.

 Here’s what CMOs and CROs need to do:

• Redesign lead management to achieve best-in-class response times (five minutes or less) – with real-time measurement and accountability.
• Ensure the first human interaction adds insight, not friction. AI-sourced leads expect expertise, not qualification scripts.
• Equip SDRs with AI tools to instantly contextualize the buyer, personalize outreach, pre-qualify intelligently, and route precisely.
• Elevate frontline technical fluency through training and revised coverage models; introduce SMEs earlier where it materially accelerates trust and deal velocity.

Remove Friction from the Buying Experience

 If buyers can research faster, they expect to purchase faster. The commercial reality is that speed and simplicity are increasingly competitive advantages.

 Here’s what CMOs and CROs need to do:

• Compress internal decision cycles – streamline pricing approvals, legal review, and contract negotiation.
• Simplify packaging, terms, and onboarding to reduce perceived risk and time-to-value.
• Deploy interactive ROI models, configurators, and AI-driven demo walkthroughs – now table stakes in competitive categories.
• Audit every stage of the buying journey for latency, redundancy, and unnecessary internal complexity.

Make Pricing AI-Resilient and Strategically Defensible

AI is increasingly interpreting and comparing your pricing model before a rep ever engages.  The question executives should ask themselves to determine how they are faring with this is if AI is reinforcing your premium (or undermining it) when it explains your pricing to a buyer.

 Here’s what CMOs and CROs need to do:

• Clarify competitive advantage and differentiation in ways that are explicit, structured, and machine interpretable.
• Simplify pricing architecture to ensure it is benchmark-aligned, value-backed, and easy to explain – both by sellers and by AI systems.
•  Evaluate outcome-based or hybrid pricing structures where they reinforce strategic positioning.
• Align pricing tightly to your core value drivers; ambiguity will be exposed and commoditized.

AI has abruptly and fundamentally reshaped the B2B buying journey. Buyers research more, shortlist differently, evaluate faster, expect transparency, and require higher-value interactions from reps. Sales organizations that respond proactively, redesigning content, tools, pricing, and capabilities, will thrive. Those that do not will increasingly lose deals before conversations ever begin.

Michael Smith is the Senior Managing Director – Technology, Media & Telecom Practice Leader at Blue Ridge Partners. Michael has over 35 years of experience helping companies accelerate revenue growth and develop winning sales strategies. Previously, Michael worked at McKinsey & Company and in multiple corporate executive operating roles running businesses and sales teams. Michael received his MBA from Stanford University and lives in the Boston, Massachusetts area.

The post The 4 Actions CMOs & CROs Must Take to Catch Up to the AI-Augmented Buyer appeared first on Demand Gen Report.

• Target specific decision-makers and hidden stakeholders instead of relying on broad account-level outreach. 
• Eliminate sales latency by synchronizing marketing and sales efforts to deliver personalized educational content at the precise moment of need. 

Account-based marketing (ABM) requires precision, intelligence, and a deep understanding of human behavior. At B2B Marketing Exchange (B2BMX) 2026, powered by Advertising Week, LiveRamp’s Ed Vander Bush and Influ2’s Doug Madey discussed the importance of focusing  marketing efforts on the right individuals. By treating key buyers as the main characters of your outreach, B2B marketers can drive unparalleled revenue growth and foster meaningful business connections.

Understanding the buyer’s journey forms the foundation of any successful account-based marketing strategy, the two stated.. As buyers move from initial awareness into deep consideration, their needs and expectations shift dramatically. Marketers must map these stages meticulously to ensure they provide relevant information exactly when the prospect requires it.

Buyer Journey and Personas

Personas play an equally critical role in this progression. Targeting an entire account often dilutes the message, whereas focusing on specific individuals allows you to tailor your communication to the distinct pain points of the decision-makers. This contact-level approach transforms generic outreach into valuable, consultative engagement.

Reflecting on this need for precise targeting, Vander Bush noted, “It really comes down to understanding not only the account, but the person on the other side of the process.”

Challenges in the Buying Process

Modern B2B purchasing decisions rarely happen in a vacuum, presenting significant challenges for sales and marketing teams. Buyers conduct extensive independent research, meaning that by the time they finally reach out for a meeting, they have often already finalized their decision. This dynamic forces revenue teams to engage prospects much earlier in the evaluation phase.

