Stop treating AI like a tool | February AI Tips
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How are you going to stand out in 2026?
Buyers are in control of the buying process. Over 70% of it is happening online. And they are putting companies on their short list of vendors that provide value and establish trust with their content.
How are you accounting for this in your 2026 strategy?
You need to stand out. To make sure your buyers notice you. Let us help you build that into your strategy for next year -->
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The Revenue Marketer
Stop treating AI like a tool | February AI Tips
Still chasing 10% efficiency gains?
2023-2025 were the years of experimentation with AI. 2026 is the year to make it transformative. If you're still trying to figure out the strategic advantage AI will bring to your team, we're here to help!
So, we’re a couple months into 2026, and I gotta be real: AI should just be part of your operating system by now.
If you’re still treating AI like a feature bolted on or a tool to play with, and not a GTM shift, then let this newsletter will help get you started. If you’re farther along, then let this uplift some use cases you might not have considered.
You’ll notice I don’t focus much on better prompting - we offer a fantastic training course if you need to get your team up to speed on that. This month, we’re tackling what’s really been on my mind consistently since October: the confluence of buying committee stratification and buyer search behavior.
The insights in this newsletter (Answer Engine Optimization, Agentic Workflows, the "Decision Drag" challenge) are designed to start addressing an approaching problem: much of the buyer journey will be automated by AI, it will be tailored to the specific interests of individual buying committee members, and our GTM processes are still working like it’s 2020.
So, let’s dive in and start making change. Just always remember: we’re not trying to squeeze 10% more out of a broken system. Our goal is to reimagine what the system will look like and free our high-performing marketers to drive 10x the results.
1. Get on Your Buyers’ Shortlist with Answer Engine Optimization (AEO)
B2B buyers are now forming their preferences earlier than ever, with 95% of winning vendors appearing on the "day one" shortlist before any seller contact occurs. As 94% of buyers now use LLMs like ChatGPT and Perplexity to research solutions, your brand's invisibility in these "answer engines" is a direct threat to your pipeline. If your technical specs and differentiators aren't machine-readable, AI will simply summarize a competitor who has done the work.
Audit your top three service pages this afternoon. Paste your URLs into Claude or ChatGPT and ask: "Based on this page, what are the three specific constraints or use cases where this product outperforms competitors?" If the AI gives a generic answer, your content is too "clever" and not clear enough for AEO. Rewrite the page headers and add a "Structured FAQ" section using schema markup. This ensures LLMs can extract and cite your specific value propositions in buyer queries.
Sources: The B2B AI Implementation Handbook for GTM in 2026 | The Agentic Shift: B2B AI Marketing Analysis
2. Standardize Your Content Repurposing
Most marketing teams are using AI to type faster, but only 19% have integrated it into daily workflows or supported it with their internal knowledge and standards. The result is "AI slop;” a high volume of low-quality content that erodes brand trust. High-performing teams are moving beyond prompt-engineering and deploying "AI Workers" to handle end-to-end tasks such as content repurposing, freeing human talent for high-stakes creative direction.
Identify the one task your team complains about most (likely meeting summaries or webinar repurposing). Open Claude Cowork or a custom GPT that has any relevant messaging frameworks or brand guidelines in its knowledge base. Upload your last three webinar transcripts. Ask it to generate a "Repurposing Kit" consisting of one blog intro, five LinkedIn hooks, and three SDR follow-up snippets for each. Have one team member spend 30 minutes editing these drafts tomorrow and make sure the blog includes the structured FAQ from item 1. Document and standardize the process. You'll move from "experimentation" to "operational gain" in a single session.
Sources: AI Workers: 18 High-ROI Use Cases | The AI Content Reset: What B2B Marketers Must Stop and Start
3. Solve for "Decision Drag" by Addressing Individual Needs Earlier
B2B buying groups have expanded to an average of 13 internal stakeholders and nine external influencers. Deals are stalling not because of your product's features, but because of "decision drag,” which is the internal friction caused by stakeholders who don't see how your solution fits their specific KPIs. When 74% of buyers feel overwhelmed by options, the vendor that excels at buyer enablement for all stakeholders wins.
Pull the notes from your three largest "stalled" deals in Salesforce. Paste the "Loss/Stall Reason" fields into ChatGPT or Gemini and ask: "Which stakeholder persona (Finance, IT, Ops) was the likely blocker here, and what specific documentation was missing for them?" If you don’t have a robust Loss/Stall Reason code pick list, then grab the transcripts from all the sales calls related to the deal. Use the output to draft a one-page "Persona Cheat Sheet" for your sales team this week. This empowers reps to proactively address the "messy middle" of the buying network where influence is currently invisible. Take it a step further and start building a connective content plan to address these disconnects earlier in the process.
