Involve builds customer intelligence platform using Powered by Fivetran

“Fivetran-based apps are so reliable, we’re not panicking to find out if our data has been refreshed or if the app has crashed. With less time required to triage problems, we can spend more time building our apps. We found Fivetran had data integrations unavailable anywhere else. As a result, proactive timely feedback allows our clients to have greater impact and improve the health of their customers.” — Saumya Bhatnagar, Chief Product Officer and co-founder

Data Stack: Fivetran, MongoDB, Snowflake, React, Python

Cloud Platform: AWS

Connectors: Salesforce, Hubspot, Microsoft Dynamics and Teams, Pendo, Amplitude, Google BigQuery, Qualtrics, Delighted.com, Zendesk, NetSuite, Slack, Churn Zeros, JIRA, SAP, Zoom, Chorus

Involve.ai is a customer intelligence platform that leverages AI to provide organizations with a 360° view of their customer health. This leads to reduced churn, early renewals and increased upsells. By considering a wide variety of inputs from CRM, SQL databases, data warehouses, net promoter-based scoring systems, task managers and support ticket software tools, the platform confidently alerts teams that work with customers of churn risks and expansion opportunities within their customer base. It also helps these teams collaborate with each other to take action on the insights that the Involve platform surfaces.
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Before Fivetran

In order to provide its customers with a holistic view of their customers, Involve needed to pull data from many data sources. It didn’t have the team to do this quickly on its own. Data integration was time consuming and resource intensive. Data schemas were unreliable and difficult to modify. The company’s clients require vastly different approaches and specific apps tailored to their sales and delivery processes, and the previous data integration solution lacked the ability to scale to meet those needs.

Without access to data from source systems, Involve wasn’t able to produce the comprehensive insights it needed to have a compelling product. Involve was forced to take a more reactive approach to data analysis.

“We were leaving money on the table in terms of upsell opportunities with our clients,” says Saumya Bhatnagar, Chief Product Officer and co-founder, Involve.
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Challenges
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• Inability to produce comprehensive and accurate insights 
• Inflexible automation for scheduled data replications
• No way to perform data transformations prior to importing into Snowflake (to save on processing time and staffing costs)
• Slower time to market, which limited the company’s growth rate 
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Fivetran Solution

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Powered by Fivetran supported data sources that other data integration tools did not. Its roadmap for new connector development also aligned with what Involve wanted to support in its platform. Fivetran Connect Cards also gave Involve the ability to easily connect to its customers’ data sources and onboard their data. Specifically, it allowed Involve’s customers to connect their data to Involve’s platform entirely on their own, by authenticating the connection themselves.

Other benefits:

• Ability to set unique schedules and sync frequency for each of its customers. Because each customer was assigned its own group in Fivetran, this made it easy to stay organized and isolate these customizations on a customer by customer basis.
• Set it and forget it. Once the data pipelines were set up and scheduled, there was little interaction required with Fivetran pipelines.

Outcome
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• Proof of first-time-to-value of the Involve approach
• Immediate payback in terms of quicker customer onboarding and easier scaling  
• Lower app maintenance by using Fivetran connectors and tools, resulting in additional cost and time savings
• Ability to win more deals with prospective customers due to the ability to quickly connect to their data and prove the value of Involve’s platform and analytics
• Improvement of internal cross-functional team collaboration 
• Gained confidence in deploying Fivetran because of its deep technical support during the evaluation/trial process
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Required Capabilities
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• Support for data sources that the Involve platform needed to connect to (current needs as well as sources they planned to incorporate into their platform in the near future)
• Easy user experience so that non-technical people on Involve’s team could create connections to data sources and not have to maintain them after setting them up. set up and maintain data integrations; that is, no deep technical knowledge needed to create and use Fivetran-based apps
• High reliability, because if a tool that supports its platform goes down, Involve’s customers are impacted. The team wanted to spend less time triaging data issues and more time building their platform.
• Ability to deliver data in normalized schemas and formatted in a way that made it easy to begin creating analytics from it 
• Flexibility to adapt workflows to different customers’ data sourcing and processing needs 

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