Sprinklr Introduces AI Studio: No-Code Machine Learning for Increased Productivity and Real-Time Insights
Sprinklr (NYSE: CXM) has launched Sprinklr AI Studio, a new feature that enables businesses to create and customize AI models for categorizing customer messages without needing coding skills. This innovation addresses challenges in manual categorization, which is costly and ineffective for brands receiving numerous daily inquiries. By employing AI, brands can enhance customer service efficiency, filter irrelevant comments, and unlock new insights. The platform has already garnered positive feedback from users like the Microsoft Azure Customer Experience Team.
- Launch of Sprinklr AI Studio enhances customer message categorization.
- Allows businesses to create AI models without coding knowledge.
- Increases efficiency by filtering irrelevant comments.
- Positive feedback from Microsoft Azure Customer Experience Team highlights its effectiveness.
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The Challenge: Manual Categorization and Brand Disambiguation
Brands can get thousands of mentions and inquiries a day across digital channels. Manually sorting these messages into standard categories such as “engageable” or “priority” is extremely cost-prohibitive and virtually impossible without AI. Additionally, many brands have common company or product names, making it difficult to find the most relevant customer comments. For example, a brand like Microsoft needs to separate the statement “I have a question about Windows 11” from “I have a question about the windows in my house.”
AI can solve these challenges, yet most AI models require brand-specific custom categories that rely on machine learning experts to manually create and maintain their consistent accuracy.
The Solution:
With
- Filter out irrelevant comments.
- Reduce labor-intensive manual work.
- Unlock new paths to derive insights via AI-powered custom categorization.
“Sprinklr AI Studio really enabled our team to create a unified, one-stop shop for organizing and responding to customer questions, and we’re thrilled with the value their listening AI has provided in identifying trends and additional engagement opportunities. Plus the dashboarding feature allows us to elicit actionable insights to improve productivity which help us deliver a better customer experience,” said a representative from the Microsoft Azure Customer Experience Team.
“Using AI to categorize public customer conversations is an essential part of creating a unified customer experience. Yet, advanced technical expertise is often required to develop effective AI models,” said
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