In the context of our partnership with IM Associates we translated our retail-oriented services at KWARTS around (big) data-driven marketing to the healthcare environment.
On Friday, the 23th of November 2018, KWARTS launched these 'healthcare engagement' services in prime time to dozens of present companies of the industry during a Consumer Healthcare Event, the CODIMP lunch, that was organized for the 15th year in row by IM Associates in Faculty Club Leuven.
CODIMP has been started by IM Associates in 2003, and unites pharmaceutical companies in a data-pooling initiative. In an anonymized way, sell-in market data are aggregated per individual pharmacy, so that each producer knows an approximation of his real market share for each of the pharmacies. This enables them to set up accuratere go-to-market strategies and to improve the general sales effectiveness.
Thanks to our new services, these companies can now approach their market even more specifically. The implications for the quality of their interactions are explained below.
- Dig deeper than merely value-based segmentation, on a quest to micro-segments:
No single customer is created equal. This leads to the rise of theoretical "customer personae". In practice it seems to be a challenge to attach an abstract 'label' to each individual customer. Via statistical correlation analysis and clustering of diverse characteristics and individual behavioral data, we identify relevant micro-segments within a group of customers with the same economical value, and we allocate all customers 1-by-1 to a certain micro-segment. Such a micro-segment possibly has specific communication preferences, whether it concerns physicians, pharmacies, hospitals, or other stakeholders.
- Physicians: "whom of the 17.000 Belgian physicians is more digitally oriented and whom prefers to receive a physical visit or flyer?"
- Pharmacies: "which of the 5.000 Belgian pharmacies is more generically oriented and has a greater odds of switching the physician's prescription; are there specific physicians for whom this risk is larger or smaller; for specific pharmacies; what is the driving parameter?"
- Hospitals: "which indications have a strong R&D focus leading to a larger propensity that my innovative drugs will end up in the formulary with the same efforts; on which indications are their rather economies; how does this vary for each of the approximately 100 Belgian hospitals?"
- Consumers: "which type of consumers orders online in your pharmacy, and for which product categories (such as food supplements) are the odds higher?"
- Build a personalized journey for each micro-segment
The identification of micro-segments is an important step to bring more relevant messages via the suitable channels. However, there is another important aspect that has to be taken into account: when is which message the most relevant for someone? A hospital's medical director might be open for a seminar, but if he has never been in contact with your brand, it will be important to first build credibility via other channels.
It is important to strike while the iron is hot: when to best send 'relation-oriented' communication, and when better to send a 'conversion-oriented' one? Which type of conversion do you aim for? This is depending on the customer lifecycle phase. KWARTS has elaborated a data-driven model where this phase can be calculated for each individual customer.
- Determine the perfect sequence of contact points in your multi-channel approach
An increasing number of producers is convinced that a diverse mix of channels is necessary, on the one hand for cost reasons and on the other hand because of preferences of specific physicians, pharmacists or stakeholders in a hospital.
Aside from the composition of this mix (a hot topic in the recent years) it is important to pay attention to the ideal sequence of contact points within a multi-channel approach. For specific micro-segments the result (e.g. addition to the formulary) can vary strongly in function of the concrete contact flow they have experienced: do you first send an email to a physican, to then call him, and to consequently visit him? Or do you visit him first, you then send him an email to de-brief, to afterwards call him to ask if everything is clear? By analyzing historical contact- & sales data, you can make better informed choices on this topic.
- Optimize go-to-market parameters in the pharmacy to increase sell-out
IM Associates' experience learns that the sell-out figures for a specific brand in an individual pharmacy are strongly correlated with a number of parameters: the visit intensity by sales representative(s), in-store visibility, sell-in pressure, patient loyalty, etc. A number of producers has performed analyses to the ideal composition of parameters for a specific brand on the national level. The KWARTS-offering now enables them to map the profile of each individual pharmacy, and this for each product reference. In this way an advanced sell-out strategy can be elaborated with a beneficial impact on market share. In a context where pharmacist and consumer increasingly deviate from the physician's advice (a.o. pressure of generic drugs, or pressure of health insurers as in the Netherlands), this is a crucial aspect to consider.
- Map the network around your brand
Your brand is never launched in a clean lab setting, but in a world where everyone influences, and is influenced by each other. That's why it is important to create a clear view of your brand eco-system: which stakeholders or specific micro-segments play a central role, and which ones rather a peripheral role? Can you more efficiently target specific stakeholders in your market approach? It could be interesting for example for 2nd line treatment drugs, to map which of the 17.000 Belgian physicians show a strong referral behavior, to then start searching for lookalike-profiles in the market.
- Increase the impact of your mHealth app
A big amount of healthcare companies is working on a "value beyond the pill"-strategy, to enlarge their market (e.g. facilitating diagnosis), or to deepen it (e.g. realize a better patient compliance). Mobile apps are a popular solution, seen that an increasing amount of people are used to manage their health and sports performance via their smartphone.
In a data-driven context this offers a lot of advantages. Interactions with an app can be measured (even 1-on-1), e.g. via Hotjar and Firebase Analytics.
This could offer you strategic advantages: you could for example learn which types of patients have a higher risk for bad compliance, or which pharmacies in the surrounding regions might possibly give a better explanation about drug administration than others.
On top of that you could use the info about (non-)usage of specific functionalities, to steer you in the right operational direction: it could indicate (lack of) relevance for the end user. You can avoid spending too much time in development to functionalities that don't interest the patient. You could also iterate the design of your app until there are less 'blockings' in usage, when the functionality is crucial for the purpose of your app.
By applying micro-segmentation and personalized interaction models on the healthcare market, you can put the customer and/or patient first when it comes to communication. This perfectly fits a context where the commercial approach towards healthcare professionals is digitized, and where the patient gets more and more control over his or her own treatment. Focus on relevant contacts to maintain impact.