Augmented Analytics Use Cases for the Life Sciences Sales Function

Even the best life sciences sales teams need data to personalize presentations to decision-makers and convert prospects to sales. However, analytics tools that require data science expertise can create roadblocks to improving sales performance. Augmented analytics tools help life sciences sales teams overcome that hurdle. 

What is Augmented Analytics?

Augmented analytics tools use machine learning, deep learning, natural language processing (NLP), large language models (LLMs), and other forms of artificial intelligence (AI) to make insights accessible to any business user. These intuitive solutions allow life sciences sales reps simply to ask questions, for example, how a brand performed last quarter or details on a physician’s prescribing activity, and receive information immediately. 

With an augmented analytics tool, users don’t need to request that the IT team build a dashboard and run analyses. The tool understands users when they ask questions conversationally and responds with accurate, contextual responses presented in optimal visualizations. The self-service nature of augmented analytics decreases reliance on the IT department—by up to 50%, according to WhizAI data—and lowers data analytics total cost of ownership (TCO). But it also gives user analytics autonomy and makes it easy to build data-driven decision-making into routine workflows.

Augmented Analytics Use Cases in the Life Sciences Sales Function 

With instant, user-friendly access to data insights with an augmented analytics tool, life sciences sales teams can enhance processes, including:

• Accurate and automated sales forecasting: Augmented analytics can use historical data and the current state to automate sales forecasting. It can also streamline lead scoring, allowing sales teams to update data on each prospect to determine which are most likely to become customers. Using augmented analytics to provide this information instantaneously frees sales managers to focus more on strategy and planning. 
• Centralized sales data access: Leading augmented analytics platforms allow life sciences sales teams to manage their data centrally to base all analyses on current information.‍
• Dynamic daily planning: A sales rep needs to stay flexible and reprioritize activities based on changes in opportunities, the market, and schedules. Augmented analytics tools can optimize their calendars and make proactive recommendations. ‍
• Intuitive sales scenario planning with simulations: Augmented analytics can generate sales simulation models that reflect real-world challenges and allow sales teams to gauge the impact of different approaches on sales outcomes. ‍
• Personalized learning: These tools can also create training for new reps or educate teams on new products. The training can be divided into manageable sessions, allowing employees to complete it around their other responsibilities conveniently.‍
• Real-time sales performance management:
• Sales reps can access real-time data on their performance. They and their managers can track key performance indicators (KPIs), including sales volume, incentives, and compensation. A leading augmented analytics platform can also provide insights into how to improve performance.
• Role-based NBAs: Users’ interfaces can display the most important information to them. Sales managers can review territory alignments, salesforce allocation, and brand performance. Reps’ dashboards, on the other hand, can show customer information, call planning, product, upselling, and cross-selling recommendations. The augmented analytics tool can automatically deliver the right insights to the right people.  ‍
• Stratified maps: Life sciences companies can use augmented analytics to detect geographical differences in data. Additionally, it can add multiple layers of data to provide location-based insights and recommendations to users. Augmented analytics can also assist sales managers in optimizing sales rep territories for balance and the greatest revenue potential. 

The Benefits of Augmented Analytics

When life sciences sales teams have on-demand access to data-driven insights, the company will benefit significantly. The company will benefit significantly when life sciences sales teams have on-demand access to data-driven insights.Its sales strategy and performance improve, which leads to increased revenues, greater competitiveness, and higher data ROI. Insights from augmented analytics tools can also enhance customer engagement and brand reputation. 

The future for competitive life sciences organizations will include analytics autonomy for sales reps, an informed and strategic approach to each sales meeting, and data analyses tools that show life sciences sales teams how to improve performance. Organizations implementing these tools will gain a definitive advantage over competitors, with sales teams still waiting for IT to provide them with insights 100x more slowly.

Download the white paper from the Everest Group, “Transforming the Life Sciences Commercial Function with AI and Augmented Analytics,” to learn more about this technology that will increasingly differentiate market leaders from the rest of the field and to learn more about each of the above use cases.