Find the answers to those questions and more in the 2026 State of AI Search Report from Exposure Ninja.

For those in digital marketing, SEO, content marketing, and marketing leadership, this report provides a data-driven look at how AI is reshaping search behavior, website traffic, brand discovery, and purchasing decisions.

Drawing on research from Pew Research Center, Ahrefs, Semrush, Adobe, and other organizations, along with Exposure Ninja’s own analysis, the report finds that AI search is becoming mainstream—but traditional SEO remains essential, and the commercial impact of AI is more nuanced than many headlines suggest.

Here are eight specific findings from the report’s authors, along with their predictions for how AI search will evolve in 2027.

1. AI Search Has Gone Mainstream, but Traditional Search Isn’t Going Away

According to a February 2026 Pew Research Center survey of 5,119 US adults, 49% have used an AI chatbot, up from 33% in 2024. Nearly one-quarter (24%) now use a chatbot daily, while 42% report using chatbots to find information. Even more significantly, 60% of US adults have encountered an AI-generated summary in conventional search results.

In the UK, a government survey found that 59% of adults had used some form of generative AI during the previous three months, although that broader measurement isn’t directly comparable to the US chatbot figures. Despite these adoption rates, AI is largely supplementing traditional search rather than replacing it.

Consumers continue to rely on search engines, review sites, retailers, and other sources when researching products and making purchasing decisions. For marketers, the implication is clear: AI search visibility is increasingly important, but abandoning conventional SEO would be a serious mistake.

2. AI Overviews Are Reducing Organic Search Clicks—Significantly

One of the report’s most striking findings comes from Pew Research Center’s analysis of nearly 69,000 Google searches. When an AI Overview appeared, users clicked a traditional search result just 8% of the time, compared with 15% when no AI Overview was present. Only 1% clicked a source cited within the AI-generated summary.

Users were also more likely to end their search session after encountering an AI Overview (26% versus 16%). However, research from Seer Interactive involving 53 brands offers an important qualification: brands cited in AI Overviews received 120% more clicks per impression than brands that weren’t cited, although they still received 38% fewer clicks than when no AI Overview appeared.

In other words, appearing in AI-generated answers can help offset lost organic traffic, even if it doesn’t fully compensate for the decline in clicks.

3. AI Overviews Appear Much More Frequently for Longer, Question-Based Searches

How often do Google’s AI Overviews appear? The answer depends heavily on the keywords being measured. Pew’s research found that AI Overviews appeared in 18% of observed US searches, while a Conductor analysis of 21.9 million searches put the figure at 25.11%.

But the differences become much more dramatic when searches are segmented by length and intent. According to Pew, AI Overviews appeared in just 8% of searches containing one or two words, compared with 53% of searches containing ten or more words and 60% of question-based searches.

These findings suggest that marketers targeting informational queries, particularly detailed questions and longer searches, may face greater competition from AI-generated answers than those targeting short, transactional searches. They also reinforce the importance of creating content that answers specific audience questions clearly, accurately, and comprehensively.

4. Traditional Google Rankings Still Matter, but Don’t Guarantee AI Citations

Strong organic rankings improve a website’s chances of being cited in AI-generated answers, but the relationship is far from straightforward. An Ahrefs analysis from March 2026 found that 37.1% of URLs cited in Google’s AI Overviews ranked among the top ten organic results for the same query.

Surprisingly, roughly the same proportion didn’t rank in the top 100 at all. One explanation is query fan-out, in which AI search systems break a question into multiple related searches and gather information from different sources. A page that doesn’t rank well for the original query may still be cited because it answers one of those related questions effectively.

This means marketers need to think beyond ranking for individual keywords. Building topical authority, addressing related questions, and publishing useful, evidence-backed content can create additional opportunities for AI visibility while supporting traditional SEO performance.

5. AI Search Citations Are Remarkably Unstable

Exposure Ninja conducted its own research into the consistency of AI citations, tracking 59 UK-focused prompts daily across ChatGPT, Perplexity, and Google AI Overviews between June 24 and August 7, 2026. The study generated 7,965 responses and revealed substantial differences between platforms.

ChatGPT and Google AI Overviews cited completely different websites in 49% of same-day comparisons, while ChatGPT and Perplexity had no sources in common 42% of the time. Citation lists also changed frequently from day to day.

ChatGPT returned exactly the same set of cited websites on only 2% of consecutive-day comparisons, compared with 6% for Google AI Overviews and 27% for Perplexity. Although the research used a limited set of marketing-related prompts and shouldn’t be treated as representative of all AI searches, it illustrates an important measurement challenge.

A single citation or screenshot doesn’t establish sustained AI visibility. Marketers need to monitor relevant prompts repeatedly, across multiple platforms, to understand whether their content is consistently being referenced.

6. AI Referral Traffic Remains Small, but Its Conversion Potential Is Growing

Despite rapidly increasing AI adoption, referrals from AI platforms still represent a relatively small percentage of overall website traffic. Semrush estimates that identifiable AI referrals account for just 0.14% of worldwide visits, while Ahrefs puts the figure at 0.25%. Conductor reports a higher 1.08% for US enterprise websites.

However, the commercial value of these visits may be improving. Adobe found that AI-referred traffic to US retail websites converted 42% better than non-AI traffic in March 2026, reversing a 38% disadvantage the previous year. Results vary by industry: Adobe also found that AI-referred travel traffic converted 28% worse than other channels.

Exposure Ninja’s own analytics provide another perspective. Across a two-year period ending July 31, 2026, six identifiable AI platforms generated 6,566 sessions, representing 1.9% of the agency’s total website traffic, with ChatGPT accounting for 63% of those referrals.

The takeaway is that AI traffic volume remains modest, but its value deserves attention—and shouldn’t be judged solely by its share of total visits.

7. AI Search May Influence More Conversions Than Analytics Can Measure

One of the biggest challenges in measuring AI search performance is that a recommendation doesn’t necessarily produce an immediate website visit. Someone might discover a brand through ChatGPT, then search for that company on Google several days later or visit its website directly.

Conventional analytics would generally attribute that visit to branded organic search or direct traffic rather than AI. The report cites Similarweb research showing that users who received a ChatGPT recommendation were 2.5 times more likely to visit the recommended brand’s website within seven days, with many visits arriving through subsequent branded searches.

Another linked-clickstream study found an association between AI recommendations and a 4.3-percentage-point increase in Google searches for the same brand, along with a 2.4-point increase in website visits. These findings don’t establish that AI caused every subsequent visit, but they suggest that referral reporting alone may substantially understate AI’s influence.

Marketers should monitor branded search trends, direct visits, and conversions alongside identifiable AI referrals to develop a more complete picture.

8. Technical Shortcuts Won’t Replace High-Quality Content and Brand Authority

With marketers searching for ways to improve AI visibility, technical approaches such as JSON-LD structured data and llms.txt files have attracted considerable attention. But the report finds little evidence that either provides a direct shortcut to AI citations.

A matched study of 1,885 pages found no measurable citation improvement from adding JSON-LD structured data, while another analysis found that 97% of llms.txt files received no traffic. That doesn’t mean structured data is useless; it continues to support established search features, product information, and rich results. It simply shouldn’t be implemented solely in the hope of improving AI citations.

