How to Embed AI into Sales for Greater Results

Introduction

It’s hard to overstate the importance of sales representatives in the pharmaceutical industry. Pharmaceutical companies have always depended on the close relationships forged with healthcare providers (HCPs) by their sales teams. Despite a historical resistance to change, though, these relationships are now being forced to evolve in the wake of COVID-19 and market disruption from innovative start-ups.

However, while the digital transformation has greatly impacted some parts of the pharmaceutical industry, few sales departments have succeeded in unlocking its terrific potential, struggling as a result to maintain client relationships as HCPs remain closed to face-to-face meetings and the market changes.

Artificial intelligence (AI) is revolutionizing sales processes in industries around the world, allowing for a most customer-centric and data-driven approach. Pharmaceutical companies that are able to fully leverage AI, machine learning (ML), and other digital tools will benefit greatly, reversing the deleterious effects of COVID-19 and market disruption and coming out the other side stronger than ever.

The emerging role of AI in pharmaceutical sales

As a historically data-rich industry, pharmaceuticals is well-positioned to benefit from artificial intelligence.

“The sector has managed to collect significant information about its healthcare professional customers—their demographics, specialty, educational background, institutional affiliations, and prescribing behavior,” writes Pratap Khedar, CEO of analytics and consulting firm ZS.

“Compare the data coverage and availability in pharmaceuticals with that of leading e-commerce providers such as Netflix or Amazon: The online outlets have great data on their products … [but] very limited customer information, something that’s critical in driving a differentiated customer experience.”

This wealth of data can be used by pharmaceutical companies to great effect. Indeed, in a previous article, I discussed the new role of AI in pharmaceutical market research. All along the value chain, the power of AI is reshaping market research thanks to intelligent automation, data-driven predictive analytics and decision-making, natural language processing (NLP), and more. Sales teams are just now starting to use these tools—and the benefits, as we’ll see, are enormous.

How AI is transforming sales worldwide

What follows is a brief overview of how artificial intelligence, machine learning, and other digital tools are being used to transform sales processes in pharmaceuticals and beyond.

 
Predictive forecasting
Predictive forecasting is an analytic technique that allows businesses to extrapolate probable future conditions (like those of the pharmaceuticals market) based on existing data.

Predictive forecasting models have been around for a long time, but AI is taking things to a whole new level. AI models are able to ingest enormous amounts of data from highly distinct sources, intelligently organize and analyze this data, and then produce recommendations based on your sales team’s existing goals and capacity.

Predictive AI solutions are already being used by businesses to predict changes in demand. This information can then be used to direct resources, adjust prices, and improve supply chains.

 
Lead generation
Lead generation refers to the process of attracting potential new customers and is an essential component of pharmaceutical sales. AI is being used to improve lead generation in a number of ways.

Virtual sales assistants who interact just as a human would, such as those offered by several companies, are an important example. These are AI-powered, natural-language chatbots (a term that fails to fully capture their sophistication and capacity for human-like interaction) that can leverage the full range of data available to your sales team. I was speaking with one of these via email for over a week and did not realise I was not interacting with a human sales agent. Businesses that use these kind of VSAs for lead generation see remarkable reductions in cost.

Email marketing is another area where AI is making waves. It can be used to generate uniquely personalized content for subscribers, intelligently segment readers into more granular and useful categories than traditional demographics, optimize headlines and content based on practitioner engagement, perform advanced A/B/n testing, and generate analytical insights and human-readable reports.

 
Personalized customer journeys and multi-channel marketing
Most sales teams manage conversations with hundreds if not thousands of HCPs. Pharmaceutical companies have traditionally relied on relatively inflexible, single-tactic customer journeys, largely because operating otherwise would be enormously costly and complex. However, AI can now generate highly personalized customer journeys for HCPs by region, past sales interest, and even practitioner publications and online activity.

Additionally, AI excels at multi-channel marketing approaches, as AI platforms can bring together any number of channels into one seamlessly organized, data-driven conversation. Machine learning can be used to better understand customers’ communication preferences across channels and integrate this information into that customer’s personalized journey. That same data, of course, can be used downstream to inform future customer interactions.

 
AI-powered Next best action
Imagine you could quantify and reproduce the expertise and wisdom of your most experienced sales reps, those whose years of experience have allowed them to develop the intuition and insights to know the next best course of action to take with any lead.

AI is now able to do just this—and make that knowledge available to every sales representative on your team. This approach leverages many of the same AI tools as those used to improve the customer journey, but on a far more granular level, providing representatives with the right content for the right channel delivered at the right time and to the right customer, for thousands of customers. Top-line can increase by up to 30% as a result of successfully implementing next best-action programs.

 
Improved customer interactions and detailing
These insights extend, of course, to customer interactions and detailing—the pharmaceutical rep’s bread and butter. AI-generated customer insight reports, based on data drawn from internal and external sources, enables representatives to better understand what products their customers may be interested in and which offers are most likely to convert them—all delivered to the rep in real-time. Compare this approach to traditional approaches, in which nearly a quarter of pharmaceutical reps’ time is spent gathering data, and the advantage is clear.

Furthermore, several new AI tools have emerged that enable sales representatives to gain keener insights into what works (and what doesn’t) on sales calls. So-called AI conversation coaches analyze not just language, but mood and tone as expressed via a customer’s voice, body language, and facial expressions.

Companies like (the cleverly-named) Cyrano.ai, for example, can analyze your calls, cross-reference them with measures of success like conversion to help representatives communicate more effectively, detail more efficiently and successfully, and learn more from sales calls.

 
Scheduling and follow-up automation
Automation was one of AI’s first great contributions to the world of sales and marketing, and it remains a key component of all AI-powered sales teams. There is no shortage of AI platforms offering such functionality. Indeed, most CRM solutions today have quite robust AI-powered scheduling and follow-up automation built-in.

Intelligent chatbots with access to customer data can take care of the brunt of scheduling, but this is only the tip of the iceberg. Intelligent follow-up automation can make a huge difference when it comes to dropped or lost leads. Software solutions exist that work in the background to carry on conversations with potential or existing customers, up until a salesperson is ready or needed to step in (because the customer is ready to buy).

Personalized messages sent at appropriate times to follow up on either remote or in-person detailing, with the information most relevant to HCPs delivered in human tones—for thousands of leads, without a single conversation lost to human error. AI’s oldest and most simple application is still one of the most important.

 
Will AI replace sales teams?

Not anytime soon. Artificial intelligence remains a tool, to be used by representatives and other experts. Machine learning, natural language processing, and neural networks have been built into sophisticated applications, but these tools augment, rather than replace human salespeople. The emerging role of AI in pharmaceutical sales is thus a supporting one.

In fact, one of the great benefits of AI is that it can rapidly and accurately perform all the repetitive tasks and complex analytics that humans, by comparison, don’t have the ability or time to do. What this does, however, is free up those same humans to focus on areas where they excel: human interactions with providers; intuition and wisdom built from years of real-world sales experience; and, of course, mapping the entire sales process in a way that matches the company’s overall goals, principles, and organization.