Abstract: Certain embodiments of the present disclosure provide techniques training a user detection model to identify a user of a software application based on voice recognition. The method generally includes receiving a data set including a plurality of voice interactions with users of a software application. For each respective recording in the data set, a spectrogram representation is generated based on the respective recording. A plurality of voice recognition models are trained. Each of the plurality of voice recognition models is trained based on the spectrogram representation for each of the plurality of voice recordings in the data set. The plurality of voice recognition models are deployed to an interactive voice response system.

Abstract: Certain embodiments of the present disclosure provide techniques training a user detection model to identify a user of a software application based on voice recognition. The method generally includes receiving a data set including a plurality of voice interactions with users of a software application. For each respective recording in the data set, a spectrogram representation is generated based on the respective recording. A plurality of voice recognition models are trained. Each of the plurality of voice recognition models is trained based on the spectrogram representation for each of the plurality of voice recordings in the data set. The plurality of voice recognition models are deployed to an interactive voice response system.

Abstract: A method including receiving a website text item of the website, where the website text item is categorized by a text category and a website element category, identifying, multiple text items of multiple websites relating to multiple businesses in an industry, searching the multiple text items using the website element category to identify multiple comparable text items, parsing the website text item to generate multiple keywords, searching the multiple comparable text items using the multiple keywords to identify a comparable text item, where the comparable text item includes a conversion rate corresponding to a percentage of transactions completed by multiple website visitors accessing the comparable text item, identifying, a modified conversion text item from the multiple comparable text items, where the modified conversion text item has a modified conversion rate that exceeds the conversion rate, generating, a conversion improved website including the modified conversion text item.

Abstract: A method including identifying a business category of a business related to a user, obtaining multiple website analytics data items from multiple websites related to multiple business in the business category, evaluating the multiple website analytics data items to generate multiple website templates for the user, providing the multiple website templates to the user, receiving a selection from the user of a website template from the multiple website templates, receiving website content for a user website from the user, evaluating the multiple website analytics data items and the website content to generate multiple recommendations for the user website, providing the multiple recommendations for the user website to the user, receiving multiple recommendation approvals of the multiple recommendations for the user website from the user, and generating the user website based on the website content, the website template, and the multiple recommendation approvals.

Abstract: A method including receiving a website text item of the website, where the website text item is categorized by a text category and a website element category, identifying, multiple text items of multiple websites relating to multiple businesses in an industry, searching the multiple text items using the website element category to identify multiple comparable text items, parsing the website text item to generate multiple keywords, searching the multiple comparable text items using the multiple keywords to identify a comparable text item, where the comparable text item includes a conversion rate corresponding to a percentage of transactions completed by multiple website visitors accessing the comparable text item, identifying, a modified conversion text item from the multiple comparable text items, where the modified conversion text item has a modified conversion rate that exceeds the conversion rate, generating, a conversion improved website including the modified conversion text item.