This year’s Dreamforce event brought together over 170,000 people in downtown San Francisco for its 16th year. One of the major themes discussed was how to cut through the noise to create a better customer experience through the use of artificial intelligence (AI) and digital engagement.
Companies today are drowning in data. The average company exceeds 50 percent per year in volume of data growth and has an average of 33 unique data sources — these are overwhelming amounts that make extracting analytical insights an arduous task. For those swamped with data that’s not being put to use, data lakes can provide immense value. Data lakes are storage systems that hold large volumes of raw, highly diverse data from many sources. Aside from providing internal benefits such as architecture flexibility and scalability, they make processing data quicker and more accurate, uncovering analytical insights that companies didn’t even realize before.
As discussed in part one of this series, machine learning and AI have already been applied in several ways in the commercial life sciences -- yet there’s potential to do even more. In part two, Veeva Systems SVP of Commercial Strategy Paul Shawah and Aktana CEO David Ehrlich discuss what’s in store for this emerging technology and how commercial and medical teams can make the most of it.
In this two-part series, Veeva Systems SVP of Commercial Strategy Paul Shawah and Aktana CEO David Ehrlich discuss how to leverage machine learning and AI to optimize go-to-market strategy — both today and in the years to come. Part one below focuses on the current state of machine learning in life sciences commercial processes, including applications, success factors, and the effect on the HCP experience.
V14 Introduces Seamless Integration with Salesforce Marketing Cloud and Increased Control and Visibility
Driven by customer success and innovation, Aktana introduces major product enhancements multiple times a year based on customer input, advancements in technology and data sciences, and industry changes. The latest enhancements to Aktana Decision Support center around improving control and visibility for customers, punctuated with a new integration with Salesforce Marketing Cloud.
Artificial intelligence (AI) and machine learning are all over the news today and a priority for most data companies. Aktana’s product marketing director, Lauren Schivley, talks with Chief Science Officer Marc Cohen about what makes machine learning so valuable and how it applies to the commercial life sciences.
Our first annual customer roundtable took place last month in Manhattan, NY. Sales, marketing, IT, and innovation executives representing top bio-pharmaceutical companies convened to network and exchange ideas about decision support and artificial intelligence (AI) in commercial processes. The conversation was lively with many common experiences across companies, and a multitude of best practices were shared as well.
Chief Science Officer Marc Cohen and the data science team at Aktana recently published their research in this area in The Journal of the Pharmaceutical Management Science Association, setting forth a successful machine learning approach for identifying message sequences that maximize open and click-through rates.
Going to Market Smarter: Aktana and Pfizer Share Real-world Application of AI at Veeva Commercial and Medical Summit
The Veeva Commercial and Medical Summit hosted commercial leaders from across the life sciences industry this past week. Abuzz with talk of artificial intelligence (AI) and its potential to transform how life sciences companies engage with healthcare professionals, attendees sought to understand how to make this a reality in their organizations.
I had the opportunity to attend the Enhancing Sales Force Productivity Conference recently at the University of Missouri. It’s an annual conference that brings together sales and marketing researchers from around the world to share their findings on using AI (artificial intelligence) to improve sales force management and performance. As the only commercial entity in attendance, we listened to several talks by academic experts and shared our own industry perspective in David’s keynote address. After two jam-packed days of networking, panel discussions, and research presentations, I came away with three main takeaways.