How to Identify a SaaS Market that Machine Learning Will Disrupt

By and large, the most frequent applications of machine learning in SaaS today are efficiency applications – automating the high-volume rote processes and reducing costs.

Extract from article by Tomasz Tunguz

In SaaS, machine learning has become an essential component to many different products. Whether it’s automating responses to inbound sales queries, identifying expense reports for audit, or surfacing anomalies in data, machine learning improves workflow software. To date, most software imbued with machine learning reduces costs rather than increase revenues.

Why is this the case? Because machine learning is focused on efficiency gains.

By and large, the most frequent applications of machine learning in SaaS today are efficiency applications – automating the high-volume rote processes and reducing costs. Consequently, if you looking to build a machine learning based SaaS company, find a really expensive internal process and automate it.

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A Matter of Pricing? A Running Update of Semi-Annual eDiscovery Pricing Survey Responses

First administered in December of 2018 and conducted four times during the last two years with 334 individual responses, the semi-annual eDiscovery Pricing Survey highlights pricing on selected collection, processing, and review tasks. The aggregate results of all surveys as shared in the provided comparative charts may be helpful for understanding pricing and its impact on purchasing behavior on selected services over time.



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