Sources: B2B Buying Behavior in 2026: 57 Stats | Forrester’s 2026 Buyer Insights
4. Operationalize Signal Follow Up
I think we’ve all gone through lead scoring working sessions where we focus on how to ascribe a score value to a buyer’s content download, web visit, or webinar registration. Why are we determining what buyer’s find value in? Predictive models are now achieving 85% accuracy in forecasting which deals will close by analyzing "digital body language,” such as account visits to pricing pages or research surge on technical forums. The advantage has shifted from those with the most leads to those who prioritize intent-ready accounts with same-day outreach.
Pull this morning's intent alerts from your platform (6sense, Demandbase, or HubSpot Breeze). Copy the top five account names and their "research topics" into ChatGPT. Ask: "Draft a personalized LinkedIn connection request for these accounts that references [Topic] and offers a specific, non-gated resource related to this topic." Send these drafts to your SDRs before their first dial block. You'll have real data on whether same-day, intent-based outreach improves response rates by Friday. If it works, do this every week.
Sources: AI for B2B Marketing: What Actually Works | Predictive Lead Scoring and Smart Funnels 2026
5. Remember that “Earned Media” Generates Authority
LLMs prioritize third-party citations over vendor websites, with 89% of citations in top models coming from earned media. If your 2026 strategy relies solely on your own blog, you are starving AI engines of the signals they need to recommend your brand. "Generative Engine Optimization" (GEO) is a real-time shift in how buyers shortlist tech solutions through conversational search.
Work with your sales team to identify the top five questions prospects are currently asking ChatGPT or Perplexity about your category. Search for those exact prompts yourself and see which publications are being cited in the answers. Reach out to one of those cited publications this week to pitch a data-driven thought leadership piece or a case study. Securing a mention in a "high-influence" publication is the most effective way to "train" LLMs to associate your brand with buyer-relevant prompts.
Source: How B2B Tech Can Build AI Visibility in 2026
About the author
Service page feature
Artificial intelligence
So, we’re a couple months into 2026, and I gotta be real: AI should just be part of your operating system by now.
If you’re still treating AI like a feature bolted on or a tool to play with, and not a GTM shift, then let this newsletter will help get you started. If you’re farther along, then let this uplift some use cases you might not have considered.
You’ll notice I don’t focus much on better prompting - we offer a fantastic training course if you need to get your team up to speed on that. This month, we’re tackling what’s really been on my mind consistently since October: the confluence of buying committee stratification and buyer search behavior.
The insights in this newsletter (Answer Engine Optimization, Agentic Workflows, the "Decision Drag" challenge) are designed to start addressing an approaching problem: much of the buyer journey will be automated by AI, it will be tailored to the specific interests of individual buying committee members, and our GTM processes are still working like it’s 2020.
So, let’s dive in and start making change. Just always remember: we’re not trying to squeeze 10% more out of a broken system. Our goal is to reimagine what the system will look like and free our high-performing marketers to drive 10x the results.
1. Get on Your Buyers’ Shortlist with Answer Engine Optimization (AEO)
B2B buyers are now forming their preferences earlier than ever, with 95% of winning vendors appearing on the "day one" shortlist before any seller contact occurs. As 94% of buyers now use LLMs like ChatGPT and Perplexity to research solutions, your brand's invisibility in these "answer engines" is a direct threat to your pipeline. If your technical specs and differentiators aren't machine-readable, AI will simply summarize a competitor who has done the work.
Audit your top three service pages this afternoon. Paste your URLs into Claude or ChatGPT and ask: "Based on this page, what are the three specific constraints or use cases where this product outperforms competitors?" If the AI gives a generic answer, your content is too "clever" and not clear enough for AEO. Rewrite the page headers and add a "Structured FAQ" section using schema markup. This ensures LLMs can extract and cite your specific value propositions in buyer queries.
Sources: The B2B AI Implementation Handbook for GTM in 2026 | The Agentic Shift: B2B AI Marketing Analysis
2. Standardize Your Content Repurposing
Most marketing teams are using AI to type faster, but only 19% have integrated it into daily workflows or supported it with their internal knowledge and standards. The result is "AI slop;” a high volume of low-quality content that erodes brand trust. High-performing teams are moving beyond prompt-engineering and deploying "AI Workers" to handle end-to-end tasks such as content repurposing, freeing human talent for high-stakes creative direction.
Identify the one task your team complains about most (likely meeting summaries or webinar repurposing). Open Claude Cowork or a custom GPT that has any relevant messaging frameworks or brand guidelines in its knowledge base. Upload your last three webinar transcripts. Ask it to generate a "Repurposing Kit" consisting of one blog intro, five LinkedIn hooks, and three SDR follow-up snippets for each. Have one team member spend 30 minutes editing these drafts tomorrow and make sure the blog includes the structured FAQ from item 1. Document and standardize the process. You'll move from "experimentation" to "operational gain" in a single session.
