WhizAI at PMSA - Making Analytics for Commercial Teams Faster and Easier with Expanded Insights
I am excited that WhizAI will be at the PMSA Annual Conference as a gold sponsor next week, hosting a roundtable, leading a presentation session, and being an exhibitor at the show. Most exciting to me as a product manager is we are showcasing our platform capabilities for helping life sciences organizations make better, faster, and smarter decisions. If you're attending PMSA, schedule a meeting with us to see the following WhizAI capabilities in action.
Expanding Insights for Better Decision Making
With predictive analytics, users can go beyond knowing what has happened to provide the best assessment of what will happen. Predictions will help every life sciences organization make better business decisions. It helps in overall business planning, budgeting, risk management, and efficient resource allocation. Predictions will help sales reps achieve their goals by identifying early warning signals in their sales pipeline and course-correct before it's too late. Home Office and field teams can see market share, TRx, and NRx predictions at any level.
Anomaly Detection and Alerts Provide Next-Level Analytics
WhizAI uses machine learning (ML) algorithms to proactively uncover insights by automatically scanning through the data and identifying anomalies within the life sciences context. Insights are sent as alerts so that users can jump-start the root-cause analysis with a single click. Our alert capabilities empower users to build alerts around broader parameters rather than only using simple mathematical equations. It is a powerful analytics platform that can help you stay aware of complex event patterns.
Diagnostic (Causal) Insights
An essential requirement in today's analytic environment is understanding why events occur. WhizAI ML algorithms can analyze the causal relationships for the performance of a metric. For example, you notice that Plabenil TRx is down in the Northeast. The next logical question for a sales representative is, "Why is TRx down for Plabenil in the Northeast?" By asking this simple question, WhizAI will reveal the cause is "Tier 1 doctors have not been called on during the quarter."
Narratives for Data Storytelling
Narratives are all about transforming the data into a 'natural language' for users to understand the data better. Our users interact with WhizAI in a natural language by asking questions, and the system responds with a visual representation of the requested data. Narratives then transform the requested data into 'natural language' for users to understand the data better. The benefit to users is this provides a standard interpretation or story of the data for all the users. Uniquely, our narrative capability is native to our platform, and our system automatically generates the natural language.
Advances in Life Sciences Focus
Automated Contextual Calendar Switching
When running time-based queries on various data sources, displaying the correct information can be complicated due to discrepancies in data collection periods. This capability allows users to automatically switch between a regular Gregorian calendar for TRx sales analysis and a custom 4-4-5 calendar used in life sciences for financial reporting analysis. This is done based on a data source. CRM data use a Gregorian calendar, and financial data sources aggregate data based on a 4-4-5 financial reporting calendar. The solution will automatically switch to a custom calendar if a user asks to see TRx sales volume in a 4-4-5 calendar. And, if they want a deeper analysis of TRx penetration, NRx for new prescribers, and PDot penetration for the quarter, the solution automatically understands intent and switches to Gregorian. Our automated calendar switching understands the context of the data and uses the correct start and end periods to calculate and generate the response.
Enhancing Ease of Deployment and Administration
WhizAI Data Modeler for Easier Data Integration
With WhizAI, you can expect rapid deployment and effortless integration, leveraging our out-of-the-box data adapters to rapidly integrate diverse data from different systems. The WhizAI Data Modeler provides a user-friendly UI to build WhizAI-supported data models. We also automate the data ingestion process so our partners can easily transport raw data from their site to our data model faster and with less effort and get up and running quickly.
We support six types of connections for data transport - three file-based connections (local files, remote files, and Amazon S3 files) and three database connections (Postgres, Snowflake, and Amazon Redshift). With our Data Modeler, customers and partners can manage solution pipelines, link data sources to a data model, identify dimensions and metrics, define hierarchies, attributes and synonyms within a data model, and configure our hybrid NLP engine.
We believe a new era is dawning in analytics, and WhizAI is leading the market in bringing new AI-powered analytics capabilities to life sciences. Our engineers and product development teams lead the industry in practical applications for guided and embedded analytics, natural language query and generation, causal inference, and AI and ML. We are excited about the future. Thank you to our team of powerhouse innovators.
Request a live demo to learn more about the WhizAI platform.
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