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Let’s take a look at a handful of business problems and how AI has been employed to solve them.These are practical, pragmatic, replicable efforts. It's not intended to be a comprehensive list but instead a group of examples of “right-sized” projects.
The system crunches an incredible 3 million responses every day.
Since launching in 1999, Survey Monkey has built up a powerful database of consumer and employee responses, and it’s now using AI to leverage this data. One of them is by tapping into past survey results to help businesses create high-performing surveys with high completion rates.
The Problem: Predicting Customer Churn -- And Acting On It VOZIQ provides customer experience management software to contact and call centers. And they do so largely by using demographic and transaction history data.
However, this approach fails to capture the real-time, dynamic customer data picked up over the phone, much of which is recorded in notes taken by call center workers.
The system delivers real-time recommendations for adjusting which questions are asked and how in order to generate higher quality data.
The data received by Survey Monkey comes from unpaid survey-takers, so optimizing for high-quality responses is essential.
Alternatives Pharma is all too aware of this, which is why it uses qualitative data from web forums, social media and blogs in its efforts to help pharmaceutical marketing teams connect with both patients and doctors.
However, sourcing, collating and analyzing such data on a suitably large scale is impossible without the help of technology.
Using a platform called Metis, Dorchester Collection parses, summarizes and contextualizes reviews in order to gain insights, plan next steps and maintain a competitive advantage.
The Problem: Creating Messaging That Resonates With Users What patients say in a clinical setting is different from what they say behind closed doors -- or in the anonymity of the internet.