In this technical blog, we examine the trajectory of how businesses leveraged social media for earnings. This essentially coincides with the development of online advertising since 1994. While the monetization of the internet still centers around online advertising, the ways businesses advertise online has undergone two major evolutions, and is now at the genesis of a third new phase. We begin this study with the first online advertisement in 1994, and proceed through online advertising strategies utilized in 2022.
These three phases fall under three categories: 1) brand-initiated advertising content, 2) user-influenced advertising content, and 3) influencer-marketing strategies. Our discussion of each of these phases reflects on the coinciding technological advances that enabled the processes by which users were served ad-based content online.
At its inception in the 1970s, the internet was a single, open, transparent network for academics and researchers to share ideas. The primary players on the internet were institutions like UCLA, the Massachusetts Institute of Technology, and Stanford University (Howe, 2022). As such, the early days of the internet were all funded by academic research grants. Because funding for the early internet was covered by external publicly funded entities, its early users grew to know the internet as a free service. Granted, all but the very early users paid for access to the internet via dial-up, but the internet was quickly established as a place where content was directly accessible without paywalls or pop-up advertisements.
When the internet inevitably expanded to the private sector in the mid-1990s, publicly-sponsored funding evaporated. However, the internet's growing user base was accustomed to free content. This established perception – that the internet was a free service where users could come and network or imbibe media without pay – would influence content-monetization strategies for the decade to come: social platforms and online journalists and publishers were reluctant to charge for the service and the content they provided. Nevertheless, they needed to generate revenue. Thus, despite the controversy and disdain from users, online business, platforms and media sites turned to advertising partnerships. Soon, businesses ranging from social media sites to online journalism began relying on advertisements as the primary way to generate revenue.
While the reliance on advertisements has continued to the present day, the ways businesses advertise online has advanced radically: it has witnessed two major evolutions, and is now at the genesis of a third new phase. Online advertising began with primitive, low resolution images with zero audience-targeting, and has now evolved to micro-targeted nano influencer marketing.
In this technical report, we chart the journey of how businesses have monetized the internet in order to build sustainable and profitable companies. We identify and discuss three “eras” around the internet’s monetization, and delve into how their emergence influenced internet commerce. We also discuss the technological advancements and developments that were created to enable each of these phases.
To conduct this analysis, we use social media intelligence from Infegy Atlas, tapping into its historical dataset (January 1, 2007 - present day). We supplement this social media intelligence with archival and academic sources.
We organize our examination and findings into three distinct phases:
The first phase of internet monetization involved non-targeted, brand-initiated advertisements. The internet was still relatively primitive in the mid-to-late 1990s, and ad-tracking infrastructure did not yet exist. Early online advertising viewed and treated webpages like they did print, and took a similar approach to placing ads as they would in print media. As a result, brands served up advertising (most commonly, in the form of banner ads) on third-party websites. Targeting was relatively passive, aimed at the persona that brands anticipated would be on a particular site. Users visiting those sites would see the advertisement amidst the content of the third-party sites and, hopefully, click on it, taking the user to the brand’s site.
While brands had little control over who saw their ad, banner-ads proved revolutionary as it provided the first instance of automated feedback for marketing. Online marketers could gauge the success of the banner ad based on user-engagement, i.e., how many people clicked on it.
AT&T purchased the first online advertisement for $30,000 in 1994. They placed a banner ad on www.hotwired.com, a future-focused technology site that has since rebranded as WIRED (Hesterberg, 2021). The ad was part of AT&T’s “You Will'' campaign, and projected the future of AT&T technology for functionalities (like video calls) that have indeed become standard to audiences today (Figure 1). Along with AT&T, other companies like Club Med, Volvo, and 1-800-Collect quickly bought subsequent ad space on the site.
Figure 1: AT&T's first ever banner advertisement from 1994.
AT&T’s advertisement was so novel and unexpected that it generated a click-through rate of 44% (Sloane, 2019). Novel techniques garnered a lot of attention, but would quickly fade away without further innovation.
Although antiquated today, AT&T’s banner ad revolutionized internet marketing in two significant ways.
For the first time ever, marketers knew how many people they engaged by the number of people who clicked on their advertisement. This collateral result of banner ads eventually led to one of the models used for determining the cost of online advertising – performance. Journalist Stuart Elliot, writing in a 1996 New York Times article, discussed the early iteration of this model. Pointing to Procter & Gamble as an example, he explained, “some advertisers, like the Procter & Gamble Company, are basing their payments for interactive ads only on click-through rates'' (Elliott, 1996).
Today, payment for performance has taken over as the prominent model for the ad-revenue compensation. According to a PricewaterhouseCoopers report, payment for performance has increased from 41% of online advertising revenue to 67% in 2020.
Before internet banner ads, marketers and brands had no easy way of knowing how well their advertisements performed. There was no reliable way to track how many drivers saw a billboard ad on the side of an interstate, or how many viewers paid attention to a SuperBowl television commercial.
Internet banner ads brought metric-based payments to the advertisement industry. It also enabled A/B feedback tests that facilitated how marketers and advertisers measured which ads performed best. In fact, for the marketing industry, feedback testing proved to be a gift that would keep on giving: it would eventually lead to the next chapter of internet-monetization strategies, user-influenced advertising. We discuss this further below.
While banner ads represented an advertising revolution, they interfered with user experience from their inception. Elliot wrote in 1996 that the ads were both boring and ineffective (Elliott, 1996). Furthermore, banner ads not only occupied precious screen-space, they also slowed down the data pipelines powering the primitive internet. Ryan Single notes this in a retrospective of Wired Magazine and its impact on online advertising, saying, “readers had to download the first banner ads over thin dial-up connections (Singel, 2010).
