An Overview of the Pay-Per-Click (PPC) System
What is Pay-Per-Click?
Pay-per-click (PPC) is a model of online advertising in which advertisers pay for the clicks their ads receive. Advertisers bid for the opportunity to show their ad in a specific context they deem valuable for their specific goals. The context may be based on keywords, a specific targeted audience, or even the placement location–any of which are calculated values for the advertiser at generating leads, selling products or services, or creating consideration. Advertisers bid for the limited space available on a search engine results page, or for prime placements in popular content for contextual ads. Clicked ads lead to targeted content, whether a product purchase page, an informational page, newsletter, app download, or other lead generation tool or action with value for the business.
The cost structure of PPC allows advertisers to estimate costs in advance with specific maximum cost-per-click (CPC), or even costs per conversion or action bids (CPA). The wide-range of placement options allows advertisers to target customers at any step of the customer journey, from connecting to a transactional search directly on the search engine results page (SERP), or at product comparison points with informational ads on social media.
The ability to show a relevant ad exactly at the moment a consumer is searching for the same or similar content allows immediate placement closest to a consumer’s query or interest. This gives advertisers the best chance of meeting users at their point of highest intent.
The diverse set of platforms and the hyper-configurability of options almost guarantees that a PPC platform is able to facilitate translating nearly any business strategy into tactics that closely align and support that strategy. Popular platforms such as Google, Bing, Facebook allow campaign structures, bidding strategies, and targeting tactics that cover multitudes of business and customer dynamics. Additionally, dozens of smaller niche platforms such as LinkedIn and Quora focus on specific audiences and journeys, further expanding businesses’ options in communicating to target markets.
Defining PPC Today
As pay-per-click evolved and expanded, the initial general description as a cost model, however, became misleading given the diverse platforms and practices generally considered pay-per-click (PPC). For most practitioners, PPC spans a broad range of platforms and purposes. Even within Google Search ads, the use of smart bidding immediately diminishes the idea of pay-per-click, as the advertiser is no longer pricing by clicks, but on acquisitions (CPA), or conversion value (ROAS). In addition, Google’s Display networks are generally bid via impressions (CPM) vs maximum click bid when bidding is manual (and not using smart bidding).
In addition to Google Ads and Microsoft Advertising, popular PPC platforms now include Facebook, Amazon, Twitter, as well as dozens of smaller specialty platforms.
While PPC is the model for paying for each ad click, the metric advertisers and platforms use to measure cost is usually expressed as cost-per-click (CPC). Many platforms are known for creating brand awareness and provide value for impressions. However, when the focus is on user interaction, advertisers are no longer concerned about impressions, but on the click, and the CPC.
Cost-per-click (CPC) is a metric determining what the average cost per click is regardless of the selling model by the publisher. This is sometimes not the source metric but is instead simply calculated out of the total cost, as shown below.
Cost-per-click ($) = Advertising cost ($) / Ads clicked (#)
A Brief History of PPC Advertising
As online research and shopping have become a daily part of the consumer experience, pay-per-click ads are a seamless part of the online user experience. However, when PPC advertising began, reception was mixed. Some business leaders pointed out they really didn’t care how many clicked through to the target website but wanted to know what they did once there. Even the CEO of Lycos questioned the integrity of placing paid ads within supposedly neutral search engine results pages (SERPs).
1996 saw Planet Oasis create a desktop application with a virtual city homepage populated by buildings branded by participating businesses. Each company paid to be featured and then paid for each click on their respective logos to launch company websites.
The same year, Open Text proposed that advertisers could bid on keywords to place their company or product high in their search engine results page (SERP). In 1998, Goto.com launched a PPC advertising model for their search engine, allowing businesses to bid against each other for keywords. At the time, however, auctions were not real-time and took hours to update.
While some may have questioned the integrity of including paid ads in SERPs, at the time, search engines were crude and returned as much spam as they did relevant results. As a result, paid results aligned with query keywords were not likely to degrade search results significantly.
