A Riddle About E-Commerce Targeting

granify ecommerce riddle behavioral targeting

A group of teenage boys, a mother and five-year old, and an elderly man walk into a pet store. The boys ogle at the snakes, the mother guides her child to the puppies, and the elderly man looks at cat food.

Of these three types of customers, your job is to maximize revenue by strategically choosing who to help.

Who Do You Help?

In a physical store, these decisions are made by observing body language cues and comparing the current situation with experience. It might look something like this:

  • The teenage boys show a lot of interest but are not old enough to buy a pet without a parent.
  • The mother and child show a lot of interest, but she will need to have questions answered before she can commit to adopt a puppy.
  • The elderly man is confident in where the cat food is and what kind he wants.

The answer is that you help the mother. Here's why:

  • The teenage boys are not able to buy what they are interested in without a parent. The pet store is on their way home from school, allowing them to stop in for their amusement and to gain interest in new pets. But until one of them returns with a parent, helping them will not lead to a sale.
  • The mother does have the authority to purchase a puppy. However, buying a puppy is a big commitment and she is hesitant to take on the responsibility. Informing her of an existing 30-day return policy will ease her concern. With your help, she knows she can adopt the puppy today and bring it back if necessary. (Let’s hope that’s not needed.)
  • The elderly man will buy whether you help him or not. He’s a regular customer that buys the same cat food once a month. He doesn’t have any questions or concerns that can be addressed to get him to buy more.

By assisting the mother, you find a home for a puppy, sell a new collar, leash and food, and also sell a bag of cat food to the elderly man.

If you help either the teenage boys or the elderly man, you’ll only sell a bag of cat food. The mother will walk away because she is hesitant to commit to adopting the dog.

How is the Riddle Different Online?

Now consider this scenario in an e-commerce pet store. Right off the bat, there are a lot of problems.

First, you’re blind to who is really in your store right now. You might have the ability to see attributes like an IP address or in some cases the shopper might have logged in, but reading the interest level and situational factors of who an individual shopper is and why they are shopping is nearly impossible online.

Second, even if the online shopper carries a cookie or pixel, that will only help you know their past behavior, not their current behavior. This means if they came to your pet store yesterday to look at cats, but have decided to buy a adopt a dog today, the cookie will tell you to still show them cats.

Third, reaching out to help one customer in a specific way is a steep technical challenge. Customer needs ought to be addressed in real-time, at the moment they have a hesitation. Once you identify who a specific customer is and the circumstances of why they are shopping today, how do you reach them?

So if the same mother is browsing your e-commerce pet store, how do you identify her and her specific needs today? And how do you help her?

How to Solve The E-Commerce Riddle

In the physical store, you use your intellect to determine who to help and how to help them. 

In an e-commerce store, you can use artificial intelligence to determine who to help and how to help them.

A subset of AI called machine learning is a tool that can be used in e-commerce to analyze the thousands of data points online shoppers generate while they are shopping. Similar to how a store clerk can observe and make decisions about customers in a physical store, machine learning can do this with customer browsing data in an e-commerce store.

Machine learning empowers retailers to identify and target individual online shoppers with the help they need. Not every customer needs help, but helping the ones that do can maximize revenue.



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