Read this first

Four things “match” can mean. We report two of them.

  1. CoverageA phone number exists in the file. This is what most “95%+” claims measure.
  2. MatchThe number belongs to the named owner on title.
  3. ActiveThe number is a live mobile today, not a landline or a disconnected line.
  4. ConnectSomeone picked up. Only a dialer export can show this.

A Scout Data record is 2 and 3 together. The connect numbers below are 4, from the floors that measured them.

Bay Area solar call center

What the floor saw

MeasureValueSampleWindowNote
wrong or dead numbers3.45%2,205 agent-tagged callsSep 1–2, 2026Share of calls an agent tagged wrong number or disconnected, on a 25,000-record no-solar file.
already had solar1.09%2,205 agent-tagged callsSep 1–2, 2026On a file built to exclude homes with panels — permits cross-checked against aerial imagery.
reached a renter1.68%2,205 agent-tagged callsSep 1–2, 2026Owner-occupied filter, checked against what the agent heard.
agent connect per dial, first pass5.02%24,879 first dialsSep 1–2, 2026A predictive dialer with aggressive machine detection; the same file’s second and third passes connected at 3.55% and 3.45%.
appointments on dials 1, 2 and 35 · 3 · 624,879 · 23,644 · 15,789 dialsSep 1–2, 2026Connect rate falls with each pass; appointments do not. A record is not spent after one dial.
more appointments per dial from active mobiles3.65×two 25,000-record files, pooledAug 31 – Sep 10, 2026Records whose mobile showed carrier activity in 5 or more of the last 12 months, against the rest of the file (95% CI 1.98–6.74). We rank on it now.

New Jersey solar call center

What the floor saw

MeasureValueSampleWindowNote
calls per live pickup4.58107,574 callsAug 1–22, 2026Calls ÷ (connects + abandoned), the dialer’s own definition. Inside the floor’s “strong” band (under 7) on all 22 days.
answered, machines included80.0%107,574 callsAug 1–22, 2026Answered = calls − no answer. Voicemail counts as answered in this report, so read it with the machine rate.
of answered calls hit a machine72.7%107,574 callsAug 1–22, 2026Strong on 16 of 22 days by the floor’s own bands; the two weak days were low-volume weekends.

Pennsylvania, Massachusetts and California solar floor

What the floor saw

MeasureValueSampleWindowNote
wrong numbers, Massachusetts vs Pennsylvania3.7% · 9.2%13,038 rep-tagged callsJul 20 – Aug 19, 2026The honest version: it varies by market. Pennsylvania’s rate is ours to fix and is why we re-verify before a repeat order.
live human answer per dial4.45%2,224,746 dials60 days to Aug 25, 2026The floor number every call center already knows. 90.54% of dials went to machine detection; 3.70% reached an agent.

across delivered files

How fast numbers go stale

MeasureValueSampleWindowNote
of records go dead within six weeks1.4%re-enriched paid ordersJul–Aug 2026Why a repeat order is re-verified instead of re-shipped.

suburban Dallas–Fort Worth pool

How many homes yield a record

MeasureValueSampleWindowNote
of homes yield the owner on title79.7%18,309 single-family parcels, TexasAug 18, 2026A returned contact whose name matches the deed.
of homes yield the owner with a live mobile54.6%18,309 single-family parcels, TexasAug 18, 2026The deliverable number. About half of owner-occupied homes produce a record; the rest are dropped rather than filled with a relative or a landline.

Method

How each number was counted.

  • Dialer exports are joined to the delivered file on phone number, then on owner name, before any rate is computed. A batch that matches zero rows is a scoping question for the floor, not a finding.
  • Attempts are stratified. A first dial and a third dial are not the same event; connect rate falls with each pass and appointments do not. Batches are only compared at the same attempt depth.
  • Dialer reports use the dialer’s own definitions and say so. ReadyMode counts a voicemail as answered, so its answer rate is read next to its machine rate.
  • Yields are stated with the denominator: an 18,309-parcel pool where 54.6% produced an owner with a live mobile means the other 45.4% were dropped, not filled.
  • Nothing is rounded up, no floor is named without written approval, and nothing about a floor’s own dialer settings or deal terms is published.

Do the math on your own numbers: dials per appointment and cost per dialable contact.

Reading a match rate

The questions a buyer should ask.

Answered the way we answer them on a call.

What can a vendor mean by a “95% match rate”?

One of four things. Coverage: a phone number exists in the file for 95% of addresses. Match: the number belongs to the named owner. Active: the number is a live mobile today. Connect: someone picked up. Most published match rates are the first. A call center needs the second and third, and only a dialer export can show the fourth.

Which of the four does Scout Data report?

Match and active together, as the definition of a record — one home, the owner on title, a live mobile — and connect from customers’ dialer exports. A coverage number is never presented as accuracy.

Why do the numbers vary by market?

Because phone data does. On one floor’s export, wrong numbers ran 3.7% in Massachusetts and 9.2% in Pennsylvania on the same month’s files. Publishing the spread is more useful than publishing the best market.

Are these numbers rounded?

No. 3.45% is 3.45%. Every figure carries the sample it was counted on and the month, and the derivation file is named in the page source.

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