List five types of data that might be collected and used by a B2C retailer.
Briefly define each category.
Provide an example of the data.
Provide an example of how an e-commerce company might use the data.
Describe challenges to collecting and legitimately using the data.
List three business functions that rely on collecting a range of customer, inventory, market, and technological data.
For each, briefly describe a financial benefit of applying this data.
How does e-commerce (vs. brick and mortar) facilitate the collection and use of relevant data?
What sort of verbiage is common among them?
Do they tend to be clear and concise?
Do they address common privacy fears?
Data to be collected: In essence, you want to collect data about your clients to better understand them. Unlike a traditional store where you interact with your clients, and get to know them face to face, online consumers are only virtual, you can't chat with them to get to know them. You want to collect data to make forecasts as to what these people would be interested. You basically want to collect as much demographical information as possible. With this information, you can then "get to know them" and then you can try to suggest products for the to purchase, and know their purchasing tendencies a bit better.
1) Age - you would want to know this to see what type of products this person would be interested in when you send them promotions or suggested product via email. A 19 year old boy has different tastes then a 40 year old man, you would want to suggest the 19 year old to buy a new Nintento WII game, while you can suggest power tools to the man
2) Gender - again, it would be nice to know the sex of your clients, so that you can suggest products to them that would appeal to their age. You don't want to be sending wrinkle cream to a man.
3) Income - this would be an ideal data to collect. If you know income, you can then know how much they would hypothetically purchase, and then you could suggest more expensive or more luxurious products based on price. Someone who makes 20,000$ a year would not be interested in expensive perfume, but someone who makes 6 digits would be more attract to this product
4) If the person owns or rents a house - this information might be useful when thinking what type of products would the person be interested in. A renter would not pay good money for new carpets or a paint job, but this might be something that a homeowner would be interested in.
5) Past purchase history - is the ...
1200 words lists business functions that require data collection, as well as looking into privacy policies on e-commerce websites.