Healthcare never stops innovating — and some of the biggest leaps have resulted from developments of artificial intelligence (AI) technology.
With its predictive and analytical power, AI has the potential to transform marketing across industries.
It is increasing in popularity across the value chain, and it will have a major, transformative effect on healthcare marketing going forward by impacting targeting, trends, capabilities and planning. It is a tool that healthcare marketers can use to do smarter, more precise work.
One of the main benefits that AI can offer health marketers is better and more sophisticated targeting of healthcare providers (HCPs).
Similar to consumers, HCPs perform different actions across different devices, moving from personal to professional laptops and cell phones.
A strategy of analyzing every single individual action taken by the HCP is not only difficult but verges on the impossible.
Instead, marketers can utilize powerful AI engines to observe -- and then act -- based on high-level consumer paths. These engines can analyze signals at a high speed and produce HCP pathways, therefore allowing marketers to learn what the most important journeys are, how to appropriately weigh channels, and calibrate their marketing plan accordingly.
For example, natural-language processing (already a key component of AI technology used by marketers across other industries) can enable data mining at scale based on topics previously discussed with patients.
Another potential use case would involve marketers enhancing their content optimization by finding the best time to deliver a message for both maximum HCP engagement and efficiency or listening to interactions across channels to predict when HCPs are most likely to respond.
HCP audience pattern recognition
Dynamic (or value-based) segmenting is already implemented in other industries and will also be effective in healthcare marketing.
This AI-backed approach constructs versions of segment groups that automatically update over time, thus removing the need for constant, supervised analysis by data scientists to produce new segments.
Because of the technology, audience clusters update themselves in real-time as new information is gleaned and create new clusters when necessary.
This approach is especially applicable for healthcare, considering that the HCP population is finite and relatively small (in the few millions). The ideal conditions for greater data accuracy and depth only add to the potential of this tactic.
Consider the case of the HCP as an influencer -- a trend that has exploded during the COVID-19 pandemic as HCPs develop personas and build their brands virtually. Typical marketing plans would rightfully emphasize stratifying the HCP audience by influence, targeting the influencer types and their audiences versus the standard HCP.
Dynamic segmenting can identify different types of audiences based on past, current and future behavior. This form of segmenting has strong predictive analytics power, as it can unearth trends that go beyond any defined clustering criteria and identify new patterns at a faster rate.
If healthcare nails down omnichannel capabilities, it has the potential to further optimize cross-channel and next-generation marketing strategies.
Currently, media plans contain specific campaigns that target segments across different channels.
By monetizing AI algorithms, marketers can optimize channel allocations and increase cross-channel efficiencies that have a multiplicative positive impact because every channel plays a crucial role.
By utilizing AI algorithms, marketers can unlock core benefits that include the ability to dynamically anticipate HCP channel preferences while making tradeoffs based on channel constraints.
They can also dynamically focus promotional investment on key prescribing decision-makers and shorten the path to prescriptions by delivering the right message at the right time.
AI technology is powerful enough to automatically calculate and predict HCP journeys while analyzing the competition and marketplace in real-time.
Marketing plan optimization
With AI, marketers can rethink their approach to plan optimization. Currently, many use an approach best described as “basic refining,” which includes the introduction of new tactics, channels, partners, client assets, creative, and other components.
This method has been popular for decades and is considered a media best practice. However, over the years, healthcare has had increased access to data. There are now vast and heavy datasets, from consumer consumption, research studies, media platforms and more.
Media teams should consider adapting their strategy as technology continues to evolve. AI can run simulations based on historical data that can be fully calibrated in seconds, giving media teams the ability to see which options are viable or not while identifying risks pre-launch.
AI technology also provides marketers with efficiencies, as they won’t need individuals to evaluate every single plan across their client portfolio -- the technology can do it for them.
Media teams can tweak their AI algorithm based on engagement and brand strategy and truly focus on the core of the customer journey. The algorithm can also be updated to focus on different segment clusters, thus improving the accuracy and efficacy of the model over time.
AI will also improve content engagement, impacting marketing plans and strategy by focusing specifically on HCP profiles based on disease area, treatment affinities, content type affinities, device usage and projected affinity.
Having this data will greatly shape strategic imperatives as organizations learn how to leverage these insights to provide specific, targeted content and messaging that can drive greater engagement.
Marketers across other industries are already using AI to connect with audiences in smarter, more efficient fashion. It’s time for health marketers to understand the impact that AI can have on how they strategize and reach HCP audiences — and utilize AI’s full potential.