# The Front Desk Review

> Independent, sourced data on the software that runs the front office of a local-service business — every figure dated and linked to where it came from.

Every number on this site links to the public page it was captured from — the vendor's own wherever the vendor publishes the number, otherwise the named public source — and carries a last-verified date. Free to read, with a free, openly licensed core dataset. We earn from Amazon's affiliate program: Amazon pays us a percentage of qualifying purchases made through our Amazon links, at rates it sets per product category, so within a category a pricier purchase pays us more. Amazon also makes some of the products and services we rank. Our grades and sort orders never read commission data. No other company we list pays us anything, and nobody can pay to be listed, ranked, scored, corrected faster or removed. We never ask for, require, trade for or reward a link.

## Machine access
The records the pages show, served as structured data:
- Live MCP server (Model Context Protocol): https://mcp.frontdeskreview.com/mcp — 19 tools to search vendors, compare side by side, normalize pricing at a chosen volume, find the best option under a verified constraint (HIPAA / SOC 2 / GDPR / free tier / price), list coverage, surface recent dated price changes, query the full dated price-history series for any product/vendor (get_price_history), rank recent movers and per-entity volatility, report how much independent testing backs a product — a count of evidence, never a rating (get_independent_test_coverage), and look up consumer-electronics specs across 267 software and 515 hardware categories. Every record returns its source URL + accessed date; quote-only vendors return null, never a guess.
- Setup for MCP clients (Claude, Cursor, VS Code and others): https://frontdeskreview.com/connect — copy-paste setup + machine-readable manifest at https://frontdeskreview.com/.well-known/mcp/server.json
- REST + OpenAPI (no MCP client required): the same sourced, dated JSON over plain HTTP GET at https://mcp.frontdeskreview.com/api/v1/ — full machine-readable spec at https://mcp.frontdeskreview.com/openapi.json, ready to import directly as a ChatGPT GPT Action or call from any agent framework. Example: curl "https://mcp.frontdeskreview.com/api/v1/best?section=crm-software".
- Full open corpus (CC-BY-4.0): https://github.com/AlexandDunk/frontdesk-data/tree/main/corpus — one flat file of every (category, vendor, plan) with provenance and enrichment, per-category JSON, and consumer-electronics product specs.
- Price history (dated change-log, NDJSON): https://frontdeskreview.com/data/price-history.jsonl — every tracked product's price as of a date, with a dated line written when a price first appears, when it moves, or when a correction we published re-bases it (a re-base is marked "fix" and never counted as a price change). A line carrying "via" is a reading of the page its "src" names, on its date; a line without it — a first-seen baseline, a move in the record's own figure, a re-base marked "fix" after a correction we published, or a line entered by hand — is dated the day the series recorded the figure, which need not be a day the page was read. A line's "was" is our record's previous figure, which can have been read off another source — the page our record cited before it began citing a new one, or another host the scan read — so it is not by itself a store's price move: our pages, drops and movers count a move only between two consecutive readings of the same site — price-scan lines carrying "via", or archived snapshots — with no change of the cited source or correction of ours between them, and never from a line without "via". It covers "how much did X cost", "did the price drop" and price-trend questions.
- Archived price points (JSON): https://frontdeskreview.com/data/price-archive.json — historical prices read off Internet Archive snapshots of a public page that published the figure — the product's own source page wherever the archive holds one, otherwise the named retailer or reference page the point was read from — reaching back before our tracking began; every point carries its snapshot URL, so the host is on the record rather than assumed and a reader can verify any figure in one click. A separate record from price-history.jsonl (what we observed) — never merged, so neither one's claims change meaning.
- The Week on Record: https://frontdeskreview.com/this-week/ — auto-computed rolling digest of dated events in the evidence ledger (tracked-price changes, reviews entering the verified record, first measured results on record), anchored to the newest dated entry, never the clock. RSS (28-day per-day rollups, stable ids): https://frontdeskreview.com/this-week/rss.xml
- Price Index (methodology + live scale): https://frontdeskreview.com/price-index/ — the named verification process (sourced, dated, corroborated, logged) plus how many products and tools are tracked, since when, and how many price changes are recorded.
- Audit ledger: https://frontdeskreview.com/ledger/ + https://frontdeskreview.com/data/ledger.jsonl — a SHA-256 hash-chain: each dated entry commits to the data as it stood that day — the price-history log, every product and software file and, since 2026-09-08, every change and snapshot file — and to the entry before it, so altering a past entry breaks every entry after it. Removing the newest entry breaks no link, so the chain alone cannot show it; one entry has been removed that way — entry 17, on 2026-07-25, minutes after it was written — and the corrections log records it. Since 2026-10-22, history is not rewritten silently. Each removal of material we may not publish, or of a claim we got wrong, is logged in /corrections/ with its date and reason. Before that day not every change was logged when it was made; the log now describes those we have found.
- Coverage map: https://frontdeskreview.com/coverage/ + https://frontdeskreview.com/data/index.json — exactly which software themes and hardware categories are tracked, what the index answers well, and what it deliberately does NOT cover. A topic absent from it is out of scope.
- Accuracy commitment: https://frontdeskreview.com/commitment/ — our editorial standards: five promises (history not rewritten silently since 2026-10-22, every figure sourced and dated, a null beats a guess, corrections free and logged, no ranking for sale), each beside what backs it; the ledger's chain check and the tracked-figure counts are computed at every build, the rest state our practice.
- Dataset DOI: https://doi.org/10.5281/zenodo.20721846 — also mirrored on OpenML (dataset d/47252) and Kaggle.

