Between the dialer report and the closing table sits a conversation nobody audits: the ISA call. Voxjar scores 100% of them against your own standards for first-touch call quality, qualification, script adherence, and appointment quality, so you can see which lead sources, scripts, and callers actually produce listings.
Set up in minutes, no sales call required. Score one of your own lead calls free.
ISA operations are drowning in metrics that measure activity and starved of metrics that measure conversation. Dials per hour, connects, talk time, appointments set: all visible on the wallboard, and your dialer and CRM already report whether the SLA window was hit. What happened once the conversation connected, whether the ISA opened on what the lead actually asked for, actually qualified motivation and timeline or just confirmed a phone number, handled "I already have an agent" the way the script says, or set an appointment the agent can win: invisible, on every one of thousands of calls a week.
That blindness gets expensive in two directions at once. Upstream, you keep buying from lead sources without knowing whether the leads are weak or the calls are weak, so the ROI conversation with the vendor runs on vibes. Downstream, agents lose faith in ISA appointments after a few no-shows and coffee-date meetings, start cherry-picking, and the whole handoff model erodes. Sampling a handful of calls a week settles neither argument, because the calls that would settle it were never reviewed.
Voxjar closes the loop. Every connected call is transcribed and scored against your qualification framework and script, every score shows its reasoning and the transcript behind it, and the pattern-level answers, which source, which script line, which ISA, which shift, fall out of full coverage instead of anecdotes.
These are the criteria high-performing teams tend to start with. Yours will differ by script and market; every line is editable, weightable, replaceable.
| Criterion | Why it's on the card |
|---|---|
| First-touch call opens on the lead's request | Your dialer reports whether the SLA was hit; Voxjar scores whether the opening acknowledged what the lead actually asked for |
| Motivation and timeline qualified (LPMAMA-style) | An appointment without motivation is a coffee meeting, not a listing |
| Objections handled per script | "Just looking" and "already have an agent" have trained answers; check they got used |
| Appointment set for the agent, on the calendar | A firm time with expectations set is the whole job; "I'll call you back" is not |
| Disposition-ready summary of what the call actually was | Voxjar scores the call itself, giving teams the record to audit CRM dispositions against |
| Nurture cadence followed on not-ready leads | Most paid leads convert later; the follow-up plan is where later happens |
Try it against a real call from your dialer; the free evaluation takes minutes.
Every connect is checked against the SLA and the script, across every dialer and lead source. Skipped qualifying questions and off-script improvisation stop hiding inside the volume.
Score appointment quality before the handoff, and let a weak set trigger a review task through universal webhooks while there's still time to firm it up. Agents get handoffs they trust; ISAs get credit for the good ones.
With every call scored, you can finally separate bad leads from bad calls by source. Renegotiate, reallocate, or cut vendors based on what the conversations show, with glass-box reasoning behind every score you cite.
Calls are scored in batches right after they end, so coaching and alerts land the same day. Works for in-house ISA pods, virtual ISAs, and outsourced calling teams alike.
"Voxjar is the best form of AI we can get now. It's made our service delivery faster, our operation more efficient, and our clients happier."
Mohamed Hesham
CTO, AK Callers
AK Callers validates real estate leads against the distinct guidelines of more than 100 clients. Turning each client's rules into a Voxjar scorecard accelerated their lead delivery by up to 30% and saved them from hiring two additional full-time QA staff.
Read the full AK Callers storyYes. Whatever framework your team runs, LPMAMA or your own variant, each element becomes a criterion on the scorecard: location, price, motivation, agent status, mortgage position, timeline. Voxjar checks every dial that connects against the full framework and shows which questions your ISAs consistently skip, with the transcript to prove it.
That's the point of automating it. The same scorecard runs against every recording regardless of which dialer produced it, so a Zillow lead worked from one platform is judged by the same standard as a PPC lead worked from another. Recordings come in through integrations, universal webhooks, or an open API, so mixed stacks aren't a problem.
You define what a real appointment sounds like: motivation and timeline confirmed, both parties on the calendar, expectations set for the agent conversation. Voxjar scores each set appointment against that definition, so you can separate solid handoffs from calendar filler before your agents drive across town for them.
Voxjar scores what happened on the call itself: whether the ISA captured the details your dispositions depend on and stated the correct outcome. Through universal webhooks, a flagged mismatch or a hot lead marked cold can push a task or alert into your CRM right after the call is scored, so bad data gets corrected while the lead is still warm.
Pricing is published and based on the volume of calls you analyze, starting at $99/month with a free tier and no setup fee. Short no-answer dials aren't where the spend goes; connected conversations are. Every plan includes unlimited users, so ISAs, team leads, and the agents receiving the appointments can all see scores without per-seat cost.
Same day. Voxjar is self-serve: create an account, connect your recordings, build or adapt an ISA scorecard, and scored calls start appearing in minutes. You can also run one of your own lead calls through the free evaluation before creating an account, and choose the AI model, GPT, Claude, or Gemini, that fits your budget.
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