Bank Call Center Interactions

This dataset provides granular records of customer interactions with banking call centers, including timestamps, agent and customer details, interaction topics, sentiment, resolution status, and full transcripts. It is ideal for customer experience analytics, agent performance monitoring, and training conversational AI models to improve banking services.

  • opened 10 times
  • last updated 21 Jul 2025
  • by GoMask
The brief that made it

Analyzing customer experience and satisfaction trends

Sample rows

preview · 8 of 200 rows · all 22 columns
interaction_idstringinteraction_typestringcall_duration_secondsintegerfollow_up_requiredbooleanlanguagestringcustomer_idstringcustomer_namestringcustomer_phonestringcustomer_emailstringinteraction_datetimedatetimechannelstringagent_idstringagent_namestringtopicstringsentimentstringresolution_statusstringresolution_time_secondsintegercustomer_satisfaction_scoreintegerescalation_requiredbooleanfollow_up_datetimedatetimebank_branch_codestringtranscriptstring
INT000001inquiry95falsedeCUST10001Sophie Müller+49 1523 456789sophie.mueller@example.de2023-05-21T09:24:15ZchatAGT1001Emily Carteraccount featuresneutralresolved484falseblankBR001Hello, I would like to know more about your account features.
INT000002complaint780trueruCUST10002Mikhail Ivanov+7 495 1234567m.ivanov@mail.ru2023-06-02T11:15:34ZphoneAGT1002Irina Morozovabranch servicenegativependingblank2false2023-06-05T10:00:00ZBR017The service at my local branch was unsatisfactory.
INT000003feedbackblankfalseesCUST10003Carlos García+34 612 987654c.garcia@correo.es2022-11-10T13:40:59Zsocial_mediaAGT1003Lucía Torresmobile banking apppositiveresolved125falseblankBR024Your mobile app is very user-friendly. Keep it up!
INT000004transaction540falsezhCUST10004Mei Lin+86 10 1234 5678lin.mei@qq.cn2023-01-27T08:19:46ZphoneAGT1004Xiaoyu Wanginternational transferneutralresolved2204falseblankBR038I need help with an international money transfer.
INT000005inquiryblankfalseitCUST10005Isabella Rossi+39 345 6789012isabella.rossi@mail.it2023-03-04T17:11:09ZemailAGT1005Francesca Bianchicredit card optionspositiveresolved355falseblankblankCould you send me information on your credit card products?
INT000006feedback73falsedeCUST10001Sophie Müller+49 1523 456789sophie.mueller@example.de2022-12-12T14:29:54ZchatAGT1006David Schmidtblankpositiveresolved105falseblankBR001Thanks for quick support!
INT000007other35falseenCUST10006Emily Murphyblankblank2023-04-21T12:12:26ZchatAGT1007Oliver Taylorblankunknownpendingblankblankfalseblankblankblank
INT000008inquiry184falsefrCUST10007Jean Dupont+33 6 45 23 78 89jean.dupont@laposte.fr2023-03-15T10:03:44ZphoneAGT1008Marie Laurentloan ratesneutralresolved674falseblankBR004Could you tell me more about current loan rates?

What the 200 rows show

from the 200-row sample

Complaint (interaction type) stands out: 26 of its 36 rows have follow_up_required = true, against 3 of 164 for the rest.

  • 14%follow_up_required = true
  • 206median call_duration_seconds
  • 3resolution statuses
  • 4sentiments
  • 5channels
  • 36.5median resolution_time_seconds
Follow up required rate by interaction_typefollow_up_required = true
0%50%100%4%inquiry3 of 6772%compla…26 of 360%feedba…0 of 340%transa…0 of 390%other0 of 24
call_duration_seconds158 rows, in bands of 250M
0801601520000000601.3B2.3Bcall_duration_seconds →

Median 206, from 0 to 2,147,483,647.

language183 rows with a value · 17 left blank
  1. de26
  2. it24
  3. en24
  4. pl23
  5. fr21
  6. es18
  7. ru15
  8. ar14
  9. zh7
  10. pt5
22 columns by typefrom the column list below
  • string 15
  • integer 3
  • datetime 2
  • boolean 2

Columns

22 columns in four groups
blueprint · 22 columns
columntypedescriptionexample
Text 15 columns
interaction_idstringUnique identifier for each call center interactionuniqueINT000001
customer_idstringUnique identifier for the customer involved in the interactionCUST10001
customer_namestringFull name of the customeroptionalSophie Müller
customer_phonestringPhone number of the customeroptional+49 1523 456789
customer_emailstringEmail address of the customeroptionalm.ivanov@mail.ru
channelstringChannel through which the interaction occurred (e.g., phone, chat, email)phone · chat · email · social_media · otherchat
agent_idstringUnique identifier for the call center agent handling the interactionoptionalAGT1001
agent_namestringFull name of the agent handling the interactionoptionalEmily Carter
interaction_typestringType of interaction (e.g., inquiry, complaint, feedback, transaction)inquiry · complaint · feedback · transaction · otherinquiry
topicstringPrimary topic or subject of the interaction (e.g., account balance, loan inquiry, card issue)optionalaccount features
sentimentstringDetected sentiment of the customer's interaction (e.g., positive, neutral, negative)positive · neutral · negative · unknown · optionalneutral
resolution_statusstringStatus indicating whether the interaction was resolvedresolved · unresolved · pending · escalatedresolved
transcriptstringFull text transcript of the interaction (if available)optional我想汇款到美国账户。请帮我。
languagestringLanguage used during the interaction12 languages · optionalde
bank_branch_codestringCode of the bank branch associated with the interaction (if applicable)optionalBR001
Numbers 3 columns
call_duration_secondsintegerDuration of the interaction in seconds0 or more · optional95
resolution_time_secondsintegerTime taken to resolve the issue in seconds (if applicable)0 or more · optional48
customer_satisfaction_scoreintegerCustomer satisfaction score for the interaction (e.g., 1-5 scale)1 to 5 · optional4
Dates and times 2 columns
interaction_datetimedatetimeDate and time when the interaction occurred2023-05-21T09:24:15Z
follow_up_datetimedatetimeScheduled date and time for follow-up (if applicable)optional2023-06-05T10:00:00Z
True or false 2 columns
escalation_requiredbooleanIndicates if the interaction required escalation to a supervisor or specialistoptionalfalse
follow_up_requiredbooleanIndicates if a follow-up action is required after the interactionoptionalfalse

Use it for

  • follow up requ…14%29 of 200 rowsmean call duration se…169.4inqu…583.7comp…99.6feed…377.8tran…

    A finance dashboard

    The follow_up_required rate, call_duration_seconds by interaction_type and a breakdown of language. Excel, Power BI or Tableau.

  • Why do 29 of 200 rows have follow_up_required = true?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable interactions with customer_id, customer_name and customer_phone to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 22 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows22 columns
Yours1,000 rows22 columnsbank_branch_code: UK only

blueprint · bank-call-center-interactions

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 22 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each interaction linked to customer and agent IDs.
  • Call reason categorized.
  • Duration and outcome recorded.
  • Sensitive data anonymized.
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
bank-call-center-interactions

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