About two weeks ago, a male coworker of mine asked for a birthday gift recommendation for his mother. You would think he would have some idea of what she wanted. But, he was having trouble making the connection between what he knows about his mom and the tangible products she might like. Before I could recommend anything, however, I needed more information.
I asked, “Tell me about your mother. What kind of things does she like or like to do?”
His response, “Well, she moved recently to be near the beach.”
I said, “So, she has a new house by the beach. Have you considered buying her something for that?”
And just like that, a light went off in his head, and he suddenly a laundry list of new gift ideas. So, we talked more about the kinds of things she likes and does not like to narrow down the list. Eventually, we decided on some candles with seashells embedded in them.
This experience got me to thinking about the “data” we used to make our decision. First, context does matter. Only knowing his mom’s age or income would not have mattered in our gift decision. What mattered was that she had a new house near the beach and that she was in the process of decorating it. Second, understanding her interests helped—especially when it comes to giving a thoughtful gift. And finally, her son’s intent to buy her a gift was key. We were not looking for something extravagant, but we definitely wanted the gift to be personal. So, we used a combination of interest and intent inputs to make our decision and these ended up being much more effective than solely relying on profile information.
Oh, and I heard a few days later that she loved the candles.