Another major hurdle is the presence of hidden stakeholders who influence the final decision but remain invisible within your CRM. When sales representatives execute unexpected outreach without understanding the full buying group, they risk alienating these unseen decision-makers. Navigating this complexity requires gathering deeper contact-level insights.

“Having been recently on the buying side, I was surprised by hidden stakeholders within my own company ” noted Vander Bush. “Colleagues who brought real, important perspectives to the table that become completely invisible if we were to try to reduce the buying journey to the account level.”

Latency and Orchestration in Sales

Latency in the sales process occurs when representatives react to outdated signals and reach out too late. Relying solely on account-level intent data often creates a lag, causing sellers to miss the critical window of opportunity when the prospect is actively seeking solutions. Eliminating this delay is essential for maintaining momentum in the deal cycle.

Vander Bush emphasized the importance of this alignment, stating, “Too often, we align around the real problem too late, waiting for a sufficient ‘score’ rather than orchestrating marketing and sales together around the signals that reveal what real people are trying to achieve as they move through the customer journey.”

To address the latency problem, revenue teams must master the orchestration of relevant materials. Serving the right content at the precise moment requires marketing and sales to operate in total alignment, moving beyond siloed activities. This synchronized effort ensures that the buyer receives continuous value without aggressive, premature sales pitches.

Personalization and Content Strategy

A robust content strategy relies heavily on personalization to drive internal consensus within target accounts. Vander Bush highlighted a case study involving a global brand where an internal champion recognized the immense value of a data clean room. However, this champion struggled to secure the necessary buy-in from skeptical colleagues across different departments.

Instead of aggressively pushing for more sales meetings, the team deployed a highly personalized content strategy. They distributed targeted educational videos designed specifically to provide thought leadership of those hesitant internal stakeholders. This strategic distribution of content naturally multi-threaded the account, elevating the conversation and ultimately leading to increased attendance at pivotal sales meetings.

“This wasn’t a time for a traditional multithreading strategy,” stated Vander Bush. “This was the time to put really well-timed, relevant educational content in front of those contacts our champion was trying to sell internally. That effort led to those contacts leaning in and asking to join the next call, because as their knowledge grew, so did their understanding of the potential business value of a clean room.”

Attribution and Campaign Impact

Proving the impact of targeted campaigns remains a persistent attribution problem for B2B marketers. Standard dashboards often fail to capture how specific marketing touches influence individual buyers over time. Accurately measuring this engagement is vital for demonstrating how ABM moves prospects further down the sales funnel. This is where taking a contact-level approach to your ABM program helps, because you can’t tailor the next message if you don’t know who engaged with what. There’s no context on which topic landed—or whether anything changed.

Such engagement can be measured at various points of the customer journey, even while performing different functions. For example, personalized messaging can serve as a powerful tool to overcome stubborn gatekeepers who block access to decision makers. By deploying the right level of personalization, you can bypass these barriers and deliver compelling arguments directly to the people holding the budget. This level of precision transforms stalled opportunities into active deals. Engagement that speaks directly to the attribution and impact of the campaign.

Vander Bush illustrated this impact with a real-world example: “I worked with a seller trying to close an end-of-quarter deal who was being blocked from everyone who needed to sign. Coming into that conversation, we were able to show how those stakeholders were already engaging, which opened the door to collaborating. We spent 20 minutes over Slack and hammered out a plan to deliver that personalized messaging to the right people.”

Collaboration Provides Results

The synergy between marketing and sales dictates the overall success of any account-based strategy, noted Vander Bush. Delivering personalized, relevant content requires both teams to share insights seamlessly and understand the buyer’s point of view.

When revenue teams collaborate effectively, they empower internal champions to advocate for their solutions with confidence.

“Understanding the buyer’s perspective fundamentally changes how you approach content creation and sales outreach,” he said. “Showing true value and relevance to stakeholders transforms your brand from a vendor into a trusted strategic partner. Delivering with empathy and specialized knowledge drive these engagements forward.”

The post Orchestrate ABM Around Main Characters, Not Extras: Lessons from B2BMX appeared first on Demand Gen Report.

What used to be considered the final stage of the funnel— advocacy— has quietly become one of the primary drivers of discovery, trust, and pipeline growth.

