Coaching studio

Aiera scores every human and AI conversation, then turns the gaps into weekly drills for the floor.

8 reps monitored

Team quality score

78+6

Rolling 4 weeks

Calls reviewed

1145

100% coverage, no sampling

Objection win rate

64%+11%

After drill rollout

Ramp time

18 days-9 days

New joiner to target

Rep scorecards

Sorted by quality score

RepCallsScoreTalk ratioObjection winConversionCoach on
Priya Joshi1658942%48%19%Capex
Priya Rao1608640%44%16%Opex per KL
Sanjay Joshi1908648%80%8%Footprint
Arjun Patel708052%58%16%Capex
Sneha Joshi1457556%56%21%Reference sites
Karthik Khan1707262%88%10%Opex per KL
Rohit Gupta807060%54%26%Pollution-board timeline
Imran Nair1656960%84%29%Footprint

Skill matrix

Team average adherence

  • Discovery depth72%
  • Objection handling64%
  • Proof points used58%
  • Next step booked81%
  • Compliance script91%

Lowest adherence is proof-point usage — the drill below targets it directly.

This week's drills

Auto-generated from lost conversations

  • Drill 1: Pricing response

    89 impact

    Conversations mentioning "capex" convert 37% lower unless the agent responds with a proof point in the first 40 seconds.

    Practice set: 212 calls analysed this month

  • Drill 2: Trust response

    78 impact

    Conversations mentioning "opex per kl" convert 18% lower unless the agent responds with a proof point in the first 40 seconds.

    Practice set: 313 calls analysed this month

  • Drill 3: Product fit response

    67 impact

    Conversations mentioning "footprint" convert 23% lower unless the agent responds with a proof point in the first 40 seconds.

    Practice set: 288 calls analysed this month

  • Drill 4: Speed response

    93 impact

    Conversations mentioning "pollution-board timeline" convert 35% lower unless the agent responds with a proof point in the first 40 seconds.

    Practice set: 170 calls analysed this month

Best-in-class moments

Clipped for the playbook

  • Aiera Support · Tender clarification

    Rohit Kulkarni from Gujarat asked about ETP — tender clarification. Agent handled opex per kl and captured requirement details.

    Score 52 · Gujarati

  • Aiera Voice · Opex per KL

    Rahul Gupta from Tamil Nadu asked about ETP — opex per kl. Agent handled opex per kl and captured requirement details.

    Score 54 · English

  • Aiera Support · Opex per KL

    Neha Menon from Maharashtra asked about STP — opex per kl. Agent handled capex and captured requirement details.

    Score 46 · Tamil

  • Aiera Followup · AMC renewal

    Pooja Patel from Tamil Nadu asked about Membrane upgrade — amc renewal. Agent handled reference sites and captured requirement details.

    Score 54 · Gujarati

  • Aiera Voice · Tender clarification

    Rahul Gupta from Tamil Nadu asked about ETP — tender clarification. Agent handled pollution-board timeline and captured requirement details.

    Score 46 · English