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Prioritize Important Emails in your Inbox with Categorizer

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Email is the most popular form of business communication on the planet, but managing inboxes becomes more complex every year as the amount of emails grows. On average, professionals have more than 200 emails in their inbox and receive 120 new ones each day, but respond to only 25% of them. Finding the most urgent emails in the sea of messages has gotten harder every year — until now.

We’re excited to introduce a new productivity-boosting feature to the Nylas APIs: Categorizer for email. Categorizer automatically distinguishes between human-to-human (H2H) and machine-to-human (M2H) emails, helping users find and respond to the most important messages first.

Now, not only can you quickly connect to your users’ email inboxes to create contextual email experiences within your CRM or application, but you can also supercharge their inbox productivity within your application.

Nylas can help your users supercharge their inbox productivity.

Reduce the Noise in Your Users’ Inboxes

Inboxes can quickly become unmanageable due to the influx of newsletters, login confirmations, password resets, spam, and more. Major email providers have features to clean up users’ inboxes, but tools aren’t universally exposed, resulting in your users spending valuable time sifting through inboxes and often missing important messages.

With Nylas Categorizer, you can build the same time-saving features that Gmail and other service providers offer in a fraction of the time.

Add an Intelligence Boost to Your Platform with Categorizer

Using advanced machine learning models, Categorizer enables your platform to distinguish between H2H and M2H emails with a single API call. Not only can you easily differentiate between the two, but you can get a filtered view of emails from humans or those sent from machines. With this endpoint, you can bring intelligence to your platform without building and training complex machine learning models in-house.

With Categorizer, you can run emails through sophisticated machine learning algorithms that intelligently apply categorization tags to incoming messages instantly. By making a simple PUT request to the api.nylas.com/neural/categorize endpoint, you can distinguish incoming emails between either “conversation” (H2H) and “feed” (M2H).

Learn more in our docs here.

Intelligently apply categorization tags to incoming messages instantly with Nylas Categorizer.

Improving Efficiency

Regardless of the industry, time is valuable. Time spent sifting through crowded inboxes could be spent much more efficiently on tasks that can’t be automated away. By providing your users with a laser-focused view of their inbox, you can increase user productivity and, consequently, the value of your platform. 

Here are just two examples of how Categorizer reduces time spent on inbox housekeeping and, in doing so, enables your users to be more productive:

  • CRM: Sales reps send 32 emails a day on average and are in constant communication with prospects. Reps need to be efficient with their time to hit their quotas. Categorizer lets sales reps ignore less important emails like newsletters and transactional messages and spend more time communicating with prospects.

  • Customer Success: Customer Success managers need to prioritize emails to quickly and effectively respond to customers, but sorting through emails to find high priority tickets amongst a sea of newsletters and other spam can cause delays in ticket resolutions. Categorizer enables you to filter and render lower priority emails in another folder, allowing CS managers to respond to urgent emails faster.

Intelligence is the Future

Driving user productivity is critical in keeping your customers happy and successful. By removing the unwanted noise in your users’ inboxes, Categorizer brings the intelligence needed to take your platform to the next level.  See how you can leverage other intelligence features like Signature Extraction and Clean Conversations.

Speak to a platform specialist now to learn more about Categorizer and the Nylas Neural API.

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