Indeed, the mobile Internet is the new frontier to conquer for any brand, even as the smartphone is now synonymous to the consumers wallet; necessitating brands to crave for access to the frequency of mobile user interactions and the sequential actions taken after engaging with its services.

While Amazon already offers Analytics for conversational AI to assist in gathering and aggregating metrics, like total customer interactions, usage time and frequency of intent.

Amazon Skill metrics dashboard features new data points and visualization on customers interactions, including data from mobile devices, to better understand how customers utilize the skill to help create better engagement and retention.

And just recently, Adobe announced new voice analytics capabilities in Adobe Analytics Cloud to help brands take advantage of conversational data to improve targeting and, ideally, conversions.

Through deep analysis of voice data complemented by artificial intelligence and machine learning capabilities in Adobe Sensei, brands can gain robust audience insights and recommendations.

The Adobe Sensei can process data from Alexa, Siri, Google Assistant, and Cortana, for both user intent and contextual data — which can be put to use by brands when targeting customers across other channels like email or social platforms.

It can also track the actions users often take with the conversational AI and the stuff mostly interacted with — for instance, using to call an Uber.

In practice, brands will have access to the the sequential actions taken after engaging with a particular service, and thus be able to pinpoint where or what next the consumer may be up to, so as to target them effectively.

How Analytics Tools for conversational AI is becoming marketers Holy Grail



Indeed, the mobile Internet is the new frontier to conquer for any brand, even as the smartphone is now synonymous to the consumers wallet; necessitating brands to crave for access to the frequency of mobile user interactions and the sequential actions taken after engaging with its services.

While Amazon already offers Analytics for conversational AI to assist in gathering and aggregating metrics, like total customer interactions, usage time and frequency of intent.

Amazon Skill metrics dashboard features new data points and visualization on customers interactions, including data from mobile devices, to better understand how customers utilize the skill to help create better engagement and retention.

And just recently, Adobe announced new voice analytics capabilities in Adobe Analytics Cloud to help brands take advantage of conversational data to improve targeting and, ideally, conversions.

Through deep analysis of voice data complemented by artificial intelligence and machine learning capabilities in Adobe Sensei, brands can gain robust audience insights and recommendations.

The Adobe Sensei can process data from Alexa, Siri, Google Assistant, and Cortana, for both user intent and contextual data — which can be put to use by brands when targeting customers across other channels like email or social platforms.

It can also track the actions users often take with the conversational AI and the stuff mostly interacted with — for instance, using to call an Uber.

In practice, brands will have access to the the sequential actions taken after engaging with a particular service, and thus be able to pinpoint where or what next the consumer may be up to, so as to target them effectively.