CRM Software for Sales

Most CRM processes have 40% adoption rates. (Which means bad pipeline data and wasted time.) Reps avoid updating CRMs because the process is time-consuming. → Extract deal signals from scattered email threads → Switch between multiple browser tabs and systems → Manually update opportunity stages and required fields → Remember to log follow-up activities and next steps Teams waste hours on data entry instead of closing deals. And when updates finally happen, half the information is already outdated. This creates a bigger problem: • New reps never learn the process correctly. • Experienced reps skip important steps. • Managers can't see what's happening in deals. That’s where Tango's browser agents bridge the gap between training and execution. Instead of forcing reps to learn new systems, they blend automation, AI, and human-in-the-loop input directly inside the tools reps already use. Record any CRM workflow once, and Tango turns it into step-by-step guidance and automation. Here's how it works: Step 1: Record your workflow once in the browser Step 2: Add rules and approval steps in plain language Step 3: Deploy real-time guidance to your entire team What your reps see in action: ➟ Tango reads conversations & suggests CRM updates automatically ➟ Shows proposed changes before updating any fields ➟ Walks reps through your exact methodology on-screen ➟ Handles complex workflows with multiple decision points ➟ Updates Salesforce data and logs activities accurately This works for any browser-based tool: ☑️ CRM systems like Salesforce and HubSpot ☑️ Email platforms and LinkedIn messaging ☑️ Quote systems and contract tools ☑️ Support chat and marketing systems Teams using Tango see immediate results: ✓ Reps work 3x faster on routine tasks ✓ 90% reduction in administrative work ✓ 100% accurate data entry & CRM updates ✓ Instant process adoption without training ✓ Better forecasting from clean pipeline data No APIs. No templates. No new systems. 👉 Just better execution of the processes you already have. 📌 Try Tango Browser Agents: https://www.tango.ai/  🔄 Repost to help RevOps teams automate CRM work #AI #Agent #CRM #Sales #AIAgent #TangoPartner #SponsoredByTango  

Your CRM can't be AI-ready if your meeting notes live somewhere else. Last week, I put 11 HubSpot-integrated AI meeting tools head-to-head on the same sales call. Same conversation. Same script. I wanted a direct comparison to gauge the quality of their meeting notes. Here's why this matters right now: Sales teams are racing to add AI capabilities. But most are missing the foundation: getting quality meeting notes into their CRM. Think about it: ✅ Your notes tell the full story of each deal ✅ They capture next steps and qualification criteria ✅ They're crucial for forecasting and pipeline insights ✅ They power every AI tool you'll layer on top But I'm seeing teams: ❌ Taking manual notes (still!) ❌ Using AI tools that don't sync to HubSpot ❌ Copy-pasting between tools ❌ Missing key details in from their conversations So I tested 11 tools that offer free trials and integrate with HubSpot: Fathom - AI Meeting Assistant, Grain, Avoma, Otter.ai, Sybill, Demodesk, tl;dv - AI Meeting Assistant, Fellow Inc., CustomerIQ, Spiky.AI, Granola A couple tools nailed it—concise, structured, actionable notes. Some of the others? Not so much. If you're thinking about AI for your sales team, this is where you need to start. Get the meeting notes right, and everything else becomes possible. I’m putting together a full breakdown of how each tool actually performed—real outputs, side-by-side comparisons + a detailed look at the depth of their HubSpot integrations. If you want to see which tools get it right (and which ones don’t), drop a comment and I’ll send it your way as soon as it’s ready! ✨

We analyzed 650M candidate profiles and discovered something shocking: multi-person outreach sequences increase response rates by 2X, yet only 20% of recruiting teams use this approach. Most teams are doing recruiting outreach completely wrong. They have one recruiter send all messages in a sequence. Candidates ignore them. At Gem, we've tested this obsessively across thousands of companies. The data is clear. Here's what actually works: 1. First message: Recruiter introduces the opportunity 2. Second message: Hiring manager shows personal interest ("I was catching up with Nolan from recruiting, who mentioned your name...") 3. Third message: VP or executive adds credibility It works because it turns cold outreach into something that feels high-touch and personal. For startups without established talent brands, this is even more critical. When passive candidates are evaluating YOU more than you're evaluating them, having multiple team members vouching for them makes all the difference. We tested dozens of sequence variations. The highest performer? A 4-stage sequence using email (not InMail) with 3 follow-ups from different people. This approach increased positive response rates by 68%. I saw this firsthand at Gem and before that at Dropbox. The best recruiters always leverage hiring managers in outreach. Everyone else is leaving responses on the table.

