Week 5: Digital Advertising as a System

This chapter covers digital advertising from the perspective of Rodgers and Thorson (2026): how digital advertising can be defined, how it developed from online advertising to omnichannel advertising, and why it is best understood as a system of mediated communication rather than a single message sent from advertiser to consumer. It describes the actors and technology in the digital advertising ecosystem (advertisers, agencies, publishers, platforms and ad tech such as ad servers, DSPs, SSPs, ad exchanges, DMPs and CDPs), the logic of programmatic buying and real-time bidding, the role of first-party and third-party data and the shift away from cookies, the main digital ad formats, and three lenses on digital advertising: algorithmic persuasion, networked communication and connected experience. It closes with the interactive advertising idea (consumer motives meet ad features), the role of the platform as mediator, and a mini case that ties the system together. The communication process, the customer journey and media planning basics are treated in earlier chapters and are only referred to here.

Defining digital advertising

Classic definitions of advertising (see Week 1, Belch and Belch) describe it as any paid form of nonpersonal communication about an organization, product, service or idea by an identified sponsor. Digital advertising keeps the core elements (paid, identified sponsor, persuasive intent) but changes three things: the message is delivered through digital media, it is often addressable (sent to a specific device, profile or audience segment rather than to a mass audience), and it is often interactive and measurable (the receiver can click, share, comment or buy, and every exposure and response leaves data behind).

Because digital channels are interactive, the boundary between advertising and other promotional mix elements (direct marketing, sales promotion, PR, interactive marketing) becomes blurred. A sponsored social post can be advertising, a promotion and a conversation at the same time. This is one reason why an integrated (IMC) perspective, discussed in Weeks 1 and 2, matters so much for digital advertising.

From online to omnichannel

The way firms use digital channels has developed in steps. The terms below are often used loosely in practice, but for the exam it is useful to distinguish them clearly.

• Online advertising: ads delivered over the internet, originally mainly banners on websites and later search ads. Online is treated as one channel next to traditional media.
• Multichannel: the firm is present in several channels (store, website, app, social media, TV), but each channel is managed more or less separately, often with its own team, budget and objectives.
• Cross-channel: channels are linked so that the customer can move from one to another (for example, an ad on social media leads to the web shop, an email reminds the customer of an abandoned cart). Data and messages are partly shared between channels.
• Omnichannel: the customer experiences one seamless brand, regardless of channel or device. Channels are planned from the customer's point of view and share data, messages and customer history in real time.

The digital advertising ecosystem

In traditional media buying, an advertiser (often through an agency) buys space or time directly from a medium, such as a TV channel or a magazine. In digital advertising, a large and partly automated chain of intermediaries sits between the advertiser and the consumer. This chain is called the digital advertising ecosystem.

The actors

• Advertisers: brands and organizations that pay to reach audiences (the demand side).
• Agencies: full-service, media and specialist digital agencies that plan, buy and optimize campaigns for advertisers. Many large agency groups operate their own trading desks for programmatic buying.
• Publishers: owners of websites, apps and streaming services that sell ad space (inventory) next to their content (the supply side).
• Platforms: large companies such as search engines and social media networks that are publisher, ad seller, data owner and measurement provider in one. They largely operate as closed environments, often called walled gardens, in which the advertiser buys through the platform's own tools and the platform keeps the user data.
• Ad tech providers: the companies whose software connects demand and supply (see below).
• Consumers: not passive receivers, but users who produce data, choose whether to pay attention, block ads, and pass messages on.

Ad tech: the machinery in the middle

Programmatic buying and real-time bidding

Real-time bidding (RTB) is the best-known form of programmatic buying. It works per impression and takes place in the fraction of a second in which a web page or app loads:

1. A user opens a page or app that contains an ad slot.
2. The publisher's SSP sends a bid request to one or more ad exchanges, with information about the slot, the context and (where available) the user or device.
3. DSPs evaluate the request against their advertisers' targeting rules and decide whether and how much to bid.
4. The exchange runs an auction and selects the winning bid.
5. The winning ad is delivered by the ad server and the impression is recorded for measurement and optimization.

Not all programmatic buying is an open auction. Advertisers can also buy through private marketplaces (invitation-only auctions with selected buyers) or programmatic guaranteed deals (a fixed price and fixed volume agreed in advance, but delivered automatically). The trade-off is typically between scale and price efficiency on the one hand and control over brand safety and context on the other.

Data: first-party, third-party and the cookieless shift

• First-party data: data a firm collects itself in its direct relationship with customers (purchases, loyalty programs, website and app behavior, email interactions). It is generally the most accurate and the most legitimate to use, because the customer has a relationship with the firm.
• Second-party data: another firm's first-party data, shared directly through a partnership.
• Third-party data: data collected by parties with no direct relationship with the consumer, often by tracking behavior across many websites, then aggregated and sold as audience segments.

