SabinoDB E-commerce Glossary
Navigating the Digital Marketplace: Your Comprehensive A to Z Guide to E-Commerce Terms
12-Month Active Customer File
In e-commerce, the 12-Month Active Customer File represents a database of customers who have made a purchase on the website within the last year. This data is crucial for analyzing recent customer engagement, personalizing online marketing efforts, and forecasting sales trends. It enables e-commerce businesses to concentrate on nurturing relationships with active customers and re-engaging those who have shown recent interest in the brand.
A/B Testing
A/B Testing, also known as split testing in e-commerce, is a method used to compare two versions of a web page or app against each other to determine which one performs better. It involves showing two variants (A and B) to different segments of website visitors at the same time and measuring the effect on a specific metric such as Conversion Rate (CVR), Click-Through Rate (CTR), or any other key performance indicator. The goal is to identify changes that increase the likelihood of what an e-commerce site wants to achieve (e.g., more sign-ups, increased sales).
Abandoned Cart
An Abandoned Cart occurs when a customer adds products to their online shopping cart but exits without completing the purchase. Abandoned Cart recovery strategies are essential for e-commerce businesses to recapture potential lost sales.
ACoS (Advertising Cost of Sale)
ACoS, or Advertising Cost of Sale, is a metric used by Amazon to measure the efficiency of an advertising campaign. It is calculated by dividing the total spend on a specific advertising campaign by the revenue generated from that campaign, expressed as a percentage. ACoS is the inverse of Return on Ad Spend (ROAS). A lower ACoS indicates a more cost-effective campaign, meaning you are spending less in advertising to generate each dollar of revenue. This metric is particularly important for businesses using platforms like Amazon to track the performance of their paid advertising efforts.
AOV (Average Order Value)
Average Order Value (AOV) is an essential e-commerce metric representing the average amount spent per order within a specific timeframe. AOV is calculated by dividing total revenue by the number of orders, providing insights into customer spending habits and the effectiveness of pricing and marketing strategies.
Bounce Rate
Bounce Rate in e-commerce refers to the percentage of visitors who navigate away from a site after viewing only one page. It’s a key metric for understanding website engagement and effectiveness. A high bounce rate may indicate that the site is not relevant or engaging enough for visitors, or that the landing page does not effectively encourage further interaction. Reducing bounce rate can involve improving website design, content relevancy, and user experience to better capture and retain visitor interest.
Bundling
Bundling in e-commerce refers to the practice of selling multiple products or services together as a single combined package, often at a discounted price. This strategy not only increases the perceived value for customers but also can drive higher sales volume and improve inventory management.
Click-Through Rate (CTR)
Click-Through Rate (CTR) is a key performance metric in digital marketing that measures the ratio of users who click on a specific link to the number of total users who view a page, email, or advertisement. Expressed as a percentage, CTR is used to gauge the effectiveness of online advertising campaigns and email marketing strategies in e-commerce. A higher CTR indicates that the content or ad is relevant and appealing to the audience, leading to more traffic to the advertiser’s website.
Conversion Rate (CVR)
The Conversion Rate (CVR) in e-commerce is the percentage of visitors to a website who complete a desired action (like making a purchase) out of the total number of visitors. A high CVR indicates successful marketing and web design.
Cost Per Click (CPC)
Cost Per Click (CPC) is a digital advertising metric that measures the amount paid by an advertiser for each click on their advertisement. In e-commerce, CPC is used to evaluate the cost-effectiveness and profitability of online advertising campaigns, such as those on search engines and social media platforms. The CPC model ensures that advertisers pay only when users actively engage with their ads, making it a focused approach to driving traffic and potential sales to their website.
Cost Per Lead (CPL)
Cost Per Lead (CPL) is a key performance metric in e-commerce and digital marketing that measures the cost-effectiveness of marketing campaigns in generating new leads. It is calculated by dividing the total cost of a marketing campaign by the number of leads generated from that campaign. This metric helps businesses understand how much they are spending on average to acquire a potential customer. CPL is essential for evaluating the ROI of marketing strategies, particularly in lead generation efforts like email marketing, social media campaigns, and online advertising. A lower CPL indicates a more efficient use of resources in acquiring leads.
Customer Acquisition Cost (CAC)
Customer Acquisition Cost (CAC) is a key metric in e-commerce that represents the total cost of acquiring a new customer. It encompasses all the expenses incurred in marketing and sales efforts to attract and convert a visitor into a paying customer. These costs typically include advertising spend, marketing team salaries, the cost of technology and tools used for marketing, and any other related expenses. CAC is crucial for understanding the investment required to expand a customer base and is often analyzed in conjunction with Customer Lifetime Value (CLV) to determine the long-term financial health and sustainability of the e-commerce business.
