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    E-commerce Glossary

    Essential terms and definitions for e-commerce personalization, product recommendations, and customer segmentation

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    A

    Average Order Value (AOV)

    Average Order Value (AOV) is a key e-commerce metric calculated by dividing total revenue by the number of orders. For example, if a store generates $10,000 from 200 orders, the AOV is $50. Increasing AOV is often more cost-effective than acquiring new customers. Strategies to boost AOV include product recommendations, cross-selling, upselling, bundle offers, free shipping thresholds, and personalized promotions. LimeSpot customers typically see a 15-25% increase in AOV through AI-powered personalization.

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    A/B Testing

    A/B testing (also called split testing) is a method of comparing two versions of a webpage, email, or feature to determine which performs better. In e-commerce, A/B tests might compare different product recommendation algorithms, widget designs, promotional messages, or page layouts. Statistical analysis determines which version drives more conversions or revenue. LimeSpot includes built-in A/B testing to help merchants optimize their personalization strategies.

    A/B Tests & Analytics

    Abandoned Cart

    An abandoned cart occurs when a shopper adds items to their online shopping cart but leaves the website without completing the purchase. Cart abandonment rates average 70% across e-commerce. Recovery strategies include abandoned cart emails with personalized product recommendations, exit-intent popups, and retargeting ads. LimeSpot helps reduce cart abandonment through personalized recommendations and integrations with email platforms for automated recovery campaigns.

    Email & SMS Experience
    B

    Bounce Rate

    Bounce rate is the percentage of website visitors who leave after viewing only one page without taking any action. A high bounce rate often indicates that visitors aren't finding what they're looking for or that the page isn't engaging enough. E-commerce personalization reduces bounce rates by immediately showing relevant products and content based on visitor intent, keeping shoppers engaged from their first interaction.

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    Bundle Offers

    Bundle offers are promotions that group multiple products together at a discounted price compared to buying items separately. Bundles increase average order value by encouraging customers to purchase more items while feeling they're getting a deal. Common types include 'Buy X Get Y,' 'Complete the Look,' and curated product sets. LimeSpot's AI can automatically suggest personalized bundles based on what customers are browsing.

    Personalized Discounts & Offers

    BigCommerce

    BigCommerce is an enterprise e-commerce platform known for its flexibility, built-in features, and support for multi-storefront operations. LimeSpot fully supports BigCommerce, including Multi Storefront functionality for enterprise merchants who operate multiple brands or storefronts from a single dashboard.

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    C

    Cart Page Recommendations

    Cart page recommendations are product suggestions displayed on the shopping cart page to encourage additional purchases before checkout. This is a high-intent placement where customers are already committed to buying, making them receptive to relevant add-ons. Effective cart page recommendations focus on complementary items, accessories, or frequently bought together products. LimeSpot optimizes cart page recommendations to maximize order value without being intrusive.

    Cross-sell & Upsell Guide

    Click-Through Rate (CTR)

    Click-through rate (CTR) is the percentage of people who click on a link, button, or recommendation compared to the total number who view it. In e-commerce, CTR measures the effectiveness of product recommendations, email campaigns, and promotional banners. A higher CTR indicates more engaging, relevant content. LimeSpot's personalized recommendations typically achieve 2-3x higher CTR than generic product displays.

    Performance Analytics

    Collaborative Filtering

    Collaborative filtering is a recommendation technique that predicts a customer's preferences based on the behavior of similar customers. It works on the principle that if Customer A and Customer B have similar purchase histories, products bought by A but not yet seen by B are good recommendations for B. This is one of several algorithms LimeSpot uses to power its recommendation engine, combined with content-based filtering and real-time behavioral analysis.

    Smart Recommendations

    Content-Based Filtering

    Content-based filtering is a recommendation technique that suggests products similar to items a customer has previously viewed or purchased, based on product attributes like category, brand, color, price range, or tags. Unlike collaborative filtering (which uses behavior of similar users), content-based filtering focuses on product characteristics. LimeSpot combines both approaches for more accurate recommendations.

