Using big data to talk local

Our response.

Knight Frank prides themselves on having a human approach. Given that, to connect with the large UK property market on a personal level, we analysed and segmented big data – over 750,000 postcodes – into 53 catchment areas surrounding Knight Frank office branches for hyperlocal social media targeting across Facebook, Twitter and Instagram.

By showing users acutely geotargeted ads with 5-year local property value rises, we piqued our audience’s interest and drove traffic with the intent to get a market appraisal from their local Knight Frank estate agent.

We used layered targeting techniques to identify the right audiences amongst social media users, based on location, age, property ownership status, and interests including affinity with Knight Frank’s competitors.

Assessing seasonal demand and key conversion periods, we weighted acquisition and native lead generation remarketing campaigns to deliver at key times to drive performance at scale, reducing CPA by 56% during the campaign period.

Despite initially only being set to run for a short period, campaign performance was so strong that it was extended by 2 months, with a view to revisiting later in the year.