Amazon (AMZN)

EarningsTranscriptsUpdated

Every word

41–63 of 63, most settled first · page 2 of 2
Amazon: every word with settled markets, most settled first
WordQ3’24Oct '24Q4’24Feb '25Q1’25May '25Q2’25Jul '25Q3’25Oct '25Q4’25Feb '26Q1’26Apr '26Q2’26last callTrendLast 8ScriptedAll-timeProbability
Grocery delivery1 time: Grocery delivery, Q3’24 Oct '24, counts as said1 time: Grocery delivery, Q4’24 Feb '25, counts as said0 times: Grocery delivery, Q1’25 May '250 times: Grocery delivery, Q2’25 Jul '250 times: Grocery delivery, Q3’25 Oct '250 times: Grocery delivery, Q4’25 Feb '260 times: Grocery delivery, Q1’26 Apr '260 times: Grocery delivery, Q2’26 Jul '26falling2/825%2/825%13/8316%21%n=1+tx from settlement history blended with transcripts
Headcount0 times: Headcount, Q3’24 Oct '240 times: Headcount, Q4’24 Feb '250 times: Headcount, Q1’25 May '250 times: Headcount, Q2’25 Jul '251 time: Headcount, Q3’25 Oct '25, counts as said0 times: Headcount, Q4’25 Feb '260 times: Headcount, Q1’26 Apr '260 times: Headcount, Q2’26 Jul '26steady1/812%0/80%25/8330%24%n=1+tx from settlement history blended with transcripts
Income10+ times8 times: Income 10+ times, Q3’24 Oct '24, below the threshold12 times: Income 10+ times, Q4’24 Feb '25, counts as said11 times: Income 10+ times, Q1’25 May '25, counts as said6 times: Income 10+ times, Q2’25 Jul '25, below the threshold13 times: Income 10+ times, Q3’25 Oct '25, counts as said12 times: Income 10+ times, Q4’25 Feb '26, counts as said7 times: Income 10+ times, Q1’26 Apr '26, below the threshold7 times: Income 10+ times, Q2’26 Jul '26, below the thresholdsteady4/850%3/838%48/8358%34%n=1+tx from settlement history blended with transcripts
Inventory management0 times: Inventory management, Q3’24 Oct '241 time: Inventory management, Q4’24 Feb '25, counts as said0 times: Inventory management, Q1’25 May '250 times: Inventory management, Q2’25 Jul '250 times: Inventory management, Q3’25 Oct '250 times: Inventory management, Q4’25 Feb '260 times: Inventory management, Q1’26 Apr '260 times: Inventory management, Q2’26 Jul '26steady1/812%0/80%6/837%18%n=1+tx from settlement history blended with transcripts
Irannever said0 times: Iran, Q3’24 Oct '240 times: Iran, Q4’24 Feb '250 times: Iran, Q1’25 May '250 times: Iran, Q2’25 Jul '250 times: Iran, Q3’25 Oct '250 times: Iran, Q4’25 Feb '260 times: Iran, Q1’26 Apr '260 times: Iran, Q2’26 Jul '26steady0/80%0/80%0/830%12%n=1+tx from settlement history blended with transcripts
Labor costsnever said0 times: Labor costs, Q3’24 Oct '240 times: Labor costs, Q4’24 Feb '250 times: Labor costs, Q1’25 May '250 times: Labor costs, Q2’25 Jul '250 times: Labor costs, Q3’25 Oct '250 times: Labor costs, Q4’25 Feb '260 times: Labor costs, Q1’26 Apr '260 times: Labor costs, Q2’26 Jul '26steady0/80%0/80%0/830%14%n=1+tx from settlement history blended with transcripts
Machine Learning1 time: Machine Learning, Q3’24 Oct '24, counts as said1 time: Machine Learning, Q4’24 Feb '25, counts as said0 times: Machine Learning, Q1’25 May '250 times: Machine Learning, Q2’25 Jul '250 times: Machine Learning, Q3’25 Oct '251 time: Machine Learning, Q4’25 Feb '26, counts as said0 times: Machine Learning, Q1’26 Apr '260 times: Machine Learning, Q2’26 Jul '26falling3/838%3/838%19/8323%29%n=1+tx from settlement history blended with transcripts