Your team should be selling. Instead, they’re drowning in admin work. Sales reps just want to sell. But when we sit down with them, it’s always the same story. They’re buried in 20 screens, clicking through fields that don’t help them close deals. And if it takes that much effort? They’ll stop using the CRM altogether. Not because they’re lazy. But because the system wasn’t built for them. Here’s what we see over and over—and how to fix it: 1) Too Much Manual Data Entry No rep wants to spend their time: • Logging calls • Typing out notes • Moving data between tools They’re here to sell—not push buttons. Fix it by automating everything you can. Use tools like Gong & QuickBooks to log calls automatically and sync invoices. The less manual data entry they do, the more time they have to close deals. 2) Clunky CRM Layouts If it takes 20 clicks to close a deal, they’re not going to use the system. Most CRM setups are bloated with fields that reps don’t care about. Half of them aren’t even for sales. The answer: fewer clicks, better layouts. • Two clicks, max • Only show fields relevant to their role 3) Tools Aren’t Integrated Reps live in: • Outreach • Gong • Slack If none of these tools talk to Salesforce, they’re forced to double their work. That kills adoption. Integrate the tools they already use. If it doesn’t make their job easier, it doesn’t belong in the stack. 4) The CRM Feels Like a Surveillance Tool Managers care about dials. Reps care about closing deals and hitting quota. If the CRM only tracks activity, it’s just another micromanagement tool. Fix it by making the CRM valuable for the rep. • AI-driven next steps • Deal insights • Sales shortcuts that actually help them win It has to feel like a competitive advantage—not a chore. 5) Training That Doesn’t Address Real Gaps Most training is based on gut feelings: “Reps need to know this.” But it doesn’t actually address the biggest problems. Fix it by making training metric-driven. If reps aren’t filling out critical fields, start there. Focus on what actually moves deals forward. Make the CRM work for reps, and they’ll actually use it. Make it a burden, and they’ll find ways around it. Enjoyed this post? Follow Jordan Nelson for more insights on making CRMs actually work for sales teams.

Years ago, I watched one of the best enterprise salespeople I've ever known lose a million-dollar deal simply because "𝗜 𝗱𝗼𝗻'𝘁 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗯𝗲 𝗽𝘂𝘀𝗵𝘆". This brilliant, capable professional was letting million-dollar opportunities slip away because she was afraid of seeming aggressive. Sound familiar? Here's the reality I've found after analyzing thousands of sales interactions: The average B2B purchase requires 8+ touches before a response, but most salespeople give up after 2-3. 𝗧𝗵𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝘀𝗻'𝘁 𝗳𝗲𝘄𝗲𝗿 𝗳𝗼𝗹𝗹𝗼𝘄-𝘂𝗽𝘀—𝗶𝘁'𝘀 𝗯𝗲𝘁𝘁𝗲𝗿 𝗼𝗻𝗲𝘀. Working with clients across industries, I've developed what some have called the "Goldilocks Sequence" – not too aggressive, not too passive, but just right for maximizing response rates without alienating prospects. It starts with how we view follow-ups. Stop thinking of them as "checking in" and start seeing them as opportunities to deliver additional value. For each client, we build what I call a "Follow-Up Content Library" with 5-10 genuinely valuable resources for each buyer persona – a mix of their content and third-party research addressing likely challenges. Having this ready means follow-ups can pull the most relevant resource based on the specific situation. The sequence itself has a rhythm designed to respect the prospect's time while staying on their radar: 𝗗𝗮𝘆 𝟭 is the initial value-focused outreach with a specific insight (never generic "I'd like to connect" language). Around 𝗗𝗮𝘆 𝟯, we send a gentle bump, forwarding the original email with: "I wanted to make sure this reached you. Any thoughts on the [specific insight]?" It's brief and assumes positive intent. By 𝗗𝗮𝘆 𝟱, we shift to an alternative channel like LinkedIn, with a personalized note referencing the insight, but still no meeting request. Around 𝗗𝗮𝘆 𝟴 comes the pure value-add – sharing a relevant resource with no ask attached: "Came across this [article/case study] that addresses the [challenge] we discussed. Thought you might find it valuable regardless of our conversation." 𝗗𝗮𝘆 𝟭𝟮 brings what I call the "pattern interrupt" – a brief email with an unexpected subject line and single-question format that's easy to respond to. Then, around Day 18, we send the "permission to close" message: "I'm sensing this might not be a priority right now. If that's the case, could you let me know if I should check back in the future? Happy to remove you from my follow-up list otherwise." This sequence generated a 34% response rate for an enterprise software client compared to their previous 11% using traditional methods. The key difference? Every touch adds legitimate value rather than just asking for time. And because it's systematic, it removes the emotional weight of deciding when and how to follow up. What's your most effective follow-up technique? I'm always collecting new approaches to share with clients. #SalesFollowUp #OutreachStrategy #PipelineGeneration

