Blog on pharma marketing and sales

Finalist Emerging Exporter Award 2024

16/9/2024

Thank you to all our clients and partners!

A Bold AI Ambition for B2B Marketing, Sales, and Service

12/9/2024

The State of Gen AI in Marketing, Sales, and Service

AI is taking the corporate world by storm, and Gen AI in particular. The 10% top performers are beginning to capture real value from the technology; they’re using it to improve efficiencies, enhance customer experience, and boost revenue.

90% of the leaders surveyed believe that in the next 3 years, Gen AI will be important or fundamental to marketing, sales, and service processes.

https://www.bcg.com/publications/2024/bold-ai-ambition-for-b2b-marketing-sales-service

AI can fundamentally transform the customer journey.

The AI transformation may include 3 phases: Organizations start by deploying Gen AI in everyday tasks and then move to reshaping critical functions end to end for radical efficiency and effectiveness and inventing new experiences, offerings, and business models.

Revolutionizing sales in distribution: Harnessing the power of AI

5/8/2024

Generative artificial intelligence (gen AI) promises to be the transformative technology of our time, catalysing the benefits from decades of progress in advanced analytics and AI that preceded the debut of Chat GPT.

Improving customer life cycle management with AI
In today’s hypercompetitive environment, distributors are increasingly turning to AI to enhance their growth capabilities. These technologies can provide deep insights into customer behaviors and preferences, automate customer interactions, and improve the efficiency of processes and workflows.

In B2B sales, AI can be applied in multiple use cases (see graph).

By deploying AI, distributors can optimize their operations, improve efficiency, and enable data-driven decision making. Companies that have already adopted these technologies are seeing measurable results in terms of improved revenues, faster growth, and stronger customer relationships.

https://www.mckinsey.com/industries/industrials-and-electronics/our-insights/distribution-blog/revolutionizing-sales-in-distribution-harnessing-the-power-of-ai

Artificial intelligence technologies are changing the game in the distribution industry, offering unprecedented opportunities for growth and efficiency improvement.
Revenue potential is up to 15% from more effective interactions.
Time saving potential is up to 40%.

For Pharmaceutical Companies, Steps to Value with Generative AI

9/7/2024

New GenAI offerings can benefit virtually every aspect of an organization, boosting efficiency and productivity in areas ranging from R&D to commercial activities.

Because the technology has such wide potential, pharmaceutical companies need to adopt a structured approach to implementing it.

The graph shows a portfolio of Gen AI solutions sorted by potential value and technical feasibility. This type of ranking enables leadership teams to identify and prioritize a few straightforward, quick-to-implement use cases—such as in support functions or commercial operations—to expand their capabilities and build momentum. Then they can shift to more advanced applications, such as in R&D, that have high potential value but are more complex.

https://www.bcg.com/publications/2024/benefits-of-generative-ai-in-pharma

In Commercial the technical feasibility is very high, as is the value to implement AI.
Top potential lies in optimization of sales targeting, personalisation of communication channels and frequency.

The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

3/6/2024

If 2023 was the year the world discovered generative AI (gen AI), 2024 is the year organizations truly began using—and deriving business value from—this new technology.

Gen AI adoption is most common in the functions where it can create the most value.

Most respondents now report that their organizations—and they as individuals—are using gen AI. 65% of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year.

The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research determined that gen AI adoption could generate the most value — as well as in IT.

The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled.

https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

Gen AI adoption is most common in the functions where it can create the most value.
The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled.

How B2B Sales and Marketing Leaders Are Getting the Most from Generative AI

7/5/2024

Leading companies are finding ways to deploy generative AI at scale, giving them an edge in the coming years.

https://www.bain.com/insights/how-b2b-sales-and-marketing-leaders-are-getting-the-most-from-generative-ai-infographic/

Successfully Scale Generative AI in Pharma

4/3/2024

Review of Bain & Company Article | How to successfully scale generative AI in pharma | February 12, 2024

The generative artificial intelligence (AI) transformation is well underway. And pharma companies have high confidence in its value:
Already, 40% of executives say that they are baking expected savings into their 2024 budget, and 60% have set targets for cost savings or productivity boosts.

