Most people have logged on to a social media site, maybe to look up an old friend, acquaintance or family 
member. Some people play games, or post funny pictures or other information they want to share with everyone. Do you ever ask yourself what happens with this information? What if your business wanted to purchase this information and combine it with structured data, such as customer data?
Let’s look at an example of how this information could be used. From your social media data, you may know that females over the age of 45 enjoy playing casino games at home. Mostly at night after 8pm in their time zone. You could group that information and sell it to game makers for use with other customer data. You could also take that analysis, compare it against your own customer demographic data, and WAHLAH (magic), you have a list of people to cross-sell.
Keep in mind – preparing social media data to compare with your list of customers takes some work. For example:
- Data types will be different.
- Codes will never match.
- Descriptions may not match.
- Dates may be in a different format.
- Emails may not match.
- Names may not match.
For each of these scenarios, you must decide what you want to do. For instance, you may want to write some logic to try to find the information in your customer data that best matches the data in the social media data store. In this case, you may want to use a data profiling tool to:
- Profile the social media data store first.
- Compare certain key attributes with your customer data, and look for fallout.
- Analyze the fallout for other types of possible matches with your customer data.
None of this is easy – it requires patience and involves a lot of detail.
Hear how SAS can help you manage your data beyond traditional boundaries.
