Home Insights Decoding Digital Footprints – Part One

Decoding Digital Footprints – Part One

The Commercial Eyes’ Innovation Series is a collection of insightful Q&A-style interviews designed to shed light on the multifaceted landscape of healthcare innovation in Australia.

In this series, we tackle crucial topics that influence the trajectory of healthcare technologies and commercial success. Our aim is to provide a platform for thought leaders and experts to share their knowledge and experiences, thereby fostering collaboration and driving progress in the industry.

Decoding Digital Footprints (Part One): A multi-faceted approach to market research, competitive intelligence and customer insights in healthcare

In this Q&A with Salem Lassoued, Founder of Data Organica, we discuss the transformative impact of digital behaviour analysis on the healthcare industry. As digital technologies permeate every aspect of healthcare, they leave behind vast amounts of data—digital footprints—that hold the key to understanding market dynamics and consumer behaviour more deeply than ever before.

Commercial Eyes partners with Data Organica to blend traditional market research and digital behaviour analysis to give a comprehensive view of the patient and healthcare professional (HCP).

Given the new and exciting nature of this combined approach, we look under the hood of the complexities of digital behaviour analysis and discover how it is being used to drive innovation, enhance patient engagement, and ultimately lead to more informed healthcare solutions.

What is digital behaviour analysis, and how can it transform market research and competitive intelligence in the Pharma, Biotech, and MedTech sectors? Could you provide a specific example where digital behaviour analysis dramatically transformed a client’s strategy within these sectors?

Digital behaviour analysis is a cutting-edge approach that taps into the rich narratives embedded in people’s digital interactions—what we refer to as their ‘data stories.’ While traditional market research relies on self-reported data and can sometimes be skewed by biases such as social desirability or recall inaccuracies, digital behaviour analysis observes actual behaviours in real-time. By overlaying these data stories with the latest in behavioural psychology and behavioural sciences, we can ask deeper questions about underlying motivators. This significantly enriches the insights derived, providing a deeper understanding of the true motivations, preferences, and decision-making processes of patients, healthcare professionals (HCPs), and carers.

In healthcare, for example, this complexity becomes evident. We found in a project focused on medical education that although 92% of healthcare professionals (HCPs) indicated a preference for medical education to be delivered via email, when analysing HCPs actual digital behaviour only 3% of traffic to medical education platforms originated from email, one might interpret this as a case of social desirability bias.

However, a deeper behavioural analysis suggested that the preference for email might not stem from a desire to align with perceived expectations but rather from a need for control over the interaction.

Email allows HCPs to engage with content on their own terms—when they choose, how much they engage, and in what depth—without the immediacy or potential intrusion of other communication methods like SMS or direct calls. This insight shifted our understanding of HCPs’ digital engagement: they aren’t just passively receiving information; they are actively choosing how and when to interact based on what suits their workflow and personal preferences best.

Armed with this understanding, we advised our client to rethink their communication strategy. Instead of pushing more content through email, we developed a strategy that provided more autonomy to HCPs in how they accessed information, such as through on-demand platforms that further empower them to control their engagement. This approach not only aligned better with HCPs true behaviours but also significantly improved the effectiveness of the educational outreach.

Through digital behaviour analysis, we move beyond the surface data to grasp the complex motivations that drive real-world actions and decisions. This deeper insight allows us to craft strategies that are not only based on actual behaviour but also respect and respond to the underlying needs and desires of healthcare professionals, ultimately leading to more effective and respectful engagement.

What are the challenges and benefits of integrating digital behaviour analysis into existing market research and competitive intelligence frameworks, and how can they be overcome?

Merging digital behaviour analysis with traditional market research is quite fascinating. There’s a unique dynamic between the two. Traditional research often captures what people aspire to be, because, let’s face it, when we’re asked directly, we tend to paint the best picture of ourselves. Digital behaviour analysis, on the other hand, reveals how people actually behave in real-time. This isn’t to say one is better than the other, rather that they complement each other beautifully by showing both where people are today and where they aim to be.

The integration challenge isn’t just technical—it’s also about understanding and reconciling these two very different kinds of insights. For instance, someone might say they prefer eco-friendly products in a survey but then consistently purchase cheaper, non-eco-friendly options online.

We use sophisticated data integration tools that help us overlay these insights. This approach allows us to see not just the discrepancies but the reasons behind them, enabling companies to address both the current behaviours and the aspirations of their consumers. The combination of approaches gives a greater understanding of the market than ever before.

How can companies leverage digital behaviour analysis to better understand the decision-making process of healthcare professionals and patients?

Companies can leverage digital behaviour analysis to gain a nuanced understanding of the decision-making processes of healthcare professionals (HCPs) and patients by examining their real-time digital interactions and behaviours. This approach provides a more accurate “current state” picture of their preferences, needs, and motivations which complements “future state” primary research where you can uncover aspirations and desires behaviours. This enables companies to create ways of bridging the current and the future, which is in essence, the behaviour change strategy.

Digital behaviour analysis allows companies to uncover the true preferences of HCPs and patients by observing their actual online activities. For instance, by analysing search queries and website visits, companies can identify the specific topics and types of information that HCPs and patients find most relevant and compelling.

Companies can identify decision-making patterns by tracking these data stories. For example, understanding the sequence of online actions that lead HCPs to prescribe a particular treatment or guide patients to choose a specific healthcare service can reveal critical touchpoints and decision-making triggers. Moreover, when combined with primary research, insights derived from digital behaviour analysis can enhance personalisation efforts. This means tailoring communications and offerings to better match the preferences and behaviours of HCPs and patients. Personalised content recommendations, targeted educational materials, and customised support services can be developed to align with their actual online behaviours and interests and expressed desires.

Companies can optimise their engagement strategies by understanding the preferred digital channels and formats of their target audiences. For instance, if analysis shows that patients prefer interactive tools over static content, companies can focus on developing more engaging digital tools such as symptom checkers, interactive webinars, or virtual consultations.

Insights from digital behaviour analysis can significantly improve product development. By highlighting unmet needs and areas of interest frequently explored online, companies can prioritise addressing these issues in their product development and patient support programs. For example, if data shows a high volume of interest related to specific side effects, addressing these in product features and support can be prioritised.

Leveraging predictive analytics is another advantage. Companies can anticipate future behaviours and trends by understanding past behaviours and applying predictive models. This enables companies to forecast potential shifts in HCPs’ prescribing habits or patients’ treatment preferences, allowing for proactive strategy adjustments.

For instance, in a recent project, we analysed the data stories of HCPs concerning a new medical device. While traditional surveys indicated moderate interest, our digital analysis revealed a high level of engagement with specific features of the device. This insight led the company to highlight these features in their marketing strategy, resulting in a significant increase in product adoption.