Instead, Exposure Ninja recommends that marketers concentrate on clear, current, evidence-rich content that AI systems can confidently reference. Original research, expert perspectives, credible sources, strong technical SEO, and consistent brand signals remain more promising long-term investments than attempting to reverse-engineer individual AI platforms.

Looking Ahead: Exposure Ninja’s Predictions for AI Search in 2027

Beyond documenting the current state of AI search, Exposure Ninja identifies several developments it expects to shape the coming year.

AI search adoption will continue growing through familiar search platforms. Rather than requiring consumers to adopt standalone chatbots, AI-generated answers will increasingly become part of the search experiences they already use. This is particularly important for reaching audiences that don’t consider themselves regular AI users.

AI search measurement will become more sophisticated. Exposure Ninja expects search platforms and analytics providers to improve reporting on AI visibility, referrals, and downstream behavior. However, accurately attributing conversions to AI-generated recommendations will remain challenging.

Branded search will become an increasingly important performance indicator. As more consumers discover businesses through AI recommendations and subsequently search for them by name, changes in branded search volume may provide valuable clues about AI’s influence on awareness and consideration.

Transparency and human oversight will matter more. With AI-generated content becoming easier to identify and regulatory requirements evolving, businesses will face growing pressure to explain how they use AI. Exposure Ninja predicts that original insights, subject-matter expertise, fact-checking, and human editorial judgment will become increasingly valuable as AI makes content production faster and easier.

These predictions share a common theme: AI search will become more deeply integrated into existing digital experiences, while the fundamentals of earning trust and demonstrating expertise will become more—not less—important.

Final Thoughts on AI Search and the Future of SEO

The 2026 State of AI Search Report makes a compelling case that AI is transforming how consumers discover, research, and evaluate brands, but the evidence doesn’t support predictions of traditional search’s imminent demise. Organic clicks are declining for many informational searches, AI citations are inconsistent, and referral traffic remains relatively small.

At the same time, AI is creating new opportunities for brand discovery and influencing purchasing decisions in ways conventional analytics don’t always capture.

For marketers, the best response isn’t to abandon SEO in favor of a completely separate AI optimization strategy. It’s to strengthen the fundamentals—authoritative content, technical performance, digital PR, and brand credibility—while expanding measurement to account for AI citations, referrals, and their influence on branded search.

The organizations that succeed won’t necessarily be those chasing every new AI feature, but those building the authority and visibility needed to be found, trusted, and recommended across both traditional and AI-powered search.

ChatGPT assisted with research for this post. But all of the bolding and edits are entirely human.

The post The State of AI Search: 8 Key Findings and Predictions for Next Year appeared first on B2B Marketing Blog | Webbiquity.

Sales compensation software may seem like a tool for Sales and Finance, but the decisions behind it often begin earlier in the revenue process. Marketing defines and tracks leads, Sales determines which opportunities qualify, RevOps manages the underlying data and rules, and Finance reviews the resulting payments.

When those teams use different definitions or update records at different times, disagreements about commission credit can follow.

Choosing a platform therefore involves more than comparing features. Teams need to agree on what counts as an accepted lead, an accepted opportunity, and an eligible commission event, then determine whether the software can apply those rules consistently and explain the results.

This article compares three platforms worth considering: Qobra, CaptivateIQ, and Salesforce Spiff. It outlines where each may be a strong fit, walks through a hypothetical commission dispute, and provides a handoff framework and vendor test criteria to help Marketing, Sales, RevOps, and Finance make a more informed choice.

Marketing attribution, sales qualification and compensation eligibility are distinct decisions. Proposed cross-team handoff map • no causal attribution claim.

For B2B marketing and RevOps teams, the key question is whether a platform can translate agreed-upon funnel definitions into compensation rules without treating campaign attribution, Sales acceptance, and payment approval as the same thing. Software can enforce a rule, but it can’t resolve disagreements about who owns the decision.

Separate funnel progress from compensation eligibility

Before asking vendors to configure a system, define these three events separately:

• Accepted lead: Sales agrees to work a lead that meets the handoff criteria. This is a service and routing commitment, not necessarily pipeline or commission credit.
• Accepted opportunity: A designated Sales owner confirms a buying opportunity meets agreed criteria. Define accepted pipeline from those records, including the value basis and acceptance date, rather than relying on a stage label alone.
• Commission event: The event that an approved plan says earns credit for an eligible person. It might be opportunity acceptance or a later milestone; the distinction must be explicit.

Marketing-qualified lead volume, engagement scores, campaign responses, influenced pipeline, and attribution-weighted revenue should not automatically count toward commission credit. They may be valuable marketing KPIs without creating a payment obligation. An attribution model assigns reporting credit according to selected rules; it does not, on its own, prove that a campaign caused a sale.

If a plan deliberately rewards a marketing-related event, the compensation policy owner must approve its definition, recipient, exclusions, and effective date. Marketing owns the attribution methodology, not unilateral changes to another employee’s earnings.

A hypothetical example: when commission credit is disputed

Consider a hypothetical example spanning September and October. On September 25, Marketing routes lead L to SDR A after the lead meets its qualification criteria. Sales accepts the lead for follow-up. On September 30, a Sales manager accepts opportunity O, which is linked to that lead, after confirming a documented business need and an agreed next step.

The illustrative September plan pays an eligible SDR $150 for each unique, newly accepted opportunity. Credit belongs to the SDR recorded at acceptance, the acceptance date determines the earning period, and later campaign or account-owner edits do not change that credit.

There are no tiers, splits, or other payments in this example. SDR A has exactly one qualifying event: 1 × $150 = $150 of September calculated commission, subject to approval—not proof of payment. This is one individual’s modeled commission component, not total company compensation expense.

On October 2, Marketing corrects the campaign source. On October 3, the account moves to a different account executive, who questions the credit. Under the illustrative rule, neither edit changes SDR A’s September $150. The account executive’s current ownership is a different fact from the SDR’s ownership at acceptance. Any closing commission is outside this example.

If the original acceptance was a mistake, that raises a different dispute. Sales must establish what happened, and the compensation policy owner must authorize how to handle it. RevOps should not assume that a stage change calls for a reversal or make an unauthorized payroll adjustment.

Turn the handoff matrix into an operating agreement

Use this proposed matrix to clarify who has authority to make each decision, not just who enters the data. Every rejected record should have a documented reason, a destination for correction, and an owner responsible for getting it back on track.

Keep a short event specification beside the matrix. It should define the unique event key, qualifying criteria, source record, recipient-at-event rule, period cutoff, duplicate treatment, and correction authority. These are proposed business requirements, not a claim that every platform supplies these exact fields automatically.

Give each shortlisted platform a specific task to demonstrate

Qobra’s guide to sales compensation software for RevOps and Finance teams provides another starting point for the software discussion. Keep your event specification—not any vendor’s feature checklist—as the basis for evaluation.

Qobra: a strong option for RevOps-managed rules and controlled reviews

Qobra documents a no-code plan editor with conditional logic, tiers, bonuses, and custom calculation rules. Plan simulation, sandboxing, and version control support checking changes. Employee statements expose calculations and targets; approval workflows, statement locks, in-context discussions, custom roles, and audit trails support review.

Qobra is a strong starting point when the priority is managing agreed-upon rules and explaining commission credit to Sales and Finance. That does not mean competing products lack no-code features or review controls. Ask Qobra to show how opportunity O retains the correct recipient and plan when ownership is disputed later.

