Data science is becoming one of the most important fields of the 21st century. A technologist with a statistics background — in other words, a data scientist — is someone who builds technology that makes valuable use of massive amounts of data. From the beginning of 2012 to the start of 2016, the amount of jobs posted on Indeed.com matching the term “data scientist” increased over 400%.
The term “data scientist” hadn’t even been coined until the end of the 20th century. But by 2010, it had arguably become the most in-demand skillset in the tech world. Predictive applications (mobile apps that can anticipate the needs of its users) will drive the mobile application marketplace for the coming years.
Building predictive applications helps consumers and businesses alike make quicker and easier decisions. Technology companies are becoming more and more savvy about how they can anticipate consumer preferences and behavior using data science. What makes these apps truly useful is their ability to be context-aware. Predicting a user’s intent is what creates the most buzz in today’s consumer technology world on mobile platforms.
Predictive Apps in the Music Industry
Content, music, and video streaming services are being made increasingly available each month. These services are all pushing to predict what their user base will want before the users themselves even know it.
Think about how many music services are out there right now. Let’s name a few: Google Play, Spotify, iTunes, Tidal, etc. Pretty much all of these music services contain similar libraries of music. Outside of some differences in availability of independent artists, their music offerings are roughly the same. If you are a listener of more popular mainstream music, you can’t go wrong with any of these services.
But the question is: how are they differentiating themselves? If their services are virtually the same, how do they compete? The answer is in the quality of their predictive engines.
You’re a big music buff but you may not have the time to discover new songs, albums and artists that you may like. This is where music apps such as the ones we’ve discussed solve the problem of discoverability. They use their predictive engines to make music recommendations to you. If you use Spotify, you must be aware of their feature called ‘Discover Weekly.’ Users of Apple Music can find something similar under the ‘For You’ tab. Playlists here are curated by experts and might be based on style, a particular artist, or even an activity like driving.
Predictive apps are only going to become more interesting and useful in the future. The music apps will soon not only be able to recommend music based on your taste but perhaps also on the basis of mood or weather.
The “Pick-it-for-me” Economy
Consumers are more eager than ever to use technology to make life easier. Just like the music services mentioned above, many other types of consumers are looking for tools to help them make decisions.
Shoppers is one such category of consumers. According to a report created by Accenture, 75% of consumers prefer that retailers know what their purchase history is in order to make the experience easier. This means businesses that collect more data on their customers are essentially set up to make decisions for their customers. If they are making decisions that satisfy their customers, then they are likely to have loyal buyers for decades.
Consumers are asking for a better mobile experience, and are also willing to give a glimpse into their spending and lifestyle habits in order to facilitate such an experience. This trend of a win-win relationship between consumers and businesses will lay the groundwork for more predictive analytics within new and existing mobile apps. If developers aren’t willing to make data science friendly mobile technology, then the businesses they are developing for will fall behind bigtime.
Preparing for Success in the Mobile Marketplace
As mobile application developers, we need to be data savvy . Applications that can make use of all of large amounts of data will win out eventually. It’s no wonder that more and more businesses are becoming big data savvy. In the last 4 years, the human race has collected and stored more data than the previous history of humankind. Yes, that’s right. More data has been collected in 3 years than in the 6,000 years leading up to the start of 2013.
And it makes complete sense. As a business, if you collect data that can tell you your customers preferences, displeasures, spending habits, buying patterns, and any other behavior, then you can identify trends that will give you an enormous advantage over your competition.
Businesses need to pivot to a more agile and forward-thinking strategy in order to get ahead of the competition.
People today don’t mind if businesses collect their data if that means a better customer experience for them. The rideshare application that suggests a ride based on an event on your calendar will beat out the one that doesn’t.
Building predictive mobile apps is the way forward. It won’t be easy, but it will give businesses the head start they need to get ahead in 2017.
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