Today, search engines use complex algorithms to ensure paid ads are as relevant as top organic results; a key platform goal is to provide relevant results that match the searcher’s intent. Returning accurate organic and paid results increases user satisfaction, usage, and ultimately, revenue.
Key Platform Milestones
1995: Yahoo! launches with advertisements.
1996: Early PPC experiments with Planet Oasis and Open Text
1999: Google begins search advertising
2000: Google launches AdWords; Yahoo! becomes the most valuable company in the world
2002: Earthlink and AOL drop Overture (formerly Goto.com) in favor or Google’s search engine
2004: Google reaches $1B in ad revenue and goes public
2005: Google Analytics launched; Youtube.com registered
2006: YouTube acquired by Google; Microsoft launches MSN adCenter
2007: Facebook launches Ad Network
2012: Amazon Advertising Platform launched
The history of PPC advertising is a cycle of acquisitions, partnerships, and rebranding. Search engines partnered with advertising innovators, bought competitors, and eventually developed their own advertising platforms. Over the last 15 years, new PPC ad platforms proliferated, and leaders such as Google, Bing, and Facebook, as well as their competitors, continuously updated and improved their advertising systems:
- Ad management UI: improved ease-of-use, accessible and impactful features, wizards for setup and configuration of ads and campaigns
- Keyword and bidding tools: bid simulators to predict impact of bid changes, keyword research tools calculating search volume and competition
- Advanced bidding methods: automated bids, e.g., by Cost-Per-Acquisition or -Action (CPA), by conversion value (Return on Ad Spend, or ROAS) using machine learning
- Mobile targeting: device segmentation, ads designed specifically for mobile.
- Tracking and analytics: internal, add-on, and 3rd party tools for multiple levels of tracking and analytics
- Platform proliferation: growth in the number of ad platforms for different specific niche targeting
- Ad formats and types: from simple image and text-based ads to dynamically generated ads
- Advanced targeting: pinpoint targeting using combinations of augmented keywords, demographics, audience interests, contextual placements, scheduling
- Automation: advanced algorithms and machine learning determining when, where, and in what context ads are placed in order to achieve advertiser goals
Over two decades of improvements have helped to make PPC dominate digital advertising today. Search engines and content platforms realize enormous revenue from advertising, both in real dollars and in many cases, as a percentage of total revenue. Consequently, ad platforms and networks are incented to continue improving the advertiser experience and impact of advertising. As businesses find platforms increasingly effective for successful marketing, the more they will spend, and the more the platform profits.
Platform Revenue and Advertising
Note: providers of predominantly free services such as social media and search engines are subsidized almost entirely by advertising, while e-commerce sites and product companies rely on profit from product margins.
The PPC Advertising Overview
PPC platforms span levels of complexity from nearly DIY for a one-person marketer-friendly Quora, in which creating trackable ads is a fairly linear no-frills exercise, to Google Ads for which the configuration options can overwhelm even experienced marketers.
However, despite the variations and complexities among the dozens of popular PPC platforms, the basic flow for auction-based PPC platforms is generally similar.
The High-Level Process
- Preparing for an Ad Auction
- Define Strategy: Before starting any ad campaign, a business should have a clearly focused strategy, informed by market analysis, defining the value proposition, and identifying the target consumers.
- Design Strategically Aligned Ads: An advertiser should learn the ad formats and targeting options of the chosen PPC platform, research the keywords aligned with the value proposition, design the ad and landing page to align with the keyword research, and select the targeting parameters that most accurately represent the target consumer personas identified by business strategy.
- Place Competitive Bid: Place the bid based on competitive values found during keyword research.