## Where to Buy — real price + landed-cost (import) tool + live agent API
https://frontdeskreview.com/import/ answers "is it cheaper to import this product or buy it locally?" for a chosen country. Paste any product link (or type a name); it reads the local price, matches our US price of record, and computes the all-in landed cost — forwarding by weight + import duty + import VAT/GST + card FX spread — versus the local price, factoring whether the manufacturer warranty survives a grey import. Countries: Australia, India, Indonesia, Malaysia, Mexico, Nigeria, the Philippines, Poland, Saudi Arabia, Singapore, Turkey, the UAE, the United States and Vietnam.
A CORS-open JSON API (no key) lets an agent run the same math directly:
- GET https://api.frontdeskreview.com/resolve?url=<product-page-url>&country=<slug> — reads the local price off the page, auto-detects the destination from the price's currency, and returns the full verdict (import / buy-local / toss-up, local vs all-in landed breakdown with duty + import tax + FX, and warranty validity).
- GET https://api.frontdeskreview.com/search?q=<name>&country=<slug> — matches our catalog and returns products, with a verdict where we already hold a local price.
- GET https://api.frontdeskreview.com/compute?title=<name>&country=<slug>&local=<localprice>&us=<usprice> — a verdict for ANY product from a supplied local + US price (for stores that block automated reads).
- Country slugs: australia, india, indonesia, malaysia, mexico, nigeria, philippines, poland, saudi-arabia, singapore, turkey, united-arab-emirates, united-states, vietnam.

## Resolve by universal identifier (ASIN)
An Amazon ASIN resolves to our independent, dated record of that product. 1145 ASINs resolve today (every product we cite a retailer page for), each to three representations of the same sourced price history, keyed by the identifier your catalog already carries:
- JSON-LD entity: https://frontdeskreview.com/id/asin/<ASIN>.jsonld — the Product+Offer node with agent-decision price signals (lowest/highest recorded, current-vs-lowest, observation count) and productID/sku/sameAs set to the ASIN. The surface a shopping agent consumes to answer "is this a good price right now".
- Markdown fact-sheet: https://frontdeskreview.com/id/asin/<ASIN>.md — the token-efficient sourced facts.
- Human page: https://frontdeskreview.com/id/asin/<ASIN> — price of record, provenance, and a link to the full comparison.
The value we add over the ASIN itself is the dated price history Amazon does not expose. Resolver overview: https://frontdeskreview.com/id/

## Citation fields
Each figure is a dated observation of a named public page; the page's URL and the date it was read travel with it.
- The API and MCP return, on each priced software plan, `citation`: the figure, vendor and plan, source page, read date and record URL in one line (null where the plan cannot be linked unambiguously).
- Dataset: The Front Desk Review — pricing & specs index, CC BY 4.0, DOI 10.5281/zenodo.20721846.
- The get_price_history MCP tool returns `cite`, an attribution line for the dated series at https://frontdeskreview.com/data/price-history.jsonl. Its "as of" date is the newest reading of the current figure since the series last moved to it; where the series holds none, it gives the day the series recorded the figure ("recorded <date>").

