Analytics Solutions for Pharma Industry | Pharma Analytics
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    Turn Commercial Pharma Data Into Better Decisions

    From HCP targeting and next best action to field-force effectiveness, commercial planning and incentive compensation, your pharma data is hiding insights.

    Talk to Pharma Experts
    Pharmaceutical
    Questions you ask based on your commercial pharma challenges

    The data exists, but there's a lot of opportunity to connect those signals across CRM, customer, sales, engagement, planning and performance data

    Customer
    Customer
    Who should we focus on?
    Find the HCPs and accounts with the greatest opportunity and keep priorities current.
    Engagement
    Engagement
    What should we do next?
    Turn customer and engagement signals into practical next best actions and channel choices.
    Economics
    Economics
    Where should we invest?
    Compare scenarios for territories, resources, campaigns and commercial plans before committing.
    Learning
    Learning
    What is working?
    See what changed, understand the drivers and feed the learning into the next cycle.
    Stop the leakage in Commercial pharma analytics loop

    Data becomes intelligence, intelligence becomes a decision, the decision becomes field action, the action produces an outcome, and the outcome should teach the next decision. That last step is where most commercial units lose the plot. We work on four stretches of this loop, and each one hands off to the next.

    Commercial pharma analytics loop
    On the loop: Data → Intelligence → Decision

    Customer Intelligence & Prioritization

    Who matters, why, and what should we do about them next?

    Fragmented HCP and account signals become one usable customer view, then a ranked list with a recommended next best action. Segmentation, targeting, propensity, opportunity and account strategy are one problem, so we treat them as one.

    What sits inside

    Segmentation & NBA HCP 360 / Customer Intelligence KAM Intelligence
    On the loop: Decision → Action

    Engagement & Omnichannel Decisioning

    How do we engage, through which channel, and what is actually working?

    Channel, content, timing and response signals in one place, so the next interaction is chosen rather than repeated. Campaign exposure and response feed straight back into targeting and investment instead of sitting in a separate report.

    What sits inside

    Engagement & Intelligence Omnichannel Decisioning & Orchestration Brand / Campaign Optimization
    On the loop: Action → Outcome

    Field Alignment & Incentives

    Is the field pointed at the right work, and does the payout agree?

    Territory potential, workload and coverage decide where capacity goes. Goal setting, attainment, payout and scenario analysis decide what gets rewarded. Run them apart and you pay people to chase last year's map.

    What sits inside

    Incentive Compensation Sales Force Effectiveness / Territory Optimization
    On the loop: Outcome → Learning → Data

    Performance, Forecasting & Planning

    What changed, what does it mean, and what should we commit to next?

    Sales, brand, territory, rep and campaign performance read in one decision context, then carried forward into demand and revenue planning and into modelled trade-offs before budget or headcount is committed. This is the stretch that closes the loop.

    What sits inside

    Commercial Performance Intelligence Commercial Forecasting Commercial Planning & Scenario Intelligence
    Built to work with your existing commercial stack.

    CRM, CDP, MDM, data platforms and planning systems stay exactly where they are. We sit on top as the intelligence, decisioning and optimization layer.

    Talk to Pharma AI experts
    HCPPulse shows which HCP to focus on and what to do next

    Bring HCP, prescription, CRM engagement and market data together to help commercial teams identify the highest-value opportunities and act on them with a clear next best action.

    Explore HCPPulse
    4X
    Higher
    Rx impact

    Versus rep-led models without AI scoring

    40%
    Higher rep
    productivity

    Through focused HCP targeting and guided field execution

    80%
    Faster decision
    cycles

    From insight generation to field action

    HCPPulse
    From 2.5 days to less than a minute: faster supply-chain decisions for Micro Labs.

    Polestar Analytics helped Micro Labs Germany replace fragmented, spreadsheet-led planning with integrated demand and supply planning across its manufacturing, sales and operations teams

    <1 Min.

    Penalty report generation
    Down from 2.5

    30 Min.

    New product integration

    Explore Micro Labs SCM planning
    Agentic Intelligence in Pharmaceutical Commercial Excellence

    Eight use cases of Agentic AI in commercial Pharma from HCP segmentation and sales forecasting to decision support

    Agentic AI in pharma use cases
    Agentic Intelligence in Pharmaceutical Commercial Excellence
    Proven AI impact across pharma commercial teams.
    Streamlined ICM process with Anaplan for a global healthcare equipment giant for their NAM region
    Streamlined ICM process with Anaplan for a global healthcare equipment giant for their NAM region
    • 43%

      Improved decision making

    • 100%

      Automation across Anaplan models and the Data Hub

    • 70%

      Reduction in time spent on target setting

    See how we did it Arrow
    Analytics & Reporting Enablement for a US Healthcare Organization
    Analytics & Reporting Enablement for a US Healthcare Organization
    • 50-70%

      Reduction in executive reporting time

    • 60+

      KPI cards redesigned across dashboards

    • 15K-20K

      Reports enabled for structured tracking and improved visibility

    Explore the full story Arrow
    Achieved 17% Cost Savings with FinOps on Azure Databricks for a Global Pharma GCC
    Achieved 17% Cost Savings with FinOps on Azure Databricks for a Global Pharma GCC
    • 17%

      Reduction in Azure Databricks spend through workload and cluster optimization

    • 100%

      Visibility into cloud costs across domains, projects, and workloads

    • 150k+

      Datasets rationalized by eliminating redundant pipelines and scripts

    See the implementation Arrow
    Why pharma teams choose Polestar Analytics?

