The Oldest Generation

Photo Credit: Clem Onojeghuo

As with any industry evolution, there must be an origin. The first generation is a physical one, e.g. Tower Records for the music industry, Blockbuster for movies, and department stores for retail. People purchase physical items in person without the use of any substantial technology. For our purposes we call this Generation One, a sacrifice of a consumer’s perfect fit for an in-person experience.

The Move to Online

Generation Two takes a huge leap forward as it transitions to the internet, removing the physical product entirely. Profits soar and costs decrease as consumers can now access their goods and services from wherever they can access the internet — tanking the Blockbusters of the world out of business. Think iTunes for music, Netflix (mail) for movies, and Amazon for retail. This was perhaps the biggest step in the digital age. This step has one fatal flaw: oversaturation.

“Learning to choose is hard. Learning to choose well is harder. And learning to choose well in a world of unlimited possibilities is harder still, perhaps too hard.”

― Barry Schwartz, The Paradox of Choice: Why More Is Less

Consumers now spend more time sifting through flat lists, toggles, and filters to find precisely what they need. Here lies the capitalization of Generation Three.

Recommendations to Displace All

After a few years of frustrated discovery, consumers look for help. Generation Three, or the Recommendation Generation, focuses on search and discovery improvements that learn about consumers which personalizes the process. Preemptive marketing strikes in the patterns of the consumer. Spotify can push recommend music instead of iTunes presenting you with content you have to search for, Netflix Online recommends streaming content instead of mailing you requested movies, and Amazon Prime knowing what you should pair with your purchase.

“For companies such as Amazon, Netflix, and Spotify, recommender systems drive significant engagement and revenue.”

― Yanir Seroussi, The Wonderful World of Recommender Systems

Each places the product in front of the consumer before they even know it and is extremely effective. It’s effectiveness is determined by the amount of time spent in finding the perfect product. The quicker it takes to find your next favorite artist/movie/product/content is now the next battle. The winning platform will draw consumers and engage with the most relevant content possible.

C ase Study: Target

We love Target — especially since it serves as a fantastic example of recommendation marketing. They’ve mastered this generation by assigning each customer a unique identification number and monitoring their purchases.

Target is famously great at targeting products to customer habits.

By analyzing demographic information and purchase history, Target can market products to customers based on their preferences and sometimes even what they might buy next. Sometimes to creepily accurate results, famously predicting pregnancies down to the delivery date.

Real Estate Hasn’t Evolved

One industry refuses to move to this next generation. Initially growing and developing like everyone else, real estate replaced newspapers and brokers with Craigslist and then companies likes Zillow. Real estate as a ‘Generation Two’ product is now the norm and, currently, remains stagnant. As noted before, there is a natural order to these content channels and it is only a matter of time before real estate is pushed into the third generation, a recommendation engine for housing is something we believe in.

Finding real estate can feel daunting, sometimes impossible.

Enter Sumu: a service able to discern the best matched opportunities for tenants, a service virtually nonexistent outside of the old-fashioned in-person broker. Our evolution makes it smoother, more accessible, and eventually, has legs to broaden the real estate industry’s range. We believe that Sumu is that. We’d love to see more examples of this exist in the space, share some inspiration with us on Twitter at @sumuapp.

Written in collaboration with Zach Martino and the team at Sumu.