Proprietary Methods

Our innovative methodologies help you answer digital's new business questions.

1. Identify channel preferences

Customers are asked to select their most and least preferred digital channel for each content type.

Technographic profiling to understand digital behaviours

Our bespoke method for technographic profiling allows you to segment customers based on their digital preferences and behaviour and target them more effectively. Using our bespoke approach, we can identify channel preferences, segment physicians by behaviour and provide a blueprint for the optimum channel reach.

Case study: Evaluating behaviour changes in market dynamics and what it means for the omnichannel strategy →

2. Segment customers

Once segments are developed, a typing tool is derived to allow reps to identify segments by asking customers ~5 highly predictive questions
Potential profiling questions in survey inc. demographics, technology adoption questions, etc. will be used by the typing tool to predict segment membership

3. Maximise channel reach

Total Unduplicated Reach and Frequency (TURF) analysis can identify the optimal combination of channels to maximise reach among customer segments

Identifying and profiling key online influencers to improve engagement

Key Opinion Leaders are regarded as influencers in the medical community. Now, a new breed of Online Influencer physician has emerged with as much power to persuade as the traditional KOL – using their significant social media following to engage the wider online medical community.

Profiling process

We use our proprietary process to identify, profile and map the key online influencers specialising in specific therapy areas. This process can be applied to influencer patients as well as HCPs.

Ranking parameters

Authority
Influence
Audience
Frequency
Focus
Opportunities
Engagement

Case study: Online influencer mapping →

MaxDiff results are used to overlay a digital propensity segmentation in client CRM to develop customer segments driven by their digital channel preferences

Bespoke research of assets to understand & improve user experience

Our specialist team can help you to understand user behaviours, needs, and motivations for engaging with digital assets through observation techniques and task analysis. We have carried out projects on website evaluation, usability testing, mobile & app research, digital journey, digital solutions and more.

The experiences that a company or brand offers through its digital assets can be integral to its success. As technologies evolve, users’ needs and expectations change. UX research helps you to understand how users are engaging with your digital assets to perform tasks and achieve goals that are important to them.

We employ a wide variety of UX techniques

Biometric testing

Explorative, assessment
& comparative testing

In-person &
remote testing

Moderated &
unmoderated testing

We can help:

Define the direction of your long-term digital strategy
Help create digital experiences that deliver results
Measure exactly how your product is performing

Virtual and in-person conference research to measure impact

Conference research is invaluable for evaluating the success of marketing and communications activity at medical conferences. Due to the shifting nature of medical events, there is more need than ever for effective research around the new ‘conference’ engagement, to understand how target customers will consume conference output.

Our proprietary mobile methodology, Conference Live, has been adapted for virtual conference evaluation.

Conference platforms now need to be monitored among other digitally-delivered content. Reaction to new science gives early signals as to the relative future strength of brands, but the mode of delivery is changing. In the coming years, we expect conference events to be a mix of live and virtual events to allow a wider pool of delegates to attend in some format.

Find out more about Virtual Conference Live →

Immersive research that takes respondents on a journey to the future

It can be difficult for respondents to imagine how they might respond to a particular scenario in the future.
Future Framing is a research technique to facilitate physicians through a “journey to the future” to fully understand how treatment pathways will evolve and to identify potential barriers in the future market place.

Journey to the future: Example stimulus

Future framing is our proprietary method to help respondents picture decision-making processes around products & services in a realistic, future context.

Respondents are taken on a journey that progresses through future market events, such as future product launches, world sporting events or schedule future macro-environmental changes.

By employing this technique, we can ensure that the opportunity to better meet patient needs is assessed in a realistic market environment rather than a hypothetical scenario.

Insights to help develop effective patient support programmes

During the pandemic, patient support has been severely impacted. Healthcare has had to find new ways of supporting patients virtually. Patient Support Programmes have had to be redesigned for this new environment.

PSP Enhance is our proprietary method for evaluating patient support programmes pre and post launch.

We follow a systematic approach to help you ensure the programme is designed to effectively meet patients’ needs.

Step 1
Explore needs

We begin by conducting qualitative market research to identify unmet needs and ‘pain points’ along the patient journey

By engaging with multiple stakeholders, including HCPs, patients and caregivers, we can gain a 360 degree perspective.

Step 2
Test the programme

Once the programme has been developed, we complete a detailed evaluation with the target audience and recommend any necessary refinements. At this stage, our objective is to find out if the programme is delivering the desired benefits and if they’re likely to be used. In addition, we test possible considerations e.g. practicalities around registration, the role of HCPs etc.

Step 3
Monitor success

After launch, we assess the impact that the patient support programme is having and test if it is still meeting KPIs. We measure proxy outcomes such as patient perceptions, reactions and assess if the various initiatives are useful at addressing the pain points identified in Step 1. Once again, we recommend ways in which the programme may be improved for future use.

Case study: How a two-phase evaluation involving interactive workshops gave guidance for improving a Patient Assistance Programme in CV →

Using artificial intelligence to assess emotional responses

A wealth of emotional information can be drawn from our facial expressions and tone of voice, which can be very valuable for uncovering emotional insights.

We partner with experts in the area of artificial intelligence and use our proprietary method Emotion AI to analyse both facial expressions and vocal sentiment.

Traditionally, market research has focused on analysing on what is said, more than how it's said. This is all the more important when we are trying to assess what people are really thinking, not just what they are saying.

Case study: Evaluating a disease awareness campaign with facial analysis →

Artificial emotional intelligence or Emotion AI uses optical sensors to measure facial expressions of emotion and cognitive states the same way people do. The technology works by identifying a human face, either in real time or in an image / video and, by using computer algorithms, identifies key facial landmarks e.g. the corners of the eyebrow, the tip of the nose or the corners of the mouth. Machine learning algorithms then analyse pixels in those regions to classifying facial expressions. Combinations of these facial expressions are subsequently mapped to a range of emotions.

When used with traditional market research methods, facial analysis can deliver an additional layer of insight by uncovering the emotional reaction to stimulus, whether static or dynamic.

Qualitative conjoint to identify preferred product attributes

In developing new digital products or solutions, you need to understand what features will be most important to your customers.
ChoiceQual is a hybrid approach using conjoint. Through the series of tasks shown below, we are able to produce utility scores which can then be used in a simulator to obtain preference shares. The advantage of this method is that it can be used in a qualitative research setting with small sample sizes or in quantitative research where you are restricted by small sample sizes.

Respondents identify their “most preferred product option” by specifying their ideal level for each feature/attribute.

Respondents identify their “least preferred product option” by specifying the least preferred level for each feature/attribute.

In this step, the levels not selected in the earlier two steps as either “ideal” or “least preferred” are rated on a preference scale.

This is followed by a MaxDiff exercise. The MaxDiff exercise measures the importance or preference of multiple items, in this case product features.