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    <title>Pipemetry blog — revenue forecasting &amp; RevOps</title>
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    <description>Practical guides on revenue forecasting, sales pipeline analytics, and running RevOps without a black box.</description>
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      <title>The CRM data hygiene checklist for forecasts</title>
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      <description>The CRM data hygiene checks that make or break a forecast — missing amounts, stale deals, past close dates, missing categories — and how to triage them in bulk.</description>
      <pubDate>Tue, 14 Jul 2026 00:00:00 GMT</pubDate>
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      <title>Why did my sales forecast change?</title>
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      <description>How to decompose a forecast move into probability shifts, amount changes, and new-or-dropped pipeline — so “the number moved” becomes “here’s why.”</description>
      <pubDate>Tue, 14 Jul 2026 00:00:00 GMT</pubDate>
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      <title>Pipeline coverage ratio — and when it lies</title>
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      <description>What the pipeline coverage ratio is, how to compute it per segment, why raw coverage misleads, and how to set the multiple from your own win rate.</description>
      <pubDate>Thu, 09 Jul 2026 00:00:00 GMT</pubDate>
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      <title>How to measure sales forecast accuracy</title>
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      <description>How to measure sales forecast accuracy with MAPE, bias, and hit rate — and why you can’t score a forecast without the pipeline as it looked that day.</description>
      <pubDate>Mon, 06 Jul 2026 00:00:00 GMT</pubDate>
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      <title>Choosing revenue forecasting for a smaller team</title>
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      <description>What a 10–100 rep sales team should look for in revenue forecasting software: transparent models, self-serve setup, published pricing, and provable accuracy.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 GMT</pubDate>
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      <title>How to forecast revenue without a black box</title>
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      <description>A transparent revenue forecasting method RevOps teams can actually explain — from pipeline coverage to accuracy tracking, without trusting an opaque model.</description>
      <pubDate>Wed, 10 Jun 2026 00:00:00 GMT</pubDate>
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