Nearly 60% say that they have moved beyond ideation and brainstorming to building out use cases. In fact, 55% reported that they expected to have multiple proof-of-concept or minimum viable product builds by the end of 2023.

54% of pharma companies have automated biomedical literature review solutions, and 46% are using AI as part of their process to find potential disease targets.

Now, generative AI is broadening the aperture of use cases with new opportunities across the value chain. Biomedical literature review and preclinical research remain among the most popular use case areas, although we’re also seeing high investment in IT, and competitive intelligence. Within these top areas, more than 60% of executives say that they have at least a proof of concept in development, and around 10% have already rolled out tools.

Commercial and research are the most popular investment areas for generative artificial intelligence in pharma. Early adopters have moved swiftly, often reaching a working pilot within about 8 weeks.

On Sales, most pharma companies already use AI to advance their Sales effectiveness:

Full rollout or implementation: 4%
Active pilot resting or minimum viable product build: 27%
Proof of concept or developed: 31%
Ideation or selected as a priority use case: 38%

The state of AI in pharma Classical data science and machine learning are nothing new to pharma executives who have been investing in productivity enhancements for years.

2024-2025 Outlook
With companies large and small making significant headway in realizing the benefits of generative AI, what will separate the best from the rest? Over the next 3-6 months, the companies that make the greatest progress will be the ones that move from isolated pilots to scaling winning use cases across the board.
These leaders will pull away from the pack with an operating model that supports fast growth at scale and prioritizes the most valuable opportunities.

https://www.bain.com/insights/how-to-successfully-scale-generative-ai-in-pharma/

Summary:
40% of pharma companies are including expected savings from generative artificial intelligence in their 2024 budgets.
The majority of pharma companies (62%) already use AI in Sales.
Leading pharma companies use generative AI to create personalized patient journeys and optimize their marketing campaigns

Generative AI in the pharmaceutical industry

1/3/2024

Moving from hype to reality
McKinsey Article | January 2024

Artificial Intelligence can offer pharma companies a once-in-a-century opportunity to transform their operations and innovation. The review is based on a survey of 63 generative AI use cases in life sciences, as well as interviews with industry experts and leaders.

Generative AI can create value for pharma companies by:

Improving commercial affairs by generating personalized patient journeys and optimizing marketing and sales campaigns
Accelerating drug discovery by generating novel drug candidates and reducing the time and cost of preclinical research
Speeding up clinical development and approval by generating synthetic data and optimizing trial design and recruitment

Generative AI could generate $60 billion to $110 billion a year in economic value for the pharma and medical-product industries.
AI is not a silver bullet and faces several challenges, such as:

Finding the right use cases that align with the business strategy and customer needs
Building the required capabilities and talent to develop and deploy generative AI solutions
Managing the ethical, regulatory, and quality risks associated with generative AI outputs
Creating a culture of experimentation and collaboration across functions and teams

Benefits and opportunities of generative AI for pharma companies are best realized by moving from isolated pilots to organization-wide scaling.

Examples:

A global pharma company that used generative AI to create personalized patient journeys and optimize its marketing campaigns
A biotech company that used generative AI to generate novel drug candidates and reduce the time and cost of drug discovery
A specialty pharma company that used generative AI to automate the generation of regulatory documents and reports

https://www.mckinsey.com/industries/life-sciences/our-insights/generative-ai-in-the-pharmaceutical-industry-moving-from-hype-to-reality

AI can provide a value of 18-30 $ billion for commercial alone. This can include AI assisted insights generation, advanced personalization and precise customer segmentation

Channel Preference in the Pharmaceutical and Healthcare Industry in 2024

28/2/2024

Introduction
The pharmaceutical and healthcare industry is undergoing a profound transformation in the wake of the COVID-19 pandemic, which has accelerated the adoption of digital technologies, transformed customer expectations, and disrupted traditional business models. In this context, it is crucial for pharma and healthcare companies to understand the channel preference of their customers, especially healthcare professionals (HCPs), who are the key decision makers and influencers in the industry.
Channel preference is the term used to describe the preferred modes of communication and engagement that HCPs have with pharma and healthcare companies and their products, treatments, and issues.
Taking channel acceptance as a proxy for channel preference is a common gap in the industry so it is important to clearly understand the difference between these two distinct concepts.