If it takes more than a week to launch, it’s not your first AI workflow. Don’t kick off a “big AI initiative.” Start with small, shippable wins and stack them. Three lanes to keep you sane: 1) Easy wins (60–90 minutes) → Form spam triage + proper routing → Waterfall lead enrichment into the CRM → Daily campaign digest to your inbox 2) Experiments (plug AI into what already works) → Classify inbound intent and trigger the next step → Automatic sales-call prep briefs sent to Slack → Press-mention monitoring with sentiment + alerts 3) Rethink the work (after you’ve earned trust) → Deal-desk approvals in Slack with clear ownership → Transcript → tasks → CRM updates (closed loop) → Closed-won signals to Slack with context for CS & Finance Build rules, then add AI: → Default to deterministic steps; use AI for extract / summarize / classify / write inside the workflow → Define the trigger, the “definition of done,” fields to update, and the owner → Ship weekly → review what moved a metric → keep what works, cut what doesn’t Month-one plan: Week 1: Form triage + routing; auto-enrichment Week 2: Call-prep briefs; meeting summary → tasks Week 3: Signal-based follow-up on high-intent actions Week 4: Deal-desk flow; closed-won → Slack with context Not flashy. Just consistent. Do this for 30–60 days and “AI in RevOps” stops being a project—it becomes how your system works. — 🔔 Follow Nathan Weill for no-fluff posts on automation, RevOps, and systems that actually ship. #RevOps #Automation #AI #GTM #SalesOps #MarketingOps #WorkflowDesign

The “CRM” you know today is quietly dying. Not with a bang, but with a slow takeover. Look at the last few months: • ServiceNow buying AI workflow and GTM automation players • Clari acquiring Groove • Clari and Salesloft merging These aren’t just logos swapping hands. This is the quiet dismantling of the old Salesforce-style CRM stack. When I first got into sales, the CRM was the source of truth. We were told “if it’s not in Salesforce, it didn’t happen.” The reality? It was mostly a graveyard of stale notes and inflated pipeline. Fast forward to now, the action isn’t in the CRM…it’s in the revenue platforms that actually run sales. Pipeline inspection, buyer engagement, AI-driven forecasting, real-time deal orchestration. It’s like the difference between a dusty ledger and a live market ticker. The contrarian take? I think the future “CRM” won’t be a single system of record at all. It’ll be an ecosystem of orchestration layers, AI-first, deeply integrated, invisible to reps. By the time you “log into” something, it will have already updated itself and acted on your behalf. The CRM will stop being a place you go and start being something that works around you. The real winners here? Not the companies that own the most logos, but the ones that nail: • Seamless AI-powered interoperability • Sales team adoption without force • An actual lift in win rates, not just prettier dashboards I’ve lived through 4 different “end-all” CRM rollouts. Each promised transformation. Most delivered… more admin work. This M&A wave? It feels different. If they execute right, sales leaders might finally stop fighting the tech stack and start trusting it. What do you think? Are we watching CRM’s evolution, or its obituary? #FutureOfSales #SalesStrategy #AIForSales #ModernSelling

Teams who take a “boil the ocean” approach to outbound will fail. Here’s how to fix it and build sequences that actually drive results: Step 1: Focus your team on accounts most likely to buy now, invest at a premium, and become long-term customers or referral sources. This means moving beyond “anyone who fits the ICP” and zeroing in on high-priority targets. Step 2: Create deeper, more meaningful segments from that refined group. Traditional segments are great for organizing territories but fall short for crafting sequences that resonate. Instead, you need segmentation that helps your team speak the language of specific sub-groups. Use multiple layers of data—firmographics, intent signals, and contact-level insights—to break your TAM into smaller, actionable groups. Step 3: Launch micro-campaigns that target those precise segments with messaging designed to feel tailor-made. When you take this approach, personalization becomes scalable because it’s rooted in segmentation. Your reps don’t waste time on one-off customization, and your messaging feels 99% relevant to the prospect. I've been teaching this process as #ValueBasedSegmentation for the better part of a decade. It’s the key to building sequences that drive higher CTRs, replies, and engagement without tedious manual effort. ➡️ With this approach, you’ll: - Improve email performance - Write copy that prospects actually care about - Give your team a clear roadmap for focused outbound 📌 How are you helping your team build relevance into their outbound sequences?