Why Advocacy Matters Now

Two structural shifts are making advocacy central in B2B marketing:

Hidden buyers wield decisive influence. Buying committees increasingly include various stakeholders, including finance, legal, procurement, and operations, who rarely meet sales reps but influence vendor selection.

Many stakeholders say thought leadership is more persuasive than product sheets, and over 79% are more likely to champion a vendor with consistent, high-quality ideas. What’s more, over 40% of deals stall due to internal misalignment, which is often driven by these silent influencers.

Discovery is shifting toward AI + third-party proof. AI-driven search is changing how B2B buyers research and shortlist vendors. According to G2’s 2025 Buyer Behavior Report, leads that originate through AI-powered search convert approximately 40% better than those from traditional search engines, primarily because buyers encounter credible, third-party content earlier in the journey.

This evolution highlights a larger truth: advocacy must exist where research actually happens. The most persuasive proof points are increasingly discovered on neutral ground. Buyers are looking at review platforms, community discussions, and practitioner-authored content long before they reach a brand’s website.

Three Advocacy Engines B2B Organizations Can Scale

1. Customer Communities That Deliver Value (and Reduce Cost)

Communities should not be treated as engagement tools alone. When structured effectively, they generate long-term ROI across support, adoption, upsell, and advocacy.

Cisco’s partnership with Khoros is a good example: over their first year, engineers published 47% more content internally, community interactions drove over 1 million annual views, and the program delivered approximately $54.2 million in case deflection savings. Mature community programs are shifting focus from vanity metrics (posts, users) to business outcomes (deflection, retention, engagement).

Tactical moves:

• Stimulate “how-we-fixed-it” threads contributed by customers and internal experts
• Surface accepted answers, highlight best practices, and integrate these into onboarding, product documentation, and training
• Track deflection rates, time-to-first-answer, usage lift, and expansion signals

2. Peer Proof on Platforms Buyers Trust

Trust increasingly forms outside of brand-owned channels. Decision-makers rely on independent, experience-based sources. Review platforms, practitioner communities, and peer content often guide vendor selection.

Demand Gen Report’s 2024 B2B Buyer’s Survey highlights that discerning buyers increasingly rely on peer reviews and in-depth research as trusted guidance in purchase decisions. These findings point to a consistent pattern: credibility is earned on neutral ground. Buyers place greater weight on what peers and practitioners say about a solution than on what the vendor claims about itself.

Tactical moves:

• Treat reviews as a structured, ongoing program rather than one-time requests.
• Keep third-party profiles current with recent customer quotes, screenshots, and implementation details.
• Reuse authentic peer feedback in enablement content—always linking back to its verified, external source.

3. Employee & SME Advocacy That Reaches Hidden Buyers

Thought leadership remains one of the few credible routes into parts of an organization where sales lacks access. Even small adjustments to employee-shared content can boost reach dramatically.

Tactical moves:

• Issue a monthly advocacy brief with three credible themes (customer story, data, contrarian insight)
• Provide lightweight framing rather than scripts, and encourage personalization
• Track reach, engagement, and account-level influence

Building an Advocacy System, Not Just Tactics

• Design mutual value exchange.
  • For customers: offer visibility, early access, roadmap influence, expert forums
  • For employees: offer recognition, guardrails, support, and training
• Make advocacy easy. Toolkit components might include business-case one-pagers, compliance/security FAQs, comparison visuals, and internal champion scripts.
• Break down silos. Let best community content feed into knowledge bases, reviews, case studies, and SME insights. Enable CSMs and product leaders to nominate strong customer stories.
• Measure what matters. Go beyond engagement metrics. Tie advocacy to account coverage (which ICP accounts have an engaged advocate?), toolkits downloaded, review velocity, and SME reach by role. Emphasize outcomes over activity counts.

What to Report (and Benchmark)

Case deflection & cost savings (modeled or actual)

Engaged-account coverage: percent of target accounts with at least one advocate touchpoint

Champion enablement metrics: downloads/shares of toolkits, internal referrals

Review velocity & depth: number of reviews per quarter, recency, qualitative depth

SME influence on hidden buyers: impressions, engagements, internal advocacy contributions

A 60-Day Advocacy Launch Plan

Final Thought

As buying journeys become more distributed and AI surfaces more third-party insight, the companies that grow fastest will be those that build credible ecosystems of proof. Advocacy is no longer simply about retention or customer satisfaction. It is a scalable demand engine that influences discovery, accelerates consensus inside buying groups, and reinforces trust at every stage of the decision process.

