You've got data on your customers and leads, details that if used correctly could translate into higher sales and faster support, that could help your team personalize marketing *and* work faster.

With Intercom, people can reach out to your team whenever they need help, and your team can proactively reach out and close the deal. But first, you have to find the needles in the data haystacks, figure out who to target and how to help them best.

That's where Datagran's new Intercom action comes in. Datagran can pull in data from your MySQL, PostgreSQL, Azure Cosmos DB, Snowflake, Google Big Query, MongoDB, SQL Server, and other databases—or bring in data from tools like Shopify, Stripe, HubSpot, and more. Then, Datagran can run machine learning models on your data for churn analysis, RFM, regressions, and more, with custom SQL queries to pull data from multiple sources into one clean set.

Then in seconds, Datagran can push that data to Intercom, to enhance your existing contact data. Your support team can see your most valuable customers, and answer their queries faster, while your sales team can identify the people most likely to buy or those who are at risk of churning, and target them with Intercom messages, all without any extra work on your team's part. And Datagran can automatically update Intercom as new data comes through your ML models.

A data pipeline example

When the Domino's Pizza team wanted to add data models to their business tools, they first had to analyze data on their local machines, then deploy it to their custom business applications.

Datagran took that process from months to minutes.

The Domino's team migrated their chat and support to Intercom and used Datagran to build machine learning models and send the results into Intercom.

More than ever, businesses need results ASAP—and a connected ML pipeline that brings Domino's RMS and churn analysis into Intercom automatically helps them solve product, marketing, operations, and sales issues together in a fraction of the time it took before.

“Datagran gives us the power to centralize and visualize our data as well as the flexibility to use machine learning across product and operations. Add to that its intuitive platform making it easy even for business units to use it as well.” Alejandro. M - IT Manager at Domino’s

Our team at Datagran has similarly streamlined our support chat with the Intercom action. Our customer success team uses Intercom tags to categorize our Happy and Unhappy customer, Enterprise and SMB clients, and more—but doing that manually takes time and is error-prone. So, we use Datagran to extract the data we want to work with from MySQL, add an RFM operator to identify the users who are most likely to buy again in a specific period, and send the outcome to Intercom to tag those users. Then, in Intercom, we can build personalized messages specifically for this group of customers.

That's only a couple of the ways Datagran's Intercom action has helped teams accomplish more in less time during our beta testing. When you want to make Intercom smarter for your team, Datagran lets you find the right people to target in Intercom with machine learning workflows that take only minutes to set up.

Start building ML workflows for Intercom