Athlete’s Foot is a common condition of which the treatment and management journey is increasingly being informed by digital resources rather than physicians. Our client needed to understand the sufferer journey further in light of this.
Using social listening to collect observational data
Social listening data was collected using the Pulsar platform. Searches were set up by identifying the most commonly used terms for the condition, established by cross-referencing existing category knowledge with Athlete’s Foot search data.
Inductive analysis (inferring generalised conclusions from patterns identified during the process) was used to build a code-frame which added structure to the data. This was built around four questions – what, why, where and when.
This approach helped us paint a more coherent picture and establish a clear narrative, while the volume of information captured enabled quantitative and qualitative analysis. Qualitative exploration built an understanding of the digital conversations being had and the key topics within them. The scale of the data then allowed us to quantify these topics, meaning we could measure their volume and relative proportions.
The blueprint built from social intelligence
There was a clear distinction between the two markets (South Korea and the US) in terms of general awareness and understanding of the condition. In one market consumers seemed aware and well-versed in the various ways to cure. Whilst in the other, they struggled to recognise the symptoms and displayed limited knowledge of treatment options.
This was a key driver behind the different consumer behaviours the social intelligence stage identified, with one market primarily focussed on ‘seeking help’ in the early stages of their patient journey, and the other displaying a culture of ‘share-commending’, where consumers were actively combining recommendations with their previous experience, mostly after a successful recovery.
Fusing listening and asking allowed us to understand more
The social listening phase revealed issues with how sufferers identified themselves as having the condition, but with the insights at this stage being based on observational data only we couldn’t explore the why behind this.
In each market, we implemented an asking phase with two target groups. As we’d already embarked upon the listening phase we were able to structure the asking in a much more concise manner, focusing it on completing, not building, the picture which resulted in a shorter survey experience for participants.
The insights gained from the social intelligence phase allowed us to create a hypothetical scenario for one of the target groups, allowing us to explore their journey in depth. These experiences would be almost impossible to capture through the conventional recruitment of Athlete’s Foot sufferers. In short, the social intelligence piece provided us with a sufferer journey map which the follow-up asking phase allowed us to complete.
Adding cultural context
Overlaid across all of this was cultural context provided by the Join the Dots’ Culture and Trends team, ensuring the impact of market nuances were fully considered.
For example, the social intelligence found that South Korean sufferers communicated in a much more concise style compared to their US counterparts , and that much of the conversation in the US was focused on sharing stories and tips for treatment. Our Culture and Trends team were able to offer some initial hypotheses as to why this has happening. Understanding the context enabled us to provide culturally considered understanding of the differing behaviours of sufferers in the two different target markets.
Our approach enabled us to deliver findings that were grounded on naturally occurring consumer conversations about the condition. Incorporating social intelligence allowed us to build a picture of the sufferer journey not limited by structured questionnaire design or constrained by the time a primary qualitative approach would have taken. However, whilst it provided us with a blueprint there were knowledge gaps, we needed further context behind why patterns in behavior were happening and only a primary asking phase could provide us with this insight.