Once you get this retail store location data, you can use a tool to create a map. In this case, I put it into Excel.Īnd you can see below that all retail stores of the competitor brand in New York, Los Angeles, and San Francisco are neatly put into the file for your analysis.ĥ. Now run the task! After the task is completed, data can be exported to the designated local file in different formats. In this case, I select data fields including store name, address, business hours, phone number, and ratings.Ĥ. Select the information you want to scrape to customize your crawler. Build a text list in the crawler and Octoparse can interact with the page by entering the text in your list one by one and scrape search results accordingly.ģ. As we have three target cities for the retail store location, we get a list of zip codes: 10021, 9002. Copy your competitor’s website (the page of retail store mapping) and enter it into Octoparse to create a new task.Ģ. Web scraping can help you get their retail locations, business hours information within a few minutes.ġ. Now you want to open new branch stores in New York, Los Angeles, and San Francisco. Say you are doing a flooring business and you have a few major competitors in the market. Let’s take an example and you will see how helpful a web scraping tool, in this case, Octoparse, can be in getting data for your retail store location decision. You can do a mapping either for retail partner selection or for competitor analysis based on what list of websites you are scraping from. Scrape from websites to generate retail store mapping How Octoparse helps with retail store location decisionġ. Scraping from Google Maps, you can get hold of the stores’ information in a certain area, including their business hours and ratings. Thus you should look into what nearby stores are selling and whether they can help boost your business. That’s because some goods are complementary in nature.įor customers’ convenience, retail stores of complementary goods tend to locate in a cluster. When you are shopping online, with one product added to the cart, an intelligence algorithm could predict what you are going to buy next. No matter how you would make the choice, what web scraping can help is to scrape down the location data in bulk and offer a big picture for your further analysis. However, you also need to know your enemy and assess the degree of competition. By carrying out field research, you can get an idea of the prospect and learn a bit about your local customer base. It is easier for you to evaluate the location if there is a competitor store running in the neighborhood. Will you choose to locate your store around your competitors? Without a clear-cut answer, this is a rather rich and multifaceted question. In the second part of the article, we can see how this is realized by using a web scraping tool. In this way, we can finally get all target URLs for our web scraping task. Most of the retail chains have their own official website where you can find a page to search for locations of available physical stores nearby. Once you get the list, you get the target domains to scrape from. With this information at your fingertips, you can select each of your store locations cautiously hence maximize your brand coverage and radiation at the lowest operating costs.īefore scraping relevant data and generating the mapping to guide your store location decision, you should have a list of potential retail partners in mind. This can give you a big picture and aid your decision on where your future stores should locate. If you are a brand looking for expansion, you should have a mapping with all potential retail partners marked on it. However, with the development of e-commerce, information about businesses and stores is mostly accessible online. Population numbers may not be open to all online. This factor would be quite important if you are selling upscale, high-class products. How important purchasing power depends on what you are selling. Unlike an e-commerce online business, for a brick-and-mortar, the local population decides your traffic hence your turnover. Are there any complementary stores nearby.Store mapping of retailers open to cooperation.Key factors to consider when you choose your retail store location: How can web scraping guide your store location decision? Most of the data available on the Internet is presented on web pages. Ideas proven by the present data, in most cases, are more reliable than your instinct. If you are a brand planning to find new locations to extend your business, or you are new to retailer business looking for a location for your first store, you should make your decision on a data-driven basis. Digitalization is not a trend, but a reality now.
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