Solvvy Chooses Rocketlane to Deliver Delightful Customer Onboarding Experiences
Rocketlane, a purpose-built customer onboarding platform that helps businesses accelerate their time-to-value, has added leading conversational AI and customer support automation solution Solvvy to its customer base.
Solvvy is the latest to join Rocketlane’s list of notable customers including Chargebee, ParcelLab, LinkSquares, Appcues, and Netcore. For Solvvy, Rocketlane enables consistency of execution, seamless internal and external collaboration, and also shortens the time-to-value.
Speaking about choosing Rocketlane for their onboarding needs, Mahesh Ram, CEO of Solvvy, said, “Rocketlane helps us win on three fronts: First, it helps us turn prospects into satisfied customers faster by showcasing our professional methodology during the sales and implementation cycle; second, we’re able to hold our teams and customer teams accountable to ensure faster and better execution; and finally, Rocketlane helps us bring consistency and repeatability to our execution. The biggest winners are our customers who enjoy the resulting acceleration of time-to-value. This, in turn, helps Solvvy to deliver higher and faster ROI and expand our partnerships with customers earlier in their journey with us.”
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Daniel Leeman, director of Solutions Consulting at Solvvy added, “Rocketlane helps us codify our onboarding methodology which helps our implementations team adhere to the process and ensure a professional experience from our end. The customer portal allows us to immediately respond to client needs, unifying the onboarding experience with our internal project management. Rocketlane also helps us scale our implementations by making it easier to manage team resources and by providing insights on all ongoing projects.”
Rocketlane continues to deliver excellent experiences for both its customers and its customers’ customers. Rocketlane also was recently named category leader on G2 for client onboarding. The team continuously enhances the product and rolls out features based on customer feedback. The company had announced its $18 million Series A funding earlier this year.
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