What is Stamped?
Stamped is a marketing platform that offers eCommerce and retailers an edge in acquiring positive images to display their brand as trustworthy, especially to first-time buyers online. It builds trust by leveraging ratings, reviews, and User-Generated Content to promote your brand, attracting more customers and driving conversion.
Automatic Analysis of Stamped Customer Feedback with Chatdesk Trends
Chatdesk Trends allows you to analyze Stamped customer reviews and UGCs alongside all the rest of your customer communications. Chatdesk automatically tags all the feedback to easily surface actionable insights.
Sync Stamped product reviews and UGCs to Chatdesk, and aggregate reporting on customer conversations from all your channels, including email, chat, social, reviews, and more – no manual tagging necessary.
Chatdesk uses machine learning to automatically tag customer feedback and conversations. This allows you to get granular insights and search capabilities, and helps you find opportunities to drive growth across different areas of your organization.
The Chatdesk Trends dashboard delivers 90%+ average tagging accuracy across 70+ tags for ecommerce businesses. It’ll scan through conversations and open-ended feedback to surface trends on shipping, product issues, and pricing, just to name a few.
With this integration, you’ll have the ability to:
- Filter feedback by date, channel, product, and sentiment to make informed decisions and drive business impact
- Compare customer feedback across various channels, including CSAT/NPS surveys, email, chat, social media messages and comments on Ads, Amazon reviews
- Segment by product defects, shipping issues, top reasons for contact, and other company-specific custom tags
- Reduce contact volume to your support team, improve self service for your customers, make product merchandising improvements, and increase repeat sales of your product or service
Additionally, you can launch your Free Trends dashboard in minutes. Chatdesk Trends requires no dev work and has more than 90% average tagging accuracy across 70+ tags.