Cynthia Ortiz is a Marketing Program Coordinator for Televerde, a global revenue creation partner supporting marketing, sales, and customer success for B2B businesses around the world. A purpose-built company, Televerde believes in second-chance employment and strives to help disempowered people find their voice and reach their human potential.

The post The New Demand Engine: Why Peer Proof Is Reshaping the B2B Buying Journey appeared first on Demand Gen Report.

• Demand Gen Report’s 2026 Campaign Optimization Series focused on marketing strategy that build trust across external channels, as B2B buyers now conduct extensive independent research well before contacting vendors.
• Speakers discussed getting on buyers shortlists, why company websites are often not the first stop in the buying funnel and what an Agent Qualified Lead is

B2B marketing professionals continuously seek proven strategies to drive revenue generation and optimize their campaign life cycles.

During Demand Gen Report’s 2026 Campaign Optimization Series (#COSeries), industry leaders from Demandbase, NetLine, and Docket shared their expertise on navigating shifting buyer behaviors. Across three comprehensive webinars, these experts detailed how marketers can build dynamic campaigns, capture true intent, and leverage artificial intelligence to foster meaningful connections.

Here are five essential lessons learned from the series.

Influence Starts Long Before the Shortlist

B2B buyers now conduct extensive independent research well before they ever contact a vendor. They review peer insights, explore trusted third-party content, and define their exact requirements in private channels. This independent approach means marketing teams can no longer wait for buyers to raise their hands.

Instead, marketing professionals must focus heavily on shaping demand during these early research phases. Building influence requires a consistent presence across the broader digital landscape, delivering credible perspectives that help buyers validate their thinking. By the time a buyer forms a shortlist, their core decisions are largely finalized.

Josh Baez from NetLine highlighted this massive shift in buying behavior and the urgent need for marketers to adapt.

“The most important buying decisions are happening well before vendors even know that a deal exists,” said Baez. “Buyers are doing more research on their own. They’re involving more stakeholders, and they are delaying vendor interaction until much later in the process. In fact, 83% of buyers define their requirements before ever speaking to sales.”

To succeed, marketing content must do more than answer basic questions. Content must actively shape the questions buyers ask themselves, positioning your brand as a trusted authority. This proactive influence secures your place on the shortlist before the buyer even realizes they are ready to purchase.

Aligning Campaign Spend with Sales Priorities

Resource allocation remains a critical challenge for marketing teams striving to maximize their return on investment. Treating all target accounts equally drains budgets and dilutes the impact of personalized messaging. Marketers need a structured methodology to determine which prospects deserve the highest level of investment.

Hannah Jordan from Demandbase stressed that implementing a rigorous account scoring model provides the necessary framework to categorize accounts into specific tiers. This tiering system allows marketing operations to dictate exactly how much budget and effort goes toward engaging each prospect. High-value accounts receive premium, highly personalized outreach, while lower-tier accounts receive more automated, scalable communications.

Jordan emphasized the importance of using these tiers to synchronize marketing and sales efforts, stating “the tier is really going to determine the spend per account…we want to align our spend and our resources and make sure that we’re prioritizing the accounts that sales is also prioritizing.”

This deliberate alignment prevents wasted spend and ensures both departments work toward shared revenue goals. When marketing invests heavily in the exact accounts that sales wants to close, the entire campaign life cycle accelerates, resulting in stronger pipeline quality and demonstrable revenue growth.

Shifting to a Coverage-Centric Strategy

Relying solely on driving inbound traffic to a corporate website is an outdated approach to demand generation. Buyers spend the majority of their time consuming information on external platforms, industry publications, and peer networks. Marketers must expand their focus beyond their own digital properties to capture attention effectively.

A coverage-centric strategy solves this problem by ensuring your brand maintains a consistent presence wherever your buyers naturally gather. This means showing up across various channels, environments, and buying groups to build familiarity and trust over time. Coverage focuses on visibility in the places where actual buying decisions form.

Baez explained the fundamental difference between these two marketing philosophies during his session. “We move from a website centric model to a coverage centric instead of asking, how do we get buyers to come to us, we ask, how do we show up where buyers already are?” Baez said.

