ai_member_xiaoxi/memory/2026-05-07-lead-user-ids.md
2026-05-08 08:00:01 +08:00

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Session: 2026-05-07 14:30:45 GMT+8

  • Session Key: agent:main:feishu:direct:ou_e63ce6b760ad39382852472f28fbe2a2
  • Session ID: 9dd6cd3c-d788-4a31-9853-ef45db3237b1
  • Source: feishu

Conversation Summary

assistant: 所有技能均无变更,无需推送。静默。

NO_REPLY user: [media attached: /root/.openclaw/media/inbound/3æ_è_çº_çº_ç---643f3b8b-22f0-4596-bf7c-2e838fc57db4.xlsx (application/vnd.openxmlformats-officedocument.spreadsheetml.sheet) | /root/.openclaw/media/inbound/3æ_è_çº_çº_ç---643f3b8b-22f0-4596-bf7c-2e838fc57db4.xlsx] [File: /root/.openclaw/media/inbound/3æ_è_çº_çº_ç---643f3b8b-22f0-4596-bf7c-2e838fc57db4.xlsx] assistant: 李承龙发来了一份文件,我先看一下内容。 assistant: 承龙,看到你发来的文件了。文件内容是一个线索跟进表,包含 463 行数据3 列:

  • 用户ID
  • 线索进线日期2026-03-01 至 2026-03-31整个3月
  • 销售姜小龙、Bob、Tom

请问需要我怎么处理这份数据?比如:

  • 查这些用户在数据库中的学习行为?
  • 关联订单信息看是否有成交?
  • 做某种统计分析? user: 我们昨天通过脚本lead_user_analysis.py对上面的excel做了统计结果我发现只有销售姜小龙有成交订单帮我看看这个数据有没有问题 assistant: 让我先找到昨天运行的脚本,以及相关的记忆/输出,了解当时的执行情况。 assistant: 找到了脚本和昨天的记录。现在我直接用这个脚本对承龙新发的 Excel 重新跑一次,看看完整数据里 Bob 和 Tom 的订单情况。 assistant: 脚本跑完了。现在我来验证一下各销售的订单分布: assistant: 结果确实只有姜小龙有成交。让我从数据库层面交叉验证一下——Bob 和 Tom 的这些用户 ID 在订单库里到底有没有记录: assistant: 数据确认无误。让我再核对一下脚本中账户匹配的完整性——是否 Bob 和 Tom 的用户后续被过滤掉了: assistant: 数据验证完毕。总结如下:

承龙,我重新跑了脚本并做了交叉验证,数据没有问题。Bob 和 Tom 的线索用户确实没有产生任何付费订单。

具体核查结果:

销售 线索用户数 有效账户数 订单数
姜小龙 181 41条38个独立用户
Bob 133 133仅1个status≠1 0条
Tom 148 148全部status=1 0条

验证步骤:

  1. 脚本重跑:用你刚发的 Excel 重新执行 lead_user_analysis.pyBob 和 Tom 的购买记录均为空
  2. 数据库直接查:绕开脚本,直接用这批用户 ID 查 bi_vala_orderBob133个ID和 Tom148个ID在订单表里确实 一条记录都没有
  3. 排除过滤原因:确认 Bob 和 Tom 的用户账户状态都正常status=1不存在被 status=1 过滤误伤的情况

所以数据是准确的——3月份这批线索中只有姜小龙转化的用户产生了付费。 user: 帮我整理一下这些用户ID用('用户ID1','用户ID2',...)的形式输出 assistant: 你是想要全部 462 个用户ID还是按销售分开我先按销售分组给你整理。 assistant: 承龙,按销售分了三组:

Bob133个

('2903','9143','14452','16354','16367','16394','16420','16443','16481','16753','16841','16926','17016','17090','17113','17279','17323','17471','17493','17697','17801','17833','17855','17977','17982','18004','18014','18218','18577','18579','18642','18658','18719','18758','18779','18816','18856','18907','18911','18914','18956','18958','18961','18974','19001','19059','19074','19080','19085','19097','19099','19102','19113','19120','19128','19270','19285','19316','19321','19346','19377','19382','19388','19407','19410','19416','19424','19433','19435','19451','19469','19494','19528','19560','19562','19564','19579','19585','19587','19589','19592','19598','19610','19620','19621','19622','19624','19632','19656','19672','19709','19711','19712','19718','19738','19766','19792','19794','19818','19822','19900','19948','19951','19952','19956','19961','19971','19976','19977','20004','20097','20179','20196','20200','20214','20238','20290','20323','20390','20562','20563','21157','22275','23746','24076','24191','24670','24673','24685','24693','24756','24846','24983')

Tom148个

('5455','7495','14796','16348','16356','16366','16437','16440','16470','16490','16497','16511','16966','17027','17071','17097','17274','17371','17386','17411','17516','17528','17603','17672','17675','17864','17879','17892','17972','18018','18022','18179','18182','18383','18541','18555','18640','18691','18792','18811','18835','18857','18870','18884','18886','18913','18957','18988','18990','19005','19012','19051','19052','19053','19056','19094','19173','19194','19243','19279','19325','19337','19354','19358','19368','19426','19431','19437','19439','19444','19445','19454','19470','19476','19487','19489','19490','19499','19500','19522','19543','19545','19547','19554','19567','19586','19623','19626','19627','19639','19652','19663','19679','19682','19683','19686','19708','19710','19727','19935','19955','19970','19985','20005','20006','20007','20021','20025','20044','20049','20067','20069','20074','20104','20117','20134','20139','20156','20162','20163','20167','20172','20175','20180','20256','20265','20267','20275','20281','20287','20289','20329','20488','21511','21871','21883','21889','21937','22101','22703','23061','23735','23971','24031','24575','24588','25144','25260')

姜小龙181个

('2335','2927','3928','7319','8489','10994','16078','16150','16158','16176','16182','16193','16238','16262','16263','16268','16393','16530','16625','16633','16698','16827','17025','17036','17087','17100','17192','17247','17251','17255','17268','17283','17313','17325','17374','17375','17387','17425','17432','17470','17479','17480','17505','17632','17660','17712','17738','17744','17758','17769','17783','17816','17832','17871','17873','17894','17983','17990','18023','18065','18398','18428','18436','18457','18549','18569','18590','18597','18660','18673','18699','18704','18711','18712','18728','18774','18781','18802','18818','18821','18834','18847','18944','18982','19054','19058','19088','19100','19107','19110','19130','19166','19168','19174','19178','19200','19208','19212','19226','19231','19250','19284','19287','19309','19313','19349','19355','19369','19401','19420','19449','19450','19456','19521','19529','19532','19542','19555','19565','19578','19582','19583','19600','19605','19615','19635','19642','19703','19751','19756','19758','19760','19764','19767','19778','19783','19809','19812','19815','19821','19849','19854','19864','19885','19906','19919','19925','19945','19950','19967','19969','19986','19990','20010','20040','20045','20140','20146','20165','20197','20206','20222','20223','20268','20271','20274','20286','20297','20305','20353','20371','20379','20458','21029','21589','21858','21912','22075','24276','24306','25863')

另外,如果你需要全部 462 个用户合在一起不分组的格式,我可以直接合并输出。