Qobra’s published ElevenLabs client story is relevant here: it describes a former BigQuery-and-spreadsheet workflow and visibility for AEs and SDRs into opportunities and commission rules. The RevOps testimonial reports fewer back-and-forth commission inquiries.

That supports evaluating explanation quality; it is not an independent benchmark, a quantified reduction, or proof of marketing attribution accuracy.

Check data timing explicitly. Qobra’s Salesforce and HubSpot inbound connectors are read-only and specify nightly full refreshes, incremental updates every two hours, and manual refresh. Do not assume instant reflection of a CRM edit or CRM writeback. Verify the fields and relationships needed to preserve your acceptance event in the proposed setup.

CaptivateIQ: a strong option when combining datasets is central

CaptivateIQ’s SmartGrid supports data transformation and commission calculation. Its platform lists joins and unions, point-and-click transformations, effective dating, crediting, clawbacks, and draws. It also lists approvals, dispute resolution, rep visibility, role-based access, sandboxing, and audit logs.

Consider CaptivateIQ when commission-eligible events must be assembled from several datasets or when time-dependent rules require extensive modeling. Ask the vendor to join opportunity O with its contact and activity records while generating only the intended commission event. The test is whether the results are correct at the record level, not simply whether the data imports successfully.

Salesforce Spiff: a strong option for tracing calculations

Salesforce Spiff lists rep statements, calculation tracing, comments, notifications, commission estimation, flexible plan setup, and audit logs. Its described connections span CRM, enterprise resource planning, human capital management, and payroll systems; it is not Salesforce-only.

Consider Salesforce Spiff when sales reps need to understand exactly why an event produced a particular commission amount, especially if Salesforce is central to the evaluation. Ask a rep to trace opportunity O from the qualifying event through the applied rule to the statement, clearly distinguishing an estimate from approved earnings.

Confirm the specific connections your technology stack needs rather than assuming the CRM integration covers everything.

Use the disputed opportunity as a common vendor test

Give every vendor the same hypothetical scenario, handoff matrix, and expected result before the demonstration. Ask each to show both the straightforward case and the disputed case. Record whether each requirement can be handled through standard configuration, needs integration work, or requires a manual process.

1. Event identity: Can the platform count opportunity O once despite multiple linked activities, repeated imports, or a lead conversion? Require the result to reconcile to the source event.
2. Effective dates and ownership: Can reviewers recover the SDR and plan applicable at acceptance rather than silently applying today’s owner? What historical source data must your team retain?
3. Freshness and missing data: How do reviewers identify the last successful import and records missing acceptance evidence? If automatic alerts or historical backfill are required, demonstrate them rather than assume them.
4. Dispute resolution: Can Marketing correct attribution without changing compensation under the agreed rule? Can Sales challenge acceptance while the policy owner retains adjustment authority?
5. Approval and delivery: Can reviewers trace the approved amount, then reconcile what the downstream system accepted? Test duplicate prevention on a repeated submission; do not assume it from an API’s existence.

Qobra’s outbound webhooks and APIs can support approved commission-data handoff. Qobra does not run payroll or move funds. Destination acceptance, duplicate handling, and reconciliation remain implementation requirements to validate.

Use the first cross-functional meeting to settle key decisions

Bring Marketing Operations, Sales management, RevOps, Finance, and Payroll together before the product demonstrations. Use the meeting to address these questions:

• Approve separate definitions for accepted lead, accepted opportunity, and commission event.
• Resolve the hypothetical ownership dispute and document the expected result.
• Assign an authoritative owner and rework destination to every matrix row.
• Agree on cutoff timing, review authority, and treatment of unresolved exceptions.
• Select a historical period for validation and name the person who will sign off each acceptance test.

Move Qobra forward if it can demonstrate the workflow with an acceptable amount of administrative and review effort. Choose another platform if it better meets the requirements for data modeling or explaining calculations.

Before buying a software platform, confirm what is included in the proposed package, which connectors are required, how much migration work is involved, and who will administer the system. The goal is not another funnel dashboard. It is a set of rules everyone understands, supported by software that applies them consistently.

The post Which Sales Compensation Tools Should B2B Marketing and RevOps Teams Shortlist? appeared first on B2B Marketing Blog | Webbiquity.

A Search Engine Journal study of 892 domain migrations found that the new domain took 523 days on average to match the old one’s organic traffic, and 17% had not caught up after 1,000 days. Rebranding SEO looks like a developer’s job, since redirects live in code. But the choices that decide where a company lands in that study are mostly made by marketing.

Picture the leadership meeting two weeks after launch. Someone shares the analytics dashboard, organic traffic is down by half, and the room turns to the marketing lead. Whether that conversation lasts two minutes or two months depends on decisions made before launch: what the traffic was doing beforehand, which pages were cut, who signed off on the information architecture and URL map, and whether anyone checked that leads still reach the CRM.

Khod, a web agency for B2B startups, went through this in 2026. It started as Tilipman Digital, a name built on the founder’s surname that made a full team read as a one-person shop, and the rebrand moved the site from tilipmandigital.com to khod.io. Its Search Console data runs through this piece as a worked example.

Summary

1. Agree on the traffic baseline with leadership before launch, using the months after the last trend change.
2. Cut content with traffic and backlink data in hand, and redirect every page you cut.
3. Sign off on the URL map yourself, and send each changed URL to its closest match.
4. Submit every form on the new site on launch day and confirm each one reaches the CRM.
5. Ask the few sites that send traffic or credibility to update their links.
6. Keep a dated change log, and space the big changes out.

1. Agree on the baseline before launch

A traffic chart only means something next to the right comparison, and the right comparison is rarely the all-time peak.

Khod’s organic clicks peaked at 2,276 in December 2025. Around January 22, two and a half months before the domain moved, rankings slipped on the articles that carried most of the traffic, and February closed at 488. By September 2026, on the new domain, clicks were 681.

Measured against December, that is 30% of the peak. Measured against February and March, the two months right before the move, it is 41% higher. Same data, two opposite stories for a leadership slide.

Khod’s monthly organic search clicks across both domains, June 2025 to September 2026. Source: Google Search Console.

The practical rule: export 12 to 16 months of Search Console clicks by page group, find the last point where the trend changed, and use the months after it as the baseline. Then put that number in front of leadership before launch, along with the expected dip.

Khod’s clicks fell 68% in the month of the move and passed the pre-move baseline about two months later. The SEJ numbers show how wide the range runs, so set the expectation in months.

2. Cut content with the data in hand

A rebrand is a natural moment to clear out or repurpose old content. It is also an easy moment to delete the pages that bring in the traffic.

In Khod’s case, 72% of the clicks at the peak went to resource articles, led by design-examples pieces such as AI website examples and pricing page examples. Those articles carried the traffic before the move and still did after it: in September, 519 of the 681 clicks went to articles that existed on the old domain.

Before anything is cut, pull three numbers for each page: clicks over the last 12 months, referring domains and leads attributed. Keep or merge anything with traffic or links. When a page does go, it needs a redirect to the closest live page. Every one of the 12 old Khod URLs that ends on an error page today is a page that was retired without one.

3. Sign off on the URL map yourself

The URL map is the spreadsheet that pairs every old address with its new one. Developers build it, but marketing knows which page replaces which, so the sign-off belongs with marketing.