By prioritizing market coverage, brands integrate themselves into the buyer’s daily research habits. This consistent, multi-channel exposure ensures that when buyers finally decide to visit your website, they already view your company as a credible and familiar solution provider.

The Demise of the Traditional MQL

For over a decade, the Marketing Qualified Lead served as the ultimate metric for measuring campaign success and pipeline health. However, static forms and basic website click data fail to capture true buyer intent accurately. A massive gap now exists between raw website traffic and genuinely qualified sales pipeline.

Modern buyers utilize sophisticated tools, including large language models, to gather information before they ever navigate to a vendor’s site. Because they gather basic facts elsewhere, their visits to your website serve a much different purpose than they did years ago. Traditional lead scoring models simply cannot interpret this new pattern of behavior.

Lauren McHugh from Docket pointed out that marketing teams must abandon outdated measurement frameworks. McHugh explained, “The erosion of our traditional conversion signals like the MQL that metric has really been defined for B2B marketing over the past decade, and it really is no longer built for how buyers are behaving today.”

Marketers must rethink how they measure website conversion altogether. Instead of tracking passive clicks or document downloads, the focus must shift to capturing substantive engagement and measuring the depth of a prospect’s actual questions.

The Rise of Agent Qualified Leads

Because buyers do their preliminary research elsewhere, the corporate website now functions as the endpoint of the buyer journey rather than the starting line. When buyers finally arrive at your site, they want immediate, specific answers to complex questions. Forcing these highly educated buyers to fill out static forms creates unnecessary friction.

Artificial intelligence provides a powerful solution through conversational engagement. AI-powered agents can conduct real-time discovery, answer sensitive questions, and provide personalized support without requiring human intervention. This interactive approach captures a much deeper level of intent than any traditional web form.

McHugh highlighted how this technological shift fundamentally changes the quality of leads passed to sales teams. Agent Qualified Leads (AQL) supply sales representatives with rich, contextual information about the buyer’s specific challenges and requirements. This intelligence allows sales teams to bypass generic introductory calls, moving directly into meaningful, solution-oriented discussions that drive faster revenue growth.

“AQL or an agent qualified lead really is substantive. In the context behind that conversation, the AQLs are moving through the pipeline faster and actually converting at higher rates because they’re arriving to those sales people,” McHugh said.

The post 5 Key Insights from the 2026 Campaign Optimization Series (#COSeries) appeared first on Demand Gen Report.

Alongside the RGI Platform, HG Insights is introducing RGI Agent Builder, its agentic infrastructure for enterprise GTM teams, now available in early preview. HG’s agentic infrastructure turns fragmented GTM data and signals into an integrated system that feeds every copilot and agent with shared context, powers agentic workflows across the stack, and gives GTM leaders reliability and control over how AI helps drive pipeline and revenue outcomes.

Built on HG Insights’ RGI Fabric, the RGI Platform delivers advanced copilots and agentic workflows to optimize GTM execution and efficiency.

Focused on GTM Use

Rohini Kasturi, CEO of HG Insights, stated GTM teams are being tasked to grow revenue with fewer resources than ever before, but the answer can’t be just spending on more tools, data, and dashboards.

“AI in GTM simply amplifies whatever data you feed it. If it is shallow or fragmented, you just scale noise and mistakes,” said Kasturi in statement. “The RGI Platform, Fabric, and our agentic infrastructure were built to flip that script. For the first time, GTM teams have a unified Revenue Growth Intelligence Platform where deep, connected intelligence doesn’t just inform decisions, it drives them into precise, scalable execution.”

Three AI Copilots. Expansive GTM Application.

GTM is undergoing a structural shift: from insights to execution, from static dashboards to guided action, and from manual workflows to agentic ecosystems. Most teams still operate on fragmented data sets and workflows that are error-prone and difficult to scale. Despite mounting pressure to do more with less budget and resources, prioritize smarter, and prove ROI, many organizations still lack the intelligence and use-case coverage their GTM teams need to execute consistently.

HG Insights’ RGI Platform is built for this shift, providing cohesive GTM intelligence, AI copilots, and composable workflows in a single system to turn insights into scalable action. The RGI Platform’s three AI Copilots deliver advanced functions across a broad range of GTM use cases, consistently turning the right insight into action.

