How to build a solid data foundation for AI and GTM systems

Companies are pouring time and budget into AI—but many still struggle to identify clear 𝗥𝗢𝗜. Why? A few patterns keep coming up: * **𝗧𝗼𝗼 𝗺𝗮𝗻𝘆 𝗱𝗶𝘀𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀**    Different teams buy point solutions, data lives in silos, and there’s no shared workflow or governance—so value is fragmented, duplicated, and hard to measure. * **𝗡𝗼 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 𝘁𝗼 𝗢𝗞𝗥𝘀 𝗮𝗻𝗱 𝘁𝗮𝗿𝗴𝗲𝘁𝘀**    AI projects launch as experiments, not outcomes. Without tying use cases to specific business objectives (win rate, pipeline, MTTR, FCR, cycle time), impact gets lost in activity metrics instead of business results. * **𝗟𝗶𝗺𝗶𝘁𝗲𝗱 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗳𝗹𝗼𝘄 𝗼𝗳 𝘄𝗼𝗿𝗸**    If AI isn’t where people already work (email, CRM, ticketing, chat, code), it won’t be used consistently—and you won’t see durable operational gains. That’s why we built 𝗚𝗹𝗲𝗮𝗻: AI agents and Search that are outcome-first, integrated, and enterprise-ready. 𝗟𝗲𝘁𝘀 𝘁𝗮𝗸𝗲 𝗔𝗜 𝗳𝗼𝗿 𝗦𝗮𝗹𝗲𝘀 𝘁𝗲𝗮𝗺𝘀 𝗳𝗼𝗿 𝗲𝘅𝗮𝗺𝗽𝗹𝗲:   The outcomes are clear: * **Increase win rates & rep participation**    Prep for calls, multithread accounts, surface competitive insights, and generate follow-up—without hunting across tools. This converts more pipeline to revenue. * **Increase pipeline generation**    Research accounts, personalise outbound at scale, and generate targeted messaging from real customer and market context. * **Accelerate time to first deal**    Onboard faster with instant access to best practices, talk tracks, customer stories, and collateral—right inside your CRM, email, and chat. * **Improve forecast accuracy**    Summarise deal activity, surface risks, and consolidate signals across communications and systems for a clearer, more consistent view. 𝗛𝗼𝘄 𝗚𝗹𝗲𝗮𝗻 𝗺𝗮𝗸𝗲𝘀 𝘁𝗵𝗲 𝗥𝗢𝗜 𝗺𝗲𝗮𝘀𝘂𝗿𝗮𝗯𝗹𝗲: * **Start with business outcomes, not tools**    Every agent maps to an objective (e.g., win rate, cycle time, rep ramp). * **Embed in existing systems**    Works in Salesforce, Gmail/Outlook, Slack/Teams, and Zoom so sellers never break flow. * **Connect your knowledge**    Search, summarise, and act across your company’s content and conversations with permission awareness. * **Scale with governance**    Prebuilt agent templates, standardised definitions, and curated answers ensure consistency and trust. If you’re trying to prove AI ROI: pick one metric, one workflow, one team—then operationalise with outcome‑aligned agents. That’s where compounding value starts.

Doubled sales outreach with a single AI workflow. Imagine what it could do for your pipeline. The uncomfortable truth: most companies waste time on manual research and messy CRM tasks. I see it every day. I architected an AI-powered workflow that changed everything for my GTM motion. Here’s what happened: – Automated research on every target account – Personalized outreach at scale (without losing quality) – Unified sales and technical knowledge in one system The result? More qualified conversations. Faster pipeline growth. Less busywork for the team. Most GTM teams still treat AI as a buzzword. The best ones use it to experiment, iterate, and measure impact, fast. Here’s the difference: → Old way: Add more SDRs, hope for results → New way: Run experiments with AI, track outcomes, scale what works Technical excellence isn’t just a nice-to-have. It wins deals. When you build GTM systems that deliver real results, you change how revenue teams operate. I’m proud of what we achieved with this AI workflow. It proved that smart engineering, plus bold experimentation, moves the needle. Curious how you’re using AI to redefine your outreach? Let’s talk about what works (and what doesn’t) in your GTM playbook.

