LimeSpot
AI personalization engine that shows each shopper the right products, bundles, and offers at the right moment.
Independent overview by new Mantra · updated July 22, 2026
- Category
- Sales
- Pricing
- LimeSpot Max only, priced by store revenue: from $50/mo (up to $15K revenue/30 days), $150/mo up to $50K, scaling to $3,200/mo at $5M; custom above; free on development/test stores; 15-day trial
- Implementation
- Under 1 week
- Adoption risk
- Low
- Integrates with
- Shopify, BigCommerce, Klaviyo, Yotpo
What LimeSpot does
LimeSpot sits on top of your Shopify or BigCommerce store and watches how each visitor behaves in real time — what they browse, what they skip, how far they scroll. It uses those signals to automatically surface product recommendations, bundle suggestions, and upsell prompts that are relevant to that specific person rather than the same generic display every visitor sees.
On the merchandising side, the solution can auto-generate 'bought together' bundles without you having to build them manually, trigger cart and post-purchase upsell offers, and adjust the products shown in collections based on individual purchase history. It also connects with Klaviyo and Yotpo, so the same personalization logic can extend into email and SMS campaigns.
Most retailers are up and running in under a week, and no developer is required to get the basics live. The platform includes A/B testing and analytics so you can see which recommendation placements and offer types are actually moving conversion rates, rather than guessing.
Key capabilities
AI Product Recommendations
Automatically surfaces relevant products to each visitor based on their real-time browsing behavior and purchase history, replacing static 'you might also like' blocks with genuinely adaptive suggestions.
Auto-Generated Bundles
Analyzes purchase patterns across your catalog to create 'bought together' bundle offers without manual curation, reducing the merchandising work on your team.
Cart and Post-Purchase Upsells
Triggers upsell and cross-sell prompts at the cart stage and immediately after checkout, targeting moments when a customer is most likely to add to their order.
Customer Segmentation
Groups shoppers automatically by behavior, preferences, and lifecycle stage so you can deliver different store experiences or discount strategies to different audiences without building segments by hand.
Email and SMS Personalization
Connects with Klaviyo to carry behavioral data into outbound campaigns, so email and SMS content reflects what individual customers have actually shown interest in.
A/B Testing and Analytics
Lets you run multivariate tests on recommendation placements and offer types, with real-time reporting so you can make decisions based on measured results rather than assumptions.
Best for
- Shopify or BigCommerce store owners who want product recommendations and upsells to adapt to each visitor automatically rather than showing the same layout to everyone.
- Retailers whose team has limited developer resources — the setup is designed to be handled without writing code.
- Stores already using Klaviyo or Yotpo who want personalization data to flow into their email and SMS programs.
- Merchants at an early or mid stage who want a low-cost entry point (from $50/month, with a 15-day free trial) to test AI personalization before committing to a larger spend.
- Teams that want to bundle products dynamically without the ongoing manual work of curating combinations themselves.
Worth knowing
- LimeSpot is built specifically for Shopify and BigCommerce — if your store runs on a different platform, this solution is not a fit.
- There is no free plan for live stores (development and test stores are free); LimeSpot Max is priced by store revenue, from $50/month up to $15,000 in 30-day revenue and $150/month up to $50,000, so it's worth modelling your expected revenue against the pricing tiers before committing.
- Personalization quality depends on the volume and quality of behavioral data your store generates — newer stores with thin traffic history will see less precise recommendations until enough data accumulates.
- The platform covers a broad feature set (segmentation, email, discounts, A/B testing), which means teams who only need one narrow capability may be paying for functionality they won't use.
- If your primary channel is wholesale, marketplace, or offline rather than a direct-to-consumer web store, the solution's core value proposition won't translate well.
Related solutions
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