Contact center, AI, and compliance terms clearly defined.

The percentage of inbound callers who hang up before reaching an agent. Distinct from the outbound abandonment rate regulated under TCPA.

Why it matters: Rising abandon rate is usually the first visible symptom of a staffing or routing problem.

The percentage of outbound dial attempts where the system connects to a live person but fails to put them through to an agent within two seconds. Regulated under TCPA in the US: predictive dialers must generally stay under 3% abandonment on a rolling 30-day basis to qualify for Safe Harbor.

How closely agents follow their planned schedule — being in the right state (available, on break, in training) at the planned time, measured against interaction state rather than just presence.

Why it matters: Low adherence quietly breaks an otherwise correct staffing plan.

AI that listens on a live call, transcribes in real time, classifies intent, pulls relevant knowledge, and suggests next actions or responses. Good agent assist drafts the wrap-up note before the call ends and keeps QA in the loop across 100% of interactions.

AI that completes multi-step tasks on its own — collecting information, calling systems, and finishing a workflow — rather than only answering a single question.

Why it matters: It extends self-service beyond FAQs into complete tasks like scheduling, payments, and verification.

Automatic application of a quality-assurance rubric to every interaction, scoring calls and chats against the same criteria a human reviewer would use.

Why it matters: It moves QA coverage from a small sample to 100% of interactions, so coaching starts from the full picture.

A conversational AI that answers phone calls, understands what the caller says in natural language, and resolves or routes the request without a menu tree.

Why it matters: It replaces legacy IVR menus with conversations, raising self-service resolution on routine calls.

Call summaries, disposition codes, and next-step recommendations drafted automatically by AI before the interaction ends, for the agent to review and sign.

Why it matters: It cuts after-call work and improves note quality at the same time.

The platform layer that routes inbound contacts — voice, chat, SMS, email, social — to the right agent based on skills, priority, and availability. Modern ACDs handle every channel on one data model rather than one ACD per channel.

Talk time plus hold time plus wrap-up, averaged across a set of calls. The default efficiency metric for voice contact centers. Shorter isn't always better — AHT cuts that come from skipping disposition or rushing the customer tend to show up later as FCR or CSAT drops.

The average time callers wait before an agent answers, usually measured per queue and per interval.

Why it matters: It is the customer-facing half of the service-level equation supervisors manage in real time.

A HIPAA-required contract between a covered entity (like a healthcare provider) and a vendor that handles Protected Health Information on its behalf. SingleComm signs BAAs on healthcare plans, which is a prerequisite for any contact center handling patient communication.

A company that runs contact center operations on behalf of other companies. BPOs typically handle multiple clients with distinct scripts, compliance profiles, and reporting requirements — which is why multi-tenant architecture matters so much on the platform side.

Cloud-delivered contact center software, billed per seat or per minute, maintained by the vendor rather than on customer-owned hardware. Replaced the earlier generation of on-prem contact center suites that required circuit-switched telephony and in-house operations.

AI that understands and responds to natural language across voice and text, resolving requests based on what the customer actually said instead of which menu option they pressed.

Why it matters: It is the technology behind AI voice agents, chat self-service, and intent-based routing.

Total contact center cost divided by the number of handled interactions, the standard unit-economics measure for support operations.

Why it matters: Self-service resolution and lower handle time both show up here first.

A survey metric asking how easy it was for the customer to get their issue resolved, typically on a 5- or 7-point scale.

Why it matters: High effort predicts churn better than a single bad interaction does.

A post-interaction survey score measuring how satisfied the customer was with the specific transaction. Usually a 1–5 scale reduced to the percentage of 4s and 5s. Distinct from NPS, which measures long-term loyalty rather than transactional satisfaction.

The outcome code an agent applies at the end of an interaction (sale, no-answer, escalated, customer-resolved, etc.). Dispositions drive reporting, campaign pacing, and follow-up routing, so the list matters more than it looks. Good platforms let you A/B test disposition taxonomies like any other script.