A cookie is a small text file that a website stores in the user's browser. First-party cookies are set by the site the user visits (for example to keep items in a shopping cart). Third-party cookies are set by other domains embedded in that site, such as ad tech companies, and allow tracking of the same browser across many sites. Third-party cookies were long the backbone of behavioral targeting, retargeting and frequency capping.

Responses to the cookieless shift include: building first-party data through loyalty programs, logins and value exchanges; using CDPs; a renewed interest in contextual targeting (placing ads based on the content of the page rather than the user's history); data clean rooms in which firms can match data without exposing raw personal data; and more reliance on the walled gardens, which hold large amounts of logged-in user data. The last point shows a systemic effect: a privacy change can shift power within the ecosystem toward the actors that own first-party data at scale.

Digital ad formats

• Search advertising: paid text or shopping ads shown next to search results, usually bought by keyword in an auction and often paid per click. Because the user has expressed intent through the query, search ads work close to the purchase decision (pull rather than push).
• Display advertising: banners and rich media ads in standard positions on websites and apps, bought directly or programmatically, often used for awareness and retargeting. Display faces banner blindness and ad blocking.
• Native advertising: paid content that matches the form and function of the surrounding platform (sponsored articles, in-feed ads, promoted listings). It is less intrusive, but it raises a disclosure issue: consumers must still be able to recognize it as advertising.
• Video advertising: in-stream ads (pre-roll, mid-roll, post-roll) on video and streaming platforms, out-stream video in articles, and ads on connected TV. Skippable formats make the first seconds crucial.
• Social media advertising: paid posts, stories and short video ads within social platforms, targeted on platform data (demographics, interests, behavior, lookalike audiences) and open to likes, shares and comments.
• Mobile advertising: ads designed for smartphones, including location-based ads and mobile web formats; mobile is a device and context, not a single format.
• In-app advertising: ads inside apps and mobile games, such as interstitials, banners and rewarded video (the user watches an ad in exchange for an in-game reward).

Three lenses on digital advertising

The Week 3 reading frames digital advertising in three ways. Each lens highlights a different part of the system.

Digital advertising as algorithmic persuasion

In digital media, many decisions that used to be made by media planners are now made by algorithms: which user sees which ad, in which context, at what moment, at what price, and even which version of the creative. Platforms optimize delivery toward the objective the advertiser selects (for example clicks, video views or conversions) and learn from every response.

• Benefits: more relevant ads, less waste, dynamic creative optimization (automated testing and combination of headlines, images and offers), continuous learning.
• Concerns: limited transparency for both advertiser and consumer (why am I seeing this ad?), possible bias or discrimination in delivery, manipulation of vulnerable groups, filter bubbles, and loss of control by the advertiser over where ads appear.
• Consumer side: consumers increasingly recognize personalization; when targeting feels too precise or the data use is unclear, this can trigger a feeling of intrusiveness or privacy concern and reduce ad effectiveness (the so-called personalization paradox).

Persuasion theory still applies. In terms of the Elaboration Likelihood Model (Petty and Cacioppo), algorithms mostly influence who is exposed and when, which affects a person's motivation and ability to process the message, and thus whether the central or peripheral route is likely.

Digital advertising as networked communication

The traditional communication model (Week 3) shows a sender who encodes a message, a channel, a receiver who decodes it, and feedback. In digital media the receiver is also a sender: consumers like, share, comment, review, remix and create their own brand content (user-generated content). Influencers and online communities act as nodes that pass messages on to their own networks.

• Paid media (bought ads), owned media (the brand's own channels) and earned media (shares, reviews, press, word of mouth) interact: paid ads are often designed to generate earned reach.
• Meaning is co-created: a campaign can be reinterpreted, parodied or criticized, and the brand no longer has full control over the message.
• Electronic word of mouth (eWOM) and social proof (number of likes, reviews) become part of the persuasive effect.
• Network effects can make messages spread quickly (viral content), but negative responses can spread just as fast.

Digital advertising as connected experience

More and more devices are connected to the internet: smart speakers and voice assistants, connected TV, wearables, cars and household appliances (the Internet of Things, IoT). Advertising then becomes part of an experience that runs across connected devices and physical surroundings, rather than a message on a screen.

• Connected TV (CTV): television viewed through an internet-connected device or streaming app, which brings TV-like screens into programmatic and addressable buying.
• Smart speakers and voice: there is no visual ad space, so brands need voice strategies (for example being the answer the assistant gives, or offering branded voice applications).
• IoT and wearables: devices generate context data (location, activity, use) that can trigger timely, useful brand messages, but also raise strong privacy questions.