    Smart Recommendations

    Cross-selling

    Cross-selling is a sales strategy that encourages customers to purchase complementary or related products alongside their main purchase. For example, suggesting a phone case when a customer buys a smartphone. In e-commerce, cross-sell widgets typically appear on product pages, cart pages, or in post-purchase emails. Effective cross-selling increases average order value (AOV) and provides genuine value to customers by helping them discover products they need. LimeSpot's AI identifies the most relevant cross-sell opportunities for each customer.

    Cross-sell & Upsell Guide

    Customer Segmentation

    Customer segmentation is the practice of dividing customers into groups based on shared characteristics such as purchase behavior, browsing patterns, demographics, location, or lifetime value. Segments might include 'VIP Customers,' 'First-Time Visitors,' 'Cart Abandoners,' 'Discount Shoppers,' or 'High-Intent Browsers.' Segmentation enables targeted marketing, personalized experiences, and more effective promotions. LimeSpot's AI automatically creates and updates segments in real-time based on customer behavior.

    Explore Customer Segmentation

    Conversion Rate

    Conversion rate is the percentage of website visitors who complete a desired action, typically making a purchase. It's calculated by dividing the number of conversions by total visitors and multiplying by 100. For example, if 1,000 visitors result in 30 purchases, the conversion rate is 3%. E-commerce personalization significantly improves conversion rates by showing relevant products and content to each visitor. LimeSpot customers typically see a 10-20% improvement in conversion rates.

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    Customer Lifetime Value (CLV/LTV)

    Customer Lifetime Value (CLV or LTV) is the total revenue a business can expect from a single customer over the entire duration of their relationship. It's calculated by multiplying average purchase value by purchase frequency and customer lifespan. Increasing CLV through personalization, loyalty programs, and excellent customer experience is often more profitable than constantly acquiring new customers. Personalization platforms like LimeSpot help increase CLV by driving repeat purchases and higher order values.

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    D

    Dynamic Content

    Dynamic content refers to website elements that change based on who is viewing them. Unlike static content (which is the same for everyone), dynamic content adapts to individual visitors based on their behavior, preferences, location, or customer segment. Examples include personalized banners, customized product grids, and tailored messaging. LimeSpot enables dynamic content personalization across Shopify and BigCommerce stores without requiring code changes.

    Content Personalization
    E

    E-commerce

    E-commerce (electronic commerce) refers to buying and selling goods or services over the internet. It encompasses online retail stores, digital marketplaces, B2B transactions, and subscription services. Modern e-commerce platforms like Shopify and BigCommerce provide the infrastructure for businesses to sell online, while personalization solutions like LimeSpot help merchants create unique shopping experiences that drive revenue growth.

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    E-commerce Personalization

    E-commerce personalization is the practice of dynamically tailoring online shopping experiences to individual customers based on their behavior, preferences, purchase history, and demographic data. This includes personalized product recommendations, customized content, targeted promotions, and individualized email campaigns. Effective personalization increases conversion rates, average order value (AOV), and customer loyalty by making each shopper feel understood and valued. LimeSpot provides AI-powered e-commerce personalization for Shopify and BigCommerce stores.

    Learn about LimeSpot's personalization

    Exit-Intent Popup

    An exit-intent popup is a message or offer that appears when a visitor shows signs of leaving a website, typically detected by mouse movement toward the browser's close button or address bar. Exit-intent popups are commonly used to capture email addresses, offer discounts, or show last-chance product recommendations to prevent abandonment. When combined with personalization, exit-intent popups can display relevant products based on what the visitor was browsing.

    Personalized Discounts & Offers

    Email Personalization

    Email personalization goes beyond using a customer's name—it involves dynamically customizing email content based on individual preferences, behavior, and purchase history. This includes personalized product recommendations, abandoned cart reminders with specific items, post-purchase cross-sells, and targeted promotions based on customer segments. LimeSpot integrates with email platforms like Klaviyo, Mailchimp, and Omnisend to power personalized product recommendations in emails.

    Email & SMS Experience
    F

    Frequently Bought Together

    Frequently Bought Together is a recommendation type that suggests products commonly purchased alongside the item a customer is viewing. Based on historical purchase data, these recommendations help customers discover complementary products they might need. For example, showing batteries with electronic devices or matching accessories with clothing. This is one of the most effective cross-sell strategies, and LimeSpot's AI automatically identifies and displays these product relationships.

