Sales Productivity Tools

The anatomy of a sales call has changed dramatically. Last week, I shadowed some of HubSpot’s top reps and what struck me was how differently the best sellers work today. They’re using AI at every stage: before, during, and after the call. And the results are real. The brain: before the call. AI does the heavy research — scanning 10Ks, news, emails, and past calls to surface the insights that matter most. Tools like Breeze Assistant can prep a full company overview in seconds. According to our State of Sales Report, 74% of sellers say buyers are showing up to calls more informed than ever before. Salespeople need to be just as ready. The heart: during the call. AI notetakers capture everything: next steps, budget mentions, open questions, so reps can focus on listening, not typing or scribbling notes on the side.  Also, AI assistants surface the right case study or testimonial in real time, making every answer sharper and every example more relevant. That means as a sales rep you are more engaged and relevant. The muscle: after the call. AI follows through fast. It drafts personalized follow-up emails in your own voice, outlines next steps, and flags what needs attention. More time with customers and less time writing emails. The result: sellers who prepare better, connect deeper, and close faster. The anatomy of a great sales call used to be manual effort and hustle. Now, it’s human connection powered by intelligence.

A market map with 10,000 companies is impossible to prioritize. These are the 300 to know. I was a VP of Product in sales tech. And I was frustrated with the maps I found. So I've been studying the space and speaking with experts. Here's the players you need to know: — ONE - Core: Revenue Operating System This is your CRM, your system of record - where your sales operation begins. I break this into 3 segments: Enterprise Platforms → Built for large organizations with complex workflows and high-volume deals → Salesforce, Oracle, Microsoft Dynamics 365, SAP Growth-Stage Solutions → Designed for growing businesses that need scalable tools but with flexibility to adapt → HubSpot, Pipedrive, Zoho CRM, SugarCRM Modern CRMs → Startups and fast-scaling companies looking to move fast without rigid systems rely on modern CRMs. → Attio, Affinity, Close.io, Copper, Freshsales. — LAYER TWO - Engagement & Intelligence These tools power outbound outreach, automate sequences, and provide real-time data on prospects: → Outreach, Salesloft, VanillaSoft, Groove Engagement tools ensure your team hits the right prospect at the right time. — LAYER THREE - Revenue Acceleration These platforms shorten deal cycles: → Gong, Salesloft, Chorus.ai, Ebsta With real-time feedback and actionable insights... — LAYER FOUR - Data & Enrichment Your outreach is only as good as the data backing it. These platforms ensure you’re reaching out to right prospects. → ZoomInfo, Apollo.io, Clearbit, Lusha, Hunter io, Cognism — SATELLITE CLUSTERS - Modern GTM Stack These tools enhance parts of the GTM journey. AI-Enhanced Tools → Automate and personalize content creation at scale. → Writer, Grammarly, CopyAI, Jasper Product-Led Motion → Identify sales-ready leads through product engagement. → Pocus, Intercom, Breyta Sales Enablement → Equip sales teams with training, resources, and playbooks to perform at their best. → Seismic, Spekit, Allego Conversational GTM → Convert prospects directly through real-time chat. → Drift (now part of Salesloft) — SATELLITE CLUSTERS- Emerging Categories These are adjacent categories sales teams often still use. Product Analytics → Track user behaviors post-sale for better upsell and retention opportunities. → Amplitude, Mixpanel Customer Success → Ensure long-term customer retention and success beyond the initial sale. → Gainsight, Catalyst, Totango Workspace Integration → Enable seamless collaboration across sales and operations. → Notion, Slack, Airtable, monday.com Revenue Orchestration → Connect workflows across different systems to streamline revenue operations. → NektarAI, Tray.io, Workato, Boomi — This took a lot of time. Reshare ♻️ if you loved this post. What tools would you add?