Strategic AI Recommendations for SMBs 1. Start with High-Impact, Low-Risk Applications SMBs should prioritize AI applications that offer immediate ROI with minimal implementation complexity: • Customer Service Automation: By the end of 2025, 80% of small businesses plan to integrate AI chatbots into their customer support strategies. AI chatbots can handle routine inquiries, reducing response times and freeing human staff for complex customer issues. • Email Marketing and Personalization: AI-driven email marketing platforms can analyze customer behavior patterns to optimize send times, subject lines, and content personalization, typically delivering 25-35% improvement in engagement rates. • Basic Data Analytics: AI-powered analytics tools can help SMBs identify trends in sales data, customer behavior, and operational efficiency without requiring dedicated data science expertise. 2. Implement a Phased AI Strategy Rather than attempting comprehensive AI transformation, SMBs should adopt a staged approach: Phase 1 (Months 1-6): Foundation Building • Implement basic AI tools for customer service and marketing • Establish data collection and management practices • Train staff on AI tool usage and best practices • Develop AI usage policies and security protocols Phase 2 (Months 6-12): Operational Integration • Expand AI usage to inventory management and sales forecasting • Integrate AI tools across business functions • Measure and optimize AI-driven process improvements • Develop vendor relationships and support capabilities Phase 3 (Months 12-18): Strategic Enhancement • Implement advanced AI applications for business intelligence • Explore industry-specific AI solutions • Develop competitive advantages through AI-driven innovation • Scale successful AI applications across the organization 3. Address Security Concerns Proactively Given security as the primary SMB concern, organizations should: • Choose AI vendors with established security credentials and compliance certifications • Implement data governance practices that limit AI system access to necessary information • Regularly audit AI tool permissions and data usage • Train employees on AI security best practices and potential risks 4. Build AI Capabilities Through Partnership SMBs should leverage partnerships to overcome resource limitations: • Work with AI-enabled software vendors rather than building custom solutions • Join industry consortiums or trade associations offering AI training and resources • Partner with local universities or community colleges for workforce development • Engage with managed service providers offering AI implementation support Takeaway: Where has your SMB company started with AI? What is the plan to implement AI across your organization? Can you keep up with competitors, old and new, while in this transition?

Strategic AI Recommendations for SMBs 1. Start with High-Impact, Low-Risk Applications SMBs should prioritize AI applications that offer immediate ROI with minimal implementation complexity: • Customer Service Automation: By the end of 2025, 80% of small businesses plan to integrate AI chatbots into their customer support strategies. AI chatbots can handle routine inquiries, reducing response times and freeing human staff for complex customer issues. • Email Marketing and Personalization: AI-driven email marketing platforms can analyze customer behavior patterns to optimize send times, subject lines, and content personalization, typically delivering 25-35% improvement in engagement rates. • Basic Data Analytics: AI-powered analytics tools can help SMBs identify trends in sales data, customer behavior, and operational efficiency without requiring dedicated data science expertise. 2. Implement a Phased AI Strategy Rather than attempting comprehensive AI transformation, SMBs should adopt a staged approach: Phase 1 (Months 1-6): Foundation Building • Implement basic AI tools for customer service and marketing • Establish data collection and management practices • Train staff on AI tool usage and best practices • Develop AI usage policies and security protocols Phase 2 (Months 6-12): Operational Integration • Expand AI usage to inventory management and sales forecasting • Integrate AI tools across business functions • Measure and optimize AI-driven process improvements • Develop vendor relationships and support capabilities Phase 3 (Months 12-18): Strategic Enhancement • Implement advanced AI applications for business intelligence • Explore industry-specific AI solutions • Develop competitive advantages through AI-driven innovation • Scale successful AI applications across the organization 3. Address Security Concerns Proactively Given security as the primary SMB concern, organizations should: • Choose AI vendors with established security credentials and compliance certifications • Implement data governance practices that limit AI system access to necessary information • Regularly audit AI tool permissions and data usage • Train employees on AI security best practices and potential risks 4. Build AI Capabilities Through Partnership SMBs should leverage partnerships to overcome resource limitations: • Work with AI-enabled software vendors rather than building custom solutions • Join industry consortiums or trade associations offering AI training and resources • Partner with local universities or community colleges for workforce development • Engage with managed service providers offering AI implementation support Takeaway: Where has your SMB company started with AI? What is the plan to implement AI across your organization? Can you keep up with competitors, old and new, while in this transition?

