Dashboards show the value Matador delivers. The AI Performance Scorecard shows the value your store is leaving on the table — it reads every conversation, every user, every intent, then tells you in plain language what's leaking and what to fix.
A GM can't read 5,000 conversations to find out why out-the-door pricing deals die. The scorecard reads all of them — every month.
"Your team has sent zero videos." "OTD conversations convert at 7%." The uncomfortable truths a dashboard is too polite to surface, in plain language.
Every scorecard ends with a concrete action plan — the performance manager's next meeting agenda, pre-written and prioritized by what it's worth.
The numbers below come from an actual 30-day scorecard — a franchise store on the full Matador suite, names anonymized. Every store gets the same spine: what happened, what's leaking, and exactly what to do about it.
AI handled 54% of all replies at a consistent 15-minute median while the team averaged 3 minutes — 457 AI-influenced wins across 701 active conversations, with 6 appointments booked and a 2% conv-to-appt rate leaving clear room to grow.
| Who replied | Replies | Median | 90th pct |
|---|---|---|---|
| Your team | 125 | 3 min | 7.8 hrs |
| AI Reply | 147 | 15 min | 15 min |
The team is fast when it answers — the 90th percentile shows leads waiting hours. The AI's floor never moves. AI Follow-Up added 429 proactive messages to 195 cold leads, and 38% replied.
| Customer intent | Convos | Booked | Rate |
|---|---|---|---|
| Buying new | 76 | 2 | 2.6% |
| Buying used | 31 | 0 | 0.0% |
| Models & configurations | 11 | 0 | 0.0% |
143 conversations carried a buying signal. The scorecard also caught 4 mandatory AI instructions — price, down payment, credit, trade-in — still sitting blank, and said so.
Completion looks perfect until you read the reply rates: the top rep answered 75% of her hand-offs, three others answered 0%. Seventy customers left waiting — each one tied to a name.
| Sequence | Leads | Reply rate |
|---|---|---|
| Inbound / chat | 21 | 71.4% |
| After hours | 85 | 50.6% |
| Third-party leads | 181 | 36.5% |
| Trade-in | 18 | 11.1% |
The verdict was specific: rewrite the trade-in opener around a concrete appraisal offer, and copy the inbound/chat playbook to the sequences that lag.
| Group | Convos | Appts | Rate |
|---|---|---|---|
| Received a video | 0 | 0 | — |
| No video | 322 | 6 | 1.9% |
Zero videos sent across 322 new conversations. The scorecard flagged it in orange and put "record one 60-second walkaround" in the plan — with a named owner.
No hedging: "this channel is completely idle while sequences work hundreds of leads." One targeted send to the unbooked pool made the next-30-days list.
Every scorecard closes with real conversations where the AI booked the appointment start to finish. This month, all four featured wins were booked autonomously:
No "consider exploring." Six actions from the same scorecard — each with an owner, an effort estimate, and what it's worth.
| # | Action | Owner | Effort | Est. lift |
|---|---|---|---|---|
| 1 | Fill the 4 blank mandatory AI instructions | GM / BDC Manager | 1–2 hrs | +appointments |
| 2 | Launch a walkaround video in the 71%-reply sequence | BDC Rep | 2–3 hrs | +conversion |
| 3 | Coach the three 0% task responders | Sales Manager | 1 hr | +task conversion |
| 4 | Rebuild the 11%-reply trade-in sequence | BDC Manager | 2 hrs | +reply rate |
| 5 | Send one re-engagement broadcast to unbooked leads | BDC Manager | 1–2 hrs | +pipeline |
| 6 | Add a follow-up prompt for buying-used leads | BDC Manager | 1 hr | 0 → booked |
BDC performance metrics tied to real conversations, not gut feel — who's keeping up with the AI, who's leaving deals on the floor, and exactly what to change first.
The rep completing 65% of 78 tasks gets highlighted as the model — "have Vanessa share her approach in a team huddle." The reps at 0% get a conversation with the manager. Handoff and task-completion rates, named per user.
See exactly how long customers wait for your team versus your AI — and what that gap costs in deals. The number that ends the "we're fast enough" debate.
Intent-level recommendations and lead-source coaching — copy the instructions and frequencies that win to the sources that lag. Plus the greatest hits: a curated list of the best AI conversations, proof of what good looks like.
The scorecard doesn’t stop at the store level. Every rep’s follow-through on AI handoffs is measured — because the AI can set the table, but somebody still has to show up.
| Rep | Handoffs answered | Avg response | Tasks closed | Trend |
|---|---|---|---|---|
| Dana R. | 96% | 4 min | 41 of 43 | Improving |
| Alex M. | 88% | 11 min | 33 of 39 | Improving |
| Sam K. | 74% | 19 min | 26 of 38 | Flat |
| Jordan P. | 61% | 38 min | 12 of 35 | Needs coaching |
In one audit, engaged users completed 65% of AI-created tasks — disengaged users completed0%. The gap is coaching, not talent. The leaderboard shows you exactly where to spend the coaching.
On the demo, we'll walk a real scorecard end to end — the leaks, the per-rep accountability, and the "Your Next 30 Days" plan your managers will actually run.