Khod’s old domain redirects every path to the same path on the new domain, with specific rules for addresses that changed. A test of 174 old URLs pulled from the Wayback Machine’s archive in October 2026 sorted them into four groups:

• 142 kept their path and landed on the same page.
• 15 had a new path and a specific rule sent them to the matching page.
• 5 landed on a general page, such as the homepage or the case-study index.
• 12 ended on an error page, all of them retired pages.

The middle two groups are where a marketer’s judgment matters. Google’s site-move guidance warns that sending many old URLs to an unrelated page such as the homepage “might be treated as a soft 404 error.” Match each changed URL to the page a visitor would expect, and keep the homepage for the homepage.

Build the list of old URLs from three places: the sitemap, the Search Console pages report and the Wayback Machine. A redirect test only covers the URLs it is given, and an earlier Khod test of 85 URLs found 3 failures where the full list later found 12.

4. Keep tracking and lead flow intact

Rankings recover on their own schedule. A broken form costs pipeline from day one, and the first sign may be sales asking where the leads went.

On launch day, submit every form on the new site, including the demo request, the contact form and any gated download, and confirm each submission arrives in the CRM with its source fields filled. Then check the reporting side:

• Analytics and the tag manager run on the new domain, and conversion events fire on the new thank-you pages.
• Both domains are verified in Search Console, and the move is submitted through its Change of Address tool.
• Campaign links in email signatures, ads, social profiles and sales templates point at the new domain.

This step is boring and load-bearing. Put a name next to each item.

5. Ask the right sites to update their links

A redirect carries visitors and link value to the new domain, but the link on someone else’s site still names the old one. The same Google guide says to update your own links and the high-volume links from other sites.

“High-volume” matters. As of October 2026, DataForSEO counts 2,010 referring domains still pointing at tilipmandigital.com. Most of them are directories and scraped pages, and nobody needs to email those. The list to work is short: partner directories, client sites that credit the agency, review profiles, podcast pages and past guest posts.

Start on launch day. Six months later, the person who placed the link may have moved on, and the request goes to a general inbox.

6. Keep a change log and space the big changes

Google’s site-move guide also recommends making big site changes one after another, and its example is a domain move, a CMS change and a redesign. Khod did all three in one quarter: the domain moved in early April 2026, and the site was rebuilt on a new platform between June 16 and July 4.

June then posted the best month since January, 934 clicks, before settling between 630 and 690 a month. Was that the domain settling, the rebuild, or a ranking shift? The data cannot say.

When the changes can’t be spaced out, a dated log is the next best thing. Every later question about the chart starts with “what else changed that week?”, and a spreadsheet with dates for launches, template changes, navigation edits and content cuts answers it in minutes.

The short version

A rebrand changes the name on the door. The website move decides whether search engines and existing customers can still find the business behind it, and most of those decisions sit with marketing: the baseline, the content cuts, the URL map, the lead flow, the links and the log.

For the technical side in launch order, Khod’s website migration checklist lists 50 checks from audit to the first month after launch.

Evgenii Tilipman is the founder of Khod, a web agency for B2B startups. He has worked with teams from seed to Series C on positioning, conversion and Webflow builds, and before Khod he led Webflow development at an agency and built products for the Webflow community with Memberstack. Outside work, he’s a husband, a dog dad and a regular on long hikes.

The post Rebranding SEO: Six Decisions the Marketing Team Owns When the Website Moves appeared first on B2B Marketing Blog | Webbiquity.

Just because a startup has little name recognition doesn’t mean its founder has to be invisible. In B2B markets, buyers, investors, prospective employees, and partners often research the people behind a young company before taking the business seriously.

A strong personal brand gives those audiences evidence of expertise and credibility. The goal is not to turn the founder into an influencer. It is to make a compelling professional reputation visible to the people who matter to the company.

Build Around a Specific Area of Expertise

Broad positioning is difficult to remember. A founder who regularly talks about “innovation” or “leadership” competes with thousands of people saying similar things.

Specific expertise creates a clearer association. The founder of a logistics software startup might discuss warehouse bottlenecks, freight visibility, or inventory data rather than general entrepreneurship. A cybersecurity founder could focus on identity management or the security problems facing a particular industry.

The strongest topics usually sit at the intersection of the founder’s experience, the company’s product, and the problems customers are actively trying to solve.

Turn Experience into Useful Content

B2B audiences generally have little reason to follow constant company promotion. They may pay attention to a founder who consistently explains something useful.

That content doesn’t need to be complicated. A founder might break down a recurring customer problem, explain why a common industry practice fails, discuss lessons from product development, or analyze a meaningful market change.

Firsthand observations are particularly valuable. Instead of posting generic advice about improving operations, a founder could explain why customers repeatedly struggle with a particular workflow and what the pattern reveals. A consistent point of view also gives marketing teams material that can support articles, conference pitches, podcasts, newsletters, and sales conversations.

Make Professional Claims Verifiable

A founder’s biography, company website, LinkedIn profile, speaking biography, and media appearances should tell a consistent professional story. Titles, previous roles, education, awards, publications, and business accomplishments should be accurate and relevant.

That record can matter beyond marketing. A founder building a career in the United States may, depending on individual circumstances, speak with an immigration attorney or O1 visa consultant about documenting professional achievements.

Public recognition can provide supporting evidence in some contexts, but immigration eligibility is a legal matter and should never be reduced to a branding exercise. Credibility is easier to build when public claims can withstand outside scrutiny.

Choose Visibility Based on the Buyer

Founders don’t need to appear on every platform. The best channel depends on where customers and industry peers actually spend time.

A founder selling specialized manufacturing technology may gain more from trade publications and industry conferences than a high-volume consumer social platform. Someone targeting corporate finance leaders might prioritize professional networks, webinars, podcasts, and publications read by finance teams.

Marketing teams can track which activities generate qualified website traffic, sales conversations, speaking invitations, newsletter subscriptions, or partnership inquiries. Visibility without a relevant audience is mostly noise.

Keep the Founder and Company Connected, but Separate

A founder’s reputation should reinforce the company without becoming identical to it. Companies change products, enter new markets, raise capital, merge, or close. Professional credibility should remain useful through those changes. That also means founders should avoid making every post a product pitch. Expertise earns attention before promotion does.

For startup founders, personal branding is most effective when it makes genuine professional experience easier to find and evaluate. Specific expertise, useful content, verifiable accomplishments, and selective visibility can establish credibility before the company itself has a long track record. Check out the infographic below for more information.

The post Building Authority Before the Brand Is Famous: Personal Branding for Startup Founders appeared first on B2B Marketing Blog | Webbiquity.

By the time a B2B buyer agrees to a first call, most of the deciding is done. Around 4,000 buyers took part in the 6sense 2025 Buyer Experience Report, and on average they reached out to a vendor about 61% of the way through their journey.

By then the shortlist is usually settled. The winning vendor was already on the day-one shortlist 95% of the time, and four deals in five went to the vendor the buyer favored before speaking to anyone.

Buyers also seem happy to keep it that way. Two in three would rather skip the rep altogether: 67% said so in a Gartner survey out in March 2026.

That leaves content doing most of the persuading, usually while nobody from the vendor is watching. It also changes what content has to do. Being found is step one. If the buyer lands on the page and finds nothing they can check, they go and look at someone else.