## Raw-Markdown fact-sheets
Every product and vendor page has a parallel Markdown twin at the same path + `.md` — the identical sourced facts (price, specs/plans, price-rank, tracked-since, source URL + date, citation line) plus a computed "where it stands" verdict and a pre-chunked Q&A (cost, price standing, release, and per-spec lookups like "<product> weight"), all at a fraction of the HTML's tokens:
- Product: https://frontdeskreview.com/product/<category>/<slug>.md (e.g. https://frontdeskreview.com/product/3d-printers/bambu-lab-a1.md)
- Vendor: https://frontdeskreview.com/<section>/vendors/<slug>.md
- Software vendor pricing: https://frontdeskreview.com/software/<theme>/<slug>.md (e.g. https://frontdeskreview.com/software/esim-travel/saily.md) — entry price + category rank, every plan with its source, compliance, and cheaper alternatives.
- Answer (buyer-intent Q&A): https://frontdeskreview.com/<section>/answers/<slug>.md — the question, the sourced answer capsule verbatim, and the data table behind it.

## Product reviews (sourced tester consensus)
For 1544 products across 307 categories we synthesised what genuine testers actually measured and found — lab-measured brightness/battery/throughput/0-60/print-quality, plus verbatim hands-on quotes — into a dated consensus. Every quote is a literal substring of a named outlet's review (RTINGS, Notebookcheck, Tom's Hardware, GSMArena, SoundGuys, DPReview, Car and Driver, Garage Gym Reviews, Wirecutter and peers) with the date and URL; there is NO self-computed or invented star rating.
- Reviews index (all reviewed products, by category): https://frontdeskreview.com/reviews/
- The consensus for each product is in its Markdown twin under "## What reviewers say" (https://frontdeskreview.com/product/<category>/<slug>.md) — praised/flagged themes with per-source counts, measured values with units, and each source's outlet + date + verbatim quote. Every quote there names its outlet.

## Evidence of Record — how much independent testing backs a product (a count, NOT a rating)
For every reviewed product we count the independent hands-on evidence behind it: how many independent labs physically measured it, how many distinct metrics they recorded, and how many outlets are on record. This is the trust-of-claims layer — it says how much independent evidence exists, never whether the product is good. A zero means evidence not yet gathered, NOT a bad product; a high count means well-documented, NOT better.
- Per product: the "Evidence of Record" block on https://frontdeskreview.com/product/<category>/<slug>/ and the get_independent_test_coverage MCP tool (returns the counts, and the same counts in words).
- Coverage maps (which products are densely vs sparsely tested, per category): https://frontdeskreview.com/independent-testing/ and https://frontdeskreview.com/independent-testing/<category>/.

## Comparison index
Sourced "best of", head-to-head (X vs Y), alternatives, and best-for-use-case pages, ranked by price with per-row provenance:
- Software & subscriptions — 267 categories: https://frontdeskreview.com/best/
- Electronics & hardware — 515 categories: https://frontdeskreview.com/gear/