Pharmaceutical0 times: Pharmaceutical, Q3’24 Oct '240 times: Pharmaceutical, Q4’24 Feb '250 times: Pharmaceutical, Q1’25 May '250 times: Pharmaceutical, Q2’25 Jul '250 times: Pharmaceutical, Q3’25 Oct '250 times: Pharmaceutical, Q4’25 Feb '260 times: Pharmaceutical, Q1’26 Apr '261 time: Pharmaceutical, Q2’26 Jul '26, counts as saidrising1/812%0/80%2/832%30%n=1+tx from settlement history blended with transcripts
Pharmaceutical / Pharma0 times: Pharmaceutical / Pharma, Q3’24 Oct '240 times: Pharmaceutical / Pharma, Q4’24 Feb '250 times: Pharmaceutical / Pharma, Q1’25 May '250 times: Pharmaceutical / Pharma, Q2’25 Jul '250 times: Pharmaceutical / Pharma, Q3’25 Oct '250 times: Pharmaceutical / Pharma, Q4’25 Feb '260 times: Pharmaceutical / Pharma, Q1’26 Apr '261 time: Pharmaceutical / Pharma, Q2’26 Jul '26, counts as saidrising1/812%0/80%2/832%31%n=1+tx from settlement history blended with transcripts
Reacher0 times: Reacher, Q3’24 Oct '240 times: Reacher, Q4’24 Feb '250 times: Reacher, Q1’25 May '250 times: Reacher, Q2’25 Jul '250 times: Reacher, Q3’25 Oct '250 times: Reacher, Q4’25 Feb '260 times: Reacher, Q1’26 Apr '260 times: Reacher, Q2’26 Jul '26steady0/80%0/80%1/831%14%n=1+tx from settlement history blended with transcripts
Redundancynever said0 times: Redundancy, Q3’24 Oct '240 times: Redundancy, Q4’24 Feb '250 times: Redundancy, Q1’25 May '250 times: Redundancy, Q2’25 Jul '250 times: Redundancy, Q3’25 Oct '250 times: Redundancy, Q4’25 Feb '260 times: Redundancy, Q1’26 Apr '260 times: Redundancy, Q2’26 Jul '26steady0/80%0/80%0/830%13%n=1+tx from settlement history blended with transcripts
Regulator / Regulation0 times: Regulator / Regulation, Q3’24 Oct '240 times: Regulator / Regulation, Q4’24 Feb '250 times: Regulator / Regulation, Q1’25 May '250 times: Regulator / Regulation, Q2’25 Jul '250 times: Regulator / Regulation, Q3’25 Oct '250 times: Regulator / Regulation, Q4’25 Feb '260 times: Regulator / Regulation, Q1’26 Apr '260 times: Regulator / Regulation, Q2’26 Jul '26steady0/80%0/80%3/834%14%n=1+tx from settlement history blended with transcripts
Repurchase0 times: Repurchase, Q3’24 Oct '240 times: Repurchase, Q4’24 Feb '250 times: Repurchase, Q1’25 May '250 times: Repurchase, Q2’25 Jul '250 times: Repurchase, Q3’25 Oct '250 times: Repurchase, Q4’25 Feb '260 times: Repurchase, Q1’26 Apr '260 times: Repurchase, Q2’26 Jul '26steady0/80%0/80%10/8312%14%n=1+tx from settlement history blended with transcripts
Retail profitnever said0 times: Retail profit, Q3’24 Oct '240 times: Retail profit, Q4’24 Feb '250 times: Retail profit, Q1’25 May '250 times: Retail profit, Q2’25 Jul '250 times: Retail profit, Q3’25 Oct '250 times: Retail profit, Q4’25 Feb '260 times: Retail profit, Q1’26 Apr '260 times: Retail profit, Q2’26 Jul '26steady0/80%0/80%0/830%14%n=1+tx from settlement history blended with transcripts
Zoox / Robotaxi0 times: Zoox / Robotaxi, Q3’24 Oct '240 times: Zoox / Robotaxi, Q4’24 Feb '250 times: Zoox / Robotaxi, Q1’25 May '250 times: Zoox / Robotaxi, Q2’25 Jul '252 times: Zoox / Robotaxi, Q3’25 Oct '25, counts as said0 times: Zoox / Robotaxi, Q4’25 Feb '262 times: Zoox / Robotaxi, Q1’26 Apr '26, counts as said0 times: Zoox / Robotaxi, Q2’26 Jul '26rising2/825%2/825%4/835%36%n=1+tx from settlement history blended with transcripts
