How Conversational AI helped with the timely collection of valuable data from the field force to improve sales and marketing efforts and enhance the brand value.

The burgeoning Pharma sector is also a fiercely competitive one. With new diseases, new remedies, and new formulations on the block, every pharma company looks to grab the market and hold a major share. Making sure that the company’s reach is far and wide is its sales force.

Pharma Field force (or Medical Sales Representatives or Field Sales Officers) act as the face of the pharma company. They are not only responsible for generating a surge in product demand but also for building brand image through product promotion among doctors, chemists, distributors, and hospital pharmacies.

A young, award-winning Pharma Company, Integrace Health Pvt Ltd, has a field force of nearly 500 executives. They are required to regularly meet and communicate with healthcare providers (leads & prospects), persuade them with insights to make purchase decisions towards their products, and maintain good post-sales and services relationships. Technology is fast becoming a key enabler in helping them effectively perform daily activities and enhance productivity.

Challenges faced by Field Sales Officers

The Company’s field sales officers need to be well-versed with medical terms, practices, and pharmaceutical data like recent clinical trial results, etc., of their product segment. They are expected to be prepared with contextual and relevant product information to answer any client queries. Assimilating and accessing all these data in real-time is a challenge for these field operatives.

They are also expected to log in all the details of every meeting to a backend system through a web application. Manually recording this data required a lot of their time and effort. Being a repetitive and laborious task, it was observed that instead of sending updates every day, the Field Officers did it at regular intervals. This led to an accumulation of botched data as the employees tended to forget a few key details over time. Apart from covering data loss, the company realized that it would like to maximize the officers’ effort into actual sales targeting rather than being occupied with operational activities.

How SmarBots helped with Conversational AI

Conversational AI systems can help field force personnel perform their daily activities through natural language conversations. AI-driven virtual assistants (or chatbots) can understand the intent and purpose of the user query and respond intelligently based on the context. Conversational AI bots can handle how each user can request information, extract contextual information from the user responses, and drive conversations through meaningful questions to achieve the intended task.

Unlike the earlier web experience, where users had to navigate through dynamic menus, lengthy dropdowns, and sifting through numerous pages to locate the correct content, conversational AI systems deliver a more natural and seamless experience to get access to desired information through meaningful questions and answers. Powered with Chat and Voice interfaces, these bots can have a dialogue with users like a human-to-human conversation, providing an enhanced, 24/7, self-service employee experience.

Maggie – SmarBots Custom Voice Bot for Pharma Field Force

Maggie, India’s first voice-enabled bot for medical representatives, provides up-to-date product information and assists them with capturing daily activities like call reports effectively. At the end of each meeting, the field officers can record the details by conversing with Maggie. The bot asks for very specific information regarding crucial data and insight into bridging the information gap.

Maggie is:

  1. Mobile: Available on mobile, employees can speak to Maggie anytime, anywhere, to request any reports, product information, and log meetings. With natural voice commands, they can easily request the bot to schedule meetings, send reminders, and capture call records on its behalf, thus saving their time to focus on core tasks.
  2. Custom Integrations: With integrated support for custom data repositories, Maggie can connect to the enterprise data spread across diverse systems. It can be trained with the enterprise knowledge base and ontology to understand the enterprise and product-specific terminologies and semantics. Based on past interactions, it can be re-trained to adapt to the ever-changing requirements of field personnel.
  3. Smart Learner: Maggie learns from every conversation to enhance its repository of knowledge. In case it doesn’t know of an answer, it logs the question to be answered by the human helpdesk and makes sure to add the right answer to its knowledge base.

Maggie is powered by AWS Language Understanding service – Amazon Lex

Medical representatives talk to Maggie in English. Maggie, leverages the Natural Language Understanding (NLU) capabilities of Amazon Lex to understand the user intent. Amazon Lex also extracts the domain specific entities like names, medical terms, sales data etc. This information is further used to store in the backend systems or for processing the user requests. Amazon Lex is a fully managed ML service on AWS cloud that runs at scale and can easily handle the high volume that Maggie receives during its peak hours.

Maggie also uses other AWS services like RDS to store the conversation logs and Amazon Lambda to execute the business logic.

Reaping Benefits

Maggie has already been used for over half a million voice interactions and continues to be used for real-time reporting by the field team, thus helping the leadership team make the right strategic decisions. Integrace Health has already recorded:

  • 40% increase in data submissions
  • Significant increase in quality of information
  • 30% reduction in incomplete entries
  • 63% decrease in late entries

With Maggie, Medical representatives can now confidently walk into their next meeting with possible customers, with all relevant data available at their fingertip, and focus on closing the deal faster with greater efficacy.