- The Ad Auction
- An ad placement is triggered:
- Someone enters a query on a search engine matching a keyword bid, or
- Someone enters a participating website containing a bid ad placement unit
- A real-time auction takes place between eligible ads to determine placement position based on combinations of:
- Targeting parameters
- Bids entered
- Quality factors (typically includes ad relevance, landing page experience, expected performance, and other proprietary factors)
- An ad placement is triggered:
- Reporting and Analytics
After the auction, marketers should evaluate performance by reviewing built-in reporting and analytics for the platform, and/or separate analytics software. Experience reviewing data allows marketers to understand how their campaigns and components (keywords, ads, targeting) are performing, and use the analytics insights to refine their efforts.
The PPC Framework: Functional Components
The Advantage of Configurability
A fundamental advantage of contemporary PPC ad platforms is in the extraordinary reconfigurability of the system: methods to build out campaigns, multiple ways to augment each keyword researched and selected manual and automated bidding strategies, nearly infinite targeting combinations. As a result, the platform can be tailored to almost any business and customer dynamic.
And because different ad platforms and tools have different applications and unique advantages (think LinkedIn Ads vs Google Ads vs Amazon Advertising; or for tools compare Hubspot vs Ahrefs), a broad working knowledge of several PPC platforms can benefit marketers with complex strategies. Such strategy may need a marketing mix that benefits from a portfolio of functionalities, targeting all of the tactics required to move strategy into practice.
The Challenge and Reward of Complexity
This complexity, however, sometimes presents a challenge. Because configuration options are numerous and interconnected, understanding the potential ramifications for each choice can be difficult to master. Fortunately, online advertisers with relatively straightforward needs can choose a single platform, utilizing a subset of features to accomplish their goals. In fact, today most platforms include wizards to guide users through simple advertising tasks. Many platforms will do nearly everything–just provide the target landing page URL–the system will pull keywords, create keywords to choose, bid selection, and create the advertisement on the fly. But a full multi-channel campaign strategy with sophisticated goals requires a bit more.
Planning, researching keywords and building out targeted landing pages and ad types are resource-intensive. Understanding methods to layer multiple targeting configurations for key audiences, and configuring the tracking of each type of conversion relevant to the business ops, sales, and marketing–all require industry and platform-specific knowledge.
Learning the Basics
While each platform implements the components and tools differently, basic knowledge of each component’s purpose and options should prepare marketers to begin. When selecting a platform, new users of a specific platform must learn how the core functionality is implemented, how configured, and how used to optimize the experience to gain and convert leads.
Understanding the typical framework of components that drive PPC Advertising, an advertiser can select a platform and learn its idiosyncrasies, naming conventions, and unique functions. These are the strategic and tactical tools used to build an exceptional campaign.
The key framework components below are described in detail:
- Ad Formats and Types
- Landing Page
- Bidding and Budgeting
- Ad Auction Functions
- Tracking and Analytics
Keywords in PPC advertising are the words and phrases that connect businesses to their targeted consumers; they are the “key” used by search engines and advertising networks to begin to select ads that align with a user search query or web page context. Advertisers choose keywords that the target audience of the offering will most likely use when searching for the product or solving the need the product meets.
Choosing the right keywords is essential, as an advertiser wants to attract only consumers likely to convert, or complete a transaction once reaching targeted content: a product page, newsletter, app, or page with a call to action (CTA). The keywords must align closely enough with a search query or web page context for the ad to be considered for the Search Engine Results Page (SERP) or targeted web page, respectively.
Because of the primary nature of the keyword in PPC advertising, most ad platforms include keyword research directly in the platform interface. These can range from a self-populating list that appears when creating ads or loading keywords, or a utility that suggests keywords based on web pages or topics. Platform tools may also provide average monthly volume and bid costs. Third-party tools, such as SEMrush and Ahrefs, provide detailed keyword suggestions and statistics regardless of the advertising platform chosen.
In order to more accurately control how closely selected keywords match search engine queries or match contextual placement, keywords may be treated more broadly or more restrictively depending on how loosely the topics should match. For example, a keyword phrase can be set to match a query exactly or can be set to match any similar variation. Controlling the match level allows advertisers to limit “bad matches” that aren’t likely to convert, or to open up the matching to cast a wider net if the initial stricter match type performs poorly.
