How Data can power Nike’s Revival
Nike needs to connect back to youngsters — Turning to data could help Nike find new opportunities.
Nike is in a tough spot to meet its projected $50 billion annual sales promise by 2020.
With the slowdown in the sports apparel and footwear category, Adidas beating them to make the best-selling sneaker for the first time in over a decade, and an increasing number of fashion brands adding sneakers in their product line, Nike knows it has work to do.
With Adidas scoring on the cool quotient from their association with Kanye West, Nike needs to find a way back to find its coolness, and its customers.
As per CEO Mark Parker, Nike’s now looking to reach out directly to customers and on focussing on differentiating its retail experience. Turning to data could help Nike find answers to some very relevant questions, and help them identify trends early.
Where do my customers live?
The figure above shows stores of Nike and Adidas in New York, and the catchment areas of visitors at each of their stores, as seen in the Near platform. By identifying their missed opportunity, Nike may need to revisit their store expansion and marketing strategy.
When do customers visit my stores vs my competitors’ stores during the week?
We observed that Nike and Adidas have stark differences in footfall patterns in the US.
While Adidas captures its maximum customer base on weekdays, Nike has a seesaw customer walk-in pattern.
This could be a defining trend, as a comparison with the UK market highlights Nike’s ability to capture footfalls better on weekdays than its competition.
Nike has seen a decline in wholesale revenue in US, and attracting shoppers to their stores on weekdays could be a strategic move to boost sales.
When do customers visit my stores vs my competitor’s during the day?
Footfall distribution during the day could be used as an indicator to determine whether your customers prefer your store to competition.
Further, looking at this data during different time periods in the week could reveal some very interesting insights.
Later peaks may mean that customers come to your store post consideration of other options at competition, and a granular look at this data can lead to better answers.
In-depth answers to many other questions such as: “What are my customers interested in?”, “What do they do online?”, “What is the demographic split of my competitor’s customer base?”, “How do my customers get online”, can be found here.
Ultimately, it’s when rather than if, Nike will embark on its course correction in the US, and it’s all dependent on how quickly they can adapt to the rapidly evolving tastes of young consumers, the key to which lies in effectively harnessing the power of data.