Old School vs. New School sales teams. With 15M+ B2B sales teams globally, we're seeing a shift. Old school: - Simple team structure: AEs and more SDRs - Overpaying for outdated tools - Great sales fundamentals New school: - Often have RevOps or GTM engineers - Consistently testing out new tools - Obsess on process Here's are the tech stack changes I'm seeing: - CRM: Salesforce → HubSpot (don't need a CRM admin to make changes) - TAM Sourcing: ZoomInfo → DiscoLike (find any company with a website) - Data Handling: Excel → Clay (AI spreadsheet linked to data sources) - Global Email Coverage: Apollo → Findymail (better coverage + accuracy + price) - Global Phone Coverage: Cognism → BetterContact (best-in-class coverage + connect rates) - Email Campaigns: Mail Merge → Instantly.ai (where do I even start) - DM Campaigns: Sales Nav → HeyReach.io (automating signal-based plays) - Micro Campaigns: Mailchimp → Landbase (AI-first at every step) - Dialer: RingCentral → Trellus (YC W22) (purpose-built sales dialer) - Call Recording: Manual Notes → Modjo (AI notetakers are a must-have in 2025) Give an old school team new school systems. That's a force to be reckoned with.

Sales Navigator should be generating 50+ meetings per month for B2B sales team. But for most orgs? It’s a line item collecting dust in your tech stack. While everyone debates new AI tools, the most powerful sales weapon is already sitting in your tech stack. Most GTM teams I speak with use it ad hoc. ↳ No filters. ↳ No playbooks. ↳ No process. Here's the math that's changing how forward-thinking sales executives operate: → A team of 25 reps sending just 25 connection requests daily = 3125 monthly touchpoints → 25% average connection acceptance rate = 781 new connections within your ICP → 10% conversion to meetings through personalized videos = 78 qualified conversations At an average deal size of $40K that is $3.1M added in pipeline just from LinkedIn. Even if you cut these results in half. → You're still looking at $𝟭.𝟱𝗠/𝗺𝗼𝗻𝘁𝗵 𝗶𝗻 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲. The difference between average teams and top performers isn't fancy AI or complicated tools. It's executing these fundamentals at scale with every rep, every day. If your team isn’t running this system daily. You’re leaving millions on the table.

Not all platforms are worth it After I shared the story behind Mongabay’s decision to deprioritize Facebook (https://lnkd.in/gtNhEDYh), several people asked: Where should impact-driven organizations focus their energy instead? There’s no one-size-fits-all answer. The best platform depends on your audience and what you want them to do with the information you share. Are you trying to spark in-platform conversation? Drive traffic to your website? Reach decision-makers or a mass audience? For Mongabay’s global English-language reporting (Mongabay News), we’ve found LinkedIn to be the most valuable platform for engaging people whose decisions shape the real world — policymakers, funders, researchers, industry leaders, and advocates. Much of the interaction happens in-platform, but it also sends meaningful traffic to our site. We’ve experimented elsewhere. Bluesky Social, for example, feels like early Twitter — conversational but resource-intensive, requiring constant activity but with little measurable impact so far. It may evolve, but for now, it’s not much of a driver of real-world outcomes for us. If your goal is mass reach, Instagram, TikTok, or YouTube might be the better play — especially for visual storytelling. But these platforms are less about driving engagement back to owned channels and more about meeting audiences where they are. This is why understanding your audience is so critical. What platforms do they use? What format resonates? Who influences them — and what motivates action? At Mongabay News, our choices reflect both analysis and mission alignment. We prioritize the channels where engagement quality — not just volume — is highest. That means LinkedIn, newsletters, syndication partnerships, and webinars. We invest less in platforms that generate empty views. One thing that’s become clear: Focusing our efforts on platforms like LinkedIn doesn’t just help us reach our audience — it helps us learn who they are. That feedback loop is invaluable when impact is the goal. Of course, every organization’s calculus will be different. Even within Mongabay, each bureau sets its own strategy based on which platforms best align with their goals. But if you’re grappling with similar questions, I’d suggest starting here: Define what success looks like, measure what matters, and be ready to shift resources as the landscape evolves. For those experimenting — what’s working for you? Where are you seeing the most meaningful engagement? 📊 Engagement score is a quick metric based on scroll depth, time on page, bounce rate, and pages/session, all of which are related of course.

