It’s no secret that customer centricity and personalization tools are rapidly becoming the gold standard for healthcare professional (HCP) interactions. The growing consensus across the life sciences industry is that automation will help organizations target down to the individual level. Using tools enabled by artificial intelligence (AI) can help brand teams design customer journeys that […]
Novartis and Aktana Present the New Commercial Engagement Model at
Veeva Commercial and Medical Summit, Europe
The Veeva Commercial and Medical Summit, Europe welcomed over 1,000 attendees this year in Madrid, including speakers from some of the world’s largest life sciences companies. Concentrated on the era of intelligent customer engagement, attendees discussed the future of customer engagement across sessions, networking conversations, and on social media.
Decision support has become a vital tool in connecting brand strategy with execution, resulting in increased CRM satisfaction and better healthcare professional (HCP) engagement. When you roll out your decision support program, how can you ensure that you’ll get the adoption and long-term user engagement with the technology to achieve these results? Below are four essentials for maximizing engagement in AI decision support.
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.