Attention

Most conversation intelligence tools were built to help managers review calls. That was fine in 2019. In 2026, revenue teams need their platform to actually do work: – Update CRM fields automatically after every call – Surface deal risk before it's too late – Coach reps on behavior, not keyword checklists – Answer pipeline questions in seconds The old model: record → review → interpret → manually update → hope. The new model: capture → understand → sync → alert → execute. Legacy platforms analyze conversations. AI-native platforms operationalize them. That's the difference. And it's why more revenue teams are rethinking what they're paying for. → Full breakdown in the blog (link in comments)

Your CRM isn't a revenue system. It's a graveyard for data nobody acts on. Here's what revenue orchestration actually looks like: – Full visibility into every conversation, not just what gets logged – Automation that removes the admin eating your reps' selling time – Coaching that turns your top performers into a repeatable playbook That's the framework behind everything we build at Attention. Which one is your biggest gap right now?

We asked our customers what they love about Attention. Hundreds of conversations later, here's what they told us. 👇 Spoiler: it's not the bells and whistles. It's the stuff that makes their lives easier every single day. CRM auto-fill. AI-powered scorecards. Automated follow-up emails. And an AI agent that can answer any question across your entire call history. These are features customers call out by name in demos, in check-ins, and in renewal conversations. What's your most-used feature?

We built an agent that reads every customer call for churn signals. Here's exactly what it does: - Looks back at every Closed Won account in Salesforce - Pulls conversations from a designated period - Scans each call for churn signals - competitor mentions, budget concerns, cancellation requests, frustration - Categorizes every finding as HIGH or MEDIUM risk - Builds a report with account name, rep name, detected signals, and a summary - Posts it directly to Slack with clickable links to every flagged conversation Schedule it for Monday morning, your CS team knows exactly where to focus. The signals were always in the calls - now someone's actually watching. Built this in about 15 minutes with our agent builder.

Most companies think they're optimizing their sales motion. Spoiler alert: they're not. They're just losing revenue more efficiently. Kyle Asay has seen this play out across hundreds of sales orgs. Jacob Fleisher, Head of Sales at Attention, is bringing Kyle in for a live conversation on the question nobody wants to answer honestly: Are you building for your team's efficiency - or for your buyer's experience? And what happens when those two things conflict? 𝗔𝗽𝗿𝗶𝗹 𝟭𝟬, 𝟮𝟬𝟮𝟲 | 𝟭𝟮 𝗣𝗠 𝗘𝗦𝗧 | 𝗟𝗶𝘃𝗲 𝗼𝗻 𝗭𝗼𝗼𝗺 Register here: https://luma.com/gl70ffor

We've scaled Unify to $XXM in ARR with a sales team of 24 people. Here are the 8 tools powering the machine:   1. Attention – AI-powered call analysis and coaching   We use Attention to generate call summaries, identify areas for improvement, and create scorecards for reps. This lets us scale coaching across the team without managers needing to listen to every call.   2. Default – Lead routing and scheduling   Default powers all of our demo routing. NBRs, AEs, and RevOps can test and tweak routing logic without writing a line of code, enabling fast experimentation and clear ownership.   3. Guru – Sales enablement   We use Guru to manage content reps need mid-deal, including competitive intel, pricing breakdowns, and integration specs. Itʼs fully searchable and synced with Slack, so reps donʼt waste time digging for docs.   4. Synch – Pipeline management and forecasting   Our sales managers use Synch for pipeline reviews and forecast tracking. It gives us a better way to visualize deal stages, flag risk, and stay accountable week over week.   5. Scratchpad – Sales notes + activity logging   The team loves Scratchpad for note-taking and keeping deal records up to date. It syncs cleanly with Salesforce, giving them a fast workspace that fits their flow.   6. Salesforce – CRM Our source of truth. Every tool in our stack connects with Salesforce to keep reporting, pipeline, and team dashboards consistent.   7. Saleo – Demo environments   RevOps uses Saleo to spin up demo environments without engineering help. We can showcase new features, verticalized use cases, and workflows based on who weʼre selling to without needing to spin up custom builds.   8. Unify – Our signal-based outbound system, workflow orchestration layer, and sequencer.   Unify powers all of our outbound. We use it to:   → Detect high-intent buyers (website visits, job changes, etc.) → Automate deep account research → Personalize outreach and follow up at scale   It lets our team scale pipeline without growing headcount linearly, and serves as the foundation of our outbound motion.   What would you add or subtract? Let us know below! 👇

We ran 180+ sales calls through Attention this month. 3 patterns nobody is talking about: 𝟏. 𝐘𝐨𝐮𝐫 𝐫𝐞𝐚𝐥 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐨𝐫 𝐢𝐬 𝐝𝐞𝐧𝐢𝐚𝐥. Prospects aren't saying "your competitor is better." They're saying "we don't have a problem." One told us word for word: "You have to prove there IS a problem before you can offer a solution." Problem creation > objection handling. 𝟐. 𝐀𝐈 𝐜𝐫𝐞𝐚𝐭𝐞𝐝 𝐚 𝐛𝐮𝐲𝐢𝐧𝐠 𝐜𝐨𝐦𝐦𝐢𝐭𝐭𝐞𝐞 𝐭𝐡𝐚𝐭 𝐝𝐢𝐝𝐧'𝐭 𝐞𝐱𝐢𝐬𝐭 𝟐 𝐲𝐞𝐚𝐫𝐬 𝐚𝐠𝐨. Multiple prospects described new internal gatekeepers for anything AI-related: AI working groups, data privacy reviews, security teams. One banking prospect said these are "always the longest, hardest, and most unpredictable" part of any decision. Another prospect's CEO dismissed the whole thing with: "We can just build an AI chatbot ourselves." Your deal is now going through people and processes that didn't exist when you wrote your playbook. Map the invisible committee or lose to it. 𝟑. 𝐓𝐢𝐦𝐞 𝐢𝐬 𝐭𝐡𝐞 𝐧𝐞𝐰 𝐛𝐮𝐝𝐠𝐞𝐭. Direct quote from a prospect: "Money is easy to find. My time is what's on the line." The phrase that moved more deals forward than any ROI stat? "We do the heavy lifting - you just comment." Stop building CFO decks. Start proving low implementation effort. — All of this came from analysing real conversations in Attention - not from industry reports.

I took thousands of sales calls and built a programmatic content pipeline designed for AEO. Here's how: I connected Claude directly to Attention’s call data. The source material isn't our marketing team's opinions but thousands of real sales conversations, anonymized of course. We have actual buyers talking about pricing, objections, and competition in their own words building content for us. This is where your biggest alpha comes from. Still early but the premise feels right. AEO content machine 🤝 conversations in Attention.

Elite Insurance Partners scaled supervisor coverage from 10 agents to 25, without adding headcount. Here's how: 28 scorecard items tracking script adherence. 365 automated coaching cycles per year. 100% call coverage across 250 agents. As Jagger Esch, CEO & Founder of EIP, shared: "Attention gives you the tools to hold your team accountable. When you do this, here are the results that happen." EIP runs the largest privately-owned Medicare supplement brokerage in the country. In that world, compliance isn't optional - a missed disclosure or script deviation can trigger regulatory consequences. Before Attention, supervisors could realistically monitor a fraction of daily call volume. Random sampling meant gaps went undetected, and coaching arrived too late to change behavior. Now every call is scored. Every underperforming agent gets targeted feedback the next morning. And supervisors spend their time on the work that actually requires human judgment. We're proud to work with teams like EIP that are building compliance infrastructure that scales with their business. Read the full story at the link in the comments: