AI-powered CRM: Path to Driving Customer Engagement in Life Sciences

IDC predicts the global spending on artificial intelligence (AI) will grow from USD 50.1 billion in 2020 to over USD 110 billion in 2024. One of the primary reasons for this growth is the increasing adoption of AI for delivering better customer experiences across industries. The life sciences industry too, after long being selective about adopting new digital customer interaction models, has recently started to show signs of embracing emerging business enablers like AI, machine learning (ML), and cognitive computing. With focus on end-to-end customer engagement, life sciences companies are beginning to utilize customer relationship management (CRM) tools beyond the traditional use backed by AI capabilities.

To foster customer engagement, sales and marketing teams depend heavily on actionable insights, predictions, recommendations, and targeted communication. They need automation to avoid repetitive tasks, scale, and increase speed-to-market. This is where AI-powered CRM can be a game-changer in helping the teams focus on elevating the customer experience, deliver personalized services, and increase customer lifetime value. By operationalizing AI in CRM, life sciences companies can benefit from customized predictions, suggest the next-best actions, offer recommendations, embed predictive insights, facilitate workflow, and help build personalized customer offerings.

AI + CRM: Formula for Success

AI can help life sciences organizations improve efficiency by reducing cost, expanding access, and optimizing the productivity of the sales and marketing teams. By leveraging AI-powered CRM, life sciences commercial teams can:

• Drive efficiency with insights derived by analyzing unstructured sales executive call notes and issue service requests, automate call planning for healthcare professionals (HCPs), offer suggestions on territory realignment, help update customer master data, arrange e-detailing assets, recommendations, and more. Additionally, integrated voice-enabled chatbots help report daily calls, record and suggest objectives for the next call, request samples or scientific collaterals on the go, and receive alerts or reminders.
• Eliminate repetitive, time-consuming, and multitasking functions, like submitting automated travel and expense statements, optimizing route planning, providing a response to HCP queries around product information, research updates, prescribing information, and so on. This helps optimize the time of the sales teams and allows them to focus on high-value activities to improve customer outcomes.
• Use custom chatbots on digital channels connected to CRM data to function as anytime-anywhere sales representatives. Chatbots can augment the sales function and provide immense value to executives with proactive recommendations based on the HCP profile and past interactions, upcoming medical conferences or events, product sampling, and surveys. It can also help arrange meetings with HCPs, provide remote detailing support, with 24/7 availability to boost customer engagement and drive customer service.

Advantage AI

AI-enabled applications are at various stages of maturity. Life sciences organizations need to explore, identify, and prioritize use cases and channels to engage the best option for driving customer engagement and delivering human-like experiences with embedded AI.

Apart from spearheading process efficiencies, life sciences companies can utilize AI-enabled CRM to gain a competitive advantage with valuable, near-real-time, and actionable insights into customer behavior and competitor data. It can also help tailor multichannel marketing campaigns for HCPs to increase marketing reach. Life sciences organizations can leverage AI to analyze multiple data points, including demographics, consent and preferences, geographic proximity, and call history, to gain recommendations on preferred messaging, channels, and customer segments.

Let AI guide you to success

CRM vendors are expected to continue with AI innovation. The industry may see AIOps and embedded AI going mainstream in CRM applications. Enterprises would stay on to work on the security of AI, while continuing to explore areas of integrated social CRM, self-servicing models across channels, advanced image analytics, efficient content management and so on.

Organizations that wait for AI perfection may miss the current opportunity and potential, especially for businesses that want to stay ahead in the competition. Going forward, AI feature would become more prominent compared with all other CRM features in this digital era of marketing. However, human interactions are still highly valued as trustworthy and when used along with AI it will help create a better customer experience.