Channel preference vs Channel acceptance:
Channel acceptance refers to the Channel that a HCP may use for professional reasons, even if it is not their preferred one. It can be measured via click or open rates and all the typical engagement measures.
Channel preference refers to the Channel that a HCP would love to use and select, based on their own personality. It is the channel that, given all options, the HCP would naturally navigate towards because that’s where they feel most comfortable.
Understanding channel preference is important for pharma and healthcare companies to design and implement effective and engaging marketing and communication strategies that can reach and persuade their target HCPs. By doing so, they can create a seamless and fluid customer experience that can lead to higher customer satisfaction, loyalty, and advocacy. This can also help pharma and healthcare companies to increase their market share, revenue, and profitability, and to gain a competitive edge in the rapidly evolving and highly competitive industry.
The aim of this essay is to investigate the topic and benefits of channel preference, using data and insights from various sources, such as studies, reports, blogs, and articles. It is structured as follows:

The first section provides an overview of the common channels that HCPs use or prefer, such as face-to-face interactions, remote interactions, email interactions, and social media interactions.
The second section analyses the patterns and differences in channel preference across multiple specialties, using data from a recent market study in Australia. In this study over 40,000 HCPs from 10 specialties were assessed in 2022 and 2023 in relation to their individual channel preference.
The third section discusses the benefits and challenges of understanding and aligning with channel preference, such as creating more effective and engaging customer experiences, increasing customer satisfaction, loyalty, and advocacy, and gaining a competitive advantage.
The fourth section summarises the main points and provides some recommendations to leverage channel preference in their marketing and communication strategies.

Common Channels in the Pharma and Healthcare Industry
In the pharma and healthcare industry, channels are the routes or modes of communication and engagement that pharma and healthcare companies use to interact with their customers, especially HCPs. Channels can be classified into different interaction categories, such as:

Face-to-face, such as individual or group meetings, visits, or conferences, which can provide a high level of personalization, trust, and interaction, but can also be costly, time-consuming, and restricted by regulations or safety measures.
Email, such as newsletters, alerts, or invitations, allows for a high level of reach, frequency, and measurability, but can also be ignored, deleted, or filtered by spam or clutter.
Phone, highly convenient, accessible, and flexible, but can also be perceived as intrusive or shallow.
Video Chat, a fast and engaging medium but can also be affected by technical issues, privacy concerns, or digital fatigue.

These channels can be used individually or in combination, depending on the objectives, content, and context of the communication and engagement. A pharma or healthcare company may use a face-to-face meeting to introduce a new product or treatment, a video call to provide a product demonstration or training, an email to send a product brochure or invitation, and a social media post to share a customer testimonial or success story.

Patterns and Differences in Channel Preference
To understand the patterns and differences in channel preference, a recent market study was analysed. In this study over 40,000 HCPs from 10 specialties in Australia were assessed in 2022 and 2023 in relation to their individual channel preference.
The following are some of the key findings, based on the aggregated data:

Across the 10 specialties assessed, the channel Email had the highest share with 31%.
Phone was the 2nd strongest channel preference with 28%
Remote 1:1 video calls were the next strongest channel with a preference of 21%
The last channel of the assessed 10 specialties was face-to-face with 20%

In the reviewed study the focus was on channel preference, not channel acceptance as previously described.

The study also revealed some interesting differences in channel preference according to the specialty of the HCP. The following are some of the highlights from the study, based on the individual data:

Channel preference by specialty

Face-to-face by General Physicians and Oncologists (34-37%)
Email by Pathologists and Neurologists (45-53%)
Phone by Gastroenterologists and Cardiologists (41-44%)
Video Chat by Endocrinologists and Oncologists (24-29%)

These findings show that channel preference is not uniform across the pharma and healthcare industry, but rather varies according to the specialty. Therefore, pharma and healthcare companies need to adopt a more customer-centric and data-driven approach to understand and segment their target HCPs based on their channel preference, and to tailor and personalise their communication and engagement accordingly.

Benefits and Challenges

Benefits: By understanding and aligning with channel preference, pharma and healthcare companies can

Create more effective and engaging customer experiences: deliver the right content, to the right customer, at the right time, through the right channel, thus increasing the relevance, value, and impact of their communication and engagement.
Increase customer satisfaction, loyalty, and advocacy: meet and exceed customer expectations, build and nurture long-term and trust-based relationships, and encourage customer retention and referrals.
Gain a competitive advantage: differentiate from the competition, increase market share, revenue, and profitability, and enhance brand reputation and image.

