In this final blog of a three-part blog series, we discover how demographics provides laser-like insight into LuluLemon’s success, and how DataSift Demographics can create new products and value from demographic and audience insights—while respecting privacy.
How does the yoga-inspired athletic apparel company LuluLemon maintain its market position, while other brands have difficulty challenging them? It was a question posed to DataSift by a financial institution customer a while back—and they asked us to investigate. Using DataSift Demographics, we examined the demographic inspiring LuluLemon’s growth and how that demographic compares with their competitors.
The financial institution did some traditional research and identified that the core demographic profile for the apparel was females in the 23-34 age bracket. However, it also appeared that this was the same demographic that was fuelling all the other competitors too. So why was LuluLemon performing so strongly? They turned to their Twitter data to give them a better insight—and what they discovered was quite revealing.
LuluLemon’s success didn’t just lie in that broad 23-34 age demographic. In fact, the company also has a huge and passionate group of customer advocates in the 17-19 range. LuluLemon was the only brand to show significant traction in the 19 and under crowd—more than 100% more than the next nearest. It was apparent that the company was tapping into a new market segment, and it was this segment that was growing the brand. Anyone competing with LuluLemon would need to displace them from that core demographic.
Thanks to DataSift Demographics, the financial institution was able to learn all this—and execute the knowledge at speed. So what’s going on inside Demographics Pro to make this happen? The data includes location, alongside multiple rich layers of individual profiling, together with deep commercial insight and detailed interest graphs for more than 300 million Twitter users throughout North America and worldwide.
In fact, the demographics taxonomy is staggering: the solution can profile 249 countries, 1,056 worldwide cities (617 within the US), 10 age bands, 8 income bands, 51 occupations, four races, three religions, affiliation with 3,268 brands, 95 likes and interests and 2,735 specific topics of discussion. Privacy is respected too. The inferred demographics are estimates based purely on public social media presence and usage of the people profiled. The solution never cross-matches or combines in any way with actual demographics from third party databases or any other sources.
DataSift Demographics also picks up on research data points not available in Twitter. If an individual doesn’t provide their age or other profile information, Demographics can infer it from the content.
So don’t be a lemon when it comes to market research—take a look at DataSift Demographics. You can find out more from our most recent Slideshare on demographics.