The cost of keywords is based on competition–the more demand for a keyword the more expensive the bid. When advertising for a mainstream competitive product, the keywords that most closely align with searchers’ and consumers’ intent can be costly. In addition to popularity (mainstream product) and competition (profitable products), keyword cost is driven by quality score (lower the score, the higher the bid required), the placement of the bid (consider a different network), search volume, and sometimes, seasonality (watersports products in July).
Cost Lowering Factors
As a result, many advertisers look for strategies that allow relevant keywords that can convert. Some find that aiming for the top search return to be inefficient, and instead bid for the 3rd position or “above organic” to receive clicks. Advertisers can also improve components of the quality score to make the bid more competitive. While reviews are mixed on Long Tail Keywords (longer specific phrases with lower bids), they are less expensive, rank highly, are contextual, and mirror the way in which consumers speak of an offering. If keyword phrases are getting poor matches, add negative keywords to change the ratio of good/bad matches. Keyword research tools can find high volume keywords that are underutilized, generating returns without bidding for the most valuable keyword.
Ad placement refers to the location of the ad, from the website to the page, to the specific location on a web page. Two main types of PPC ad placement are on Search Engine Results Pages (SERPs) and on topically-aligned websites or pages.
Specific placement on either page type depends on the ad auction and the complex set of variables used in calculating an ad rank. The ad rank determines if an ad is first or second, etc., on a SERP, or whether it gets a premium or secondary location on a topically aligned web page, or if it doesn’t place at al
In some ad platforms, advertisers can bid estimated amounts to appear in specific SERP locations: top of page, before organic, on the first page. In these cases, some advertisers choose to bid a lower amount and target “before organic” to save costs while still appearing in a highly visible position. In other platforms, advertisers can bid for specific locations, as in Amazon PPC in which advertisers can compete for Sponsored Products (usually appearing at top of search results and on the “Add to Cart” page), or Sponsored Brands (which appear as a group of products in a banner at top of page). Generally, the most prominent placements (sites with high traffic volume, or distinct page placements) require higher bids.
Note: the targeting options selected for an ad or campaign can widen or limit placement opportunities. For example, selecting specific websites may limit ad appearances, and opening up targeting to a platform’s extended partner networks expands placement opportunities.
Ad Formats and Types
Ads come in a wide variety of basic formats (image, text, video, animation), as well as more unique ad types that vary across ad platforms and placement websites. As each platform has slightly different purposes, the way in which formats are combined to create specific types is platform-specific.
Search ads are usually text ads displayed among the results. Google search ads are often expanded with “extensions” to include additional links within the landing page website, brief descriptive phrases, pricing, etc. Bing and Google both provide product ads in which text, product images, and pricing are displayed at the top or side of SERPs.
Social Media Ads
Social media ads use predominantly image and video ads with descriptive text. Facebook offers a collection of images or videos (Carousel), and an immersive full-screen collection of images, videos, and links (Instant Experience).
Automated Ad Creation
Additionally, most platforms offer automated ad creation in which the platform uses a business’s keywords, product, and web pages to generate ads based on machine learning and historical data.
The Landing Page (LP) is the targeted page a visitor sees when clicking through the ad. The LP is the target content the brand is promoting and is specifically what a PPC advertiser is paying for–the ad click that leads to targeted content.
Landing Page Content
The LP can be a product information page, purchase page, or an opportunity to download additional information or sign up for a newsletter. Most importantly, the landing page is the locus of key interaction with the brand: potentially the first impression of the brand, what users click, where users navigate from the LP, how much time is spent where.
Landing Page Quality
The quality of an advertised business’s landing page is critical on any ad platform, as the landing page experience is a significant component for evaluating an auction bid. In fact, part of the quality score is derived from the landing page experience (nearly 40% according to analysis of Google’s API in 2016). However, a key metric in the quality of an LP is the alignment between it, the keywords, and the ad that led visitors there. As the keywords should represent the way in which target users think about the offering or the unmet need it resolves, the LP should reflect the same.