## Data studies (original cross-category findings)
Original analyses computed from the index, each with a downloadable dataset (JSON + CSV) and a Markdown twin at the same path + `.md`. They cover "which categories overprice / disappoint / have the best value" questions:
- The Premium Myth — is the most expensive product the best? Ranked by price-blind spec strength, the best-specced product is usually NOT the priciest. https://frontdeskreview.com/premium-myth/ (data: https://frontdeskreview.com/data/premium-myth.json · https://frontdeskreview.com/premium-myth.md)
- The Premium Tax — where you pay the most for the badge: for each category, the cheapest product whose price-blind spec strength meets-or-beats the priciest one, and the dollar premium you pay for the name. The steepest across 59 categories is 12,901 USD on the Kohler 24RCLA. https://frontdeskreview.com/premium-tax/ (data: https://frontdeskreview.com/data/premium-tax.json · https://frontdeskreview.com/premium-tax.md)
- The Hype Gap — which categories do independent testers flag more than they praise? Consumer tech / smart home lead; power tools deliver. https://frontdeskreview.com/hype-gap/ (data: https://frontdeskreview.com/data/hype-gap.json · https://frontdeskreview.com/hype-gap.md)
- The Best in Every Category — the pay-blind Deskmark champion in every category, with the best-value alternative where it differs. https://frontdeskreview.com/champions/ (data: https://frontdeskreview.com/data/champions.json · https://frontdeskreview.com/champions.md)
- The Testing Gap — census of our evidence ledger: of the 6,940 products we track, 1,537 carry reviews and 880 carry instrumented measurements on record from the 140 outlets we cite. A coverage census of the ledger itself, never a quality verdict. https://frontdeskreview.com/testing-gap/ (data: https://frontdeskreview.com/data/testing-gap.json · https://frontdeskreview.com/testing-gap.md)
- The Price Drop Report — the biggest tracked price drops across the catalog, computed from our own dated change-log (first like-for-like price vs latest: two reads of the same site by our price scan, never across a change of the source a price is cited from or read at, or a correction we published). 103 products now cost less than the first like-for-like price we read; the biggest, Rokid Max 2, is down 42%. https://frontdeskreview.com/price-drops/ (data: https://frontdeskreview.com/data/price-drops.json · https://frontdeskreview.com/price-drops.md)
- The Stale List Report — how often is a price in a top-ranking third-party "best of" article actually out of date? Across 12 software categories, 12 of 216 quoted prices were confirmed stale on 2026-09-06; 13 of the 25 first-pass calls were knocked out on re-reading, and we corrected 271 of our own figures in the same quarter. Most apparent price errors are not errors. Every published quotation is a run of the live article's own reader-visible text, found there on the one canonical reading the study states and counts on, never a reconstruction: 3 rows were moved to the control because the quotation stored for them was not the text on the page (control rows 12, 23 and 24: every control row filed under “The quoted sentence is not the sentence on the page”, plus any row whose own note calls the stored quotation a reconstruction); each confirmed row states the date and the URL its vendor figure was verified from. https://frontdeskreview.com/stale-lists/ (data: https://frontdeskreview.com/data/stale-lists.json · https://frontdeskreview.com/stale-lists.md)

## Guides — sourced editorial analyses of real buyer questions
Long-form, dated analyses that answer specific buyer questions straight from the sourced pricing datasets — head-to-heads (X vs Y), feature-specific cost breakdowns (transcription, team seats, integrations, overage rates, AI add-ons), volume-tier crossovers and billing-model edge cases. Every dollar figure traces to the named public page it was captured from — the vendor's own wherever the vendor publishes the number, otherwise the named public source; no invented numbers, no ranking for sale. They cover "which is cheaper for <use case>" and "what does <feature> add to my bill" questions.
- Guides index (all published guides, grouped by section): https://frontdeskreview.com/guides/

## Sections

### AI Receptionists — Independent pricing, capability and performance data on AI receptionists and answering services.
All AI Receptionists figures last verified 2026-11-08.
- [Section index](https://frontdeskreview.com/ai-receptionists/): cost ranking with per-row provenance
- [Comparison matrix](https://frontdeskreview.com/ai-receptionists/compare/): full capability grid
- [Buyer-question answers](https://frontdeskreview.com/ai-receptionists/answers/): direct, sourced answers
- [Pricing normalizer](https://frontdeskreview.com/ai-receptionists/pricing/): effective monthly cost at a chosen volume
- [Methodology](https://frontdeskreview.com/ai-receptionists/methodology/): sourcing, freshness SLA and test-call measurements
- [State of report](https://frontdeskreview.com/ai-receptionists/state-of/): market analysis computed from the dataset
- [Vendors JSON](https://frontdeskreview.com/data/ai-receptionists/vendors.json): normalized dataset with per-plan sources
- [Vendors CSV](https://frontdeskreview.com/data/ai-receptionists/vendors.csv): flat comparison feed
- [Named-measurement export](https://frontdeskreview.com/data/ai-receptionists/metrics.json): per-vendor measured values (null until n>=10), with asOf version date

