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Building Pharma Sales Momentum with AI & ML-led Technologies

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Pharma Sales Enablement

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Artificial Intelligence (AI) & Machine Learning (ML) are rock-solid use cases for pharma sales enablement. They can help enterprises in aligning sales & marketing teams, minimizing friction between them, accurately reaching the right target audience, simplifying sales cycles, and driving business growth. Leading Pharma companies are able to simplify sales cycles and reach many tangible benefits downstream. Others must follow to remain competitive and relevant. Modern-day pharma companies must break their previous molds and transition to AI & ML-led technologies for spurring business growth and driving sales momentum. Here is how AI & MI-led technologies are making inroads into the pharma landscape and enabling it to transcend.

Typical Revenue Enablement Pharma Sector

The pharma sector is one of the earliest adopters of AI & ML technologies. Smart enterprises are already using it for fast-forwarding the drug discovery processes. They are aligning people, processes, and technologies for faster manufacturing of minimum viable products and streamlining the supply chain. However, its applicability to pharma revenue enablement is fairly new. Pharma sales processes are still running on archaic business systems. There is a lack of alignment between sales and marketing processes that work on different goals. Friction arises when the marketing teams generate leads and fail in handing them over to the sales teams on time. Another relevant challenge is the inability to build the right database of prospects. The sales communication often lands in the wrong inboxes. This leads to several inefficiencies in the sales and marketing processes. The pandemic further added to the woes of pharma companies as the demand for life-saving drugs grew by manifolds. The supply chain and sales collapsed due to the sudden surge in demand.

Skewing the Pharma Sales Trajectory

Driving ROI-driven sales & marketing operations: AI & ML can help in initiating ROI-driven and optimized sales and marketing operations. The technologies can be cross-leveraged to identify opportunities and optimize marketing spend. It can recommend the most effective sales strategy based on account market conditions, customer needs, and competitor moves. This results in increased revenues and market share.

Pharma companies use a lot of channels for marketing their products – emails, telemarketing, social media, etc. Each campaign needs to be carefully planned and executed for optimum results. AI & ML can help in better targeting the right audience with relevant messages and improving response rates.

Simplifying sales cycles: It’s no secret that pharma sales cycles are getting more complex. They are becoming lengthier and often involve multiple decision-makers. AI & ML can help in shortening the sales cycles by automating several processes and tasks.

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Segmenting leads: It’s easier to target high-quality leads when they are segregated into different groups. This way, the sales teams can focus only on quality leads that matter. AI & ML can help in automatically segmenting the leads into different categories. The leads can be targeted on the basis of their preferences, needs, and buying stage. This advantage builds speed and scale in the sales processes.

Building sales enablement database: A well-built AI & ML sales enablement database can help in building an accurate database of prospects for marketing and outreach campaigns. FIrmographic, demographic, technographic, geographic data of customers can be used for extracting from-the-trenches insights of prospects. It helps in identifying buying signals and qualifying leads through the funnel. Moreover, complex jobs like data validation, data maintenance can be simplified to a large extent.

Establishing smoother symbiosis between sales and marketing teams: AI & ML can enable a symbiotic relationship between sales and marketing teams. The technologies can be used to develop a closed-loop feedback system between the two teams. The technologies can also be used to create a centralized customer view for both teams. This will help the sales team to get real-time updates about customer engagement with the brand.

Weeding out supply chain inefficiencies: Transcendent AI and ML-tech bundle virtual and real-time dashboards. These dashboards can identify and rectify supply chain inefficiencies as they occur. This unique advantage helps improve the costs, optimize supply chain costs, and ensure a continuous supply chain without disruption.

Personalizing sales communication: AI & ML-led technologies can personalize the sales communication for each customer. It identifies the right prospects and sends relevant information to the relevant audience. This helps in minimizing missed opportunities and shortening the sales cycle. It also helps in better understanding customer needs and preferences.

Creating serendipitous experiences: Serendipity is the art of making happy accidents. It’s about finding something valuable or delightful that you weren’t expecting to find. AI & ML-driven chatbots can help in creating serendipitous experiences for customers and prospects. The technologies can be used to identify customer needs related to drugs or medicines and strategically address them at the right time. Complex tasks like onboarding certificates or accepting orders can be fast-forwarded in minimum moves.

Conclusion

The Covid-19 pandemic has over wrecked many pharma sales processes when the demand for medicines skyrocketed. AI and ML in Pharma can crunch a big chunk of Big Data and turn it into intelligence for sales enablement. It can give strategic new advantages to pharma sales teams by enabling actionable insights about the target market and target audience. Pharma teams can move their sales teams towards the stream of opportunities where business is being done.


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