Who reads the content first now?

Increasingly, a machine does. Half of B2B software buyers (51%) now open their research in an AI chatbot more often than in Google, according to G2’s Answer Economy research from April 2026. A year before, it was 29%. The number I keep coming back to is a different one: 69% of those buyers chose a different vendor than the one they had planned on, because of what a chatbot told them.

Estimates of AI use vary with the definition. Forrester puts the share of business buyers using AI somewhere in the process at 94%, in its 2025 Buyers’ Journey Survey. What stands out more in that survey is that twice as many buyers as the year before rated generative AI or conversational search above every other source, vendor websites and salespeople included.

Gartner’s narrower question found that 45% used AI during a recent purchase. Either way, the first summary a buyer reads about a category is often written by an assistant, put together from whatever sources it can find and is willing to repeat. Webbiquity’s recent post on Livestorm’s Claude connector showed marketers running webinars by asking an assistant for what they want. Buyers have started doing their research the same way.

The click data shows the cost. Pew Research Center found that Google users who saw an AI summary clicked a traditional result in 8% of visits, against 15% for users who saw no summary. Links inside the summary itself got clicked in about 1% of visits. Ahrefs measured a 58% lower average click-through rate for the top-ranking page when an AI Overview appears.

Being cited inside the answer helps a great deal. Seer Interactive’s 2026 analysis of 5.47 million queries found that brands cited in an AI Overview earned about 120% more organic clicks per impression than brands that weren’t cited. Seer is careful to say the data doesn’t prove the citation causes the extra clicks, but the gap is large.

What makes a buyer, or an assistant, trust a page?

Google doesn’t hedge on this one. Its Search Quality Rater Guidelines put trust in the middle of E-E-A-T, and say a page that can’t be trusted gets a low rating, however expert it looks. Buyers apply much the same test.

When Redpoint Insights asked B2B professionals what makes them trust a piece of content, original research topped the list at 70%. Expert opinion got 64%, peer insight 62%, case studies 54%. A byline by itself? 22%. So putting a name on a post does very little on its own. Put that same name next to data the person gathered, or a project they actually ran, and buyers start paying attention.

Edelman and LinkedIn found something similar in their 2024 B2B Thought Leadership Impact Report. Asked how they judge what a company can really do, 73% of decision-makers said they trust its thought leadership more than its marketing materials and product sheets. And 86% said a company that keeps publishing good thought leadership is likely to get an invite to their RFP.

Meanwhile, buyers have gotten warier. Almost half (47%) told TrustRadius, for its 2026 B2B Buying Disconnect report, that they trust online resources less than they used to. Among those using AI, 94% go back and fact-check what it tells them at least some of the time.

And Gartner found 69% of buyers spotting differences between what a vendor’s website claimed and what its salespeople said. A buyer who is checking will keep checking until something either holds up or doesn’t.

How common are these signals on real company websites?

Less common than all of that would suggest. Content RevOps spent much of 2026 auditing close to 14,000 company websites across seven B2B sectors for its State of Content Marketing 2026 study, and read about 5,500 marketing job posts alongside them. For each site the question was simple enough: what does it publish, what proof is on it, who stands behind the content, and does any of it show up in search or in AI answers?

Original research shows the widest spread. Among companies that publish content regularly, it appears on about 71% of life sciences sites, where publishing data is close to standard practice. The figure is 42% in manufacturing, 35% in fintech, roughly 3 in 10 in pharma and education, and about 1 in 8 in construction.

A construction firm with even a modest annual benchmark of bid volumes or project timelines would be doing something seven in eight of its peers don’t.

Named authors are common. Somewhere between 56% and 82% of content-active sites in most sectors put a name on their content. Credentials are another matter. Author bios that show credentials appear on about 60% of life sciences sites and about half in pharma, then drop to 28% in fintech, 26% in education, and below 20% in manufacturing.

Most of these sites tell the reader who wrote the piece and not why that person should be believed, which is the part Redpoint’s respondents care about.

In fintech, the two signals most closely linked to content excellence were original research and credentialed authorship.

Where is the trust gap widest?

At the point of decision. Take the average content library of a company that publishes regularly. Roughly 40% of it is there to get attention. About 1 in 6 pieces is written for someone ready to pick a vendor. Manufacturing sits lowest at around 15%, pharma highest at about 25%, and nobody is anywhere near an even split.

Pricing shows how thin decision-stage proof can get. TrustRadius has found transparent pricing to be the top item on buyers’ wish lists for four years running, with 59% wishing vendors were more open about it in 2026.

In the audit, some form of pricing information appeared on about 38% of construction sites and about 23% of active education sites, then fell to 8% in manufacturing, under 5% in life sciences, 1.5% among asset managers, and 0.5% in pharma. Comparison pages appeared on 5% of sites or fewer in every sector where they were measured, and ROI calculators were rarer still.

This matters more as buying groups grow. Forrester’s 2026 research puts the typical B2B purchase at 13 internal stakeholders and nine external influencers, and Gartner found that 74% of buyer teams show unhealthy conflict while they decide.

The person who found a vendor has to justify the choice to people who never read the original blog post. A pricing range, an honest comparison, and a named case study with numbers are the materials that make that conversation possible. When they’re missing, the champion has nothing to forward to the rest of the group.

The audit scored this kind of material, which it called sales enablement, out of four. Education averaged 1.57, manufacturing 1.42, and asset management 0.20, so even the better sectors give buyers far more reasons to notice them than to pick them.

What do AI assistants find when they look?

Often, very little from the companies themselves. AI Overviews appeared on about 85% of high-intent education searches tested in the study and on every life sciences query tested. Yet company websites were largely absent from AI-generated answers in six of the seven sectors. In construction, the cited sources were mostly Reddit, Wikipedia, Indeed, and OSHA rather than any construction firm.

Fintech was the exception, with roughly 60% of established firms appearing in AI answers. Why fintech? Mostly because those firms are all over review sites like G2, Capterra, and NerdWallet. That fits the wider data. Muck Rack’s analysis of more than 25 million links found that earned media accounts for 84% of AI citations, and 45% of buyers in G2’s research said citations from software review sites are the most reassuring signal in an AI-generated answer.

Assistants lean on sources they can verify and on what other people say about a company. A company with no data of its own, no named experts, and little third-party coverage gets described by whoever else has written about its category.

Few teams are organized to deal with this yet. Answer-engine optimization came up in well under 1 in 50 marketing job posts across the sectors studied, and in roughly 1 in 200 in construction and pharma.

Does any of this connect to growth?

Probably, though the study is careful to call these signals and not proven causes. Maturity went up with company size, growth rate, and funding stage in every one of the seven sectors. Among education companies, 52% of the high-growth ones had an active content presence, against 43% of the slow growers.

Construction showed 39% against 31%. And inside each sector, the same companies kept turning up together: the ones that were clear about who they serve, that gave buyers material to decide with, and that bothered to publish for the late stage of the deal.

Volume isn’t what’s missing. In CMI’s 2026 research, 96% of B2B marketers said their company produces thought leadership, yet in many of those companies fewer than 5% of employees ever contribute to it.

Think of an engineering firm whose blog is written entirely by the marketing coordinator, while the project director who has delivered forty hospitals never appears. The expertise buyers are looking for exists. It just isn’t on the page.

