In the final part of our series looking at the strategies businesses are using to engage with developers (B2D), we summarize three Developer Experience (DX) models from Brian Koles (ChallengePost), Pamela Fox (Khan Academy), and Ronnie Mitra (Layer 7).
Successful Twitter engagement is generally measured with the simple goal of gaining a high follower count, but true engagement doesn’t end with a follow-back—that is just the beginning. What you really need for success on Twitter is an ongoing conversation with like-minded individuals, folks who will provide informed feedback on your tweets, introduce you to their friends on Twitter who share your opinions and help spread your messages. This series of articles on engagement programming will show you how to use Twitter API 1.1 to move from simply following to truly engaging on Twitter.
Walk through any shopping mall food court and you’re bound to be offered a free sample from at least one of the restaurants. The taster is such a staple of mall marketing for one simple reason: it just plain works. This tactic has been borrowed with success by software-as-a-service (and even downloadable software) companies and as such is also common with API Products.
Along with the growth of APIs in general has come the emergence of the API as a product. Many times a new startup is entirely an API. When the entire company is an API, you’d better choose the right API business model. When the API is the product, or the whole business, many times this means charging developers to use your API. It turns out, it’s not just about how much you charge them, but how. This post will look at the many different ways that API-as-product companies are getting developers to pay for access.
Last week, the social posting site Buffer had both their database of access tokens and their OAuth client secrets compromised by attacks on Github and MongoDB. Buffer uses Github to store their client_secret in source code and MongoDB to store their access tokens.
In our continuing focus on Analytics APIs that help enterprises come closer to the customer by easier integration through APIs, here is an interview with José Luis Martinez of Textalytics. Textalytics is a brand by Daedalus, a Spanish SME that has been working in the field of natural language processing since 1998.
We have covered Machine Learning APIs before, including BigML.com, Algorithms.io and others. We now continuing the series in an interview with Simon Chan of Prediction.io which aims to further bring machine learning closer to the common man, in an easier interface. PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
Swift IQ belives Machine Learning as a Service (MLaaS) will become a key market in the near future as more providers look to integrate predictive APIs with their customer transaction data. After presenting at the recent API Strategy and Practice Conference, Swift IQ CEO Jason Lobel spoke with ProgrammableWeb about how businesses can use an API-driven approach to improve their “adaptive intelligence”, and shares four techniques that can be tested immediately.
Here is an interview with Scott Gimpel Founder and CEO of FantasyData.com. The site used to be known as NFLdata.com and provides NFL statistics. The site claims to have almost 25 million API calls /month during football season with over 300 developers working with it’s API.