The company wanted to know the topics that most concerned people when selecting an HIV treatment.
Response bias can alter results of any survey with a topic as sensitive as this, so they complimented their existing poll of healthcare professionals with social data.
Historical data from offline research had led to pharmaceutical companies focusing their resources on increasing the life expectancy of those with HIV.
However, by analyzing unsolicited peer-to-peer conversations on healthcare forums, it was revealed that what most concerned the patients themselves was passing on the virus to loved ones.
The discovery led to a change in drug development direction and marketing messaging.
Real consumer insights
Online clothing retailer Asos wanted to better understand the needs and interests of their loyal customers.
Looking only at people who had mentioned the brand on multiple occasions within the time period, they segmented the data into different localities, demographics, and professions.
Splitting the data into UK and US mentions demonstrated clear differences between the markets.
A much larger proportion of UK customers were students. This may have given context to another finding, that the UK audience was active during later times of the day than the US audience.
This insight allowed the brand to align their social activity to match their audience: vital when consumers expect a fast response on social.
When talking about the brand, the US audience often mentioned events and celebrities.
For the UK audience, fashion blogs were often mentioned alongside more emotive words.
These consumer insights allow for a tailored approach to the different markets. Partnering with influential bloggers would provide better ROI in the UK than celebrity endorsements or event sponsorships, which should work better in the US.
When discussing fashion outside the brand, the US stuck primarily to talking about clothes.
Their UK counterparts spread their interests more evenly to include accessories, hair and fashion blogging. Again, this raises the potential for highlighting different products in different markets to drive sales.
Blended data
An ice cream brand had been experimenting with a blended data approach, attempting to map sales data onto weather patterns. Despite previous attempts, it was difficult to determine anything useful enough to act upon.
Most of the sales data was pointing to purchases made during weekly shopping trips, rather than implying any information about when people were choosing to eat the treat.
The brand then decided to blend the sales and weather data with conversations from social media – specifically mentions of customers actually eating the ice cream. These mentions were isolated using language around ‘about to eat’, ‘just finished eating’ and other descriptive statements.
Analysts found that consumers were often eating this brand of ice cream while at home in front of a movie on rainy weekends.
Prior to this research, the assumption was that people mainly eat ice cream on hot, sunny days. This revelation uncovered new and unique marketing opportunities, such as redirecting paid spend to align with weather forecasts, or repositioning the messaging behind PR campaigns.
These examples all show how there are a growing number of imaginative uses for social data.
Whether taking a fresh look at an audience, or blending data to reveal new insights, there are many paths to actionable insights that add business value.
From the innovative people we speak to, it is clear that users increasingly aren’t just listening to social data anymore, but using it intelligently.