Picture the buyer at the end of all this. They built the shortlist on their own, quite possibly with ChatGPT or Gemini reading alongside them, and now they have to walk a finance lead, an IT manager, and two skeptical colleagues through why this vendor.

What they need in that meeting is something to point at: a number the vendor published, a named person with the right background, a customer story with figures in it, a price range. Most of the company websites in the study had very little of that to offer.

Stefan Kalpachev is the founder of Content RevOps, a demand generation agency that builds content, data, and automation systems for B2B companies with long, trust-led sales. He leads its research into how companies across seven sectors market, hire, and show up in AI search, and previously worked on content for Pearson Online Learning and King’s College London.

The post What B2B Buyers Check Before They Trust Your Content appeared first on B2B Marketing Blog | Webbiquity.

B2B marketers work hard to get the right message in front of the right accounts. They buy targeted ads, build nurture sequences, sponsor events, and chase placements in trade media.

The B2B Campaign Channel Already Built into Every Sales Email

Meanwhile, the sales and account teams send thousands of one-to-one emails every week to the exact people those campaigns are trying to reach, and most of those emails end with nothing more than a name, a title, and a phone number.

That sign-off is a campaign slot most marketing plans never use.

Why one-to-one email deserves a place in the plan

B2B buyers spend very little time with vendors. Gartner’s research found that buyers spend only 17% of their time meeting with suppliers, and that share gets split across every vendor on the shortlist. With three suppliers in the running, each one gets about 5%. Buyers spend around two-thirds of the journey researching and learning on their own.

That makes each real contact point with a buyer more valuable. An email from an account manager is one of the few messages a buyer reads with full attention, because it comes from a person they know and usually answers a question they asked. A relevant, well-timed banner under that email reaches someone who is already engaged.

It also adds reach without adding spend. The emails are going out anyway. The only question is whether they carry a message that supports the current campaign.

How a signature campaign works in practice

Consider a B2B team promoting a webinar. Exclaimer, an email signature management platform, can run it as an email signature campaign beneath every account manager’s sign-off, scheduled to start and stop on set dates, shown only to recipients on a HubSpot or Salesforce list, and tagged with UTM parameters so the clicks sit in the same report as the rest of the campaign.

G2 named Exclaimer in its list of the Best Marketing and Digital Advertising Software Products for 2025.

A few details make that setup work:

• Targeting by list. The banner appears only for the accounts in the webinar’s target segment; it’s not included in emails to everyone else, so existing customers and unrelated contacts don’t see an irrelevant offer.
• Dates set in advance. The banner goes live when registration opens and comes down the day of the event, with no reminder emails to the sales team.
• Nothing for reps to do. The banner slots in below each person’s signature automatically, so account managers keep writing their emails as usual.

Measuring it like any other channel

A signature banner is only worth running if you can see what it does. The simplest route is the same tagging you already use elsewhere. Google Analytics explains how to add UTM parameters to campaign URLs, such as utm_source, utm_medium and utm_campaign, so traffic from each link shows up in acquisition reports under the right campaign name.

For signature banners, a sensible convention might look like this:

• utm_source: email-signature
• utm_medium: email
• utm_campaign: the same campaign name used on your ads and nurture emails
• utm_content: the team or banner version, such as sales-east or banner-b

Using the same campaign name across channels matters. It lets you compare signature traffic with paid and owned channels in one view, and it keeps the signature from turning into an orphan channel that nobody reports on.

Where signature campaigns fit best

Signature banners suit messages that benefit from repetition and a personal sender. Good candidates include:

• Webinar and event registration
• New research reports or benchmark studies
• Customer case studies relevant to an account’s industry
• Product launches and feature announcements for existing customers
• Trade show meeting booking in the weeks before an event

They are less suitable for substantial discounting and heavy promotion. A sales rep’s email carries personal trust, and a banner that shouts at the reader can undercut the relationship the email is trying to build. Match the tone of the banner to the tone of the conversation.

Getting sales onboard

Sales teams sometimes worry that banners will clutter their emails or distract from the message. Two steps help.

First, involve a few senior account managers when you choose the first campaigns, so the banners reflect what buyers actually ask about. Second, share the results. When reps see that a banner drove registrations from their own accounts, the conversation changes from mere acceptance to enthusiastic requests.

Start with one campaign

You don’t need a full program to test this channel. Pick one upcoming event or content launch, choose a target list, set clear dates and tag the link. After the campaign ends, compare the signature traffic with your other channels on cost, volume and quality.

For many B2B teams, the result is a low-cost channel that runs quietly in the background of every sales conversation, reaching the accounts that matter most at the moments they are already paying attention.

The post The B2B Campaign Channel Already Built into Every Sales Email appeared first on B2B Marketing Blog | Webbiquity.

Strategic partnerships can give a young company access to customers, expertise, technology, or distribution channels that would take years to build independently. Yet the type of partnership that helps a startup gain traction may become less useful as the business grows.

Treating partnerships as something that should change with the company can keep them connected to actual growth priorities.

Early Partnerships Can Provide Market Proof

Startups usually enter partnership discussions with limited leverage. They may have an interesting product but little brand recognition, a small customer base, and few documented results. At this stage, the right partner can help establish credibility.

These relationships can also generate useful marketing material. Customer results, implementation lessons, and credible case studies often carry more weight in B2B markets than broad promotional claims. The goal should still be specific. A recognizable partner is valuable only if the relationship helps solve a real business problem.

Growth Changes What a Good Partner Looks Like

Once a company has established demand, partnership decisions need to become more systematic. The question shifts from whether a relationship can create an opportunity to whether that opportunity can be repeated.

Consider a referral partnership that produces a handful of valuable customers but requires substantial attention from senior leadership. That arrangement may work during the startup phase. At a larger scale, however, the company may need a formal channel program with defined incentives, training, lead-sharing procedures, and performance expectations.

Marketing teams also need clearer attribution. Leads generated through webinars, partner referrals, integrations, or co-branded campaigns should be tracked through the sales process. Otherwise, companies can continue investing in relationships that appear active without knowing whether they contribute meaningful pipeline or revenue.

Larger Partnerships Require More Scrutiny

As the financial and operational stakes increase, partner evaluation becomes more important. A relationship involving customer data, shared technology, international expansion, or a major distribution agreement can create risks that a simple referral arrangement does not.

Companies should examine a potential partner’s financial position, leadership, reputation, legal history, security practices, and ability to fulfill its commitments. For higher-stakes relationships, a due diligence firm may be brought in to investigate areas that require deeper verification.

This work matters because partnership problems can affect customers directly. If a critical technology provider experiences repeated outages or a distribution partner fails to meet service expectations, customers may associate the resulting problems with both companies.

Partnerships Need an Exit Point

Business relationships can outlive their usefulness. A partnership created to enter one market may matter less once the company builds its own sales presence there. Another partner may gradually stop producing referrals even though both companies continue promoting the relationship.

Periodic reviews should compare the original purpose of the partnership with current results. Revenue is one measure, but companies can also examine qualified leads, customer retention, product adoption, market access, and the resources required to maintain the relationship. Ending or restructuring an underperforming partnership can free employees to concentrate on relationships with greater potential.

Strategic partnerships can support growth at every stage, but their purpose should evolve with the company. Startups may use them to build credibility and prove market demand. Growing businesses need relationships that can produce repeatable results, while larger organizations require stronger governance and performance measurement.