    Smart Recommendations
    H

    Headless Commerce

    Headless commerce is an e-commerce architecture where the front-end (what customers see) is decoupled from the back-end (commerce functionality). This allows brands to use any technology for their storefront while leveraging platforms like Shopify or BigCommerce for cart, checkout, and order management. LimeSpot supports headless implementations, providing personalization APIs that work with custom storefronts.

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    Hyper-Personalization

    Hyper-personalization goes beyond basic personalization by using real-time data and AI to deliver highly individualized experiences at every touchpoint. While traditional personalization might segment customers into groups, hyper-personalization treats each customer as a unique individual. This includes real-time product recommendations, dynamic pricing, personalized content, and contextual offers. LimeSpot's AI enables hyper-personalization by processing behavior signals in real-time.

    Explore LimeSpot Solution
    K

    Klaviyo

    Klaviyo is a leading email and SMS marketing platform designed for e-commerce businesses. It enables automated flows, segmentation, and personalized messaging based on customer data. LimeSpot integrates natively with Klaviyo to inject AI-powered product recommendations directly into email campaigns, increasing click-through rates and revenue from email marketing.

    LimeSpot + Klaviyo Integration
    M

    Multi Storefront

    Multi Storefront is a BigCommerce feature that allows enterprise merchants to manage multiple online stores from a single account. Each storefront can have unique branding, products, and pricing while sharing a common backend. LimeSpot supports BigCommerce Multi Storefront, enabling personalization across all storefronts with the ability to share learnings or keep strategies separate per store.

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    Machine Learning

    Machine learning is a subset of artificial intelligence where algorithms learn from data to make predictions or decisions without being explicitly programmed. In e-commerce personalization, machine learning analyzes customer behavior, purchase patterns, and product data to predict what each shopper is most likely to buy. LimeSpot's machine learning models continuously improve based on your store's data, delivering increasingly accurate recommendations over time.

    Learn about LimeSpot AI
    P

    Post-Purchase Upsell

    Post-purchase upsell is a strategy that presents additional product offers to customers immediately after they complete a purchase, typically on the thank-you page or order confirmation. Since the customer has already committed to buying, they're often receptive to relevant add-ons. LimeSpot's Checkout & Post-purchase Upsells feature (for Shopify) enables one-click upsells on checkout, thank-you pages, and order status pages.

    Smart Recommendations

    Product Recommendations

    Product recommendations are suggestions shown to shoppers based on algorithms that predict what they're most likely to purchase. Types include 'Frequently Bought Together' (complementary products), 'You May Also Like' (similar items), 'Recently Viewed' (browsing history), 'Trending Products' (popular items), and 'Personalized For You' (AI-driven individual suggestions). AI-powered recommendation engines like LimeSpot analyze real-time behavior and purchase patterns to deliver highly relevant suggestions that increase conversion rates and revenue.

    Explore Smart Recommendations

    Personalization Engine

    A personalization engine is software that analyzes customer data and behavior to deliver individualized experiences across digital touchpoints. It uses algorithms (often AI/ML-based) to determine what content, products, or offers to show each visitor. Key capabilities include product recommendations, content personalization, customer segmentation, and A/B testing. LimeSpot is an AI-powered personalization engine specifically designed for Shopify and BigCommerce stores.

    Explore LimeSpot Features
    R

    Recommendation Box

    A recommendation box (also called a recommendation widget) is a UI component on an e-commerce site that displays personalized product suggestions to shoppers. Recommendation boxes can be placed on product pages, home pages, collection pages, cart pages, and checkout. LimeSpot provides fully customizable recommendation boxes that match your store's design and can be configured with different algorithms like 'You May Also Like,' 'Frequently Bought Together,' or 'Trending Now.'

    Smart Recommendations

    Recommendation Engine

    A recommendation engine is the AI/ML system that powers product recommendations by analyzing customer data, behavior patterns, and product attributes to predict what each shopper is most likely to purchase. Unlike simple rule-based systems, modern recommendation engines like LimeSpot use machine learning algorithms including collaborative filtering, content-based filtering, and deep learning to continuously improve accuracy. The engine processes real-time signals to ensure recommendations stay relevant as customers browse.