    Pharma decisions are interconnected across clinical, commercial, and access. Polestar Analytics brings these signals together, so every decision is informed, timely, and aligned across the lifecycle.

    Enterprise-grade security & compliance

    Your data never trains our models. Full audit trails. Deployment on your own cloud environment. Validated for use in GxP environments with audit-ready outputs for regulatory submissions.

    • HIPAA
    • SOC 2
    • GxP-Ready
    • 21 CFR
    Talk to Pharma & LS Expert
    • 01
      Pharma DNA, not retrofitted AI Built for pharma workflows from day one. Not a horizontal analytics tool with a life sciences module bolted on. Every model, metric, and output is calibrated for the industry.
    • 02
      Agentic workflows, not dashboards Our AI agents don't just surface insights - they take the next step. Automated recommendations, triggered field actions, closed feedback loops. The dashboard is the output, not the product.
    • 03
      8 weeks to live. Not 18 months. Average deployment: 8 weeks. First meaningful insight: Day 14. We've done this across 50+ engagements. Your team has a launch to plan - we won't slow it down.
    • 04
      Stack-agnostic. Works across Azure, AWS, Databricks, Snowflake, and Veeva CRM, Salesforce Health Cloud, and IQVIA OCE - without a rip-and-replace. Our standard connectors cover 85% of the pharma data estate out of the box.
    • 05
      Purpose-built for Emerging Pharma, not just top-20 Commercial AI shouldn't require a 500-person data team. Polestar Analytics deploys for emerging and specialty pharma with the same enterprise-grade models, lighter footprint, and time-to-value under 8 weeks.
    Make your data AI ready without any rip-and-replace

    Polestar Analytics plugs into the CRM, data platform, and planning tools your commercial team already runs. No rip-and-replace, no migration project to greenlight first.

    Commercial Pharma What we do at each layer
    Three layers. One decision at the end of it.

    Across all three: MLR consent privacy. audit trail

    Commercial Applications

    Where the decision gets made & owned. Brand, sales ops, omnichannel, KAM, IC.

    Segmentation & NBA Omnichannel decisioning Campaign optimization Incentive design & payout KAM & account strategy Forecasting & scenario planning Performance intelligence Territory & field sizing
    03
    Interface Layer · Studio

    The governed surface teams build on, and the route a decision takes to the field.

    Data governance AI governance & guardrails Model & agent catalog Consent & channel preference Territory-level access control Delivery into CRM Governed decision APIs
    02
    Foundation Layer

    The data and plumbing everything above it inherits, for better or worse.

    Data readiness assessment HCP & account MDM Rx, claims & specialty integration Data engineering Data Ops & FinOps ML engineering & ML Ops
    01

    Read it bottom up. Fix the foundation, govern the surface, and the commercial team stops waiting on a report to make a call.

    Our latest thinking on commercial Pharma solutions
    • Pharma
    • Agentic AI
    The Future of Specialty Pharma: Blending AI and Emotional Intelligence
    Field Force Effectiveness in Pharma
    • Farmacie
    • AI
    Field Force Effectiveness in Pharma: From Call Plans to Next Best Action ft. HCPPulse
    Databricks for CPG, Retail, and Life Sciences
    • CPG
    • Farmacie
    What Polestar Analytics Builds on Databricks for CPG, Retail, and Life Sciences?
    Frequently Asked Questions

    AI in the pharmaceutical industry helps companies optimize commercial performance through HCP targeting, territory alignment, rep call planning, prescription trend analysis, and promotional effectiveness measurement. By leveraging AI for pharma, including predictive models and real-time analytics, organizations can identify the right physicians, channels, and engagement timing to improve field force productivity and drive higher brand adoption.

    Yes. As part of our pharma AI capabilities, Polestar Analytics helps companies map the end-to-end patient journey, from cohort identification and diagnosis to treatment initiation, adherence, and persistence. Our AI-powered models identify drop-off points, predict non-adherence risk, and recommend interventions that improve patient outcomes, especially in specialty and rare disease therapies.

    Analytics powered by AI in pharmaceuticals enables brands to accurately measure the impact of digital campaigns, field force activities, media investments, and HCP engagement strategies on prescription lift and revenue outcomes. Using AI for pharmaceutical industry use cases like forecasting and MMM, leadership teams can optimize budget allocation, improve ROI, and make faster data-driven decisions.

    Polestar Analytics combines deep domain expertise in life sciences with advanced capabilities in AI, machine learning, data engineering, and decision intelligence platforms such as Anaplan and cloud analytics ecosystems. We focus on scalable, business-impact-driven solutions that improve commercial growth, operational efficiency, and patient-centric decision-making.

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