• The Market Analyzer helps organizations identify and size their top market opportunities, giving CMOs, RevOps, and strategy leaders actionable insight into which segments and accounts to prioritize, where competitors are gaining or losing ground, and where to invest. From TAM/SAM/SOM modeling and ICP analysis to territory optimization and whitespace analysis, Market Analyzer brings clarity to market complexity.
• The Data Studio lets marketing and RevOps teams score and prioritize leads and accounts by combining internal data with HG Insights’ Fabric data, and then applying fully explainable predictive models. The result is coordinated GTM execution, higher-propensity targeting, sharper ABM performance, and more effective engagement and conversion.
• The Sales Copilot puts the right intelligence in front of sellers at the right moment. By connecting and contextualizing disparate signals with HG Insights Fabric data to automate account research, trigger sales plays, and shorten sales cycles, Sales Copilot ensures sellers spend more time building and closing pipeline.

HG Insights Platform and Fabric lets customers integrate their own first- and third-party data with HG Insights intelligence, enabling copilots to analyze a richer, combined dataset to generate even more precise insights and actions.

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The new framework includes AI Agent Builder, AI Toolkits, a centralized AI Library, and the Domo MCP Server, which connects enterprise data directly to external AI platforms.

These capabilities allow leaders to build what many describe as an “AI workforce,” specialized agents that support teams and automate work directly within business operations, according to company officials.

Domo’s Josh James

Josh James, founder and CEO of Domo, said AI doesn’t become valuable when a model gets smarter.

“It becomes valuable when it’s connected to your business and becomes a system of action,” said James in a statement. “The tools we’ve announced will help users build AI agents connected to trusted enterprise data and workflows, turning AI from an abstract capability into something that actually drives business outcomes.” ‍

Orchestrating AI

Domo’s AI and Data Products Platform provides a centralized environment for building and managing AI agents that operate with trusted, governed business data. At the center of the announcement is the Domo AI Library, a central hub for curating and managing AI solutions, available to customers this summer. Within the AI Library, users can leverage AI Agent Builder to create conversational agents or agentic workflows tailored to specific use cases.

To power these agents, teams can create AI Toolkits, packaged sets of capabilities that define what an agent can do. Toolkits allow users to combine tools, data, and workflows with the instructions and business context that guide how an agent operates. These reusable packages can include operational logic and domain-specific knowledge, enabling agents to take on roles such as a financial analyst or operations manager.

These toolkits may be created by customers, provided by Domo for common use cases, or connected to external services. Assigning toolkits to agents allows organizations to control the actions and systems those agents can access. Toolkits can also be exposed externally through MCP, allowing AI assistants such as Gemini or Claude to access those capabilities through the Domo MCP Server.

MCP Server 

A key component of today’s announcement is the Domo MCP Server, which extends Domo AI Toolkits and agents to external AI platforms such as Claude, Gemini, and ChatGPT. Through MCP, these systems can securely interact with Domo data, services, and workflows. Built on the emerging Model Context Protocol (MCP) standard, the Domo MCP Server acts as a universal connector, giving AI tools access to governed enterprise data and actions inside Domo.

Through MCP, AI assistants can:

• Query datasets and analytics
• Trigger workflows and automation
• Create dashboards and applications
• Configure alerts and operational processes

While traditional integrations often return simple text responses, Domo’s MCP implementation allows AI tools to render interactive business experiences directly inside chat interfaces, including dashboards and other interactive workflows. This approach allows intelligence to move seamlessly between AI tools and enterprise systems without duplicating logic or compromising governance.

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The acquisition is the latest move in Apollo’s evolution into an AI-native GTM operating system. The company has recorded 400% growth in enterprise accounts over the past 12 months and the recent launch of its AI Assistant is part of their vision for the future of go-to-market: a unified, AI-powered system capable of detecting buying signals, prioritizing accounts, and guiding execution all within a single platform

Only the most advanced customer facing teams have been able to operationalize intent signals and behavioral data, and AI has made this more accessible than ever before, according to company officials. Business leaders are looking for AI applications to enable their teams to do more with fewer tools. Pocus’ integration with Apollo eliminates the need for a conventional legacy GTM tech stack in favor of an intelligent, unified operating system for GTM workflows.

Apollo’s Matt Curl

The acquisition of Pocus accelerates Apollo’s vision to build the leading AI-native operating system for go-to-market teams from SMB to enterprise, said Matt Curl, CEO of Apollo.io.