GenAI is no longer an experimental add‑on, it’s reshaping how marketing and sales operate. From smarter lead targeting to AI copilots in the CRM, companies that combine model capabilities with clean data, strong governance, and integrated workflows are already seeing measurable uplifts in revenue and rep productivity. But success is uneven: the biggest gains come from realistic pilots, human oversight, and investing in the plumbing that makes AI reliable and safe. ► Hyper‑personalization at scale — Use genAI to create tailored messages and offers for individual prospects and accounts. Combine customer data, behavior signals, and retrieval‑augmented generation to produce dynamic emails, landing pages, and ad creative that reflect each buyer’s context — then A/B test and monitor performance to avoid voice drift and reduce churn. ► Sales copilots that free reps for high‑value work — Automate routine tasks and surface next best actions. Deploy AI assistants in your CRM to summarize calls, draft contextual follow‑ups, prioritize leads, and suggest negotiation moves. Keep humans in the loop for validation to prevent hallucinations and ensure brand and legal compliance. ► Operational excellence and risk management — Treat data, MLOps, and governance as strategic priorities. Clean, versioned customer data, embeddings/ vector stores, monitoring, and provenance controls determine ROI. Add consent management, red‑teaming, and contractual safeguards (private deployments or vetted enterprise models) to manage IP, privacy, and security risks. GenAI’s potential for sales and marketing is real — driving better targeting, faster pipeline creation, and meaningful rep productivity gains — but it’s not plug‑and‑play. Winners will pair ambitious use cases with disciplined data infrastructure, rigorous governance, and change management that helps teams adopt AI as a trusted copilot. Start small, measure clearly, scale safely — and the next few years will separate organizations that use genAI to transform commercial performance from those that merely experiment.

🚀 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 𝐒𝐚𝐥𝐞𝐬𝐟𝐨𝐫𝐜𝐞 𝐄𝐢𝐧𝐬𝐭𝐞𝐢𝐧 𝐆𝐏𝐓 – 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈 + 𝐂𝐑𝐌 The world’s first generative 𝐀𝐈 for 𝐂𝐑𝐌 is here! ✨ 💡 With Einstein GPT, your sales, service, and marketing teams can: 📨 Draft emails, responses & insights instantly 🎯 Get personalized recommendations powered by AI + Salesforce data ⏳ Save hours of manual work and focus on building relationships 📈 Boost productivity & customer engagement like never before ⚡ 𝐀𝐈 + 𝐂𝐑𝐌 = 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 ⚡ #Salesforce #EinsteinGPT #GenerativeAI #CRM #AI #BodenAx #bodenax

The biggest risk to AI in GTM that I see is running it on bad data. The board says “Where’s AI in our sales engine?” and immediately everyone panics. RevOps leaders are under pressure and jump to show AI workflows in sales cycles. Good intent but bad execution. Any AI workflow set up on bad data is likely to fail. The broken CRM is a shaky foundation to implement fancy automation. Some very common datagaps that can completely derail your ability to build AI workflows: - Duplicate records across systems → two reps chase the same account, wasting effort and embarrassing the team in front of prospects. - Stale contact info → execs have moved on, but your outreach still lands in an abandoned inbox. - Fragmented activity data → emails live in one tool, LinkedIn touches in another, calls in a third — so the AI never sees the full picture. - Inconsistent titles and roles → “VP, Sales Ops” vs. “Head of Revenue Enablement” — same person profile, but scoring models can’t map it. - Signals delayed by weeks → competitor engagement or job changes get spotted too late, so your outreach hits after they’ve already chosen. Get the data in order first! Having a real-time, well enriched CRM is 90% of the job done. Stop thinking of it as a "nice to have" you can get to after implementing the more front facing AI flows. I strongly believe your CRM should be a living, breathing data store. These are the building blocks: 🧩 Capture intent + behavioral signals early in the funnel 🧩 Enrich + score continuously \(not just in batches\) 🧩 Clean up legacy data debt before layering automation on top 🧩 Connect signals → sales actions seamlessly so no one is stuck in workflow hell We built @highperformr-ai to solve this for exact scenario \(starting for ourselves\). Check us out! . #CRMEnrichment #RevOps #Sales

