The ultimate result of incorporating your knowledge of the customer into your product is personalization. But most people – even those of us in the Product space – misunderstand or fail to grasp the potential of this tech. To help you understand the power of personalization, Chris Maliwat from DreamCloud presents a scenario that he learned from Mark Zuckerberg during his time at Facebook:
Imagine you are visiting a city for the first time.
You walk into a bar that you’ve never been to before. You enter, and the bartender already knows your favorite drink and can make recommendations based on your tastes. Your favorite song starts to play over the speakers, and an app on your phone suggests that you go over and approach the gentleman in the corner who shares your passion for classical music.
If this is the future of personalization, what is the past, and what is the present? Understanding personalization in context can help us make better use of this technology.
Personalization in the Present
Over the last six or so years, people have mostly equated personalization with product recommendations. “If you liked this, you may also like…” etc. It’s a common feature of many eCommerce websites like Amazon.
Now, some people are seeing other uses of personalization. For example, have you noticed Gmail’s Smart Reply and Smart Compose features? Using information about you and machine learning, Google can sometimes predict what you intend to say and fill in things like your address for you.
Personalization in the P
Personalization actually began before technology. Your hairdresser probably knows you and your preferences. When you walk in, you ask for “the usual.” But you don’t think of it as personalization. You think of it as a relationship.
Personalization is routed in the first part of the word. Personal. It’s about people relating to people. It begins with something as simple as making an introduction.
Effective interfaces parallel human interactions.
Let’s break that down:
The Four Elements of P
Back in the day if you went to a store, you wouldn’t browse the products yourself. You’d tell the shopkeeper your needs, and he or she would go and fetch you the best products for your situation. This input form takes the shape of a dialogue, it’s an explicit process.
These days, most inputs online are implicit. If you watched an entire season of Stranger Things on Netflix in one day, Netflix doesn’t need to ask you what you thought of the show: It knows you liked it! On the other hand, if you drop a show after 10 minutes and never return to it, that’s a good sign that you didn’t enjoy it.
This implicit gathering is going to greater lengths. Spotify Running used to learn not only your music
Back in the day, shoe stores would keep a written history of a customer’s preferences. If a product came in which matched the customer’s needs, the clerk would make this recommendation the next time he or she came in. The customer would feel catered too.
In the digital age, this kind of experience took two different routes. Pandora analyzed the elements of music tracks that people listened to and suggested similar tracks based on the style of music with the help of composers and music experts. Netflix instead analyzed a user’s rating of different movies, and suggested similar movies based on their preferences using heavy math and machine learning.
Both camped learned from each other and discovered there was value in combining both machine learning with specific product expertise.
Selection used to be very controlled and curated – an optometrist would suggest a narrow range of lenses that the customer was permitted to try. Warby Parker gave the customer more freedom and power, which changed the model for this segment of retail.
These days, there are so many products online that selection is once again about narrowing it down based on a user’s specific needs. The trend is now heading towards more connection. The success of websites like Etsy is a desire to return to a connection between the creator and the user. People are also increasingly concerned about the values and the missions of the company they shop from.
Bespoke tailored clothing is also growing fast. The ability to further customize what you have is almost a step towards the past, back to the cobbler days before mass production!
Success in eCommerce used to be purely about conversion. Delivery and how it is part of the personalized experience is now being taken more seriously. In some ways, this is also a step back to earlier times, back when people knew the milkman who came every day, and the milkman knew your requirements and preferences.
The rise in eCommerce made the delivery experience quite impersonal. Now, eCommerce companies are taking responsibility for how successful a customer is with their product. Success for eCommerce is no longer “did you buy the product?” It is now “did the customer solve their problem?”
- Start with an introduction
- Make it a collaborative dialogue
- Presentation matters
- Follow through with feedback
Meet Chris Maliwat
With a proven track record to turn concepts into award-winning products, it is safe to say that Chris Maliwat is a seasoned Product professional. As the current VP of Product & Design at DreamCloud, Chris Maliwat has used his extensive and impressive experience to become a major influence in the world of Product.
His extensive background includes working in product roles at Artnet, Warby Parker, Skillshare.com, Facebook, Gilt, Netflix, eBay, and many more. He is a specialist in the art of Business and Product strategy, requirements and roadmap definition, user interaction, competitive analysis, and usability test design.