The keyword reflects the target audience’s thinking about the offering, the ad also reflects this thinking and includes additional valued information including an effective call to action (CTA), and the LP should provide offering details the visitor needs.
A landing page can be measured by the visitor’s time on page, session duration, bounce rate, and, of course, the conversion rate.
PPC ad platforms gain much of their impact by the degree of targeting specificity possible. An advertiser can show an ad (on weekends only) for car parts, and only to men 35-55, making $80-100k, living in San Antonio, and driving older Fords. The amount of targeting control PPC ads provide increases advertisers’ ability to spend funds efficiently and time presenting ads and content to target markets without wasted effort displaying ads to audiences far less likely to convert.
Targeting narrows the advertising to a business’s target audiences and can do so in a wide variety of dimensions. However, all targeting falls into two main categories: 1) ads are targeted by audience or audience characteristics, and 2) placement or placement characteristics, including when, where, and how ads are presented. Ads can target by using actual target audiences (e.g., remarketing) or characteristics of an audience (affinity or interests), or limit when and where ad placement occurs to coincide with target audience browsing behaviors. The ad must still compete in a competitive ad auction and rank high enough to place, regardless of targeting choices. Depending on the platform, targeting data and tools may be built-in or augmented by combining 3rd party data with platform data.
Demographics and Interests
When targeting audience characteristics, ads can focus on specific demographics (marital status, income), or on audience affinity or interest (entertainment choices, hobbies, etc.). Each platform has widely varying demographic options available, with Google Ads offering the widest range; however, even Google limits these options depending on the history of the advertiser.
One of Facebook’s most popular targeting features is Lookalike Audiences. After an audience has built up over time, reflects the business target market, and is reasonably successful, advertisers may choose to mirror the audience to use in other campaigns.
Topic and Specific Placement Targeting
In placement targeting, advertisers use contextual data to determine which websites and pages are requested for ad placement, or they select actual ad networks, specific sites, or even pages for desired placement based on their perceived value in reaching target audiences. For contextual placement targeting, an advertiser can choose which topics should be targeted, and platforms will offer sites that match.
Remarketing allows advertisers to target high-value prospects: consumers who have had some prior connection to the brand. For example, a remarketing campaign might advertise to previous visitors to the business site, those who purchased in the past, or even consumers who started a transaction but abandoned the cart.
Ad platforms such as Google Ads and Microsoft Ads offer an audience type called In-Market. Using recent web browsing behavior as a data source, the ad platform algorithm calculates which users are actively seeking a product or service and can be considered “in-market” for an offering. Advertisers can select this audience to target consumers who are already well into the customer journey and can drive conversions.
While keywords are an essential component of auction-based PPC advertising, especially search advertising, keywords are also used for additional targeting in some platforms or networks, and can be applied to the target audience or to the target topic content. A keyword such as “motorcycle dirt racing” could be applied to an audience, or to websites. In the first instance, the ad would target anyone who is likely an enthusiast of motorcycle dirt racing, and the second would target webpages that cover motorcycle dirt racing and related topics.
In contextual website placement, often keywords or lists of keywords form the core of matching an ad to placement opportunities. A series of keywords can be used to automatically place an ad by the theme represented by the collection of keywords.
When advertisers need to limit the geographical location reached by ads, they use geolocation targets. Ads can be limited to specific cities or even mobile users within walking distance of a business. Advertisers may use this targeting to target only cities with physical stores, or regions where a product is more in demand (e.g., ski equipment and clothing in regions with significant skiing opportunities).
After a sufficient period of online advertising, businesses accumulate data revealing when conversions are highest and lowest. As a result, they may choose to limit advertising to the most effective days and times. Some products and services advertising may realize an activity peak between 5pm to 10pm on weekdays, but few conversions on Sundays between 1am and 6am. Scheduling ads to pause during a low conversion period may reduce costs by limiting non-converting clicks.
