Gorgias Uses Machine Learning To Suggest Customer Support Answers

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Meet Gorgias, an artifial intelligence-powered help desk to make you much more efficient when it comes to answering customer support requests. The company just raised $1.5 million from Charles River Ventures, Amplify Partners and Kima Ventures. Gorgias lets you make educated decisions without having to switch between multiple tools.

Behind the scenes, Gorgias grabs information from your CRM and e-commerce platforms so that you know everything about your customers when they contact you. Then, Gorgias analyzes the request to suggest canned answers. You can also create templates and shortcuts so that it auto-expands a small snippet of text into a polite support answer.

Finally, Gorgias integrates directly with other tools for action-based support decisions. For instance, you could refund someone using Stripe directly from Gorgias.

Gorgias competes with popular help desk solutions, such as Zendesk, Desk.com and more. But compared to existing solutions, the startup has a secret sauce — it uses machine learning and semantic analysis to automatically tag incoming tickets so that you can deal with refund requests in batches for example.

And combining CRM and payment processing tools with an auto-tagging solution lets you do powerful scenarios. For instance, you could automatically refund someone if they are a good client with recurring orders.

On the other end of the spectrum, you could automatically deny a refund if someone keeps asking for refunds. Others are experimenting with a similar approach, such as Wise.io, but it doesn’t gather as much information from your customers as Gorgias.

For now, Gorgias’s help desk is still in beta. The company started with a Chrome extension to improve your customer support and is now working on this full-fledged help desk.

In the future, the startup wants to integrate other support channels, such as text messages, Twitter and WhatsApp. It also wants to integrate with analytics tools.

So Gorgias is tackling a specific market: e-commerce websites and on-demand startups with important customer support needs. But these companies would likely pay for anything that could make their support teams a bit more efficient.