Written by: Amaninder Dhillon

Segmenting and targeting are critical components of any successful marketing strategy, and the pharmaceutical industry is no exception. In a highly competitive and constantly evolving industry, pharmaceutical companies must be able to identify and understand the needs and preferences of their target audiences and develop tailored marketing campaigns to effectively reach them. By segmenting and targeting their audiences, pharmaceutical companies can maximize the impact of their marketing efforts, increase brand awareness and loyalty, and ultimately, drive sales and revenue growth. In this regard, segmenting and targeting are not just important, but essential for success in the pharma industry.

Sharing a use case of AI prompted persona of an Oncologist

A general list of potential social and professional personas of oncologists practicing in India that could help a pharma marketer better understand and target their audience. It’s important to note that each oncologist is an individual and may not fit into any of these categories perfectly.

1. Research-oriented oncologists: These oncologists are highly focused on research and may prioritize clinical trials and data-driven treatments over more traditional methods. They are likely to be active on professional social media platforms and attend conferences and meetings to stay up-to-date on the latest research in the field.
2. Patient-centric oncologists: These oncologists prioritize the well-being of their patients above all else. They may be active on patient support groups and may focus more on the quality of life of their patients rather than simply treating the disease.
3. Traditional oncologists: These oncologists may prefer more traditional methods of treatment and may be more skeptical of newer, innovative treatments. They may also be more hesitant to engage with social media and may rely more on in-person networking and referrals.
4. Academically-oriented oncologists: These oncologists may be highly focused on academic research and teaching, and may prioritize education over the clinical practice. They may be involved in teaching and mentoring younger oncologists, as well as conducting research and publishing papers.
5. Collaborative oncologists: These oncologists prioritize collaboration and teamwork with other healthcare professionals, including other oncologists, nurses, and other support staff. They may be active in networking and may value open communication and a multidisciplinary approach to patient care.
6. Business-oriented oncologists: These oncologists may be focused on the business side of running a medical practice and may be more interested in marketing and branding themselves and their practice. They may also be more active on social media platforms and may prioritize building a strong online presence.

ChatGPT recommendation for each of the persona

I would design a targeted omnichannel marketing campaign for each of the different personas of oncologists listed, with the goal of reaching and engaging each audience segment effectively.

For research-oriented oncologists, I would leverage professional social media platforms, such as LinkedIn and ResearchGate, to share research updates and clinical trial results relevant to their areas of interest. I would also invest in targeted email campaigns to highlight new publications and research opportunities that may align with their research goals.

For patient-centric oncologists, I would create patient-centered content, such as videos or infographics, that focus on improving patient outcomes and quality of life. I would also invest in targeted social media advertising, with a focus on patient support groups, to reach patients and their caregivers with relevant content and resources.

For traditional oncologists, I would prioritize in-person networking and events, such as industry conferences and trade shows, to build relationships and establish credibility with key opinion leaders in the field. I would also consider targeted print advertising in professional journals and publications to increase brand awareness and engagement.

For academically-oriented oncologists, I would focus on thought leadership content and educational resources, such as webinars and whitepapers, to establish our brand as a leader in the field. I would also invest in targeted social media advertising, with a focus on research-focused communities and academic institutions, to increase engagement and brand recognition.

For collaborative oncologists, I would prioritize interactive content, such as quizzes or polls, to encourage engagement and participation. I would also invest in targeted social media advertising, with a focus on healthcare professional networks and communities, to build relationships with key influencers and decision-makers in the field.

For business-oriented oncologists, I would focus on building a strong online presence, including website design and SEO, to increase brand recognition and drive traffic to our website. I would also invest in targeted digital advertising, with a focus on business-focused social media platforms such as LinkedIn, to generate leads and drive conversions.

AI-Powered Recommendations Are Everywhere

If you use Netflix, you are familiar with AI-powered recommendations (even if you don’t realize it). With over 7,000 TV shows or movies on the streaming service, it’s impossible for a user to find all the shows they want to watch. So Netflix helps them. With only a 90-second window to help viewers find a movie or TV show, Netflix leverages artificial intelligence and machine learning to recommend the right content for the right user based on that user’s usage patterns and preferences. And it works.

But it’s not just Netflix. Amazon leverages AI to recommend new products to purchase. All social media platforms, including LinkedIn, TikTok, and Meta (Facebook, Instagram), use AI and ML to surface content personalized to each user’s preferences.

With an overwhelming amount of content available, it can be difficult for marketers to reach their target customers at the right time with the right message. By utilizing AI and ML, companies can recommend content and products based on user’s preferences and usage patterns, leading to increased customer satisfaction and loyalty. The use of AI and ML is a crucial factor in successful marketing strategies in today’s highly competitive market.

What Does Next-Best Action Mean?

Personalization is a table-stakes for optimal digital experiences. However, many companies implement personalization at the persona or audience level, using information like demographics, website traffic, location data, and other similar attributes. It can work, but it’s not true one-to-one personalization.

Next-best action is a technique that uses data-driven insights and analytics from marketing, sales, customer service, and other departments to predict the next action brands should take with a consumer. By pulling together data from all interactions across all departments, and analyzing that data using machine learning and AI, a company can more accurately predict the right content, message, or offer a consumer might want or need next.

How Do Next-Best Action Models Work?

Next-best action requires several things to work correctly. First, it requires a single customer view to understand the customer or buyer deeply. Second, it requires a real-time feedback loop that continually ingests new customer interactions, and adjusts insights based on those changes. Every interaction is captured: website visits, emails opened, links clicked, pages viewed, products viewed, past log-ins to a mobile application, and so on. These interactions must be timestamped properly to understand the consumer’s correct flow of engagement across channels. 

Finally, AI, machine learning, and predictive capabilities are required to process all this customer data and determine the next best action. These capabilities can analyze millions of data points, look for patterns, and make recommendations on preferred channels, the best time of day to reach out, and the message, offer, or content recommended.

Next-Best Action for Pharma Sales and Marketing Service

A next-best action strategy works not only for marketing but also for sales and customer service teams. For marketing, it helps determine the next piece of content to send, the next offer to make, and the next brand to pitch. For sales, next-best-action can tell a salesperson what additional products to recommend, or services to sell.

The point is that the next-best action isn’t based on a persona or a general customer segment. Instead, it’s based on a customer’s specific interactions with the company, and continually adapts and improves over time. 

“If you go to a website and trigger an email that goes out within 24 hours that says, “Hey, you might be interested in checking out our exhibit booth at the major medical conference coming up next month,” Then, if they go to that conference, send them another thing that says, “Hey, would you like to join one of our free webinars with the leading medical experts in this field? You might know them. You went to medical school with them,” – and then invite them to the webinar. “It’s all about triggering the next best message or action.”

From Product-Centric to Customer-Centric Experience

Consumers are open to AI-powered recommendations. It’s already part of their everyday lives and increasingly a part of a good customer experience. Next-best action, aka, the steps a marketer, sales rep, or customer service rep should take to meet customer needs, can help brands predict and anticipate consumer behavior to help drive deeper personalization.

Will be happy to receive comments and opinion

Screen Shot of ChatGPT