The Benefits of Conversational Analytics for Life Sciences

Conversational analytics combines forms of artificial intelligence (AI), such as natural language processing (NLP), natural language query (NLQ), natural language understanding (NLU), and natural language generation (NLG). These technologies allow users to communicate with machines as if they were speaking to another person – and receive contextual insights in return.

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WhizAI’s conversational analytics capabilities allow the platform to understand and analyze users’ queries, whether typed or spoken. WhizAI uses data from human speech to continually learn. The platform learns what’s most important to the user, how individual users interact with it, and how to respond with exactly what the user is looking for.

See How WhizAI Brought Conversational Analytics to a Top 3 Global Pharma Company

Each type of artificial intelligence that contributes to WhizAI’s user-friendly augmented analytics platforms has a specific role to play in creating conversational analytics.

  • NLQ allows users to ask questions in natural language.
  • NLU enables a platform to understand human speech and intent.
  • NLG gives a machine the ability to generate responses that users can easily understand.
  • Machine learning allows the platform to be pretrained for life sciences and then continue to learn as users ask questions and request additional information.

See How WhizAI Brought Conversational Analytics to a Top 3 Global Pharma Company

One leading pharmaceutical company offers medications and treatments to people in 26 countries, and teams in each region have unique analytics needs. The company needed a platform that provided self-service analytics to its multinational organization.

The legacy analytics solution that the company used required heavy intervention from the IT department, and requests from employees throughout the company monopolized much of the IT teams’ time. Furthermore, users struggled with this lack of autonomy, always forcing them to wait for help when they needed data analytics insights.

The company implemented WhizAI’s intuitive, multilanguage platform that translates life science team members’ unstructured queries, analyzes data and provides the insights they need for data-driven decision-making. Additionally, WhizAI tailors responses to individual users and learns with use, understanding how each team member speaks and asks questions and continually refining responses.

Furthermore, WhizAI’s user-friendly approach to analytics has resulted in nearly 100% user adoption, the lower total cost of ownership (TCO) for data analytics, and more efficient, competitive operations.

What Makes WhizAI Different From Other Analytics Platforms

Pretrained for Life Sciences

WhizAI is the only augmented consumer platform specifically designed to provide data insights via conversational analytics to life sciences teams. It is pretrained with life science data to understand how people on life sciences teams speak, including acronyms and abbreviations. It’s also capable of using data from multiple life sciences sources to provide answers to complex questions.

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Speed and Scalability

Life sciences employees accustomed to waiting weeks for their IT or data teams to build new dashboards and run analyses will appreciate WhizAI’s speed. It can analyze billions of data points from multiple sources in less than a second. Additionally, WhizAI’s microservices architecture gives it limitless scalability while maintaining speed and performance.

Enterprise Ready

WhizAI deploys quickly and is also fluent in five languages – English, French, German, Spanish, and Italian – to enable global team members to use the platform in their preferred languages. The platform also includes access control at record, row, or role level while applying user authentication. Data is also protected in transit and at rest.

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Multi-Channel Access

WhizAI users can access insights on their mobile devices, via web browser, or through messaging tools like Slack. It also integrates with the applications that life sciences teams use, such as Microsoft Teams, Veeva, and Salesforce, making it easy for employees to build data-driven decision making into their daily workflows.

Conversational Analytics

WhizAI also stands out in the market as the only platform that effectively delivers conversational analytics to the life sciences industry. Users don’t have to choose from a menu or use key phrases when they enter a query. They just type or talk as if they’re having a conversation, and the platform learns and responds with relevant, contextual answers.

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Frequently Asked Questions

How does WhizAI help users arrive at the insights they need?
WhizAI has its own life-science-focused library of algorithms that it uses to identify insights automatically from the data landscape. WhizAI is working to build this library, focusing on prediction models. WhizAI also seamlessly integrates with third-party data science algorithms.
Can we integrate WhizAI with our organization’s landing page?
WhizAI supports integration with landing pages via multiple options.
Which companies use WhizAI?
WhizAI is currently helping life sciences teams in top 3 global pharma companies as well as smaller organizations in different parts of the world.
Can WhizAI work with the algorithms our data science team has created?
Yes. You can use WhizAI with your algorithms to add a self-service element to accessing insights, make them more user-friendly regardless of employees’ data science expertise, and encourage data-driven decisions.
What kinds of data sources can WhizAI use?
WhizAI is designed to use life sciences data sources, both external and internal. It can connect to data sources via API as well as use data stored for corporate use.

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