    Smart Recommendations

    Recently Viewed

    Recently Viewed is a recommendation type that displays products a customer has previously looked at during their browsing session or past visits. This helps shoppers quickly return to items they were considering, reducing friction in the purchase decision. Recently Viewed widgets are particularly effective on home pages and cart pages, serving as a reminder of products the customer showed interest in.

    Smart Recommendations

    Retargeting

    Retargeting (also called remarketing) is a marketing strategy that shows ads to people who have previously visited your website or interacted with your brand. In e-commerce, retargeting often displays products a customer viewed but didn't purchase. While LimeSpot focuses on on-site personalization rather than ads, its data can inform retargeting campaigns by identifying high-intent products for each customer.

    Performance Analytics

    Real-Time Personalization

    Real-time personalization delivers customized experiences instantly as customers browse, rather than relying solely on historical data. It adapts to in-session behavior like products viewed, time on page, and cart contents. Real-time personalization is more effective than batch-processed personalization because it responds to immediate intent signals. LimeSpot processes behavior in real-time to ensure recommendations are always relevant to what the customer is doing right now.

    Explore LimeSpot Solution
    S

    Shapeshifting

    Shapeshifting is LimeSpot's philosophy of creating dynamic, adaptive e-commerce experiences that transform based on who is shopping. Rather than showing the same static store to everyone, a shapeshifting store continuously adapts its product recommendations, content, promotions, and messaging to match each individual customer's preferences and behavior. This approach treats personalization as a core store capability rather than an add-on feature.

    Learn about Shapeshifting

    Smart Collections

    Smart Collections are dynamic product groupings that automatically adapt based on customer behavior, preferences, and real-time trends. Unlike static collections that show the same products to everyone, Smart Collections personalize which products appear and in what order for each visitor. LimeSpot's Smart Collections feature elevates product discovery by ensuring customers see the most relevant items first.

    Content Personalization

    SMS Personalization

    SMS personalization involves customizing text message marketing based on individual customer data, behavior, and preferences. This includes personalized product recommendations, targeted promotions, and segment-specific messaging delivered via SMS. LimeSpot integrates with SMS platforms to enable personalized product suggestions in text message campaigns, increasing engagement and conversion rates.

    Email & SMS Experience

    Shopify

    Shopify is a leading e-commerce platform that powers millions of online stores worldwide. It provides tools for building, managing, and scaling online businesses. LimeSpot is available in the Shopify App Store and provides AI-powered personalization including product recommendations, customer segmentation, and email personalization for Shopify and Shopify Plus stores.

    LimeSpot for Shopify
    T
    U

    Upselling

    Upselling is a sales technique that encourages customers to purchase a higher-end version of a product or add premium features to their order. Unlike cross-selling (which suggests complementary items), upselling focuses on upgrading the primary purchase. Examples include suggesting a larger size, premium edition, or extended warranty. Smart upselling increases revenue while ensuring customers get the best product for their needs. LimeSpot's recommendation engine identifies optimal upsell opportunities based on customer behavior and product data.

    Cross-sell & Upsell Guide
    W

    Widget

    In e-commerce personalization, a widget is a self-contained UI component that can be placed on any page of your store to display dynamic content like product recommendations, personalized banners, or promotional offers. LimeSpot widgets are fully customizable to match your store's design and can be configured with different recommendation algorithms, layouts, and styling. Widgets can be added via app blocks (Shopify 2.0), embed codes, or API integration.

    Smart Recommendations
    Y

    You May Also Like

    You May Also Like is a recommendation type that suggests products similar to the item a customer is currently viewing, based on product attributes, browsing patterns, and purchase correlations. These recommendations help customers discover alternatives or related items they might prefer. LimeSpot's 'You May Also Like' algorithm uses AI to identify the most relevant similar products rather than just matching by category.

    Smart Recommendations
    Z

    Zero-Party Data

    Zero-party data is information that customers intentionally and proactively share with a brand, such as preferences, purchase intentions, or personal context. Unlike first-party data (observed behavior) or third-party data (purchased from external sources), zero-party data comes directly from the customer. Examples include quiz responses, preference settings, or wishlist items. Personalization platforms can use zero-party data alongside behavioral signals for more accurate recommendations.

    Customer Segmentation

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