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US Appointment Booking Users Database (2024–2025) — 736K Records

Price range: $1,600.00 through $4,900.00

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736K US users who booked services via online appointment systems (2024–2025). Includes email, phone, booking frequency, and preferred scheduling times.

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Description

Published February, 2026


Pricing tiers

TierDescriptionPrice
Low-Activity Bookers2–3 bookings — ~559,500 users with light engagement. Ideal for broad campaigns, testing, or expanding reach across service-seeking consumers.$1,900
Mid-Activity Bookers4–7 bookings — ~140,500 moderately engaged users. Perfect for targeted email/SMS campaigns to service users showing recurring interest.$2,400
High-Activity Bookers8+ bookings — ~36,600 highly active users (top ~5% most engaged). Best for high-intent campaigns, premium offers, and high-conversion outreach.$1,600
Complete DatasetAll users (2–946 bookings) — 736,600 records combining low, mid, and high-activity audiences. Maximum coverage with full segmentation options for serious campaigns.$4,900

Notes:

    • All tiers Include email and/or phone contact fields

    • Covers observed 2024–2025 appointment booking activity

    • Mixed audience: consumers + SMB stakeholders (~10–20% corporate domains)

    • Delivered as-is, no enrichment or licensing guarantees

    • High-Activity tier captures top ~5% most engaged users, offering best targeting ROI


This dataset contains 736,600 deduplicated US-based users who have actively booked services through online appointment scheduling platforms during 2024–2025. Records reflect observed booking behavior, not inferred interest, making the audience suitable for demand-generation, service marketing, and appointment-driven campaigns.


The audience spans a wide range of service-based verticals, including personal care, wellness, fitness, automotive, legal, healthcare, pet services, and professional services. The dataset includes a mix of end-consumers and SMB stakeholders, with approximately 10–20% corporate-domain emails, indicating potential business owners, operators, or administrative decision-makers alongside regular service customers.


Each record includes direct contact fields (email and/or phone) and engagement attributes derived from real booking activity, such as total number of bookings and preferred booking day/time. These behavioral signals allow segmentation by engagement intensity and scheduling patterns, enabling more targeted outreach than generic consumer lists.


This dataset is best suited for:

  • Appointment-driven service marketing

  • SMS and email outreach campaigns

  • Lead generation for service tools, platforms, and offers

  • Market research on service booking behavior

  • Audience modeling and intent-based segmentation


 

Data is delivered as-is, with no licensing or usage guarantees implied. No enrichment, consent flags, or demographic modeling has been added beyond the observed fields.


Sample data:

IdFirstNameLastNameEmailPhoneNumberBookingsEverFavoriteDayFavoriteTime
3013DawnMello[email protected]20885598934Thursday15:00:00
3827LeslieMartinez[email protected]83262237707Monday11:00:00
3993YaraLozano[email protected]28125008728Friday17:30:00
4044DaveSlomski[email protected]86041679504Wednesday14:00:00
4321PeppaKapfer[email protected]80570447193Monday10:30:00
4510JudyKoch[email protected]86031412304Wednesday09:30:00
4514dawnkale[email protected]20356086773Wednesday11:00:00
4572BarbaraLuchansky[email protected]86091925667Friday10:30:00
4636JamesTremaglio[email protected]860307249423Wednesday10:30:00
4654RickCallahan[email protected]20388600522Tuesday09:00:00
4687JenniferMalentacchi[email protected]860480038117Thursday10:30:00
4701BeckyWells[email protected]512901016861Wednesday11:00:00
4716JohnBate[email protected]860307165811Thursday11:30:00
4732CassandraDiogostine[email protected]20344165239Friday09:00:00
4769KristopherGal[email protected]86048118087Thursday11:00:00
4796RobinBruneau[email protected]20370744423Thursday02:30:00
4822CarolynClapp[email protected]86099592917Friday11:30:00
4833ClintonJackman[email protected]86032976058Thursday16:30:00
4841RobertLevine[email protected]86067341574Monday10:00:00
4933JeffreySchaefer[email protected]86087765119Friday10:00:00
4982RoniWhite[email protected]860214912579Tuesday09:00:00
5045NicoleStarkey[email protected]214995557417Friday10:30:00
5199AngieRoberson[email protected]817265712749Tuesday11:00:00
5269PeterGillespie[email protected]20323561796Thursday09:30:00
5314JakeChamberlain[email protected]248437261033Thursday08:00:00
5355KrystalTrevino[email protected]83262026166Wednesday17:00:00
5360JimLynam[email protected]203644702411Tuesday12:00:00
5361JeanConnor[email protected]81062399112Wednesday12:00:00
5364ImeldaGarza[email protected]817988231012Monday10:30:00
5545DawnHedden[email protected]60722797042887Saturday11:30:00
5678ScarlettNarvaez[email protected]83265676427Wednesday16:00:00
5718MARVASCHWAGER[email protected]20833370006Wednesday09:00:00
5868DavidHead[email protected]2488917836197Tuesday10:00:00

Additional information

Product pack (see table below)

Low-Activity Bookers, Mid-Activity Bookers, High-Activity Bookers, Complete Dataset

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