With mobile devices now accounting for half of all online searches, advertisers may find that conversion rates for some offerings are significantly higher for mobile device users, or at a minimum in specific situations. As a result, advertisers target devices to maximize returns. Whether advertisers choose to target one device only, or to increase bids for the most profitable device, prioritizing devices effectively limits costs and increases CTR and conversions.
Bringing it Together
Many targeting approaches can be combined, further narrowing to audiences more likely to be interested in a business’s offering, while reducing spends on clicks unlikely to convert. For example, an advertiser could select an affinity audience whose lifestyle includes activities related to the offering, use a set of keywords that narrows further, limits advertising to mobile devices, and to the time of day that conversions historically increase.
While layering can be effective, the more targeting options are combined, the smaller the prospective customer pool becomes. Often advertisers using a complex targeting combination will monitor closely over a short duration; then, based on results, the targeting can be adjusted to balance targeting accuracy and over-reduction of eligible users.
Purpose: to get an effective placement that will drive the advertising goal.
In its most popular form, PPC advertising is auction-based, allowing advertisers to compete for placement based on their monetary bid value and a set of quality factors that vary among platforms.
Put keyword bidding here, if not somewhere else.
Placement bidding on Topics, slots
Like the Google search network, Google display uses a real-time auction to determine ad placements. The same factors generally determine bid winner–Ad Rank, Quality Score, etc.
However, instead of bidding on a keyword alone, an advertiser is effectively bidding on an entire ad context. The bid is to have the ad show up, or to place, or to get clicked, or to get converted. All the other parameters–the placement location, keywords, demographic parameters are the prerequisites set for the ad.
For this ad, with these keyword themes, aimed at sites with these topics, and audiences with these interests, the advertiser bids $x. All other competing ads for the specific placement enter the auction and are judged on the totality of their selected attributes, bid, and quality.
One way of thinking about auctions that are not keyword-driven, is that the ad network doesn’t care so much about the keyword, but in the totality of the ad, the quality score, past and expected performance–the entire package that best matches the context of the placement location.
Many features of an ad or campaign can be used to adjust bids. For example, an ad can use scheduling to adjust bids at specific times (e.g., increase bids by 50% each day from 11am to 1pm after seeing significant lunchtime activity for ads). Similarly, an advertiser may choose to increase bids for specific locations, decrease for tablet devices, etc. Not all targeting characteristics can drive bid adjustments, and options vary by platform
Calculation of final cost
While each platform has some variation for calculating the final bid CPC, all fall within the Max CPC set by the advertiser–if a cap is set. For example, Google Ads calculates final CPC price using the advertiser’s quality score, the ad rank of the advertiser below it, and adds $.01 for search placements.
Second Price Auctions
However, for non-search placements such as in Google Display, the winning advertiser does not pay the full amount for all clicks for that placement. Instead, advertisers pay the amount required to beat the next ranking ad for the “incremental clicks” Google estimates are received from the higher ranking. The remaining clicks received are charged at the lower ranking. Basing the cost for the auction winner on the bid of the runner up is often termed “Second Price Auctions,” and is used on several platforms. Amazon Ads works similarly.
Smart, Dynamic, and Automated Bidding
In addition to bidding a maximum cost per click (CPC), other bidding strategies are available across platforms that automate some part of the bid and placement processes. In some cases, a bid may still be entered manually, but the platform uses machine learning (ML), historical data, and myriad relevant signals to calculate the best possible placements to reach a particular goal identified by the advertiser.
In other cases, the advertiser does not place a bid for Max CPC. Instead, he or she may choose a strategy not aligned with the CPC, focusing instead, for example, on the cost per acquisition or action (CPA). However, even though the advertiser does not enter a monetary value for the bid, the auction occurs and a bid is entered for the ad based on the parameters the advertiser has set. If the ad is set for a Target CPA of $100, the system will automatically enter bids that will achieve the goal based on the evaluation of thousands of signals.