Sources: AI Workers: 18 High-ROI Use Cases | The AI Content Reset: What B2B Marketers Must Stop and Start
3. Solve for "Decision Drag" by Addressing Individual Needs Earlier
B2B buying groups have expanded to an average of 13 internal stakeholders and nine external influencers. Deals are stalling not because of your product's features, but because of "decision drag,” which is the internal friction caused by stakeholders who don't see how your solution fits their specific KPIs. When 74% of buyers feel overwhelmed by options, the vendor that excels at buyer enablement for all stakeholders wins.
Pull the notes from your three largest "stalled" deals in Salesforce. Paste the "Loss/Stall Reason" fields into ChatGPT or Gemini and ask: "Which stakeholder persona (Finance, IT, Ops) was the likely blocker here, and what specific documentation was missing for them?" If you don’t have a robust Loss/Stall Reason code pick list, then grab the transcripts from all the sales calls related to the deal. Use the output to draft a one-page "Persona Cheat Sheet" for your sales team this week. This empowers reps to proactively address the "messy middle" of the buying network where influence is currently invisible. Take it a step further and start building a connective content plan to address these disconnects earlier in the process.
Sources: B2B Buying Behavior in 2026: 57 Stats | Forrester’s 2026 Buyer Insights
4. Operationalize Signal Follow Up
I think we’ve all gone through lead scoring working sessions where we focus on how to ascribe a score value to a buyer’s content download, web visit, or webinar registration. Why are we determining what buyer’s find value in? Predictive models are now achieving 85% accuracy in forecasting which deals will close by analyzing "digital body language,” such as account visits to pricing pages or research surge on technical forums. The advantage has shifted from those with the most leads to those who prioritize intent-ready accounts with same-day outreach.
Pull this morning's intent alerts from your platform (6sense, Demandbase, or HubSpot Breeze). Copy the top five account names and their "research topics" into ChatGPT. Ask: "Draft a personalized LinkedIn connection request for these accounts that references [Topic] and offers a specific, non-gated resource related to this topic." Send these drafts to your SDRs before their first dial block. You'll have real data on whether same-day, intent-based outreach improves response rates by Friday. If it works, do this every week.
Sources: AI for B2B Marketing: What Actually Works | Predictive Lead Scoring and Smart Funnels 2026
5. Remember that “Earned Media” Generates Authority
LLMs prioritize third-party citations over vendor websites, with 89% of citations in top models coming from earned media. If your 2026 strategy relies solely on your own blog, you are starving AI engines of the signals they need to recommend your brand. "Generative Engine Optimization" (GEO) is a real-time shift in how buyers shortlist tech solutions through conversational search.
Work with your sales team to identify the top five questions prospects are currently asking ChatGPT or Perplexity about your category. Search for those exact prompts yourself and see which publications are being cited in the answers. Reach out to one of those cited publications this week to pitch a data-driven thought leadership piece or a case study. Securing a mention in a "high-influence" publication is the most effective way to "train" LLMs to associate your brand with buyer-relevant prompts.
Source: How B2B Tech Can Build AI Visibility in 2026
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About the author
Service page feature
Artificial intelligence
Stop treating AI like a tool | February AI Tips
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So, we’re a couple months into 2026, and I gotta be real: AI should just be part of your operating system by now.
If you’re still treating AI like a feature bolted on or a tool to play with, and not a GTM shift, then let this newsletter will help get you started. If you’re farther along, then let this uplift some use cases you might not have considered.
You’ll notice I don’t focus much on better prompting - we offer a fantastic training course if you need to get your team up to speed on that. This month, we’re tackling what’s really been on my mind consistently since October: the confluence of buying committee stratification and buyer search behavior.
The insights in this newsletter (Answer Engine Optimization, Agentic Workflows, the "Decision Drag" challenge) are designed to start addressing an approaching problem: much of the buyer journey will be automated by AI, it will be tailored to the specific interests of individual buying committee members, and our GTM processes are still working like it’s 2020.
So, let’s dive in and start making change. Just always remember: we’re not trying to squeeze 10% more out of a broken system. Our goal is to reimagine what the system will look like and free our high-performing marketers to drive 10x the results.
1. Get on Your Buyers’ Shortlist with Answer Engine Optimization (AEO)
B2B buyers are now forming their preferences earlier than ever, with 95% of winning vendors appearing on the "day one" shortlist before any seller contact occurs. As 94% of buyers now use LLMs like ChatGPT and Perplexity to research solutions, your brand's invisibility in these "answer engines" is a direct threat to your pipeline. If your technical specs and differentiators aren't machine-readable, AI will simply summarize a competitor who has done the work.