The post From First Customers to New Markets: How Strategic Partnerships Change as Companies Grow appeared first on B2B Marketing Blog | Webbiquity.

A corporate event budget can change significantly based on the room selected. The lowest rental rate does not always produce the lowest final cost because each type of space creates different requirements for seating, audiovisual equipment, catering, staffing, and setup.

For B2B marketers planning conferences, product launches, client events, or executive meetings, evaluating those secondary costs can provide a much more accurate picture of what the event will require.

Conference Rooms Keep Smaller Events Focused

Conference rooms are usually practical for workshops, sales meetings, executive sessions, and small client presentations. Many include tables, chairs, screens, and basic video conferencing equipment, which can reduce setup requirements.

Capacity deserves closer attention than the number listed by the venue. A conference room rated for 30 people may technically fit that many seats but feel crowded once presentation equipment, catering, or additional staff enter the space.

Event technology can also change the cost. A basic screen may be included, while better microphones, multiple cameras, or dedicated technical support carry separate charges. For a hybrid B2B event, these expenses may be necessary if remote participants need to interact with people in the room rather than simply watch a presentation.

Ballrooms Create More Production Decisions

Ballrooms provide flexibility because organizers can build the room around the program. The same space might host a keynote in the morning and a networking reception that evening. That flexibility often means more production work. Stages, screens, lighting, sound equipment, draping, and furniture may need to be installed specifically for the event.

A large ballroom can also require additional audiovisual equipment because attendees seated far from the stage still need to see presentations clearly.

Labor costs can increase when the room changes configurations during the event. Moving from theater seating to banquet tables requires time and staff, which should be discussed with the venue before the schedule is finalized.

For events that will generate video, interviews, or other marketing assets, media production services may add another layer to the budget. Camera placement, lighting, recording equipment, and crew space should be considered during room selection rather than after the layout has been approved.

Auditoriums Reduce Some Setup Costs

Auditoriums are built around presentations, making them useful for keynote sessions, industry panels, training programs, and company-wide meetings. Fixed seating and established sightlines can reduce furniture and staging requirements.

The tradeoff is less flexibility. Networking, meals, and exhibits usually need to happen elsewhere. If an event includes a presentation followed by a reception, organizers may have to rent a lobby, ballroom, or additional function space. Food and beverage costs can therefore shift rather than disappear.

Breakout Rooms Multiply Small Expenses

Breakout rooms are common at conferences where attendees separate into smaller educational or discussion sessions. Individually, these rooms may seem inexpensive. Across several rooms, however, repeated expenses can become substantial.

Each space may need presentation equipment, microphones, water, signage, and technical support. If five sessions run simultaneously, equipment usually cannot be shared between them. Scheduling affects this calculation.

Staggered sessions can sometimes allow equipment or staff to move between rooms, although the event schedule needs enough transition time for that approach to work reliably.

Room selection should ultimately be evaluated against the event format rather than rental price alone. A ballroom offers flexibility but may require substantial production. An auditorium can simplify presentations while creating separate reception costs.

Conference and breakout rooms solve different needs but bring their own capacity and technology considerations. Look over the infographic below for more information.

The post Beyond Square Footage: How Room Type Shapes Corporate Event Costs appeared first on B2B Marketing Blog | Webbiquity.

B2B marketing efforts can often take weeks or months and require marketers to connect with multiple stakeholders. While a digital campaign can effectively target multiple businesses in a short amount of time, marketers can incorporate direct mail to amplify their efforts. Direct mail can continue the conversation and further build brand awareness.

Significant Impact When Direct Mail is Combined with a Digital Campaign

A U.S. Postal Service (USPS) white paper evaluating the impact of direct mail in marketing reported the following statistics:

• 40% conversion rates when digital and direct mail are combined
• 68% of marketing respondents said combining digital and direct mail increased website visits
• 60% of marketing respondents said combining digital and direct mail increased ROI

Some companies even experienced an average 15% increase in sales when they incorporated direct mail with digital marketing strategies.

Together, these statistics show that direct mail can strengthen digital campaigns by generating more traffic, conversions, and sales.

Why is Direct Mail Different from Digital Marketing Channels?

Direct mail stands out from most (digital) marketing channels because its real, tangible nature makes it harder to ignore. It also delivers these four benefits.

Physical Interaction

Unlike digital marketing channels, direct mail requires the target audience to engage physically by opening it up and reading its content. Just the act of touching an object, such as a piece of mail, activates parts of the brain that digital media cannot, making direct mail an effective way to cut through the noise and connect with an individual.

Unique Experience

Direct mail also provides the opportunity to appeal to the recipients’ senses. Examples include using specialty paper, scented materials, and interactive designs. To take it one step further, B2B marketers can also direct their audience to advanced technology, such as augmented reality and near field communications, via a QR code or link in a mail piece.

A fun, unique experience will likely create a lasting impression and stand out from competitors.

Greater Visibility  

Even if the target audience doesn’t open the mail immediately, the mail will likely be on their desk for a few days. This allows for more visibility and awareness of a brand since a piece of mail can’t be easily dismissed like an email with a single swipe.

A piece of mail doesn’t have to compete in a crowded email box, making it more likely that the recipient will notice it. Combined with personalization, mail can speak directly to an individual and show how their organization will benefit from working with a particular business.

Personalization

Direct mail provides marketers the opportunity to send a personalized message. For example, if they’re targeting a particular stakeholder, they can create a message that will get the stakeholder to take action. Custom postcard printing services make it easy to produce personalized postcards with tailored messaging, branded graphics, and unique calls to action for different audience segments.

How Can Direct Mail Amplify the Efforts of a Digital Campaign?

When building a digital campaign, marketers should brainstorm ways they can amplify their efforts. While using a combination of online channels will build awareness and reach more audience, direct mail can serve as a personalized follow up to businesses who have engaged with the campaign online. It can also redirect prospects back to the digital campaign, driving additional online engagement.

As with any marketing strategy personalization is key to achieving higher response rates. B2B marketing teams can segment their direct mail list using the data from the prospect’s initial interaction with the digital campaign. Here are 4 B2B segmentation methods (dimensions of a B2B buyer persona) to try:

• Firmographic: Group prospective organizations by broad business characteristics, such as industry, company size, location, and revenue. These characteristics will help produce messaging that speaks to a group’s priorities.
• Needs-based: Different companies have different needs. Think about the problems they are trying to solve and generate direct mail content that focuses on solving those issues.
• Account-based: Marketers targeting high-profile prospects should create custom outreach for individual organizations rather than grouping companies broadly.
• Technographic: Technographic segmentation evaluates the systems and tools a business already uses and focuses on how a new product can improve that business’s efficiency and return on investment (ROI). It can also highlight how a product reduces risk.

Strengthen Digital Campaign Performance with Direct Mail

Continue the momentum of a digital campaign by following up with prospective businesses via direct mail. Direct mail offers unique experiences and lasting impressions that online mediums can’t provide, making it a valuable tool for B2B marketers.

Denise Denton is Vice President of Marketing, Franchise Services, LLC. Franchise Services is a franchisor that owns the printing, signs and marketing services brands Sir Speedy, PIP and Signal Graphics.

