Many popular startups from the last 10 years began as native apps. As they proved themselves out, they expanded to the web. Instagram and Uber, for example, had no web app components when they first launched. Since then they've launched web versions of their services that offer functionality more in line with their native counterparts.
In the first episode of The Savvy Apps Podcast, Ken speaks with Savvy's Creative Director Rob Soulé about the importance of branding for apps. Learn the role branding plays in successful app-focused businesses as well as for organizations with an existing, established brand.
When we published our massive review on how much an app costs back in 2015, we had no idea it would become the top resource on the web. Two years later, that piece is still considered the definitive resource in our industry. It’s because of its popularity that I feel compelled to revisit this subject. Additionally, doing so will allow for some fresh perspectives based on what's changed in the app industry as well as another way to look at the topic.
Alex Villanueva, the founder and CEO of Sprynt, recently gave us an insider's look at his brand new, on-demand, ride-sharing business Savvy Apps helped launch. A few members of Savvy's team toured downtown Arlington, Va. in the unique, fully-electric Sprynt vehicles. Not only did we get to hear Alex talk about going from concept to reality, we got to see the Sprynt app and branding we created in action. Sprynt is a great example of why we continually tell entrepreneurs they're building a business and not just an app.
We build apps of all shapes and sizes here at Savvy Apps, but a common element is that they communicate with servers. Very few apps today operate without some sort of Internet connectivity, meaning that they interact with a backend, web services, or APIs. These APIs could be provided by Google, Amazon, Facebook, or comparable third-parties. They also could be APIs that are developed internally.
Machine learning has quickly become an important bedrock for a variety of applications. Its mobile implementation, however, has been out of reach for many in the mobile app development community. The training and implementation processes for machine learning libraries require dedicated processing power, which is outside the purview of mobile devices. That processing power requirement and existing frameworks usually mean that a server-side component is necessary for even the smallest, machine learning-backed apps. Finally, training a machine learning model requires a good deal of knowledge that lies outside the normal developer spectrum.