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The Ultimate Guide to O2O Commerce Data 2021

Learn about o2o commerce data analytics, sources, and collection.

What is O2O Commerce Data?

O2O commerce data is information regarding online stores and their physical store counterparts. Basically, an online to offline commerce is a business strategy that uses online stores via apps to attract and to draw potential consumers in buying from their physical store. An example of the strategy is offering of coupons online via social media or email, and then consumers redeem these coupons when buying to its physical store. This encourages the consumer to visit their physical stores, meaning the retailer gains more sales opportunities.  

How is O2O Commerce Data collected?

O2O commerce data is collected from various sources. These sources may include online surveys and forums, social media platforms, e-commerce websites, and shops and stores. These sources are collected and gathered by data providers. The role of data providers is to organize and analyze all the available information to turn it into useful data. Providers compile this data to turn into accurate O2O commerce datasets. In obtaining an accurate dataset, information must be gathered from credible and reliable sources. 

What are the typical attributes of O2O Commerce Data?

Typically, before you decide which O2O Commerce Data to purchase, you must ensure that the following attributes are offered:
 

  • Consumer information – this refers to the overall information regarding personal data, geographical locations, and contact information.
  • Buying pattern attribute – this refers to the behavior of a consumer when buying products, brand preferences, most visited sites, and average money spent.
  • Business attribute – this refers to related information about a business that offers O2O commerce like physical address, type of products offered, and annual income/sales.
     

    What is O2O Commerce Data used for?

    O2O Commerce Data is mostly used to gather personal information that can be used to target specific consumers based on their data. Businesses use this data to identify and to reach prospective customers. Aside from that, marketers also benefit from this data by formulating personalized marketing campaigns. Another use for this data is for advertisers to gain insights about the preferred brands and apps based on their mobile device online searches.

    How can a user assess the quality of O2O Commerce Data?

    In order to assess the quality of O2O commerce data, it must observe the following:
    · Accurate: this refers to the accuracy of data. Erroneous value or information must be avoided at all times. The data must also be precise and comprehensive.
    · Credibility: the gathered information must come from credible sources that are validated and doubled check for errors.
    · Timeliness: information must be real-time. The data must be updated regularly and must be relevant to its use case. 

Who are the best O2O Commerce Data providers?

Finding the right O2O Commerce Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular O2O Commerce Data providers that you might want to buy O2O Commerce Data from are Dianping.

How can I get O2O Commerce Data?

You can get O2O Commerce Data via a range of delivery methods - the right one for you depends on your use case. For example, historical O2O Commerce Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time O2O Commerce Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to O2O Commerce Data?

O2O Commerce Data is similar to Consumer Review Data , Product Data, Ecommerce Data, Shopper Data, and Brand Data. These data categories are commonly used for Online-To-Offline (O2O) Analytics and Retail Analytics.

What are the most common use cases for O2O Commerce Data?

The top use cases for O2O Commerce Data are Online-To-Offline (O2O) Analytics and Retail Analytics.