Gather round people: we’ve got a brand new design, we’ve got dramatically improved encryption UX, we’ve got new login, new settings, new room list and we’ve got dozens and dozens of stability and performance enhancements! That’s right: it fillets, it chops, it dices, slices! We’re out of beta: it’s Riot 1.0.

In the past few years, companies have become significantly more interdependent—users share passwords, and systems use backend technologies operated by third parties. So when hackers breach a company’s security, they often gain access to a wider set of services and information than initially expected.

Measuring and analyzing your customer support team’s performance can be challenging. The quality of an interaction between two people is subjective, and given that customer interactions are ultimately what make up the majority of a support team’s work, standard metrics like costs and returns aren’t often the best way to gauge and improve quality.

Artificial intelligence, or AI, has been a hot topic within the customer support community recently and there are many good reasons for that. By using AI intelligently (no pun intended) support teams can be more efficient and effective, and create a better experience for customers, all without sacrificing quality.

A whole lot of data comes out of support interactions, enough so that astute support leaders can pull insights, discover trends, and improve how their business serves customers. While the data may only suggest what’s going on with your customers and agents, it’s important to be able to spot trends quickly.

Imagine the benefit your business could achieve if every customer interaction was intelligent? Artificially intelligent? Yes. The era of Artificial Intelligence (AI) has dawned upon us. From personal assistants on our smartphones to bring the keyword at boardroom meetings, AI is now ubiquitous.. But, what makes AI a beeline for personalized customer support?

Providing great customer service has always been a challenge, even for the most decorated support agent. Thanks to three factors, this challenge is only growing. First, customer support workflows are growing increasingly complex. Where once it was just a person and a phone, now agents often work with complex, clunky interfaces.

Sometimes how a customer speaks to you is just as important as what is being said. A compact label for this type of refined communication is customer sentiment. As more customer service software solutions are placing an emphasis on sentiment, it should come as no surprise that companies are looking to leverage this “hidden code” in communication to work smarter and more efficiently.

The internet landscape is changing. Evolution is occurring, much like it does in the animal world. Customers become more active and interested in new areas of the internet and continue to require help. Subsequently, forced by outside influences to adapt, support people also evolve and learn new software in order to better serve their customers. One of these new customer-first skillsets is the ability to use omnichannel software and methodology in order to provide a better experience to customers.

Yesterday, February 5th, was Basecamp‘s 15th birthday. As a company we’ve been around for 20 years (we used to be called 37signals), but one random Thursday back in 2004 marked the beginning of Basecamp, the product. And we launched it right here in this post on this very blog, Signal vs. Noise. The blog looked a lot different then, but the spirit’s the same. And here’s a link to the original home page, as well.