function track_msdynmkt_websiteinteractions_114741865() { window["msdynmkt"].setUser({ authId: ""}); // ID, e-mail or phone number - see instructions window["msdynmkt"].trackEvent({ name: "msdynmkt_websiteinteractions_114741865", //Trigger title: Website Interactions ingestionKey : "d12470e34c7a4283ac8769a2797687ca-fab4c50f-f357-4516-a3f8-b908fdfbc681-7154", version: "1.0.0" ,     properties: { "dateandtime" : "", "url" : "", "bindingid" : "" } }); } global eia # ID, e-mail or phone number - see instructions user = User(auth_id='') eia.set_user(user) #Trigger title: Website Visit sampleEvent = Event('msdynmkt_websitevisit_083156767') sampleEvent.set_property("bindingid", "") eia.track_event(sampleEvent)
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Text classification

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The need

Better understand and analyse large amounts of text data coming from customer interactions.

Automate news classification that appears on the web (Ex:news).

Understand customer sentiment.

Identify and classify languages coming from different countries.

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The solution

Create AI models based on the historical classification.

Web scraping to find any type of news related to the company.

Create retrain pipelines to guarantee a continuous improvement of the models.

Integration of the new process internally among the teams.

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Time reduced significantly for newspaper article analysis.

Employee’s time is optimized.


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