Gathering, managing and ultimately using data is one of the main drivers of progress in pharma digital marketing. Communication personalisation has been highlighted as a 2022 and 2023 trend by many pharma marketers.
But are you sure you are collecting the right data? Do you even know what “the right data” means?
I have no doubt that you are already sending out questionnaires and gathering basic details from your healthcare professionals. Email addresses, ages, therapy areas, email vs WhatsApp preference, and more.
But here’s the thing. Basic data is not enough.
You need to collect data that will be actionable in your personalisation plan. Most of the time, healthcare professionals will only give you very limited information on their preferences.
That’s where understanding the difference between implicit and explicit data becomes important. The latter will require some additional thoughts but will give you very actionable data.
Let’s have a look at what both these data categories are, how to collect them, and how to put them to good use.
Before we dive into it, remember that data is only the first of the three steps to a good personalisation strategy.
Check out our article on personalisation to learn about the other two steps
In a nutshell
|Characteristics||– Voluntarily and directly shared with you|
– Doesn’t require analysis to understand what it means
– Available as raw data that can easily be compared
|Collection||– Face-to-face encounters|
– Virtual encounters
|Use case||Content creation or email campaigns based on interests|
|Characteristics||– Received by analysing behaviour and engagement|
– Obtained by interpreting explicit data
– Requires gathering vast amounts of generalised data
|Collection||– Virtual engagement|
– Physical engagement
– Social behaviour
|Use case||Creation of more detailed physician profiles and fine-tuning of marketing campaigns|
Explicit data is data that has been shared directly with you. There’s no guesswork here – the physician has directly shared a piece of information with your company that you can use to market to them.
A basic example would be a survey you send to your physicians. They can tick a box to indicate they want to receive emails from you and add their email address. This is explicit data – it tells you that this physician likes to communicate via email and you can use this email address to contact them.
- Has been voluntarily and directly shared with you,
- Doesn’t require analysis to understand what it means,
- Is available as raw data that can easily be compared.
You can certainly draw implicit data through explicit data, but first, let’s figure out what explicit data to collect and how to use it.
How to Collect Explicit Data
In pharma, there are several ways you can collect explicit data from physicians and other healthcare professionals. These fall into three main categories:
These allow reps to ask physicians questions directly. A set list of questions, or a form to fill out, allows you to attain data about all the physicians you work with. Importantly, the encounters need to be uniform to attain data that allows you to segment
These may be a video call or conference, but not always. Having physicians sign up to your website or sign up for a webinar gives you an opportunity to gather data
An honest and straightforward method. If you want to know which areas of medical development they are most interested in, for example, you could create a questionnaire on the topic
How to Use Explicit Data
Explicit data allows you to instantly use that data to take action. You can use it to create content that physicians indicate they are interested in or sign them up for email campaigns.
It’s quite likely that you are using explicit data in this manner already.
To take it a step further, you can begin to draw implicit data from this. For example, explicit data tells you that a physician opts into email marketing but never signs up for in-person symposiums. The implicit data you could infer from this is that the physician prefers digital communication over face-to-face – you could then adjust your marketing to suit.
Implicit data is the kind of data that you can infer from your audience’s behaviour. It is not provided directly by them. Unlike explicit data, there’s an element of guesswork and analysis to find the real meaning of the data.
For example, implicit data could be looking at how often physicians open emails from your marketing team. Depending on the frequency, you can imply whether a physician prefers contact via email or another method of communication.
If a physician always clicks to view the webinars in your email, you may deduct that they like webinars. You may retrieve the same data from the fact that they signed up for several webinars in the past. In both examples, the physician doesn’t tell you that they like webinars, but it’s implied in their actions.
Let’s take a different example: if an existing user on your pharma portal always goes back to check information on the same drug and the disease associated with it, they may have a specific interest in it.
But implicit data is not limited to content preferences. Imagine a user comes to your web property from one of your social media posts, you will know that they use social media and even which network they prefer.
- Received by analysing behaviour and engagement,
- Obtained by interpreting explicit data,
- Requires gathering vast amounts of generalised data.
Unlike explicit data, implicit data isn’t handed to you on a plate. Begin by asking yourself what could help you better communicate with your audience, then gather the data to attain that understanding and analyse it to draw conclusions.
How to Collect Implicit Data
Implicit data is collected by gathering general data in three categories:
It can be gathered from emails and website engagement. Did they open the email? Which links were clicked in the email? What time of day do they open emails? What articles did they read on your website? Having physicians log in to your site to access content allows you to pin implicit data to specific individuals. You should look at the channels they use too – look for traffic sources.
It is also trackable. Recording who comes to seminars, who engages by asking questions rather than picking up leaflets, etc. Gathering this implicit data relies on training reps to look out for it!
It can also be analysed by looking at the social media content shared, liked and engaged with by physicians. Which virtual engagement data can fall into your lap, social media behaviour requires more planning and resources.
How to Use Implicit Data
Implicit data can be used to build a more detailed profile of physicians, which can then go towards optimising and fine-tuning marketing campaigns.
When you begin to collect implicit data, it can look a lot like white noise. However, with segmentation (and then personalisation) you can use it to paint a detailed picture and optimise processes to an incredibly accurate degree.
So, What Next?
With a strong understanding of both explicit and implicit data, plus how to gather it, you may be ready to jump in the deep end. However, that would be a mistake.
Personalisation is best approached with a ‘slow and steady’ approach. Selecting enablers, integrating human skills, and retraining cross-functional teams will take time.
To take the next step, learn more about personalisation in our article How to Use Personalisation in Healthcare Digital Marketing