The federal DNC registry (and state equivalents) of phone numbers that cannot be called for marketing purposes under TCPA. Outbound contact centers must scrub their call lists against DNC before every campaign launch, not just at list import.

The tones your phone makes when you press keys on the keypad. In PCI-compliant payment capture, the platform masks DTMF digits from the agent and recording so the agent never sees or hears the card number — keeping the agent desktop out of PCI scope.

The percentage of customer issues resolved in a single interaction, without requiring a callback, transfer, or follow-up. Usually the best single predictor of both CSAT and cost per contact — a 10-point FCR improvement tends to pay for itself in reduced repeat-call volume.

The initial report a policyholder makes to file an insurance claim — the starting point for every claims workflow. Structured FNOL intake at the contact center determines how fast the claim moves through adjudication and how often the adjuster has to re-ask basic facts.

How closely predicted contact volume matched actual volume, measured per interval. Modern forecasting reports a likely demand range rather than one point estimate.

Why it matters: Schedules are only as good as the forecast they were built from.

When an AI model states something plausible-sounding but false. In contact centers, the main defense is grounding answers in a verified knowledge base with citations rather than the model's memory.

Why it matters: It is the core reason KB-grounded retrieval matters when evaluating AI vendors.

The US law governing the privacy and security of Protected Health Information. Healthcare contact centers must handle PHI through systems that meet HIPAA's administrative, physical, and technical safeguards — and must have a BAA with every vendor that touches the data.

A certification framework specific to healthcare data security. HITRUST r2 certification signals that a vendor's controls have been independently audited against a healthcare-specific threat model — a stricter bar than SOC 2 alone for BAAs that involve significant PHI volume.

The moment a self-service conversation transfers to a live agent, carrying the transcript, detected intent, and any information already collected.

Why it matters: A handoff that loses context forces the customer to start over — the fastest way to undo self-service goodwill.

Identifying what a customer is trying to accomplish from their own words — billing question, appointment change, cancellation — so the platform can resolve or route accordingly.

Why it matters: It is what lets routing react to the customer's words instead of a menu tree.

The automated voice system that answers an inbound call and either resolves it or routes it to the right agent. Legacy IVR forced callers through a menu tree ("Press 1 for billing"). Modern conversational IVR understands plain-language intent and routes on what the caller actually said.

Adjusting staffing during the day as actual volume diverges from forecast — moving breaks, reassigning agents between channels, extending or releasing shifts.

Why it matters: The forecast is never exactly right; intraday management is how teams stay inside service levels anyway.

Pulling answers from an organization's own documented policies and articles — with citations to the source — instead of relying on an AI model's general training.

Why it matters: Grounded retrieval is the difference between an AI that quotes your policy and one that improvises it.

A loyalty metric built from one question: "How likely are you to recommend us?" on a 0–10 scale. The score is the percentage of promoters (9–10) minus the percentage of detractors (0–6). Measures long-term relationship rather than transactional satisfaction — which is why it tracks retention better than CSAT does.

The percentage of paid agent time spent handling interactions or doing after-call work, as opposed to waiting for the next contact.

Why it matters: Too low wastes payroll; too high burns agents out — staffing plans balance the two.

A contact center stack where voice, chat, SMS, email, and social run on one data model rather than as separate products stitched together. The test: when a customer messages on chat and then calls later, the agent sees the earlier thread. If not, it's multi-channel, not omnichannel.

The security standard that governs how cardholder data is handled. Contact centers that take payments must either become PCI-compliant themselves or — far more common — use DTMF masking and tokenization to keep card data out of the agent desktop and the recording, reducing their PCI scope to near-zero.

An outbound dialing mode where the system dials ahead of agent availability, predicting when agents will be free based on average call length. Maximizes agent talk time but must stay within TCPA's abandonment cap — too aggressive and you blow past 3% and lose Safe Harbor.

An outbound dialing mode where the agent reviews the customer record before the system dials, and can choose to dial, skip, or reschedule. Lower throughput than predictive, but used for complex sales or high-stakes collections where the agent needs context first.

