A few days ago, the editorial team of Yaowenjiaozi announced the top 10 buzzwords of 2023, and "large artificial intelligence model" made the list without surprise.
Top 10 buzzwords of 2023. Source: Yaowenjiaozi editorial team
This era is no longer only an era of digitalization; we have entered the starting point of digital intelligence. Although digital intelligence is more than AIGC, AIGC is undoubtedly the easiest part to understand, the most anticipated, and the hottest.
Today, using digital-intelligence transformation to reduce costs and improve efficiency has basically become a consensus, and the life sciences industry is no exception. In conversations with many pharmaceutical companies, we found that they have accumulated large amounts of information data and business reports, but:
- Data is scattered across different systems and cannot form effective connections with each other.
- Most reports are single-dimensional and cannot comprehensively or objectively reflect engagement effectiveness and customer insight.
Digital-intelligence transformation is not the accumulation of business reports; it is the deep integration of data and artificial intelligence technology. To this end, MeDomino developed AIGC-powered customer (HCP) insight, using four steps to help pharmaceutical companies achieve precise engagement:
Step 1 Understand group engagement effectiveness from trends and conversion in key indicators
a. Extract public data from group and individual customers, including online consultations, meeting speeches, article content, and clinical trial research. Deeply mine and continuously track customer mindsets.
b. Use "customer mindset" as the starting clue, clarify trends and internal conversion logic in customer mindset changes, then divide data across dimensions such as time, BU, and TA. Explore engagement across channels and dimensions, and combine customer mindset to analyze the engagement behind changes.
Step 2 Expand channel-engaged customer characteristics to understand customer group profiles
a. Convert HCP engagement data into customer attribute information and clarify all characteristics of group customers, such as physician level, physician mindset, department, city tier, and market type.
b. Quantitatively analyze HCP collaboration with competitor companies, including collaboration forms, collaboration volume, competitive landscape, and other information.
c. Use HCP relationship data to understand collaboration information and collaboration preferences between HCPs, quickly locating more target HCPs with similar collaboration preferences.
Step 3 Present hospital-level business data and cover customer characteristic information
Through hospital-level business data, combined with insights into customer interests, preferences, and needs, business personnel can receive targeted suggestions and recommendations, helping them better interact and communicate with customers and guiding relevant business advancement strategies.
Step 4 Reorganize omnichannel engagement data to form effective HCP profiles, clarify individual characteristics, and achieve precise reach
a. Present HCP engagement data within the system on a timeline by engagement channel or type, providing reference for different departments' engagement and showing whether different departments have repeatedly engaged the same HCP.
b. Present metrics from different engagement channels to understand HCP feedback to each channel and provide reference for engagement strategy.
c. With physician tags and external data, understand HCPs more comprehensively, form effective HCP profiles, and maximize precise insight and proactive marketing.
Final Thoughts
1. If successful digital transformation depends on fully using data;
2. Then successful digital-intelligence transformation depends on fully using AI technology to achieve data-driven intelligent decision-making and business optimization through data analysis and insight, intelligent decision support, automated and intelligent business processes, and personalized intelligent customer experiences.
3. MeDomino's mission is to use the power of data and AI technology to drive transformation in the life sciences industry, helping enterprises accelerate into the era of digital intelligence, obtain business value from data faster, and empower the enterprise more effectively with AI.
Borrowing one of the top buzzwords of 2023, MeDomino hopes to use big data + AI to work hand in hand with more life sciences companies and jointly achieve digital-intelligence transformation.
