Predict customer purchases through hyper-personalized emails
SwiftERM uses AI to analyze customer behavior like product views and purchase history to predict what they'll buy next. It automatically sends tailored email recommendations at the optimal time, helping e-commerce businesses increase sales without manual effort. The tool focuses on maximizing customer lifetime value while reducing marketing overhead costs.
Runs 24/7 without staff input or campaign management
Identifies next likely purchase using behavioral data
Measures revenue impact with case studies showing 1,400%+ returns
Customizable email templates that auto-populate product recommendations
Works with Stripe and Microsoft Azure Marketplace
Install the plugin and start free trial immediately - works autonomously once implemented
Purchase history, product views, time spent on pages, and visit frequency
Fashion, groceries, luxury goods, pet supplies, and other repeat-purchase verticals
This tool is best for:
Explore more niche AI tool websites by clicking on a tag* (works only if it has enough tools).
SwiftERM can be integrated with these apps and services:
Recent data shows that SwiftERM has 13.5K monthly visits (25.5% increase from the previous month), 37.0% bounce rate, and average 1.75 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by Vietnam contributing 22% of total traffic. SEO performance is shown by 5 tracked keywords, with "uniqlo global one headless pim" being the top-performing keyword with 110 monthly searches. See below for more info.
Monthly Visits
13.5K
Pages per Visit
1.75
Bounce Rate
37.0%
Average Time on Site
20s
| SEO Keyword | Volume | CPC |
|---|---|---|
| uniqlo global one headless pim | 110 | - |
| how many impressions on search console is good | 190 | - |
| fastest brand growing in uk | 170 | - |
| largest ecommerce brands in the uk | 60 | - |
| statistic on email marketing roi mckinsey | 0 | - |
| Source | Traffic Share |
|---|---|
| Direct | 42% |
| Search | 45% |
| Social | 3% |
| Referrals | 8% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 22% |
 | 18% |
 | 15% |
 | 14% |
 | 8% |
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