Category: Shopping Ads

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.

A **Clearance Label** is a structured way to mark products that a business wants to sell through quickly—typically because they’re discontinued, end-of-season, overstocked, or being replaced. In **Paid Marketing**, that label becomes more than internal merchandising; it becomes a targeting and bidding signal that helps you control how those products appear and compete in **Shopping Ads**.

Catalog Health is the discipline of keeping your product catalog accurate, complete, and consistently structured so ad platforms can reliably select, rank, and display your products. In **Paid Marketing**, it’s the foundation that makes **Shopping Ads** work as intended: the ad system can only promote what it can understand, trust, and match to user intent.

Buy on Google is a commerce experience that lets shoppers discover products on Google surfaces and complete a purchase with less friction—often without feeling like they’re “starting over” on a separate retail site. In **Paid Marketing**, it’s closely connected to **Shopping Ads** because it changes what “conversion” looks like: the ad click may lead to a streamlined checkout flow that keeps shoppers in a purchase mindset instead of forcing multiple steps and page loads.

Buy Box Percentage is a deceptively simple metric with outsized impact in **Paid Marketing**, especially when you run **Shopping Ads** for products that compete against other sellers, offers, or retailers on the same item. It tells you how often your offer is the one customers can actually buy from in the primary purchase area—meaning your ads and product visibility can translate into sales instead of “almost” sales.

In **Paid Marketing**, the **Buy Box** is one of the most consequential pieces of real estate in commerce: it’s the default purchase option a shopper sees on a product detail page when multiple sellers (or multiple offers) exist for the same item. In practice, the **Buy Box** determines which offer gets the primary “add to cart/buy now” path—and, on many marketplaces, it also determines which offer is eligible to appear in **Shopping Ads** placements tied to that product.

Branded Search Volume is the amount of search activity that includes your brand name (or clear brand identifiers) in the query—signals like “YourBrand shoes,” “YourBrand running trainers,” or “YourBrand promo code.” In **Paid Marketing**, this demand is one of the clearest indicators of brand awareness and purchase intent, because the searcher is explicitly looking for you, not a generic category.

A **Brand Store** is a dedicated, brand-controlled storefront experience—typically hosted on an ecommerce marketplace or retail media network—where shoppers can browse a curated catalog, learn your value proposition, and move from discovery to purchase without leaving the platform. In **Paid Marketing**, a Brand Store often functions as the “owned destination” that your campaigns (especially **Shopping Ads**) send traffic to when a standard product detail page is too narrow for storytelling, cross-selling, or portfolio merchandising.

Brand Metrics are the set of measurements that tell you how people perceive, remember, and prefer your brand—and how those perceptions influence commercial outcomes. In **Paid Marketing**, they connect what happens at the top of the funnel (awareness, consideration, trust) to what you can measure at the bottom (clicks, conversions, revenue).

In **Paid Marketing**, product-driven campaigns live or die by the quality of the data that describes each item you sell. A **Brand Attribute** is one of the most important pieces of that data: it tells ad platforms what brand a product belongs to, in a consistent, machine-readable way. In **Shopping Ads**, where targeting and ad rendering are heavily influenced by product feeds, the **Brand Attribute** often determines whether a product is properly matched to shopper intent, compared against competitors, or grouped into meaningful performance reporting.

In modern **Paid Marketing**, product catalogs are rarely “equal.” A handful of items usually drive a disproportionate share of revenue, conversions, and repeat purchases. **Best Seller Tier** is the practical framework marketers use to identify those top-performing products and give them the right level of budget, bidding, and creative emphasis—especially inside **Shopping Ads**, where product-level performance differences can be dramatic.

Availability Mismatch is one of the most common (and costly) operational issues in **Paid Marketing**, especially for retailers running **Shopping Ads**. It happens when the availability a platform believes you have (based on feeds, structured data, or landing pages) doesn’t match what customers actually encounter when they click—such as seeing an “out of stock” message, backorder notice, or an unavailable variant.