Over the past 9 years, I’ve acquired 1,000+ clients for my agencies. If I were starting over today, here’s exactly how I’d land my first 10 clients: Step 1: Start with the right data The biggest challenge when starting out? Finding highly targeted prospects who are ready to buy. Here’s how I’d solve that: Google Maps. Yes, I said Google Maps. Why? Because it’s an untapped goldmine for qualified leads. With over 4,000 B2B categories, it’s packed with local businesses and SMBs often overlooked - or missing - from LinkedIn. These are hidden gems waiting to be discovered. Scrap (https://scrap.io/s/9MYK) transforms this goldmine into actionable leads by extracting from Google Maps listings: - Emails, phone numbers, & websites - Social media profiles - Website technologies - Even Google Maps ratings & reviews Filter and focus on your ideal targets in just 2 clicks. For example: - Restaurants with 4+ ratings but no Instagram. - Local businesses with websites but no ad pixels. - SMBs in specific niches or locations. Scrap’s real-time data extraction ensures you always have the most accurate info - and it’s available as a Chrome Extension for instant insights. Step 2: Personalize your outreach Generic outreach doesn’t work - relevance is everything. Try this playbook: - Subject Line: Use something attention-grabbing like “Quick question about [business name]” or “Idea for [service].” - Personalize: Reference their Google Maps reviews, website, or niche. For example: “Congrats on your 4.9-star rating - I can see why people love your café.” - Partner Up: “I help cafes like yours boost foot traffic through email marketing. I noticed a few opportunities I’d love to share.” - CTA: End with a low-pressure ask: “Does this sound worth exploring?” Pro Tip: Pair the emails from Scrap (https://scrap.io/s/9MYK) with LinkedIn outreach - connect or engage with their posts to build trust. Step 3: Stay consistent and scale your efforts Build momentum through persistence: - Follow Up: Most responses come after the 2nd or 3rd touch. Example sequence: Email → LinkedIn connect → Follow-up email → Call. - Track Metrics: Monitor open rates, replies, and booked calls. Aim for a 20%+ email response rate and 10%+ meetings booked. - Leverage Referrals: Once you’ve landed a few clients, ask, “Know anyone else who might benefit?” and share testimonials like, “We helped a local coffee shop grow foot traffic by 20% in 30 days.” - Automate: Use Scrap for fast lead gen and a CRM to manage outreach. Recap: - Use Scrap (https://scrap.io/s/9MYK) to turn Google Maps into a lead-gen machine for local businesses, SMBs, and niche prospects. - Personalize your emails with insights and a clear CTA. - Stay consistent by following up, tracking results, and leveraging referrals. - And remember: Your first 10 clients lay the foundation for scaling. #ScrapPartner