Ad platforms describe these bid strategies as either dynamic, automated, smart bidding, etc.
Smart bidding strategies allow the machine learning (ML) algorithms to bid for the advertiser while maintaining the goals of the campaign–getting the most clicks, the most conversions per budget, or the most conversions at an agreed cost.
Types of Automated Bidding
Describing automated bid types across platforms can quickly become confusing, as some platforms use proprietary terminology to describe available bid strategies instead of “automated” and “manual,” for example, to help advertisers think about bidding a certain way. Similarly, while many PPC platforms offer similar bidding strategies, they may look and function slightly differently.
For example, while Microsoft Advertising, Google Ads, and Facebook all support setting a target for cost per action (CPA), Facebook calls it Cost-Cap Bidding. Amazon has “Dynamic Bidding” which is allowing the platform to raise and lower your bid, or just lower the bid when set up. However, most allow choosing maximum conversion value for a budget, maximum clicks, or targeting a specific cost of action/acquisition limit.
Not all bidding strategies work with all ad types. Each platform determines the combinations supported.
In many platforms, bid simulators can estimate what specific bidding strategies and values can achieve. For example, a simulator can estimate additional clicks the ad will receive if the bid is increased to the first position on the SERP or if the weekly budget is increased by 50%. Simulator tools have advanced significantly over recent years, from individual keyword simulators to specific campaign type simulators (shopping campaigns, video campaigns) and even smart bidding simulators.
Ad Auction Functions
Ad auctions occur each time an ad opportunity is triggered:
- a query is submitted relevant to a bid, or
- a user arrives at a participating website whose context is relevant to a bid.
Advertisers bid in advance to win the placement of their ad on the targeted location (on the SERP, on a targeted website, etc.), and for traditional PPC, they pay only for the instances a user clicks on the ad.
What Does an Ad Auction Determine?
Ad auctions determine several things:
- Whether an ad will get shown
- If more than one place (ad unit) is available for the bid, which page position an ad is placed (ad rank)
- What the final cost-per-click will be for the winning ad(s)
What Does an Ad Auction Evaluate?
During the auction, a collection of parameters are evaluated for each ad:
- The bid monetary value
- The quality of the ad and landing page
- Expected performance/success rate
For most ads, placement or Ad Rank is based on the quality factors, monetary bid, as well as competition, ad formats, past performance. Both Google Ads and Microsoft Advertising rate the quality factors into a Quality Score.
Quality Score variables are controllable to a large degree and dependent on the design of the ad, the target landing page, and the alignment of all with the keyword(s).
- Ad relevance: describes how clearly the message in the ad matches the keyword triggered by the user’s query. If a user queries “british curry powder prices,” and the advertiser keyword is “british curry powder,” but the ad (and landing page) focuses on the history of British curry powder–the ad will have low ad relevance.
- Landing page experience: measures whether the page is lucid and useful, answers the query intent, and provides what the customer needs. A disconnect between the keyword/ad and the landing page results in a poor experience, reflected by searchers leaving quickly (i.e., a high bounce rate), and their return to the search engine.
- Expected performance: measures the likelihood the ad will receive clicks when displayed for the keyword currently used, and whether the click will lead to a conversion.
Both Microsoft Advertising and Google Ads calculates the expected click-through rate (eCTR) at the time of auction. The eCTR is calculated based on the triggering search term, historical performance of the advertiser’s keyword, and other auction factors. A low eCTR translates to an ad that does not compel the user.
Amazon Ads also uses a similar overall formula (ad relevance, quality, expected performance), but their specific data points mirror the purpose and needs of the Amazon platform. For example, instead of landing page experience, Amazon reviews the product listing page, seller and product review ratings, even shipping speed. Expected performance is grouped under “Amazon Profit Components,” and includes the history of all products sold by the advertiser.