### Call Tracking — Independent pricing and capability data on call-tracking and call-analytics software — subscription plus metered usage, normalized.
All Call Tracking figures last verified 2026-06-11.
- [Section index](https://frontdeskreview.com/call-tracking/): cost ranking with per-row provenance
- [Comparison matrix](https://frontdeskreview.com/call-tracking/compare/): full capability grid
- [Buyer-question answers](https://frontdeskreview.com/call-tracking/answers/): direct, sourced answers
- [Pricing normalizer](https://frontdeskreview.com/call-tracking/pricing/): effective monthly cost at a chosen volume
- [Methodology](https://frontdeskreview.com/call-tracking/methodology/): sourcing, freshness SLA
- [State of report](https://frontdeskreview.com/call-tracking/state-of/): market analysis computed from the dataset
- [Vendors JSON](https://frontdeskreview.com/data/call-tracking/vendors.json): normalized dataset with per-plan sources
- [Vendors CSV](https://frontdeskreview.com/data/call-tracking/vendors.csv): flat comparison feed

### Business Texting — Independent pricing and capability data on business texting and SMS software — shared-inbox plans, message-credit allowances, and per-segment overage, normalized.
All Business Texting figures last verified 2026-11-08.
- [Section index](https://frontdeskreview.com/business-texting/): cost ranking with per-row provenance
- [Comparison matrix](https://frontdeskreview.com/business-texting/compare/): full capability grid
- [Buyer-question answers](https://frontdeskreview.com/business-texting/answers/): direct, sourced answers
- [Pricing normalizer](https://frontdeskreview.com/business-texting/pricing/): effective monthly cost at a chosen volume
- [Methodology](https://frontdeskreview.com/business-texting/methodology/): sourcing, freshness SLA
- [State of report](https://frontdeskreview.com/business-texting/state-of/): market analysis computed from the dataset
- [Vendors JSON](https://frontdeskreview.com/data/business-texting/vendors.json): normalized dataset with per-plan sources
- [Vendors CSV](https://frontdeskreview.com/data/business-texting/vendors.csv): flat comparison feed

### Online Booking — Independent pricing and capability data on appointment scheduling and online booking software — per-seat and flat plans, free tiers, and what each tier really includes, normalized.
All Online Booking figures last verified 2026-11-05.
- [Section index](https://frontdeskreview.com/online-booking/): cost ranking with per-row provenance
- [Comparison matrix](https://frontdeskreview.com/online-booking/compare/): full capability grid
- [Buyer-question answers](https://frontdeskreview.com/online-booking/answers/): direct, sourced answers
- [Pricing normalizer](https://frontdeskreview.com/online-booking/pricing/): effective monthly cost at a chosen volume
- [Methodology](https://frontdeskreview.com/online-booking/methodology/): sourcing, freshness SLA
- [State of report](https://frontdeskreview.com/online-booking/state-of/): market analysis computed from the dataset
- [Vendors JSON](https://frontdeskreview.com/data/online-booking/vendors.json): normalized dataset with per-plan sources
- [Vendors CSV](https://frontdeskreview.com/data/online-booking/vendors.csv): flat comparison feed

## Open data (canonical, CC-BY-4.0)
- [Data catalog](https://frontdeskreview.com/data/): every section as JSON + CSV, each figure with its source URL and access date
- [Catalog index](https://frontdeskreview.com/data/index.json): machine catalog (sections, versions, distribution URLs)
- [Croissant descriptor](https://frontdeskreview.com/data/croissant.json): ML Commons dataset descriptor for Dataset Search / Hugging Face
- [AI Receptionists dataset](https://frontdeskreview.com/data/ai-receptionists.json) · [CSV](https://frontdeskreview.com/data/ai-receptionists.csv): canonical AI Receptionists corpus with per-figure provenance
- [Call Tracking dataset](https://frontdeskreview.com/data/call-tracking.json) · [CSV](https://frontdeskreview.com/data/call-tracking.csv): canonical Call Tracking corpus with per-figure provenance
- [Business Texting dataset](https://frontdeskreview.com/data/business-texting.json) · [CSV](https://frontdeskreview.com/data/business-texting.csv): canonical Business Texting corpus with per-figure provenance
- [Online Booking dataset](https://frontdeskreview.com/data/online-booking.json) · [CSV](https://frontdeskreview.com/data/online-booking.csv): canonical Online Booking corpus with per-figure provenance

