Bradley Luna

Cold calling just got a data upgrade that changes the math. Cognism's 2025 data: verified contacts hit 13.3% answer rates. Warm AE calls? 14.4%. The gap collapsed. Not because reps got better at scripts. Because intent signals and verified data turned cold dials into warm opportunities. This isn't incremental. It breaks the "cold = low yield" assumption that shaped every outbound playbook for the last decade. If your call strategy still treats every prospect as equally cold, you're leaving pipeline on the table. The new constraint isn't willingness to dial. It's access to the right signals before you pick up the phone.

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Most AEs spend their days reacting.   To leads. To timing. To whatever hits their inbox next.  But top performers don’t just react — they *engineer control.*  They protect their time.   They prepare with intent.   They measure what matters.   And they stay on the line.  Sales Caddy gives you the guardrails to make that discipline repeatable — prompts that drive action, data that reinforces habits, and clarity that compounds.  Because revenue doesn’t reward effort.   It rewards control.  #sales #b2b #revenue #salesleadership #ai #salescaddy #revops #salesprocess #salesperformance #accountexecutive

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CSMs aren’t sales reps. In fact, most chose the CS path because it’s *not* sales. And that’s exactly what makes them powerful revenue drivers. Customer success was never about chasing quotas. But today, CSMs are being asked to deliver growth and protect the customer experience. No wonder so many feel caught between a rock and a hard place – between helping *and* selling. Here’s how the best CSMs are turning that tension into their superpower. 👇 https://lnkd.in/eYQ4ZzG2

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Your SDR team can't scale outbound because personalization breaks at volume. Writing custom emails for 200 prospects weekly is humanly impossible. So reps make a choice: send generic blasts that get 2% response rates, or cherry-pick 30 high-value accounts and leave pipeline on the table. Both options lose. The first trains prospects to ignore you. The second caps your growth at however many personalized touches one human can produce daily. The constraint isn't effort. It's that real personalization requires research, context synthesis, and message adaptation for every single prospect. Most teams can't operationalize that at scale, so they default to templates with merge tags and call it "personalized." Prospects see through it immediately. Enter This Week's Featured Agent: AiSDR AiSDR removes the personalization constraint entirely. It handles prospect research, contextual message writing, response management, and meeting coordination as a complete workflow. The agent researches each prospect across 323+ data sources, including recent LinkedIn activity, company news, job postings, tech stack changes, and funding rounds. It then writes messages that reference specific business context rather than generic pain points. When prospects reply, AiSDR responds within 10 minutes. If someone says "we're focused on other priorities right now," it doesn't mark them closed-lost. It schedules a follow-up for when their roadmap likely shifts. When they ask technical questions, it provides specific answers and moves the conversation toward a demo. When they raise objections, it handles them using your company's playbooks. The agent operates from your actual inbox through Gmail or Outlook integration, learns your messaging patterns through its persona builder, and maintains consistent positioning across every interaction. Your reps stop spending hours on email composition and sequence management. They focus on the conversations AiSDR has already warmed up. This fundamentally changes your outbound economics. The bottleneck shifts from "how many personalized emails can we write" to "how many qualified conversations can we handle." Your pipeline becomes a function of market size and offer strength, not human capacity to research and write. That's the unlock. Most SDR teams are productivity-constrained when they should be market-constrained.

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The premise behind intent data made sense: track what buyers are researching and reach out at the right time. The reality? A firehose of signals with no context. Accounts that "surge" and go cold. Reps chasing intent scores they don't trust. We broke down why the model is failing and what's starting to replace it. Spoiler: it's not more signals. It's understanding the pain behind them. Read the full piece → https://hubs.la/Q046cJzF0

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