After an advertising opportunity is triggered, the eligible ads compete for Ad Rank: the value that determines which position the ad places on the SERP or contextual webpage, or whether the ad is shown at all for this auction. Ad Rank is calculated from the bid amount (Max CPC), the ad Quality Score (ad relevance, expected performance, and landing/product page experience), the competition in the auction, and other variables. Both the Ad Rank and Quality Score are calculated each time an ad is eligible to appear so that the current context and competition are included.
Tracking and Analytics
Without tracking and measuring, the advertiser would be operating in a non-interactive pre-digital model. With today’s tracking abilities, the volume of meaningful data is immense but requires systems in place to use the data to evaluate current campaign/ad success, identify actionable insights, and adjust tactics to increase performance. Finally, it’s also an opportunity to learn more about the customer, along with all the variables at play in the digital ecosystem.
Contemporary PPC platforms usually include baseline tracking, but to track conversions on external landing pages usually requires the “installation” of a small code snippet on the page to facilitate the data getting back to the ad platform (the installation is minimal, and accomplished with a utility in moments).
If using an analytics platform, an additional code snippet is required; however, 3rd party or external analytics platforms provide powerful details that drive true actionable insights that can change not just the immediate tactics but elements of the business and marketing strategy. This granular tracking can help evaluate multiple goals, clarify the customer journey, and allow comparisons between channels, ads, campaigns, goals, relevant revenue, and start to build a customer understanding.
Built-in platform tracking metrics are focused on specific data points for campaign components, ad groups, ads, keywords, and usually describe elements tied to a specific platform. While these may be local and seemingly isolated data elements, pulled together into different comparisons yields significant insights. Advertisers can review all keywords by clicks, cost, conversions; view all search terms which triggered their ads, and which ads converted. Less tangible but striking are insights for share of voice: how much of the volume for a keyword is the brand getting? Is it quality score or budget that is stopping share and conversion growth?
Measurability and insights: not just measuring CTR for different ads and KWs, but data that informs changes in strategy (ex here like what channel responds best to which ad components or ad construction), informing continuous optimizing of advertising from the keyword to multi-campaign for more efficient ROI; historical data as well as built-in data from bid simulators, KW volume, and cost estimates, etc.
Learn more about how quantitative marketing assessment (QMA) can help a business understand its market positioning and operate more successfully.
Why use PPC Today?
Pay-per-click advertising has evolved into a robust set of platforms and practices, providing mechanisms for reaching nearly infinite discrete targets, for a wide range of situational goals. As interactive data-driven advertising overtakes one-way advertising media, streaming services cut into commercial television advertising, and AI- and ML-driven digital advertising extends to both essential and complex tasks, the PPC platforms (and digital advertising overall) continue to adapt and change.
As digital ad platform revenue exceeds $100B each year, platforms will strive to make enabling technology more effective so that more ad dollars are spent. Maintaining current knowledge and skills in the field may require frequent application, as the strategy-enabling tactics used last year will have changed the next time a practitioner designs a campaign.
|Pay-per-click (PPC)||The online advertising model in which advertisers pay for each time their ad is clicked|
|Cost-per-click (CPC)||Metric measuring ad cost|
|Cost-per-mille (CPM)||Metric measuring ad cost per thousand impressions|
|Click-through rate (CTR)||The percentage of ads that receive a click, taking visitors to an advertiser’s target content (landing page, newsletter, app, etc.)|
|Cost-per-acquisition or -action (CPA)||Metric measuring advertising cost for each action or acquisition. Can be used as a bidding strategy.|
|Ad Rank/Ad Position||Ad value calculated during ad auction that determines whether and where the ad is placed. While a similar value is used by most PPC platforms, Ad Rank is a term used specifically by Google Ad, and Ad Position is used by Microsoft|
|Quality Score||Ad quality value calculated during the auction and determined by ad relevance, expected CTR, and landing page experience. Variations used by most PPC platforms originated with Google AdWords in the early 2000s|
|Relevance Score||Facebook ad value estimating how well the target audience is responding to advertisers ads|