Drive-Thru Analyzer

What was once hidden is now visible

Get a clearer view of the full drive-thru experience, revealing missed revenue, service breakdowns, and coaching opportunities that traditional reporting can miss.

See the moments behind the numbers

Sales, speed of service, and complaints show the score, but not the game. Drive-Thru Analyzer uses AI to listen to real drive-thru interactions, process what is heard, and identify the operational signals inside those conversations: missed upsells, confused guests, skipped confirmations, and the same issue showing up again by store, shift, or daypart. In plain English, it shows operators what is actually happening in the drive-thru without someone standing beside the headset all day with a clipboard.

Read why we built it

Benefits

  • Objective measurement at scale

    Measure performance the same way across shifts and stores. Scoring follows fixed, versioned rules, so trends stay comparable over time instead of depending on who reviewed what.

  • Analyze every customer interaction

    Process your drive-thru conversations at scale, so you’re not relying on mystery shoppers, manual reviews, or small samples.

  • Coaching-ready intelligence

    Surface best-practice and improvement examples with evidence, so teams can coach from proof, not opinions.

Drive-Thru Analyzer dashboard: visits, average score, time to greet, and drive-thru time across the top, then a grade distribution, a performance trend, and an evaluation breakdown by criterion

The metrics you can’t afford to ignore

Revenue
  • Upsell success rate
  • Missed upsell opportunities
Experience
  • Customer sentiment score
  • Error rate
Operations
  • Efficiency score
  • Conversation complexity
Benchmarking
  • Store rankings
  • Percentile performance
  • Comparisons by store, shift, daypart, chain average, and historical period

From conversation to action

  1. See what’s happening

    Real visit information becomes visible, with the moments that matter highlighted.

    A list of drive-thru visits for one store, with time, duration, grade, and status for each
  2. Understand why it matters

    Evaluation details turn the conversation into observable performance signals.

    One visit in detail: an overall rating of “Not met” because the order was closed without a confirmation, next to the transcript and visit stats
  3. Know what to do next

    Detected issues surface the action your team should take.

    A development coaching brief listing strengths and areas for growth, each with evidence from the conversation
  4. Know where to focus

    Store comparisons show where performance is strongest, weakest, and drifting.

    A performance view comparing stores, with evaluation trends by criterion

Features spotlight

  • Store performance dashboard

    Shift, store, and chain views with trends, comparisons, and rankings, plus the number of conversations behind every figure.

  • Conversation examples report

    Filter to find high- and low-scoring examples with highlights, annotations, and context.

  • Export and sharing

    Export data (CSV) and charts (PNG or PDF), and export coaching examples (text or PDF) with annotations.

How scoring works
Deterministic, versioned scoring
Fixed scoring rules run over stored features, so comparisons stay consistent and auditable over time.
Evidence-backed explainability
Pointers to spans of the transcript explain why a feature triggered, without using that evidence as a scoring input.
Metric eligibility
Each conversation is classified first, so order-specific metrics only count the conversations they apply to. The eligible counts are stored alongside the results.

Frequently asked questions

Is Drive-Thru Analyzer real-time?

It’s designed for batch processing, so you can analyze every conversation at scale. Near-real-time workflows can be aligned to your requirements and timeline.

Do you integrate with POS systems?

Drive-Thru Analyzer can work without POS integration by extracting order details from the conversation text. POS connectors are an expansion path when customers want enriched order context.

How do you keep scoring consistent?

Scoring is deterministic and versioned. Changes create explicit new versioned outputs, with no silent overwrites.

What outputs can I share with my teams?

Export dashboard data and charts, and generate coaching-ready example packs (text or PDF) with highlights, annotations, and context.

Stop guessing today

Drive-Thru Analyzer surfaces issues, explains why they happen, and shows where to focus next.

Request a demo