AI-Powered Segmentation Resolution for Personalised Healthcare Engagement – Knowledge & Analytics Options & Providers


Legacy enterprise guidelines – Our shopper’s current opinion-leader segmentation course of included legacy enterprise guidelines that didn’t match with present market requirements. It lacked fashionable options equivalent to analyzing the digital actions of healthcare influencers and professionals, their reputation, relationship matrix and extra.

Premature information updates – Their medical gross sales workforce up to date information manually in its backend system at irregular intervals. It had a direct affect on medical skilled classification resulting in incorrect segmentation.

Want for automation – The present course of for computing segments was effort-intensive, gradual, and error-prone requiring excessive collaboration from world medical groups. Cumbersome, market-centric information studies had been distributed to world and on-field groups for handbook evaluate, making the method troublesome to scale for different therapeutic areas.

Data loss – Poor information governance created gaps between current segments and associated attributes as per enterprise guidelines. Handbook information processing coupled with lack of high quality checks whereas importing healthcare professionals’ information on the central portal resulted within the lack of native intelligence.

Various methods throughout markets – Resulting from differing compliance norms throughout international locations, segmentation accounting for world regulatory frameworks was an even bigger problem.


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