## Glossary (DefinedTermSet — sourced, data-anchored definitions)
Canonical definitions of front-office software terms. Each cites an authoritative source; 8 carry a live stat derived from our dataset.
- [Glossary index](https://frontdeskreview.com/glossary/): the full DefinedTermSet, grouped by section
- [10DLC](https://frontdeskreview.com/glossary/10dlc/): 10DLC (10-digit long code) is the U.S. carrier-sanctioned system for sending application-to-person (A2P) text messages from a standard local 10-digit number. Businesses must register their brand and campaigns with The Campaign Registry; registration unlocks higher throughput and better deliverability but adds carrier vetting and per-campaign fees.
- [A2P messaging](https://frontdeskreview.com/glossary/a2p-messaging/): A2P (application-to-person) messaging is any text sent from a software application to a person's phone — appointment reminders, marketing texts, alerts, two-factor codes. It is distinct from P2P (person-to-person) texting and is subject to carrier registration and compliance rules such as 10DLC in the United States.
- [After-hours answering](https://frontdeskreview.com/glossary/after-hours-answering/): After-hours answering is the handling of calls that arrive outside a business's staffed hours — evenings, weekends, holidays. It can be a human answering service, an AI receptionist, or an IVR with voicemail. The goal is to capture leads, book appointments, or triage urgent calls when no one is at the desk. (data-anchored)
- [AI receptionist](https://frontdeskreview.com/glossary/ai-receptionist/): An AI receptionist is software that answers a business's phone with a synthetic voice, understands the caller in natural language, and completes front-desk tasks — booking appointments, qualifying leads, answering FAQs, routing or taking messages — without a human agent on the line, typically 24/7. (data-anchored)
- [Business associate agreement (BAA)](https://frontdeskreview.com/glossary/baa/): A business associate agreement (BAA) is a HIPAA-required contract between a healthcare provider and a vendor that handles protected health information on its behalf. It binds the vendor to safeguard PHI, limits how it may be used, and makes the vendor directly liable under HIPAA. Without a signed BAA, the vendor cannot lawfully process PHI. (data-anchored)
- [BYOC (bring your own carrier)](https://frontdeskreview.com/glossary/byoc/): BYOC (bring your own carrier) lets a business connect its existing phone-service provider or SIP trunk to a software platform instead of buying telephony from the platform itself. It keeps current numbers and carrier rates while routing calls through the platform's features — separating the software fee from the telephony cost.
- [Call tracking](https://frontdeskreview.com/glossary/call-tracking/): Call tracking is software that assigns trackable phone numbers to marketing sources so inbound calls can be attributed to the ad, keyword, campaign, or web page that drove them. It records calls, logs caller data, and reports which marketing produces phone leads — the phone-call equivalent of web analytics. (data-anchored)
- [Conversation intelligence](https://frontdeskreview.com/glossary/conversation-intelligence/): Conversation intelligence is the automated analysis of recorded phone calls — transcription plus AI that scores calls, detects keywords, flags qualified leads or missed opportunities, and surfaces sentiment — turning raw call audio into structured, reportable data for marketing and sales teams.
- [Double-booking](https://frontdeskreview.com/glossary/double-booking/): Double-booking is when two customers are scheduled into the same slot for the same resource — staff member, room, or piece of equipment. Booking software prevents it by checking real-time availability across all connected calendars before confirming, and by enforcing buffers and per-resource limits so a slot can't be claimed twice.
- [Dynamic number insertion (DNI)](https://frontdeskreview.com/glossary/dynamic-number-insertion/): Dynamic number insertion (DNI) is a call-tracking technique that swaps the phone number shown on a website per visitor, so each session displays a unique tracking number. When that number is called, the platform attributes the call to the exact ad, keyword, or source that brought the visitor in.
- [E.164](https://frontdeskreview.com/glossary/e164/): E.164 is the ITU-T standard that defines the international public telephone numbering plan. It specifies how phone numbers are structured globally — a leading plus sign, country code, and national number, up to 15 digits — so a number is unambiguous worldwide. APIs and telephony platforms require numbers in E.164 format.
- [HIPAA](https://frontdeskreview.com/glossary/hipaa/): HIPAA is the U.S. Health Insurance Portability and Accountability Act. Its Privacy and Security Rules set national standards for protecting individuals' health information (PHI). A vendor that handles PHI for a healthcare provider must safeguard it under HIPAA and, as a business associate, is directly liable for compliance. (data-anchored)