“Pocus is a natural complement to Apollo’s platform, bringing powerful AI-driven signal intelligence, recommendations, and intelligent workflows that enable teams to execute with greater precision and speed,” said Curl in a statement. “By combining Pocus’ talent and technology with Apollo’s scale, we strengthen our position today and unlock new opportunities as we continue to expand upmarket.”

Focus on Better Opportunities

Apollo has a GTM data and execution platforms, powered by a living data network of 230M+ contacts and AI-driven prospecting, sequencing and engagement workflows. The platform includes inbound webforms and routing, an embedded domestic and international dialer, conversational intelligence, and deal management. Apollo has driven tremendous growth in customer engagement with its AI-native platform. Since launching its AI Assistant in beta in October, the company touted that:

• Credit consumption has doubled in less than 6 months
• AI adoption by customers has grown from 35% to 75%
• Since its GA launch of AI Assistant, total weekly active users are up 94%

Pocus enhances that foundation with an intelligence layer that surfaces CRM signals, behavioral data and other high-impact opportunities to help revenue teams identify where to focus. Pocus’ customers include Asana, Canva, and Monday.com, to optimize the pre and post sales workflows.

“We started Pocus to solve a simple but critical problem: revenue teams were drowning in data but starving for direction,” said Alexa Grabell, CEO of Pocus. “Apollo has built the execution layer modern GTM teams trust. By joining Apollo, we can scale our mission in delivering signal-powered clarity and helping teams focus on the opportunities that matter most.”

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As part of this strategic partnership, Clari + Salesloft is announcing the gradual sunset of its Drift conversational marketing solution, a decision underscoring the company’s dedication to enhancing the Predictive Revenue System, ensuring clients gain access to the most advanced and impactful technology available.

Under an exclusive agreement with 1mind, Clari + Salesloft will refer existing clients to 1mind as the successor to ensure a seamless transition. This integration allows Clari+Salesloft to embed 1mind’s AI signals directly into the Predictive Revenue System. This creates a closed-loop connection between AI engagement, human follow-up, and revenue forecasting, ensuring every buyer interaction moves seamlessly from first touch to

Driving Growth in the Agentic Era

The collaboration is focused on redefining what’s possible for modern revenue teams by providing a unified framework that transforms buyer engagement and drives measurable impact, said Steve Cox, CEO of Clari + Salesloft.

“We are thrilled to partner with 1mind, transforming the industry from merely observing revenue to actively engineering it,” stated Cox min a statement. “Our system serves as the ‘heartbeat’ of the enterprise. By partnering with and integrating 1mind, we provide our customers with a distinct competitive edge, turning fragmented buyer signals into high-fidelity intelligence essential for sustained success.”

Addressing the Revenue Crisis

This announcement arrives as a recent Clari + Salesloft global survey conducted by Censuswide highlights a significant “Revenue Crisis,” revealing that 87% of enterprises not utilizing Clari + Salesloft missed their revenue targets last year.

The company is bridging this gap by replacing human guesswork with a dynamic, predictive platform. By transitioning from the Drift conversational marketing product to prioritize 1mind’s advanced AI sales capabilities, Clari + Salesloft empowers customers to move past legacy chat tools towards a more robust, intelligent multimodal engagement strategy. Key Benefits of the partnership includes:

• Eliminating Data Latency: The integrated PRS allows teams to predict and shape the future in real-time. Buyer intelligence captured by 1mind flows into Salesloft Cadences without switching between tabs or creating data silos.
• Massive Capacity Multipliers: Clari + Salesloft agents return up to 300 hours a year to enterprise reps and save managers over 1,200 hours a year on coaching prep. 1mind Superhumans extend this by augmenting revenue teams, handling qualification and buyer engagement with human-like precision at any scale—driving pipeline, product adoption and revenue.
• Unified Forecasting and Pipeline Precision: Every 1mind interaction generates structured signals that feed the Clari forecast, ensuring AI-led engagement contributes to, rather than sits apart from, a company’s revenue intelligence.

“We are excited to partner with Clari + Salesloft, the leaders in Revenue Orchestration,” said Amanda Kahlow, Founder and CEO of 1mind. “By merging Clari + Salesloft’s exceptional workflows with 1mind’s advanced AI capabilities, we empower companies to cut costs, scale their go-to-market teams, and ensure no lead is left behind—all while delighting every buyer.”

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