Audit your top three service pages this afternoon. Paste your URLs into Claude or ChatGPT and ask: "Based on this page, what are the three specific constraints or use cases where this product outperforms competitors?" If the AI gives a generic answer, your content is too "clever" and not clear enough for AEO. Rewrite the page headers and add a "Structured FAQ" section using schema markup. This ensures LLMs can extract and cite your specific value propositions in buyer queries.
Sources: The B2B AI Implementation Handbook for GTM in 2026 | The Agentic Shift: B2B AI Marketing Analysis
2. Standardize Your Content Repurposing
Most marketing teams are using AI to type faster, but only 19% have integrated it into daily workflows or supported it with their internal knowledge and standards. The result is "AI slop;” a high volume of low-quality content that erodes brand trust. High-performing teams are moving beyond prompt-engineering and deploying "AI Workers" to handle end-to-end tasks such as content repurposing, freeing human talent for high-stakes creative direction.
Identify the one task your team complains about most (likely meeting summaries or webinar repurposing). Open Claude Cowork or a custom GPT that has any relevant messaging frameworks or brand guidelines in its knowledge base. Upload your last three webinar transcripts. Ask it to generate a "Repurposing Kit" consisting of one blog intro, five LinkedIn hooks, and three SDR follow-up snippets for each. Have one team member spend 30 minutes editing these drafts tomorrow and make sure the blog includes the structured FAQ from item 1. Document and standardize the process. You'll move from "experimentation" to "operational gain" in a single session.
Sources: AI Workers: 18 High-ROI Use Cases | The AI Content Reset: What B2B Marketers Must Stop and Start
3. Solve for "Decision Drag" by Addressing Individual Needs Earlier
B2B buying groups have expanded to an average of 13 internal stakeholders and nine external influencers. Deals are stalling not because of your product's features, but because of "decision drag,” which is the internal friction caused by stakeholders who don't see how your solution fits their specific KPIs. When 74% of buyers feel overwhelmed by options, the vendor that excels at buyer enablement for all stakeholders wins.
Pull the notes from your three largest "stalled" deals in Salesforce. Paste the "Loss/Stall Reason" fields into ChatGPT or Gemini and ask: "Which stakeholder persona (Finance, IT, Ops) was the likely blocker here, and what specific documentation was missing for them?" If you don’t have a robust Loss/Stall Reason code pick list, then grab the transcripts from all the sales calls related to the deal. Use the output to draft a one-page "Persona Cheat Sheet" for your sales team this week. This empowers reps to proactively address the "messy middle" of the buying network where influence is currently invisible. Take it a step further and start building a connective content plan to address these disconnects earlier in the process.
Sources: B2B Buying Behavior in 2026: 57 Stats | Forrester’s 2026 Buyer Insights
4. Operationalize Signal Follow Up
I think we’ve all gone through lead scoring working sessions where we focus on how to ascribe a score value to a buyer’s content download, web visit, or webinar registration. Why are we determining what buyer’s find value in? Predictive models are now achieving 85% accuracy in forecasting which deals will close by analyzing "digital body language,” such as account visits to pricing pages or research surge on technical forums. The advantage has shifted from those with the most leads to those who prioritize intent-ready accounts with same-day outreach.
Pull this morning's intent alerts from your platform (6sense, Demandbase, or HubSpot Breeze). Copy the top five account names and their "research topics" into ChatGPT. Ask: "Draft a personalized LinkedIn connection request for these accounts that references [Topic] and offers a specific, non-gated resource related to this topic." Send these drafts to your SDRs before their first dial block. You'll have real data on whether same-day, intent-based outreach improves response rates by Friday. If it works, do this every week.
Sources: AI for B2B Marketing: What Actually Works | Predictive Lead Scoring and Smart Funnels 2026
5. Remember that “Earned Media” Generates Authority
LLMs prioritize third-party citations over vendor websites, with 89% of citations in top models coming from earned media. If your 2026 strategy relies solely on your own blog, you are starving AI engines of the signals they need to recommend your brand. "Generative Engine Optimization" (GEO) is a real-time shift in how buyers shortlist tech solutions through conversational search.
Work with your sales team to identify the top five questions prospects are currently asking ChatGPT or Perplexity about your category. Search for those exact prompts yourself and see which publications are being cited in the answers. Reach out to one of those cited publications this week to pitch a data-driven thought leadership piece or a case study. Securing a mention in a "high-influence" publication is the most effective way to "train" LLMs to associate your brand with buyer-relevant prompts.
Source: How B2B Tech Can Build AI Visibility in 2026
About the author
Service page feature