𝗦𝗮𝗹𝗲𝘀 𝗰𝘆𝗰𝗹𝗲𝘀 𝗮𝗿𝗲𝗻’𝘁 𝗹𝗼𝗻𝗴. 𝗧𝗵𝗲𝘆’𝗿𝗲 𝗷𝘂𝘀𝘁 𝗹𝗼𝘀𝘁 𝗶𝗻 𝗻𝗼𝗶𝘀𝗲. Many sales leaders believe they can improve performance by adding more training, tools, or dashboards. But the reality doesn’t change. Deals continue to stall. Forecasts remain inaccurate. The problem isn’t a lack of effort or even talent. It’s the absence of a real-time execution layer that turns data into action. 𝟭. 𝗡𝗲𝘅𝘁-𝗦𝘁𝗲𝗽 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Reps no longer guess their next move. AI reads deal patterns and gives them precise, timely actions that move the pipeline forward. 𝟮. 𝗗𝗲𝗮𝗹 𝗥𝗶𝘀𝗸 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗥𝗲𝗰𝗼𝘃𝗲𝗿𝘆 Most lost deals show early warning signs. AI detects when momentum drops and triggers recovery actions before the deal slips away. 𝟯. 𝗦𝗮𝗹𝗲𝘀 𝗖𝗮𝗹𝗹 𝗣𝗿𝗲𝗽 𝘄𝗶𝘁𝗵 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 Reps walk into calls fully prepared. AI surfaces the key insights, talking points, and questions tailored to each persona and stage. 𝟰. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Not every deal deserves equal attention. AI helps reps focus on the right opportunities at the right time. 𝟱. 𝗜𝗻𝘀𝘁𝗮𝗻𝘁 𝗥𝗲𝗽 𝗖𝗼𝗮𝗰𝗵𝗶𝗻𝗴 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 Coaching doesn’t have to wait for a review. AI analyzes performance patterns and provides real-time guidance for improvement. 𝟲. 𝗣𝗹𝗮𝘆𝗯𝗼𝗼𝗸𝘀 𝗳𝗿𝗼𝗺 𝗥𝗲𝗮𝗹 𝗪𝗶𝗻𝘀 Winning deals leave a trail of patterns. AI turns those into living playbooks that adapt across industries and personas. 𝟳. 𝗪𝗼𝗿𝗸𝘀 𝗜𝗻𝘀𝗶𝗱𝗲 𝗧𝗼𝗼𝗹𝘀 𝗬𝗼𝘂 𝗔𝗹𝗿𝗲𝗮𝗱𝘆 𝗨𝘀𝗲 Adoption is everything. Modern AI integrates into your team’s daily tools, so insights appear exactly where reps work. 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀, 𝗿𝗲𝗽𝘀 𝗿𝗲𝗹𝘆 𝗼𝗻 𝗴𝘂𝘁 𝗳𝗲𝗲𝗹𝗶𝗻𝗴 𝗮𝗻𝗱 𝗿𝗲𝗮𝗰𝘁𝗶𝘃𝗲 𝗽𝗹𝗮𝘆𝗯𝗼𝗼𝗸𝘀. 𝗪𝗶𝘁𝗵 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀, 𝗲𝘃𝗲𝗿𝘆 𝗺𝗼𝘃𝗲 𝗶𝘀 𝗴𝗿𝗼𝘂𝗻𝗱𝗲𝗱 𝗶𝗻 𝘀𝗶𝗴𝗻𝗮𝗹 𝗮𝗻𝗱 𝘁𝗶𝗺𝗶𝗻𝗴. 𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝗲𝗮𝗿𝗹𝘆 𝗮𝗰𝗰𝗲𝘀𝘀 to your own AI sales agent that does this for your team: 👉 https://tally.so/r/m6BA6P

Most sales orgs have too many tools and not enough results. Ya'll are spending money in the wrong places. You've got a CRM. You've got a dialer. You've got an SEP. You've got conversation intelligence. You've got 14 dashboards nobody looks at. And your reps are still manually researching prospects. Still sending the same generic sequences. Still doing demos that don't convert. The stack is bloated with the WRONG things. The results are flat. Meanwhile, the modern buyer has changed. They want to self-educate. They want data. They want to move on their timeline, not yours. Or your still using what was cool 2-5 years ago because it was 'on the quadrant' If your tech stack isn't built around AI, data-driven decisions, and meeting buyers where they are — you're already behind. Tech has changed. There are some new up and comers that are just rocking right now 𝗧𝗛𝗘 𝗖𝗔𝗧𝗘𝗚𝗢𝗥𝗜𝗘𝗦 𝗧𝗛𝗔𝗧 𝗔𝗖𝗧𝗨𝗔𝗟𝗟𝗬 𝗠𝗢𝗩𝗘 𝗧𝗛𝗘 𝗡𝗘𝗘𝗗𝗟𝗘 These aren't tools I just talk about. I actually use them with my team. One of the few "influencers" left that's still in the trenches building. I get asked all the time my 'stack' so kicking the year off with some of my favorites. Here's where I'm focused for 2026: 𝗗𝗮𝘁𝗮 & 𝗘𝗻𝗿𝗶𝗰𝗵𝗺𝗲𝗻𝘁 Bad data = wasted activity. Period. If your reps are calling wrong numbers and emailing dead addresses, no amount of "more dials" fixes that. Using: Cargo, ZoomInfo, TitanX 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 & 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 The manual stuff that eats your team's time — follow-ups, research triggers, multi-touch sequences — needs to run without humans babysitting it. Using: Swan AI, Trigify 𝗗𝗲𝗺𝗼 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 Your AEs are doing the same demo 47 times a month. Most of those demos are qualification calls in disguise. What if prospects could experience the product on their own time? 24/7. Customized to their use case. Scalable. Repeatable best practices baked in. Better qualified prospects. Shorter cycles. Higher conversion. Using: Consensus 𝗔𝗰𝗰𝗼𝘂𝗻𝘁 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 "Find me companies that just raised a Series B, are hiring SDRs, and use Salesforce." That level of specificity used to take hours. Now it takes seconds. Using: Exa 𝗧𝗛𝗘 𝗕𝗜𝗚𝗚𝗘𝗥 𝗣𝗢𝗜𝗡𝗧 Stop buying tools because they're "cool" or because your competitor has them. Buy tools that solve a specific constraint in your funnel. If connect rate is killing you — fix the data. If cycle time is too long — fix the demo process. If reps are drowning in admin — fix the workflows. Constraint first. Tool second. The orgs that win in 2026 will be the ones using AI to make smarter decisions, move faster, and meet buyers where they actually are. Most orgs have it backwards. They buy the tool and then try to find a problem for it to solve. That's how you end up with 47 logins and the same results. Be intentional with your stack, ya'll.