Recent headlines suggest CRM is disappearing. But what does that really mean? A good week-end reflection. Over the past year, vendors like Salesforce, Microsoft, and HubSpot have begun embedding AI directly into collaboration tools employees use (Slack, Teams, or email). Users no longer need to open the CRM. This is supposed to make traditional CRM interfaces obsolete. Some recent examples: - Salesforce: AI in Slack allows users to query customer data, update opportunities, and generate summaries directly within conversations. - Microsoft Dynamics 365: Integration with Teams and Microsoft Copilot captures meeting notes and updates CRM records automatically. - HubSpot: Emails and meeting transcripts are logged automatically, keeping CRM records up to date in the background. Consulting and analyst perspectives reinforce this trend. McKinsey and Accenture call it “workflow-embedded AI”: Insights and actions happen inside the tools employees already use. What this looks like: Traditional CRM: User → opens CRM → updates record → continues work AI-embedded CRM: User → works in Slack / Teams / email → AI updates CRM automatically The CRM remains the system of record. But its interface gradually disappears from daily work. How I see it: 1. This is more than a usability improvement. It is a platform competition between collaboration platforms (Slack, Teams), AI assistants, and CRM platforms. Whoever wins may control the enterprise customer ecosystem. 2. This all makes sense. People spend most of their day in collaboration tools and communication platforms, not inside CRM systems. Adoption may finally improve if users no longer feel like they are feeding a system. 3. Customer processes may become less transparent: If interactions happen primarily through AI agents and collaboration tools, visibility into the sales process may become harder. Organizations need even stronger discipline around data quality, data models, governance, and AI supervision Executive takeaways: 1. CRM interfaces may become less visible, but architecture, data quality, and governance are more critical than ever. 2. Executives should evaluate collaboration platforms as part of their CRM and AI architecture strategy. Not as standalone tools. 3. Organizations must remain cautious about overdependence on AI and collaboration ecosystems, to avoid new forms of vendor lock-in. #CRM #salesforce #AI

In 2012, we cared that we used software. Today we care how we use it. The difference is trajectory. In the last decade, adopting software was the priority. Moving from on-premise to the cloud or digitizing a manual workflow promised productivity gains. Adoption was the finish line. Today software is ubiquitous. Every salesperson uses a CRM & every engineer uses an IDE. The edge no longer comes from having the tool but from the specific path & manner in which that tool is used to achieve an outcome : a trajectory through software. A salesperson creates a lead, enriches the lead, adds in information about the prospect in a particular way. That’s one kind of trajectory. A Q&A session with AI is another trajectory : how do I conduct a research project with AI on post-quantum encryption? What are the leading algorithms? Which companies are implementing them? What’s the timeline for quantum computers to break current encryption? Who are the experts I should talk to? Tracking a user working through the day like a pinball ricocheting around a machine is tremendously strategic. First, automation requires trajectories. To automate work, you must first understand the path of that work. In the past we hired consultants to map processes manually. Now AI agents can watch & record & understand these trajectories in real-time. AI learns by observing. Second, optimization requires repetition. Trajectories provide the dataset for improvement. By analyzing thousands of passes through a workflow, AI identifies success patterns & failures & inefficiencies. Third, trajectories become the new moat. The higher the resolution of the data, the more differentiated the AI product becomes, which increases vendor lock-in. Fourth, company leadership benefits from understanding employee trajectories. We think we work together in one way, typically with some aspirational ideas. It’s another to truly understand the workflows in the field. Fifth, trajectories are the basis for optimizing AI models through reinforcement learning or fine-tuning. Smaller specialized models trained on high-value paths replace massive generalists. Lower inference costs & higher accuracy lead to increased margins. The strategic nature of trajectories raises the question of whether enterprises will negotiate the rights to their trajectory data when buying AI software, both to capture critical data & prevent lock-in. How those power dynamics play out will determine the pricing power for software broadly. The companies that master these trajectories will define the future of work.