Challenges: To understand and align with channel preference, pharma and healthcare companies need to

Collect and analyse customer data: collect and analyse large amounts of customer data from various sources, such as studies, reports, blogs, and articles, using advanced analytics and artificial intelligence. It is essential to ensure that data quality, privacy, security and ethics are in the forefront.
Integrate and optimise multiple channels: integrate and optimise multiple channels, such as face-to-face, remote, email, and social media interactions, using digital platforms and tools, such as apps, chatbots, and virtual reality together with cross functional teams working in unison towards a richer customer experience.
Adapt and innovate in a dynamic environment: adapt and innovate in a dynamic environment, where customer needs and expectations are constantly increasing. Therefore it is important to embrace a culture of agility, flexibility and creativity.

Pharma and healthcare companies need to overcome the challenges and leverage these benefits by understanding and aligning with channel preference in the pharma and healthcare industry.

Conclusion
Channel preference is a key factor that influences the communication and engagement between pharma and healthcare companies and their customers, especially HCPs. Importantly, channel preference is not uniform across the pharma and healthcare industry, but rather varies according to the specialty and individuals.
Pharma and healthcare companies need to adopt a more customer-centric and data-driven approach to understand and segment their target HCPs based on their individual channel preference, and to tailor and personalise their communication and engagement accordingly.
This can help to create a seamless and fluid customer experience that can lead to higher customer satisfaction, loyalty, and advocacy, and to gain a competitive edge in the rapidly evolving and highly competitive industry.

Recommendations to leverage channel preference in marketing and communication strategies are:

Conduct regular and comprehensive studies to collect and analyse customer data on channel preference, using advanced analytics and artificial intelligence.
Integrate and optimise multiple channels and train cross functional teams to work in unison towards a richer customer experience.
Adapt and innovate in a dynamic environment, where customer needs and expectations are constantly increasing.

The 2023 channel preference study shows that channel preference is not uniform across the pharma and healthcare industry, but varies according to the specialty.

Generalizing the specialty by the dominant preference would lead to addressing the majority of HCPs with their non-preferred channel.

Ultimately it is critical for pharma and healthcare companies to understand the individual preference of each HCP.

The Evolution of Pharma Marketing

6/2/2024

How has Pharma Marketing changed in the last 10 years?
In the last 10 years Pharma Marketing has come a long way - all the way from content marketing to hyper-personalization. Here are some of the key steps along this journey:

2014: Content marketing, mobile marketing, social media marketing, patient engagement, multichannel marketing, and big data analytics.
2015: Patient empowerment, wearable technology, virtual reality, storytelling, biomarkers, marketing and medical automation, and data security and privacy.
2016: Generic drug pricing, product tracing, specialty drug spending, and limited drug distribution channels.
2017: Omnichannel marketing, programmatic advertising, biosimilars showdown, and innovation outlook.
2018: Hero stories, technology maturity, shifting front door to healthcare, patient-centricity, social media interactions, and electronic health records.
2019: Influencer marketing, data-driven strategies, digital transformation, personalisation, and video content.
2020: Marketing automation, telehealth, online video engagement, Google featured snippets, real-world evidence, and thought leadership content.
2021: Patient-centricity, social media interactions, electronic health records, virtual reality, AI-generated videos, and personalised video content.
2022: Data-driven personalisation, interactive content and experiences, data privacy and compliance, omnichannel transformation, community management, and streamed content.
2023: Marketing automation and AI, telehealth and online patient care, online video engagement, expanded use of real-world evidence, creating thought leadership content, and experimenting with streamed content.
2024: Leveraging personalisation, creating interactive content and experiences, data-driven strategies for effective targeting, omnichannel transformation, trust and authority, and using social media to reach HCPs.

Moving forward some of the strongest trends are data-driven strategies to further advance personalization, including channel preference and personality profiling.

Moving forward some of the strongest trends are data-driven strategies to further advance personalization, including channel preference and personality profiling.

First

Last

Blog

Global Marketing and Sales Trends in Pharma