If you’re building toward $10M+ ARR and thinking about AI agents in GTM, read this. Everyone’s talking about “agents.” But most of what you see online aren’t agents, they’re glorified workflows.   A few APIs stitched together in Make, n8n or Zapier with a GPT call in the middle. That’s not autonomy, that’s automation.   We’ve been testing real agent systems across 60+ GTM teams, Outbound, inbound, demand, RevOps.   And only a handful actually work in live sales environments. Here’s what real agents do: ✅ They make decisions based on inputs (not fixed scripts) ✅ They learn from results and adjust next steps ✅ They operate toward a goal, not completing tasks   If you’re serious about building a $10M+ GTM engine, these are the 7 roles AI agents can fill right now so your team can focus on Tier 1 prospects, high-context calls, and closing deals:   1) 🧠 Research Agent Finds, enriches, and prioritizes ICP-fit accounts in real time. Tools: Claygent, Exa, Browserbase 2) 🧬 Buyer Insights Agent Understands tone, seniority, and buying behavior. Tools: Humantic AI, Humanlinker 3) 📬 Outreach Agent Executes personalized multichannel outreach across email + LinkedIn. Tools: Valley, Magic Reach, Instantly.ai 4) 🔁 Follow-Up Agent Manages replies, reactivates cold leads, adjusts timing. Tools: AiSDR, Artisan, 11x 5) 📈 Sales Call Agent Analyzes calls, flags objections, triggers CRM actions. Tools: Attention, Avoma, Gong 6) 📅 Meeting Agent Books, confirms, and reschedules meetings automatically. Tools: Reelay®, Tactiq, Superhuman 7) 🧱 CRM Agent Cleans data, syncs records, flags missing info. Tools: HubSpot, Attio, folk Here’s how top 1% GTM teams are using them: 💡 Agents handle volume, data, and speed. 💬 Humans focus on trust, context, and Tier 1 conversations. That’s how you scale to $10M+ ARR with a lean team.   We’re testing the next wave of agent-native GTM right now (including OpenAI’s Agent Builder 👀). If you want the workflow map of how these fit in a full GTM stack, let me know below and i'll write a post about it.   #AIagents #GTMstack #Outbound

I just spoke to the VP of Ops @ a Series B tech startup. She said 1 automation we built saved them $56,250 per year. Here’s the math 👇 Their reps were scoring leads by hand. • To decide if a lead was “good” a rep had to: • Check company size • Check email activity • Check job title • Check website visits Time spent: 15 minutes per lead They get ~5,000 leads per year. That’s: • 4 leads per hour • 1,250 hours per year • 156 full workdays • Rep cost = $45/hour Do the math: $56,250/year Just to decide if a lead is worth working. This is way more common than people think. I’ve been helping sales teams for 8 years. Most aren’t lazy. They’re stuck doing work they weren’t hired to do... Manual work. Here’s the pattern I see: • Data entry • Clicking around Salesforce • Researching every lead by hand On average, reps waste 12–20 hours per week on this. That’s 30–50% of their job. This isn’t a hiring problem. It’s an ops problem. If something happens every time… A system should do it. Not a person. This is why ops is about leverage. Humans think. Systems repeat. If you’re in ops in tech startup: Start by subtracting work. Not adding headcount. Thought this tip was helpful? Join my FREE weekly newsletter I send out every Friday morning ☀️ 1 Salesforce tip to help you automate your business. https://lnkd.in/gswdmJkW