An outbound dialing mode that dials one record per available agent, one at a time. No abandonment risk (the agent is already on the line when it rings), lower throughput than predictive. Often the mode of choice for TCPA-sensitive campaigns or healthcare outreach.

Any individually-identifiable health information covered by HIPAA — name plus diagnosis, name plus prescription, member ID plus visit date. Contact centers handling PHI must redact it from recordings and transcripts or keep it out of scope entirely.

The scoring criteria a quality team applies to interactions — greeting, verification, accuracy, compliance language, resolution, wrap-up.

Why it matters: With AI scoring, the rubric can apply to every interaction instead of a 3% sample.

The number of contacts currently waiting in a queue, the most immediate real-time signal of whether staffing matches demand.

Why it matters: Supervisors watch it by interval to fix problems before wait times and abandons climb.

An AI architecture that first retrieves relevant documents from a trusted source, then generates an answer based on what it found — rather than answering from model memory alone.

Why it matters: It is how contact center AI stays grounded in current policy instead of hallucinating outdated answers.

The TCPA provision that protects outbound dialers from abandonment penalties, provided they meet specific conditions: under 3% abandonment on a rolling basis, abandoned calls played a recorded message identifying the caller, and records retained for at least 24 months. Most compliant predictive-dialing operations aim for Safe Harbor as the baseline.

AI assessment of how a customer feels during an interaction — positive, neutral, frustrated — derived from their words and phrasing in real time.

Why it matters: It feeds supervisor alerts, escalation triggers, and voice-of-customer reporting.

The percentage of contacts answered within a target time, such as 80% of calls within 20 seconds. The standard contract metric between operations and the business.

Why it matters: Most staffing, routing, and intraday decisions exist to protect this number.

SingleComm's DTMF-masking payment capture pattern. The customer enters card digits on their keypad; the platform tokenizes and processes, and the agent never sees or hears the numbers. Keeps the agent desktop — and the call recording — out of PCI scope.

SingleComm's unified agent desktop: one browser tab handling voice, chat, SMS, email, and social, with screen-pop from the CRM and AI-drafted disposition notes. Named for the operational principle — agents should work from one pane of glass, not tab-hop between four vendors.

An ACD strategy that routes each contact to the agent best equipped to handle it — language, product knowledge, certification, tenure. Stronger than FIFO or round-robin at improving FCR, but only as good as the skill data actually assigned to agents.

An audit report on a vendor's controls across security, availability, processing integrity, confidentiality, and privacy. SOC 2 Type II covers effectiveness over a period of time (typically 6–12 months) rather than a point-in-time snapshot. The standard compliance bar for B2B SaaS vendors handling customer data.

A business that answers calls on behalf of other businesses — doctors' offices, law firms, plumbers, property managers. TAS operators run dozens of clients on one shift, each with distinct scripts and dispatch rules. Multi-tenant scripting and rules-based dispatch aren't features for TAS; they're the product.

The US law governing outbound telemarketing — consent requirements, call-time windows, DNC scrubbing, abandonment caps, autodialer restrictions. TCPA class actions commonly land in the tens of millions of dollars, which is why outbound platforms treat compliance as the baseline rather than a feature.

Why it matters: It affects consent, DNC scrubbing, call-time windows, and abandonment limits for every outbound campaign.

A transfer where the originating agent stays on the line long enough to hand off context to the receiving agent before dropping. The opposite of "cold" transfer where the customer is dumped into a new queue and asked to start over. Good platforms attach transcript, intent, and customer profile automatically so warm transfer feels seamless.

For example: A patient calls about billing, but the issue needs insurance verification. The first agent introduces the call to the insurance specialist and passes the customer context before dropping.

The browser-native real-time communications protocol that lets a contact center run voice without a softphone or separate voice network. Agents take calls in the same browser tab as everything else. SingleComm has been a WebRTC pioneer since 2012, with 50M+ interactions in production.

The contact center discipline and toolset covering forecasting, scheduling, intraday adjustments, adherence, and coaching. Historically split off as a separate vendor; modern CCaaS platforms bundle it back in so forecasts, schedules, and adherence signals share the same data model as the interactions they're managing.