Suggestr
https://suggestr.coAmazon-level personalization for Shopify merchants
Suggestr is a self-serve, no-code personalization solution for the 20M+ e-commerce brands that sell on platforms like Shopify. Marketplaces like Amazon drive up to 30% of their sales from personalized surfaces (recommendations, bundles, frequently bought together, et cetera). They have large data science teams that build such in-house recommendation engines. However, DTC brands can't afford to do this, and they don't have enough customer data to make the conventional recommendation approaches work. Suggestr uses innovative multi-modal AI technology that sees and understands products (needs 100x less data), allowing it to work with brands of all sizes (SME, mid-market, enterprise). The solution takes less than 30 minutes to integrate and helps merchants increase online store revenues by up to 10% with AI-driven upsells and cross-sells.
Total Open and Closed Positions
Total open positions, and positions newly closed since the previous update
Department Headcount Over Time
Open positions per department · top 6 at any point in the window
Newly Opened and Closed Positions
Position Churn Rate
Positions closed within 14 days of opening · a high rate suggests posting instability — duplicates, pulled listings, or roles filled through internal or off-market channels
Time-to-Fill Distribution
Days from open to close · closed positions only
Salary Trend Over Time
Monthly median base salary · USD · annualized · p25/p75 dashed
Salary Range by Department
Employment Type
Technical vs. Non-technical
Open positions · by department
Top Roles by Department
Seniority Mix
Derived from job title keywords
Equity Range by Department
Top Skills
Top Tech Stacks
Skills Trend
Change in share of postings · recent 3 months vs. prior 3 months
Tech Stack Evolution
Positions opened per month · top 5 technologies