Sheinnever said0 times: Shein, Q3’24 Oct '240 times: Shein, Q4’24 Feb '250 times: Shein, Q1’25 May '250 times: Shein, Q2’25 Jul '250 times: Shein, Q3’25 Oct '250 times: Shein, Q4’25 Feb '260 times: Shein, Q1’26 Apr '260 times: Shein, Q2’26 Jul '26steady0/80%0/80%0/830%13%n=1+tx from settlement history blended with transcripts
Shutdown / Shut Down0 times: Shutdown / Shut Down, Q3’24 Oct '241 time: Shutdown / Shut Down, Q4’24 Feb '25, counts as said0 times: Shutdown / Shut Down, Q1’25 May '250 times: Shutdown / Shut Down, Q2’25 Jul '250 times: Shutdown / Shut Down, Q3’25 Oct '250 times: Shutdown / Shut Down, Q4’25 Feb '260 times: Shutdown / Shut Down, Q1’26 Apr '260 times: Shutdown / Shut Down, Q2’26 Jul '26steady1/812%0/80%3/834%17%n=1+tx from settlement history blended with transcripts
Sustainabilitynever said0 times: Sustainability, Q3’24 Oct '240 times: Sustainability, Q4’24 Feb '250 times: Sustainability, Q1’25 May '250 times: Sustainability, Q2’25 Jul '250 times: Sustainability, Q3’25 Oct '250 times: Sustainability, Q4’25 Feb '260 times: Sustainability, Q1’26 Apr '260 times: Sustainability, Q2’26 Jul '26steady0/80%0/80%0/830%14%n=1+tx from settlement history blended with transcripts
Temunever said0 times: Temu, Q3’24 Oct '240 times: Temu, Q4’24 Feb '250 times: Temu, Q1’25 May '250 times: Temu, Q2’25 Jul '250 times: Temu, Q3’25 Oct '250 times: Temu, Q4’25 Feb '260 times: Temu, Q1’26 Apr '260 times: Temu, Q2’26 Jul '26steady0/80%0/80%0/830%13%n=1+tx from settlement history blended with transcripts
Thursday Night Football0 times: Thursday Night Football, Q3’24 Oct '241 time: Thursday Night Football, Q4’24 Feb '25, counts as said0 times: Thursday Night Football, Q1’25 May '250 times: Thursday Night Football, Q2’25 Jul '250 times: Thursday Night Football, Q3’25 Oct '252 times: Thursday Night Football, Q4’25 Feb '26, counts as said0 times: Thursday Night Football, Q1’26 Apr '261 time: Thursday Night Football, Q2’26 Jul '26, counts as saidrising3/838%2/825%17/8320%46%n=1+tx from settlement history blended with transcripts
Trumpnever said0 times: Trump, Q3’24 Oct '240 times: Trump, Q4’24 Feb '250 times: Trump, Q1’25 May '250 times: Trump, Q2’25 Jul '250 times: Trump, Q3’25 Oct '250 times: Trump, Q4’25 Feb '260 times: Trump, Q1’26 Apr '260 times: Trump, Q2’26 Jul '26steady0/80%0/80%0/830%14%n=1+tx from settlement history blended with transcripts
Warehouse0 times: Warehouse, Q3’24 Oct '240 times: Warehouse, Q4’24 Feb '250 times: Warehouse, Q1’25 May '250 times: Warehouse, Q2’25 Jul '250 times: Warehouse, Q3’25 Oct '250 times: Warehouse, Q4’25 Feb '260 times: Warehouse, Q1’26 Apr '260 times: Warehouse, Q2’26 Jul '26steady0/80%0/80%33/8340%14%n=1+tx from settlement history blended with transcripts
World Cup0 times: World Cup, Q3’24 Oct '240 times: World Cup, Q4’24 Feb '250 times: World Cup, Q1’25 May '250 times: World Cup, Q2’25 Jul '250 times: World Cup, Q3’25 Oct '250 times: World Cup, Q4’25 Feb '260 times: World Cup, Q1’26 Apr '260 times: World Cup, Q2’26 Jul '26steady0/80%0/80%1/831%13%n=1+tx from settlement history blended with transcripts
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

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Agents: this page as TSV at /api/v1/entity/amazon · words: /api/v1/history?entity=amazon · columnar JSON in #parrot-data · llms.txt · MCP