Launching Conversational AI: Six Keys to Success

Posted by Satish Jha on Tue, Jul 16, 2019

Vaibhav Bansal co-wrote this post with Satish Jha 

A witty, ever-reliable butler is a must-have for crime-fighting billionaires — just ask Bruce Wayne. The closest thing that Tony Stark has to a butler is his AI assistant Jarvis, with its alert, intelligent and unaffected responses to Ironman’s perpetual snark.

While we are still years away from creating a chat bot as sophisticated as Jarvis, the recent advancements in NLP, (natural language processing, the technology that powers chat bots,) have been very encouraging. Someday, we believe these AI agents will become so advanced that they allay the common belief that AI can’t be as perceptive or intuitive as humans. Though such a future is a few decades away, conversational AI is already solving countless problems and driving better engagement and experience.


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Intelligent Process Automation: Starting Is Easy, Scaling Is a Different Ball Game

Posted by Vishal Kabra on Thu, May 09, 2019

Satish Jha co-wrote this blog post with Vishal Kabra 

Today, there is no denying that when it comes to increasing efficiency, reducing cost and offering a better customer experience, intelligent process automation (IPA) is a go-to strategy for businesses, and pharma is no exception. IPA promises that it can free up people to do more value-added work and play more strategic roles within their organizations. At a fundamental level, IPA is an emerging set of new technologies that include robotic process automation (RPA), conversational AI and machine learning to mimic activities carried out by humans. With the evolution in IPA technologies and the broad applicability of such automation, IPA continues to be a buzzword in every industry. Given the many benefits and possibilities, it’s understandable why organizations are jumping onto the IPA bandwagon.

However, most organizations aren’t succeeding at scaling intelligent process automation.


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Making the Case for a New Analytics Consumption Model

Posted by ZS Editors on Thu, Nov 29, 2018

Industries like retail and technology are transitioning to an AI-driven, personalized approach to surfacing insights to end users, and they’re reaping the benefits. Life sciences companies have the same opportunity to capitalize on the runaway growth in data and rethink the way that analytics are consumed.  

ZS recently partnered with IDC to study how commercial life sciences teams are currently consuming data, and to determine their data and analytics pain points. The study revealed that sales and marketing professionals in life sciences want


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New ZS Research on Forecasting in an Evolving Landscape

Posted by Ram Ramakrishnan on Mon, Jul 09, 2018

This post is the second in a four-part series on how pharmaceutical companies can elevate their forecasting operations.

The pharmaceutical industry is facing an increasingly challenging environment with looming biosimilar launches, tighter access and pricing controls, and saturation within primary care markets. Forecasting as a functional area is affected by these changes, given the range of decisions that forecasts inform.


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Having Customer-Centric Capabilities Doesn’t Mean That You’re a Customer-Centric Organization

Posted by Pete Mehr on Mon, Jul 02, 2018

This post is the second in a three-part series on how pharma companies can achieve customer centricity.

In my previous blog post, we spoke about pharmaceutical companies moving from a tactic-based marketing process to an orchestrated marketing process. The motivation for making this change is to optimize the customer experience. To achieve this goal, pharmaceutical companies have started to leverage cloud-based computing capabilities, purchase marketing automation platforms, enhance their analytic capabilities using data science and machine learning, use social media platforms, and hire digital experts from other industries, just to name a few of the changes. Yet companies still struggle to realize the value from these investments. 


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