Area store visits data | Visits to shoe stores in NYC in 2022 | Free sample

This is a free sample of our Area Store Visits dataset. It contains weekly store visit data for shoe stores across New York City throughout 2022.

Tables included:
- Area store data shoe stores NYC 2022

Fields included:
- store_id
- name
- brand
- month_starting
- month_ending
- total_visits

With our Area Store Visits dataset, you can process and analyze the store visits to over 1.2m retail locations across the US. Historical data is available from 2019, and predictive data is available 3 months into the future. Select the area you're looking to analyse (e.g. zipcode, city, state) and add optional filters such as category and brand.

Olvin's store visits data helps you analyze the performance of over one million retail stores across the US. Use it to reduce operational waste in retail, analyze competitors on a local, state or national level, or identify localized signals on retail brand performance.

Why Olvin?
At Olvin, we know that bad data leads to bad decisions. That’s why our in-house team of data scientists and machine learning experts have spent 3 years ensuring our data is to the highest standard possible.
- Ground truth validated: Our store visits data is trained and validated against in-store foot traffic counters, enabling a correlation accuracy of up to 91%.
- Largest sample panel: The location data of over 145 million mobile devices are analyzed to power our analytics.
- Representative panel: This panel of devices closely matches the US national average on age, income, race and more, making them a representative sample of the population.
- Proprietary AI models: From clean data, to attributing store visits, to producing predictive insights - our AI models are the key to the quality of our datasets.
- Comprehensive network of datasets: As well as location data, these models are powered by census data, Safegraph’s point-of-interest data, Transunion’s consumer data and more.

搜集汇总

背景与挑战

背景概述

该数据集提供2022年纽约市鞋店的周访问量样本，包含店铺基础信息及月度访问统计。完整版覆盖美国120万家零售店，融合多源数据并通过AI验证，定位准确率达91%，支持零售业竞争分析和运营优化。