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[04.CX] Capturing Messenger LiveChat Data in Real-Time with ManyChat and Google Sheets

Capturing Messenger LiveChat Data inReal-Time with ManyChat & Google Sheets ManyChat is a vital component of our digital agronomy solution as itenables us to disseminate farming advice to farmers and receive theirdirect inquiries via messenger. The platform's built-in integrationfacilitates the capture of chat flow and live chat data, which is thentransmitted directly to Google Sheets. The Digital Marketing teamestablished this integration during the early stages of development, whilethe Data team is responsible for managing and architecting this data toderive valuable insights from it. Although we plan to upgrade to a moreadvanced data storage solution, such as a Snowflake Cloud DataWarehouse, the current ETL pipeline represents our current workflow. 2) Context: A senior management member has made a last-minute requestto modify the naming on the dashboard, which serves as the front-end for allthe backed-end processes. This approach is not recommended as it is notfuture-proof. To address this, I need to collaborate with the backend team. Ibelieve this presents an opportunity for business-side individuals to enhancetheir understanding of system designs and engineering. By doing so, we canfoster better collaboration between system and business personnel andwork towards a common goal. [ManyChat]LiveChatCleaned Data for PBIDashboardOnly for ClosedLiveChat Transformed with series ofRule EnginesLast-minute requeston Naming StructureGoogle SheetsReader Excel Writer Rule-basedRow Splitter Row Splitter InquiryType +InquiryTopic Service Line Product segment LiveChat ID +InquiryType Rule-basedRow Splitter Product segment +Product category Joiner Service Line InquiryTopic LiveChat ID +ServiceType Concatenate Rule Engine Google SheetsConnection GoogleAuthentication Data Transformation Capturing Messenger LiveChat Data inReal-Time with ManyChat & Google Sheets ManyChat is a vital component of our digital agronomy solution as itenables us to disseminate farming advice to farmers and receive theirdirect inquiries via messenger. The platform's built-in integrationfacilitates the capture of chat flow and live chat data, which is thentransmitted directly to Google Sheets. The Digital Marketing teamestablished this integration during the early stages of development, whilethe Data team is responsible for managing and architecting this data toderive valuable insights from it. Although we plan to upgrade to a moreadvanced data storage solution, such as a Snowflake Cloud DataWarehouse, the current ETL pipeline represents our current workflow. 2) Context: A senior management member has made a last-minute requestto modify the naming on the dashboard, which serves as the front-end for allthe backed-end processes. This approach is not recommended as it is notfuture-proof. To address this, I need to collaborate with the backend team. Ibelieve this presents an opportunity for business-side individuals to enhancetheir understanding of system designs and engineering. By doing so, we canfoster better collaboration between system and business personnel andwork towards a common goal. [ManyChat]LiveChatCleaned Data for PBIDashboardOnly for ClosedLiveChat Transformed with series ofRule EnginesLast-minute requeston Naming StructureGoogle SheetsReader Excel Writer Rule-basedRow Splitter Row Splitter InquiryType +InquiryTopic Service Line Product segment LiveChat ID +InquiryType Rule-basedRow Splitter Product segment +Product category Joiner Service Line InquiryTopic LiveChat ID +ServiceType Concatenate Rule Engine Google SheetsConnection GoogleAuthentication Data Transformation

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Created by: Data Analytics Team
Created at: 2023-04-16
On NodePit since: 2023-04-17
Last update: 2024-04-27
Created with KNIME version: v4.5.2

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