Keep missing data separate from service opportunities in a Maps export

说明与用途

问题：Google Maps 导出中缺失的数据可能导致需求被高估。解决方案：使用 Google Maps Service Opportunity Scorer，应用四个信号，保留信号状态，归一化评分，并单独处理已关闭地点。结果：生成透明、可审计的潜在客户列表。

问题

Missing website fields in a Google Maps export can be misinterpreted as businesses without websites, inflating apparent demand and misleading outreach prioritization.

结果

The workflow produces a transparent, auditable queue of business opportunities, distinguishing between truly missing data and valid observations, and preventing false positives in outreach.

工作流

• 1. Inspect each source row to confirm field values and identify missing data.
• 2. Apply the four playbook signals, recording the state of each signal (absent, blank, missing, invalid).
• 3. Compute raw points using default weights (40,30,15,15) or custom weights, then normalize the score.
• 4. Record confidence as the number of resolved signal states and keep partial signal-state columns visible.
• 5. Route permanently or temporarily closed places to a distinct review queue, preserving closure evidence.
• 6. Export the assessment table with opportunityScoreNormalized, weightTotal, and source coverage notices.
• 7. Use the exported data to build an auditable research queue for outreach.

证据

If every missing website field is interpreted as a business without a website, a sparse export manufactures apparent demand.

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Google Maps Service Opportunity Scorer processes an existing places batch using four disclosed playbook signals.

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The four checks concern website presence, low rating, owner description and listing sparsity.

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Default weights are 40, 30, 15 and 15 for the four signals.

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Listing pricing read on 23 October 2026 is $0.012 per result-found event on the FREE tier.

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