The connected experience lens links advertising to customer experience (CX) and user experience (UX), introduced in Week 3: the value of the ad lies increasingly in whether the interaction is useful, fitting and smooth within the customer's daily routine.

The interactive advertising model: motives meet ad features

An important idea in digital advertising research is that the effect of an online ad depends on both the user and the ad. The interactive advertising model (Rodgers and Thorson, 2000) distinguishes two sides:

• User-controlled aspects (functions): why the consumer is online (internet motives such as searching for information, communicating, shopping, entertainment or just surfing), the mode of use (serious and goal-directed versus playful), and the information processes (attention, memory, attitude formation).
• Advertiser-controlled aspects (structures): the ad type (for example product, service, corporate or issue ads), the format (banner, video, sponsored content and so on) and the ad features (objective features such as size, color, sound and animation, and subjective features such as perceived attractiveness).

The key insight is fit: an ad works better when its features match the user's motive and mode. A user who is searching goal-directedly for information responds to relevant, informative ads (such as search ads) and may ignore or resent distracting animated ads, while a user in a playful entertainment mode is more open to video or playful branded content. This gives a consumer-centered counterpart to the technology-driven view of the ecosystem: targeting decides whether the ad reaches the person, but motive and ad fit decide whether it is processed.

Digital advertising as a system of mediated communication

Combining the elements above gives the central Week 5 idea: digital advertising is a system. Advertisers, intermediaries, technology, data, formats and consumers are interdependent, and outcomes emerge from their interaction. It is also mediated: between the advertiser and the consumer stands a platform or chain of technology that shapes what is communicated.

Practical implications of mediation:

• Dependency: advertisers depend on platform rules, algorithm changes and policies that they cannot control.
• Measurement: platforms often measure their own performance, which raises questions of transparency and independent verification, and makes cross-platform comparison difficult.
• Brand safety and fraud: in automated buying, ads can appear next to unsuitable content or be shown to bots instead of humans, which requires verification tools and careful supply choices.
• Value distribution: each intermediary in the chain takes a share of the media budget, so not all of the advertiser's spend reaches the publisher.
• Responsibility: questions of privacy, manipulation and discrimination are shared across the system; ethics in digital systems returns in Week 10.

Thinking in systems helps managers ask better questions: not only "what message do we send?", but also "who decides where it appears, on what data, at what price, how will people pass it on, and how do we know it worked?"

Mini case: a sports apparel brand launches a running shoe

This is a constructed teaching example, not a real campaign. A mid-sized sports apparel brand launches a new running shoe in Greece and wants awareness among recreational runners and online sales.

1. Omnichannel set-up: the brand links its web shop, app, loyalty program and physical stores in a CDP, so a customer who tries the shoe in a store and later opens the app sees the same offer and is not retargeted for a product they already bought.
2. Ecosystem and programmatic: the media agency uses a DSP to buy video and display inventory on sports and lifestyle sites through private marketplaces (for brand safety), and uses search ads on running-related keywords to capture intent.
3. Data and cookieless shift: instead of third-party audience segments, the brand targets loyalty members (first-party data) and uses contextual targeting on running content.
4. Algorithmic persuasion: on social platforms the campaign is optimized for conversions; the platform's algorithm decides which users see which of six creative versions. The brand checks results by segment to detect unwanted skews.
5. Networked communication: running club members get early pairs and share reviews; a hashtag challenge invites runners to post their routes, generating earned media.
6. Connected experience: the shoe's companion app syncs with smartwatches, and a CTV spot with a QR code links the living room screen to the web shop.
7. Interactive advertising fit: informative ads for searchers comparing shoes, entertaining short videos for users browsing social feeds.

Analysis: the brand does not control a single message but configures a system. Its main risks are dependence on platform algorithms and platform-reported results; its main assets are first-party data and an engaged runner network. A good answer to a case like this names the actors, the data, the decision rules (who decides exposure), the role of consumers as senders, and how success will be measured independently.

Key points to remember

• The ecosystem connects advertisers and publishers through agencies, platforms and ad tech (ad server, DSP, SSP, ad exchange, DMP, CDP); programmatic buying and real-time bidding automate the trade per impression.
• The cookieless shift moves value toward first-party data and contextual targeting, and toward platforms that own logged-in data.
• Algorithmic persuasion, networked communication and connected experience are three lenses on the same system.
• Ad effects depend on the fit between user motives and ad features (interactive advertising model).
• The platform is a mediator, not a neutral channel. Add the four DASC dimensions from Rodgers and Thorson (2026) to complete this chapter.