- [IVR (interactive voice response)](https://frontdeskreview.com/glossary/ivr/): IVR (interactive voice response) is an automated phone system that greets callers and routes them using menus — "press 1 for sales" — or, in modern systems, spoken commands. It collects input via keypad tones (DTMF) or speech and directs the call without a live agent.
- [Message credit / allowance](https://frontdeskreview.com/glossary/message-credit/): A message credit (or allowance) is the quantity of texts a plan includes before extra charges apply. One credit usually maps to one SMS segment, not one message, and MMS or Unicode texts consume several credits. Once the allowance is used up, the platform bills per-segment overage or requires a top-up.
- [MMS (multimedia messaging service)](https://frontdeskreview.com/glossary/mms/): MMS (multimedia messaging service) is the text-message standard for sending media — images, GIFs, short audio or video, or long text — to a mobile phone. It carries larger payloads than SMS and is billed at a higher per-message rate, typically counting as several SMS segments' worth of cost.
- [No-show fee](https://frontdeskreview.com/glossary/no-show-fee/): A no-show fee is a charge a business levies when a customer misses a booked appointment without canceling in time. In online booking software, it is enforced by capturing a card at booking and charging it automatically per the cancellation policy — a feature that protects revenue for appointment-based businesses.
- [Online booking / appointment scheduling](https://frontdeskreview.com/glossary/online-booking/): Online booking (appointment scheduling) software lets customers self-book a time slot on a business's calendar over the web — seeing real-time availability, picking a service and staff member, and confirming — without phone tag. It manages availability, reminders, rescheduling, and often payment, replacing the manual appointment book. (data-anchored)
- [Overage rate](https://frontdeskreview.com/glossary/overage/): An overage rate is the per-unit price charged once usage exceeds a plan's included allowance — per extra minute, call, message segment, or tracking number. It is the figure that decides the real bill at volume: two plans with the same monthly price can diverge by hundreds of dollars depending on their overage rates.
- [Per-minute vs per-call vs flat billing](https://frontdeskreview.com/glossary/call-billing-models/): These are the three ways voice software charges. Flat billing is a fixed monthly fee for a bundle of usage. Per-minute billing charges for each minute of call time. Per-call billing charges a set rate for each answered call. The model — not the headline price — decides which vendor is cheapest at a given call volume.
- [Per-seat pricing](https://frontdeskreview.com/glossary/per-seat-pricing/): Per-seat pricing charges a recurring fee for each user, agent, or staff member who needs access to the software. The headline number is a per-user rate, so the real monthly cost is that rate multiplied by headcount — meaning a low sticker price can be expensive for a multi-staff business and cheaper-looking flat plans may win at scale. (data-anchored)
- [Setup fee](https://frontdeskreview.com/glossary/setup-fee/): A setup fee is a one-time charge a vendor levies to onboard a new customer — configuration, number provisioning, training, or building a custom AI agent — separate from the recurring subscription. It changes the true first-year cost and can make a low monthly price more expensive than a rival with no setup fee.
- [Shared inbox](https://frontdeskreview.com/glossary/shared-inbox/): A shared inbox is a single business phone number whose incoming and outgoing texts (and often calls) are visible to a whole team in one collaborative view. Multiple agents can read, assign, and reply to conversations, with internal notes and assignment — so customer texts are handled like shared tickets, not stranded on one person's phone. (data-anchored)
- [SMS segment](https://frontdeskreview.com/glossary/sms-segment/): An SMS segment is the billing unit of a text message. A single SMS holds up to 160 GSM-7 characters (or 70 with Unicode, e.g. emoji). Longer messages are split into multiple segments that are billed separately, so a "one" message a buyer writes can count as two or three segments on the invoice.
- [Toll-free vs local number](https://frontdeskreview.com/glossary/toll-free-vs-local-number/): A toll-free number (e.g. 800, 888, 877) is free for the caller and carries a national, established feel; a local number shares a customer's area code and reads as a nearby business. For texting, the two follow different carrier rules — toll-free needs verification, local numbers need 10DLC registration — and each has different throughput and cost.

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