With the primary objective to boost sales, leading global sports apparel brand was running a year-end promotion in five store locations across Singapore. The brand wanted to drive awareness among its target audience for this promotional activity, thereby looking to drive store footfall as well.
The brand realized this could be done with a data partner who could accurately identify, create, and reach its audience
segment at scale, by using relevant data and analytics. By exposing the messages to the right audience, it wanted to
boost engagement and purchase frequency at their stores.
Strategy and Execution
To meet the objective, Near decided to build and target audiences using Allspark, Near’s SaaS audience product. Allspark enables organisations to create custom audience segments with precision by choosing multiple data sets such as location, visit frequency, demographics, affluence levels, and content-consumption patterns among other data sets.
Firstly, Near curated the audience segment of users between 18-45 years seen in Singapore in the past 30 days. Since the promotions were different for Males & Females, two separate audience cards were created in Allspark, and age and gender rules were combined to get the desired audience segment. These users were then targeted across Singapore in real-time with the brand’s promotion.
Near then added more users in Allspark based on user’s content consumption, interest, preferences, places of visit etc. to increase the brand’s audience outreach. These users were then targeted in addition to the already existing audience segment to increase awareness about the year-end promotion.
The brand’s messaging resonated with the audience leading to a high response rate.
Even though the brand had other active channels such as social and email, Near was able to provide granular information about the type of people walking into their stores and store performance measured on footfalls. Some of the insights included: