Digital commerce has a “shelf,” even when there are no physical aisles. In **Paid Marketing**, understanding where your products appear—both in paid placements and unpaid results—can determine whether you win the click, the sale, or the repeat customer.
Ntb Rate is a practical way to understand how much of your growth in **Paid Marketing** is coming from *new* customers rather than people who already know and buy from your brand. In the context of **Shopping Ads**, it helps answer a crucial question: are your product ads expanding your customer base, or mainly converting existing shoppers who would have purchased anyway?
New-to-brand is a measurement and optimization concept in **Paid Marketing** that helps you understand how much of your advertising performance comes from customers who haven’t purchased from your brand before. In the context of **Shopping Ads**, it’s especially valuable because these campaigns often capture high-intent shoppers who are comparing products, prices, and sellers in real time.
Misrepresentation is one of the fastest ways to lose efficiency, trust, and platform access in modern Paid Marketing. In the context of Shopping Ads, Misrepresentation happens when an ad, product feed, or landing page communicates information that is inaccurate, incomplete in a misleading way, or inconsistent with what the shopper will actually receive.
Merchant Promotions are a structured way for retailers to surface special offers—such as discounts, free shipping, or gifts—directly alongside product listings in **Shopping Ads**. In **Paid Marketing**, where shoppers compare prices and value in seconds, promotions can be the difference between a scroll-past and a click.
Merchant Center Diagnostics is the health check system for your product data and account eligibility in Paid Marketing—especially when you rely on Shopping Ads to drive revenue. It surfaces what’s preventing products from serving, what could limit performance, and what you can improve in your feed, policies, pricing, and shipping setup.
Margin Tier is a way to group products (or services) by how much profit they generate, then use those groups to guide bidding, budgets, and priorities in **Paid Marketing**. In **Shopping Ads**, where you often advertise thousands of SKUs at once, a Margin Tier approach helps you avoid a common trap: optimizing for revenue while quietly losing profit.
In **Paid Marketing**, product-based campaigns rise or fall on data quality and consistency. One of the most important pieces of that foundation is the **Item Id**—a unique identifier that represents a specific product in your catalog across your product feed, ad platform, reporting, and optimization workflows.
In **Paid Marketing**, product-based campaigns live or die by data structure. One of the most important (and misunderstood) pieces of that structure is the **Item Group Id**—a value used in product catalogs and feeds to group related product variants so ad platforms can understand what belongs together.
Inventory Filter is a foundational concept in **Paid Marketing**, especially for retailers and brands running **Shopping Ads**. At its core, an Inventory Filter is a rule-based way to decide *which products* are eligible to be promoted (or excluded) based on inventory-related signals such as stock availability, sell-through rate, margin, seasonality, pricing, or fulfillment constraints.
In **Paid Marketing**, images are often the first (and sometimes only) element a shopper evaluates before clicking. An **Image Quality Issue** is any problem with a product image that reduces eligibility, visibility, trust, or conversion performance—especially in **Shopping Ads**, where the image is the core creative asset.
A **Harvest Campaign** is a deliberate approach in **Paid Marketing** where you run a discovery-oriented campaign to uncover new demand—then “harvest” the winners into more controlled structures for scaling and efficiency. In the context of **Shopping Ads**, it typically means using broad or less-restricted inventory (products, queries, audiences, or placements) to find what converts, then moving high-performing learnings into tightly managed campaigns with clearer budgets, bids, targeting boundaries, and reporting.
Product feeds are the backbone of performance for ecommerce advertising, but they only work as well as the data behind them. **Google Product Category** is a standardized classification you assign to items in a product feed so Google can understand what you sell and match products to relevant queries and placements. In **Paid Marketing**, especially with **Shopping Ads**, this classification helps drive accurate targeting, compliance, and reporting—often with a bigger impact than people expect.
Free Local Listings are unpaid product placements that help nearby shoppers discover in-stock items at local stores across search, maps, and other commerce surfaces. Even though they are “free,” they matter deeply in **Paid Marketing** because they use many of the same inputs—product data, inventory signals, and store information—that power modern **Shopping Ads**.
Free Listings are a product visibility opportunity that sits at an interesting crossroads of **Paid Marketing** and commerce SEO. They let eligible products appear across shopping-focused surfaces without paying per click, yet they still rely on many of the same feed, policy, and measurement foundations used for **Shopping Ads**.
A **Feed Rule** is a structured instruction that automatically changes, enriches, or filters product data before it’s used in advertising. In **Paid Marketing**, especially in **Shopping Ads**, the quality and consistency of product data often determines what gets shown, how it’s described, and whether it’s eligible at all. Feed Rules help teams scale improvements across thousands of SKUs without manually editing every product record.
Feed Fetch is a foundational concept in modern **Paid Marketing**, especially for brands running **Shopping Ads** across comparison-style ad placements. At a high level, Feed Fetch describes the process of *retrieving a data feed* (most often a product feed) from a source system so it can be processed, validated, and used to power ads.
Feed Disapproval is one of the most common (and most costly) issues teams run into when scaling **Paid Marketing** through **Shopping Ads**. Even a well-funded campaign can stall if products aren’t eligible to serve because the product feed fails policy or data-quality requirements.
A **Feed Attribute** is a single, structured piece of product information—such as title, price, availability, brand, or color—submitted as part of a product feed to power **Shopping Ads**. In **Paid Marketing**, these attributes act like the “input fields” that ad platforms and retail networks rely on to match products to user queries, enforce policy compliance, and decide how (and whether) items show.
A **Feed API** is a programmatic way to send, update, and validate product or content data between systems—most commonly between your commerce platform (or product database) and the channels that power **Paid Marketing** and **Shopping Ads**. Instead of relying on manual uploads or occasional file exports, a Feed API enables near-real-time updates to prices, availability, titles, and attributes that determine whether your products are eligible and competitive in auction-based marketplaces.
Detail Page View Rate is a performance metric used in **Paid Marketing** to show how often shoppers who engage with your **Shopping Ads** actually reach a product’s detail page (also called a product page or PDP). In plain terms, it measures whether your ad traffic is progressing from “I saw or clicked the ad” to “I’m viewing the product.”
Detail Page Sales is a revenue-focused concept used in **Paid Marketing** to understand how much sales value is generated after a shopper lands on a product’s detail page (often called a product page). In many ecommerce journeys—especially those driven by **Shopping Ads**—the product detail page is the moment of truth: it’s where shoppers decide whether to trust the product, choose a variant, and purchase.
A **Defense Campaign** is a deliberate paid strategy designed to protect your existing demand, profitability, and brand presence from competitors—especially in high-intent placements like **Shopping Ads**. In **Paid Marketing**, it’s the difference between “we’re growing” and “we’re losing our best customers to someone else’s bidding strategy.”
A **Deal Badge** is a visual label shown alongside a product in an ad or product listing to signal a promotion—such as a price drop, limited-time offer, or special deal. In **Paid Marketing**, especially in **Shopping Ads**, this small piece of UI can have an outsized impact because it changes how users scan results, compare products, and decide what to click.
Custom Label Bidding is a strategy in **Paid Marketing** where you adjust bids, budgets, or bid targets for products in **Shopping Ads** based on *custom labels* you assign in your product feed. Instead of treating every SKU the same, you use business-aware groupings—like margin tiers, seasonality, inventory status, or best-seller flags—to steer spend toward what matters most.
In **Paid Marketing**, the difference between “running product ads” and “running profitable product ads” often comes down to how well you structure and control your product segmentation. A **Custom Label** is one of the most practical ways to add business context to your product data so you can organize, bid, and report on products based on what *matters to your business*—not just what’s available in default product attributes.
A **Coupon Badge** is a visual label that highlights an available discount (such as a percent-off, fixed amount off, or “save with code” offer) directly on an ad or product listing. In **Paid Marketing**, especially within **Shopping Ads**, this small element can have an outsized effect: it changes how a shopper perceives price, value, urgency, and trust before they ever click.
In **Paid Marketing**, the ads you buy are only as effective as the content behind them. **Content Quality Score** is a practical way to evaluate how strong, complete, and conversion-ready your marketing content is—especially the product information, landing pages, creatives, and messaging that power **Shopping Ads**. Think of it as a structured assessment that answers: “Is this content good enough to win the click, earn trust quickly, and convert efficiently?”
In **Paid Marketing**, few product data details are as deceptively influential as **Condition**. In the context of **Shopping Ads**, Condition describes the state of the item you’re advertising—most commonly **new**, **used**, or **refurbished**—and it shapes how platforms interpret your offer, how shoppers perceive your listing, and how efficiently your budget turns into revenue.
Competitor Conquesting is a deliberate **Paid Marketing** strategy where you design campaigns to win customers who are actively considering a competing brand or product. In the context of **Shopping Ads**, it typically means shaping product feed data, bidding, and targeting so your products appear when shoppers search for competitor terms, compare options, or browse competitor-like products.