StackTome vs. Klaviyo
We Are Trusted By
StackTome offers verified review collection while Klaviyo cannot, as it doesn't generate unique Trustpilot invite links for service.
Customers no longer need to login to leave a review on Trustpilot, which increases the review rate sharply.
StackTome sends accurate reminders only for people who haven’t left a review. Klaviyo cannot do that due to a static link.
Also, collected reviews won't have email and order data matching ID, making it harder to identify the person who left a review.
StackTome allows you to leverage customer segmentation by review data so that you can run incentive campaigns, and reward customers that left a review, while Klaviyo doesn't support segmentation and cannot send response emails when a review is left.
StackTome supports review tickets, allowing your agents to respond to review in your customer support platform, or even automatically respond to reviews using chat GPT.
Klaviyo doesn't access reviews API and doesn’t support any interactions with them.
StackTome provides extensive reporting options to understand how many reviews campaign is generating, review metrics for service and product from multiple platforms, review keyword analysis etc.
Klaviyo has no reporting associated with reviews, it only allows you to track email performance metrics.
Trick #1
Segment by Purchases, Reviews & Support Ticket status to narrow down your best customers
Reach your customers when they're most likely to leave a positive review
Collect both service & product reviews on multiple platforms without additional integrations
Leverage AI to quickly generate reply suggestions and review tickets
Customize your emails without additional fees
Reward your customers to leave product or service reviews with Incentive Campaigns
Reviews Collection
Verified review collection
Targeted review reminders
Customer segmentation by review data
Recovery campaigns
Auto review replies with AI
Reviews associated reporting
Flexible email campaign workflows
SMS invites
Email actions (clicks/opens) filtering