Customer Lifetime Value (CLV)
Customer Lifetime Value (CLV) is a critical metric in e-commerce that estimates the total revenue a business can reasonably expect from a single customer account throughout the business relationship. CLV helps companies identify the most profitable customer segments, guiding marketing strategies and resource allocation. It factors in the customer's purchase history, frequency of transactions, and average order value, providing insights into customer behavior and the long-term value they bring to the business.
Discovery
Discovery in the context of e-commerce refers to the process by which customers find new products or brands that they were previously unaware of. It involves the initial encounter and subsequent interest in products that align with customers' preferences or needs. Effective discovery mechanisms include personalized product recommendations, curated content, and targeted marketing strategies.
Dynamic Product Listing
Dynamic Product Listing in e-commerce refers to the real-time personalization of product displays on a website based on user behavior, preferences, or other specific criteria. This approach adjusts the product listing dynamically, showing items more likely to interest the user, thus enhancing personalization and potentially increasing conversion rates.
Facets
Facets in e-commerce are specific attributes or characteristics of products used to refine and organize search results. They allow customers to filter products based on criteria like size, color, price range, brand, etc. Facets enhance user experience by simplifying the search process, helping customers navigate large inventories, and making it easier to find products that meet their specific requirements.
Filters
Filters in e-commerce are tools that allow customers to refine product searches or category views based on certain criteria. These criteria can include facets like size, color, brand, or price, as well as other types of criteria like customer ratings, availability, or shipping options. Filters improve the shopping experience by helping customers narrow down choices and find products that fit their specific needs or preferences quickly.
Personalization
Personalization in e-commerce refers to the customization of the shopping experience to individual customer preferences and behaviors. It involves tailoring product displays, recommendations, and content to meet specific user needs. For example, 'Shop the Look' recommendations suggest complete outfits based on a customer's browsing history, while personalized 'Site Search' enhances search results and suggestions based on previous interactions and queries. This targeted approach aims to improve customer engagement and increase sales by providing a more relevant and individualized shopping experience.
Product Detail Page (PDP)
The Product Detail Page (PDP) is a web page on an e-commerce site that provides detailed information about a specific product. This typically includes product images, descriptions, specifications, pricing, and customer reviews, all aimed at helping customers make informed purchasing decisions.
Product Listing Page (PLP)
The Product Listing Page (PLP) in e-commerce is a page that displays a collection of products, usually categorized or grouped by certain criteria like type, brand, or collection. This page allows customers to browse through products, often with options to filter or sort them based on various attributes.
Pay-Per-Click (PPC)
Pay-Per-Click (PPC) is an online advertising model in which an advertiser pays a publisher (typically a search engine, website owner or a network of websites) each time an advertisement link is "clicked" on. PPC is commonly associated with search engines and social media platforms and is used extensively in digital marketing campaigns.
Product Attribution Tagging
Product Attribution Tagging in e-commerce is the practice of assigning relevant tags or attributes to products, such as color, size, brand, or material. These tags help in categorizing and organizing products within a database, allowing for more accurate and efficient search and filter functions. Effective product attribution tagging is crucial for enhancing product discoverability, site search and product recommendation algorithms, and improving the overall shopping experience.
Product Discovery
Product Discovery in e-commerce refers to the process through which customers find and become aware of a product that meets their needs or interests. It involves the journey from initial awareness to the consideration and eventual decision to purchase. Effective product discovery is facilitated by personalized recommendations (e.g., shop the look, frequently bought together), intuitive site navigation, and efficient search functionality, aiming to connect customers with the right products quickly and seamlessly.
Product Recommendations
Product Recommendations are a feature in e-commerce that suggests products to customers based on a variety of factors including browsing history, purchase history, and user preferences. This personalization enhances the shopping experience and can lead to increased sales and customer satisfaction. Common types of product recommendations include: frequently bought together, customers who viewed this also viewed, customers who bought this also bought, shop the look outfits, and best sellers, among others.
ROAS (Return on Advertising Spend)
Return on Advertising Spend (ROAS) is a marketing metric that measures the efficacy of a digital advertising campaign. ROAS calculates the amount of revenue earned for every dollar spent on advertising. It's a key indicator of the success and profitability of online advertising efforts. For more information on ROAS, see here.
Shop the Look
'Shop the Look' is an e-commerce product recommendation type used in fashion and apparel retail to showcase how individual products can be combined into a styled outfit, enhancing the shopping experience by providing style inspiration and facilitating cross-selling. For more information on ‘Shop the Look’ recommendations, see here.
UX (User Experience)
User Experience (UX) in e-commerce refers to the overall experience a user has when interacting with a website or digital application, especially in terms of how easy or pleasing it is to use. A positive UX is crucial for keeping visitors engaged and converting them into customers.