🚀 Want to close more deals with less effort? Here are 10 ways to use AI-powered CRM for sales growth & smarter lead management. 👇 💡 #Sales #AI #CRM #Stackvate 1️⃣ Prioritize prospects with AI lead scoring. Focus on the ones most likely to convert. #SalesGrowth #AI #CRM #Stackvate 2️⃣ Automate follow-ups so no lead goes cold. AI ensures consistent touchpoints without manual effort. #SalesAutomation #AI #Stackvate 3️⃣ Use AI to detect buying signals in chats & emails. Strike while the interest is hot. #AIInsights #CRM #Stackvate 4️⃣ Get AI-powered “next-best action” suggestions. Boost rep confidence and close rates. #SalesAI #CRM #Stackvate 5️⃣ Keep your pipeline clean & updated. AI auto-updates deal stages so you don’t have to. #SalesOps #Automation #Stackvate 6️⃣ Smart lead routing: AI assigns leads to the right rep based on territory & expertise. #CRM #AI #LeadManagement #Stackvate 7️⃣ Use AI alerts for at-risk customers. Step in before churn eats your revenue. #CustomerRetention #AI #CRM #Stackvate 8️⃣ AI notifies you when a hot lead revisits your site or reopens your emails. Strike instantly. #SmartAlerts #AI #Stackvate 9️⃣ Let AI optimize pricing strategies. Stay competitive and win more deals. #SmartPricing #AI #CRM #Stackvate 🔟 Recover cold leads with AI-suggested re-engagement tactics. #LeadRecovery #CRM #AI #Stackvate AI-powered CRMs aren’t the future. They’re the present. Which of these will you try first? 👇 #SalesAI #CRM #Stackvate

🚀 AI and Automation: The Future of GTM Structures and Sales 🚀 In today’s fast-paced business world, the key to staying ahead is efficiency and insight. That's where AI and automation come into play! As Revenue Operations leaders, we need to rethink how we approach our GTM (Go-To-Market) strategies. Traditional methods are being replaced by innovative, AI-powered solutions that can automate tedious tasks, provide real-time insights, and drive smarter decisions. Here's why AI and automation are the future of GTM structures and sales: 1️⃣ Automated Data Entry: AI tools eliminate manual CRM data entry, allowing sales reps to focus on high-value activities, like nurturing relationships and closing deals. Less time spent on admin = more revenue. 2️⃣ Smart Insights: With AI, you can extract actionable insights from mountains of customer data. This helps your team target the right leads at the right time, boosting conversion rates and customer retention. 3️⃣ Personalization at Scale: Automation allows for personalized outreach at scale. Crafting messages that feel individual, yet reach a wider audience, is a game changer for scaling GTM teams. 4️⃣ Better Forecasting: AI-driven forecasting tools predict sales trends and customer behavior, giving your team the data they need to make proactive adjustments and avoid surprises. 5️⃣ Increased Efficiency: Automation tools connect and streamline your tech stack, improving workflow and ensuring all systems work together seamlessly. 🌟 The Future is Now: AI and automation aren’t just trends; they’re the future of GTM strategies. Teams that leverage these technologies will not only improve their operational efficiency but will also unlock new levels of growth and profitability. Let’s embrace the future of sales and GTM with AI and automation! What’s your take on the role of AI in transforming GTM structures? #GTM #SalesAutomation #AI #RevenueOperations #SalesTech #FutureOfSales Santiago Suarez Ordoñez Ashley Wilson Moiz Virani

⚙️ 5 High-Impact AI Automations That Transform Businesses 1️⃣ AI-Powered Sales Pipeline Forecasting Integrate your CRM (HubSpot, Salesforce, Pipedrive) with AI to predict which deals are most likely to close. Helps you prioritize follow-ups and allocate resources where they matter most. 2️⃣ AI Customer Support Triaging Go beyond chatbots. Set up AI that reads inbound tickets, categorizes urgency, detects sentiment, and routes to the right department automatically. Cuts response times dramatically while improving customer satisfaction. 3️⃣ Dynamic Pricing Automation AI can adjust prices in real time based on demand, competition, and inventory levels. Common in e-commerce, but also works in services (think gyms, salons, or agencies offering peak/off-peak pricing). 4️⃣ Intelligent Document Processing (IDP) Automate extracting data from invoices, contracts, applications, or compliance docs. AI models can read PDFs, validate fields, and push structured data directly into your systems. 5️⃣ AI-Driven Marketing Campaign Optimization Instead of manually A/B testing, AI can continuously optimize ad creatives, headlines, and audiences across Meta/Google Ads. The system learns in real-time which variant drives the most ROI and reallocates budget accordingly.