The post How B2B Marketers Can Use Direct Mail to Strengthen Digital Campaign Performance appeared first on B2B Marketing Blog | Webbiquity.

That’s increasingly where business software is headed. Livestorm’s new verified connector for Claude lets marketers manage events, sessions, and attendees simply by asking for what they want in plain English.

The big picture: The announcement is about more than making webinar management easier. It’s an example of a larger shift in how we’ll interact with business software.

Instead of learning how to operate software, we’re increasingly going to tell software what we want accomplished.

Livestorm turns conversation into action

Livestorm MCP is now available as a verified connector in Claude’s connector directory.

Once connected, users can ask Claude to work with their Livestorm workspace conversationally. No API key generation, copying URLs, or developer assistance is required for the verified Claude connector.

Why it matters: Consider two of the least glamorous parts of running webinars and virtual events.

Before an event, marketers have to create sessions, organize registrants, and import or manage signup data.

Afterward comes another administrative slog: exporting attendance information, comparing attendees against registrants, analyzing engagement, and determining which people warrant follow-up.

The Livestorm connector can collapse much of that work into a conversation. Instead of navigating through interfaces and spreadsheets, a marketer can ask Claude to retrieve information, analyze it, and—in supported cases—take action in Livestorm. That’s a subtle but significant change.

Wait—what exactly is MCP?

Quick definition: MCP stands for Model Context Protocol, an open standard introduced by Anthropic in 2024 for connecting AI assistants with external data sources and business applications.

Think of MCP as a common language that enables AI systems to communicate with other software. Rather than building a completely different custom AI integration for every application, developers can expose data and capabilities through a standardized protocol.

The key phrase is two-way connections. MCP isn’t limited to letting AI retrieve information. Depending on the implementation and permissions, an AI assistant can also take actions in the connected system.

That’s what makes this development more interesting than simply asking an AI chatbot questions about webinar data.

What marketers can actually do with Livestorm MCP

State of play: Livestorm exposes tools covering events, sessions, attendees, and related data through its MCP server. For marketers, several applications immediately stand out:

• Create events conversationally. Tell Claude something like, “Create a product demo next Wednesday with morning and afternoon sessions,” rather than working through the setup screens.
• Register people in bulk. Give it a group of webinar signups and ask that they be registered for the appropriate event.
• Analyze event performance. Ask for registration and attendance numbers across events and calculate show-up rates without exporting everything to a spreadsheet first.
• Segment attendees. Identify people based on whether they registered, attended, or demonstrated particular levels of engagement.
• Manage event information. Update events and sessions or retrieve organizational information without hunting through menus.

These aren’t necessarily revolutionary tasks individually.

What’s different: The interface is becoming the conversation. That eliminates much of the mechanical work that sits between knowing what you want to accomplish and actually getting it done.

The killer use case may come after the webinar

Creating events through a conversation is convenient. But the post-event possibilities may offer greater business value.

Why it matters: B2B marketers don’t ultimately care how many people registered for a webinar. They care whether the webinar generated engagement, opportunities, pipeline, and eventually revenue.

Suppose 500 people register for a webinar.

Traditionally, marketing might export the registration and attendance data, manipulate it in a spreadsheet or marketing automation platform, identify useful engagement signals, and then create a list for sales follow-up.

With the Livestorm connector, a marketer can instead ask: “Show me which registrants attended more than 30 minutes of yesterday’s webinar and rank them by engagement.”

That’s where conversational software starts becoming genuinely interesting. A simple registration tells you someone was interested enough to fill out a form. Actual attendance tells you more.

Thirty or 45 minutes of attention can be an even stronger buying signal—particularly when combined with other first-party intent and engagement data. The connector helps turn that behavioral information into something marketing and sales can act on while the event is still fresh.

From dashboards to conversations

For decades, improvements in business software interfaces followed roughly the same path. Command lines gave way to graphical interfaces. Desktop applications moved into browsers. Mobile apps simplified those interfaces for smaller screens.

Generative AI may produce a more fundamental change.

The emerging model: You don’t necessarily need to know where a function is located in an application. You need to know what you want to accomplish.

The AI handles more of the translation between intent and execution. That doesn’t mean traditional interfaces are disappearing tomorrow. Complex applications will still need dashboards, controls, visualizations, configuration screens, and other conventional UI elements.

But: The conversational layer may increasingly become the starting point.

A marketer won’t necessarily think, “Where do I go to export last month’s webinar attendance?”

They’ll ask, “Which webinars last month had the highest attendance rates?”

And then: “Which attendees stayed for at least 75% of those sessions?”

And perhaps: “Rank those people by engagement and prepare the list for follow-up.”

The interface starts fading into the background.

Claude is a big part of the story—but not the whole story

Livestorm’s verified Claude connector makes this capability particularly accessible because the connection can be made directly through Claude’s connector directory.

But Livestorm’s MCP implementation isn’t limited to Claude.

Go deeper: Livestorm describes its MCP server as client-agnostic. Its documentation currently includes connection instructions for other MCP-compatible environments, including ChatGPT, Cursor, GitHub Copilot, Gemini CLI, Microsoft 365 Copilot, and Dust.

That’s important strategically. MCP potentially gives software vendors a way to make their applications accessible through multiple AI environments without reinventing every integration from scratch.

For marketers, it points toward a world in which the AI assistant may increasingly become a unified conversational layer across the marketing technology stack. Instead of jumping among a dozen applications, you may eventually ask an AI agent to retrieve information and execute tasks across several of them.

There are still guardrails

Yes, but: Conversational access doesn’t mean giving an AI agent unlimited control.

The Livestorm connector respects the permissions associated with the user’s account, so Claude can only access workspaces and information that user is authorized to access. And because the connector can perform write actions—not merely retrieve data—users should review proposed actions before confirming them.

There are also limits to the information available through the connector. It works with event data such as attendance, chat, and contact information from completed sessions, but it doesn’t currently handle event recordings or transcripts.

Those are reasonable boundaries for a technology that is moving business software from “show me information” toward “do this for me.”

The bigger shift: Software becomes less visible

For B2B marketers, the Livestorm connector is useful on its own.

But its larger significance may be what it tells us about where martech is going.

The old model: Learn the software > navigate the interface > manipulate the data > perform the task.

The emerging model: Describe the outcome > let AI work across the software > review the result.

That’s potentially transformative for a martech landscape notorious for complexity, underutilized features, integration headaches, and endless tabs.

It also changes what makes business software valuable. Features still matter. Integrations still matter. And data quality certainly matters.

But increasingly, accessibility to AI agents may matter too. Software that can securely expose its data and capabilities to AI systems becomes easier for humans to use—not because its interface necessarily gets simpler, but because users may need to interact with that interface less often.

The bottom line

Livestorm’s Claude connector is a practical productivity enhancement for webinar and event marketers today. It’s also a preview.

We’re moving toward a world where using marketing software means less clicking, exporting, importing, sorting, and navigating—and more simply saying what needs to get done. Livestorm’s new MCP connector makes that future surprisingly tangible.

Want to see what Livestorm can do? Visit Livestorm to explore its webinar and event platform and learn more about its AI-powered capabilities.

Disclosure: I am a Livestorm affiliate partner.

The post Livestorm’s Claude Connector Offers a Glimpse at the Post-UI Future of Marketing Software appeared first on B2B Marketing Blog | Webbiquity.