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Author: Arjan Haring
Arjan Haring is co-founder of Science Rockstars and one of the creators of PersuasionAPI.
His main interest is the practice and theory of behavior change. This brings him in fields such as social psychology, user experience design and even machine learning. His passion in bridging together different scientific fields led him to co-create PersuasionAPI, closing the gap between online optimization & personalization with persuasion profiling. And paving the way to a better marketing.
Many experts assume the social recommendation system is its killer feature.
But what exactly about this feature makes it so? What in fact is the magic sauce of Amazon?
Sure, there is some predictive value in keeping track of many different variables. There always is. It’s Amazon’s best kept secret.
But I am guessing it’s not only a secret for people outside of Amazon. If you would ask me what the most persuasive ingredient is of the sauce, I would say it’s copy.
The smartest algorithms make sure you get to see products that you love (to buy). A recommendation engine knows what you really want, what you really really want. Computing thousands of variables is the key to predicting consumer behavior.
Nah, I don’t buy it. The black box probably does have an impact, but I know for sure the copy has.
“It's the little details that are vital. Little things make big things happen.” John Wooden
I am a big fan of the micro-conversion vs. macro-conversion discussion (go team micro!). Coming from a behavioral science angle to take up conversion challenges I would like to start the micro persuasion vs. macro persuasion discussion as well.
Marketers often have too ambitious persuasion goals to really be effective. Behavioral scientists are trained to start with micro goals when they aim for macro goals.
When you want to motivate someone to exercise regularly, a first push up is a great start! The same goes when you want to sell products.
Persuasion is a hot topic. But do you also know which of your customers you can persuade?
I recently talked to one of the leading figures in Data Science, Eric Siegel, author of Predictive Analytics. And he concludes that organizations in essence don’t just want to know what consumers will do – they want to know what they can do about it.
I never really thought about it that way, but it makes sense right?
It turns out that it's not that interesting to know what customers will do. Knowing a customer will click, or doesn't click, will move left or move right, isn't useful data. The key is to know which of your customers you can persuade to behave the way you want them to.
By focusing on persuadables marketers can achieve better results. Next to that, it could just help improve marketing's reputation.