Smart Selection (SS) is a data intelligence service offered by Tencent Cloud in collaboration with TalkingData based on their technical advantages. Leveraging classical models and predictive algorithms, SS integrates massive amounts of data with machine learning to help solve various problems with site selection of brick-and-mortar stores and operations of commercial districts, promote smart retail and diversify offline trades.
Backed up by massive amounts of high-quality data, SS can bring you the most accurate and unbiased insights into site selection. Data variance makes a big difference. Bad data is worse than no data. In order to ensure that the services it provides can effectively help with your business growth, SS takes more rigorous measures in data processing and tag selecting and will not load any unverified data entries into its platform. Instead of relying on the number of tags to build content, SS brings greater value to your business based on its unique high-quality data.
SS offers more targeted exclusive data to each brand of each customer, making it possible to empower different brands with different recommendations for site selection with the most relevant results. This relies on a variety of flexible configurations in the platform: you can retrieve your own brand and other brands that co-exist or compete with it and configure flexible factors and weights in the site selection model to create a custom model based on the characteristics of your brand.
SS has a lot of efficient tools: the isochrone map tool can help you define the commercial district more scientifically and delineate areas based on walk and drive time, avoiding incorrect delimiting of commercial district radius due to poor commuting; the real-time foot traffic heat map tool can help you understand the macroscopic changes in resident population and working population by analyzing the spheres of influence of primary, secondary and peripheral commercial districts and the differences in foot traffic between daytime and nighttime; and the comparison tool can help you horizontally compare multiple site candidates in a more intuitive manner to find the optimal one.
SS displays the spheres of influence of primary, secondary and peripheral commercial districts in the city through foot traffic heat maps.
Where is the ideal target area? How to find the right area for your business? How to distinguish the advantages and disadvantages of the selected area? In order to help with your large-scale urban store coverage strategy in the new era of smart retail, SS recommends ideal sites accurate to within a 100 x 100 m area with one click based on the administrative district and analysis period you select, and the recommended sites can be filtered and scored on demand. The recommendation process comprehensively assesses the foot traffic, population size, potential customer concentration, commercial atmosphere and competition intensity in each area and quantifies them as model scores, simplifying the workload that otherwise would take a few months to complete into a one-click report generated in just seconds and changing the needle-in-a-haystack passive selection to a more targeted active solution.
SS provides heat analysis of local customers and out-of-towner customers, supports fine-grained exploration down to the street level and interprets the changes in resident population and working population by analyzing the foot traffic differences between daytime and nighttime. On the basis of the detected heat, it incorporates additional information about your own stores, competing stores and allying brands for analyzing foot traffic in the target area and competing and allying conditions of stores, helping you identify the optimal area for new store site.
Leveraging the big data processing capabilities of Tencent Cloud and TalkingData, SS performs comprehensive and in-depth analysis of the areas of interest by evaluating the foot traffic and sales per unit area in the commercial district in various aspects, including demographic properties (such as gender, age and occupation), hobbies and surrounding supporting facilities. It displays monthly, weekly and daily changes in foot traffic to help you fully assess the concentration and proportion of potential customers in the total foot traffic and quantitatively evaluates any area for site selection potential based on data quantification and traditional site selection models and factors.