Banner ads rapidly spread across the internet after AT&T’s first take on them in 1994. However, banner ads had a fatal flaw: advertisers could not programmatically control what content their ad sat next to.This posed some real marketing, and brand-attachment issues. For example, a family-focused brand like Johnson & Johnson would not want an ad for their products in – and thereby associated with the content – a blog post discussing adult entertainment.
A software developer named Ethan Zuckerman was the one to solve this problem: he created the pop-up ad. Zuckerman was working for a software company called Tripod when a major car brand “freaked out” when one of their ads landed on a pornography site. Zuckerman set out to devise a solution that would allow ads to appear on third-party websites but not create any unintended association with the site. At the time, JavaScript was a brand new programming language that brought interactivity to traditionally static websites. Zuckerman developed code that would prompt a JavaScript based window to immediately appear when a user browsed to a page (Zuckerman, 2014).
The pop-up proved immediately significant for online advertisements, as it allowed websites to host interactive web ads (Figure 2). This not only “forced” user interaction (users had to click on the ad to make it disappear), but it also diffused the potential conflicts advertisers had between their ads and content. In a 2014 article for The Atlantic, Zuckerman says, “It was a way to associate an ad with a user’s page without putting it directly on the page, which advertisers worried would imply an association between their brand and the page’s content” (Zuckerman, 2014). The underlying technology of pop-ups also allowed advertisers to rapidly pull advertisements in light of a controversial event, or poor performance.
Figure 2: Early examples of pop-up advertisements on the internet.
This latter significance is taken for granted today but, at the moment of its emergence, the quick responsiveness and control Zuckerman’s pop-up technology gave brands propelled the adoption of online advertising exponentially. This new flexibility around advertising allowed ad agencies to rapidly change their advertising strategies based on ad performance. This took the A/B testing associated with banners ads to the next level. If an ad wasn’t performing, ad agencies could immediately replace it with ads that were.
This level of responsiveness and activity on behalf of brands made online agencies a vital and powerful new industry. Online ad agencies did the work required to engage online audiences and create visibility for products and services to millions of people.
With internet ad agencies on the rise, websites could begin funding their entire enterprise with online advertising. This meant they only had to touch one industry to stay afloat. Zuckerman explains in his Atlantic Monthly essay that Tripod.com “tried dozens of revenue models, printing out shiny new business plans to sell each one… At the end of the day, the business model that got us funded was advertising” (Zuckerman, 2014). Although Tripod.com was the first website to deploy pop-ups, the ad-supported model spread all across content-based websites. To this day, most content-based websites support themselves through advertising.
While websites and ad agencies loved this new arrangement, users were less than thrilled. Users have hated pop-ups since they first appeared on their screens over twenty years ago. Three years of social media data shows that 91% of the conversation about pop-up ads contain sentiment (users discuss pop-up ads with positivity/negativity), but only 34% of it is positive (Figure 3, Infegy Atlas - Sentiment Trend Graph around pop-up advertisements, 2022). Infegy Atlas associates topics like “spam,” “virus,” or “security risks” with popup advertisements (Figure 4, Infegy Atlas - Overall Word Cloud showing positive and negative keywords, 2022).
Figure 3: Sentiment around pop-up advertisements, Infegy Atlas data
Figure 4: Word cloud showing negative sentiment around pop-up advertisements, Infegy Atlas data.
Ultimately, the first phase of online marketing witnessed brands initiating contact with users through banner ads and pop-ups. Users had no options to influence the type of content they viewed. Thus, while digital and revenue-generating for the content-based sites that hosted them, early online ads were not that different from interstate billboards, with potential customers passively driving by them.
The second phase of internet advertising allowed users’ browsing behavior to dictate what types of advertisements websites showed them. For example, if users looked at websites related to puppy supplies, advertisers could dynamically show ads for big brands like Petco or Petsmart.
The very existence of this phase is a direct result of the creation of Google Search and, subsequently, Google Analytics. If a user used Google Search as a launchpad for their browsing activity, their online movements would be tracked, fed into Google Analytics, and the resultant data and profiles would be available for purchase by advertising companies. In 2017, Facebook (now Meta) created its own iteration, tracking user activity to build advertising profiles.
Google began as a personal project in the residential halls of Stanford University in 1997. Doctoral students Larry Page, Sergei Brin, and Scott Hassan conceived of the internet as a huge connected network. Each web page had links to other web pages. Google would “crawl” each of those pages to build a map of the internet. Page, Brin, and Hassan wrote a program called Back Rub that explored each of these links and allowed users to “search” for the specific content that they wanted.
After a few months, Google’s founders realized they could monetize this: companies could pay Google to put their website up at the top of the search results. For example, if a potential customer searched for “dog food,” a dog food brand would be at the top of the page. This internet real estate quickly became some of the most valuable on the internet, as consumers had real buyers' intent when they looked for terms like “best place to purchase a computer.”
Almost immediately after its conception, Google became the gateway to the internet, dominating search engines like Yahoo and Ask Jeeves (now called Ask.com). As Google Search rapidly expanded to consume the rest of the search market, the space at the top of the search results became very valuable for advertisers. Today, Google Search owns 83% of the global market share for search (StatCounter, 2022). Infegy Atlas data reflects this dominance, showing that Google Search accounted for 97% of search-related post volume (Figure 5, Infegy Atlas Post Volume For Google, Yahoo, and Bing, 2022).
Figure 5: Post volume graph showing Google's domination of the search market, Infegy Atlas data.
Google Search offered the first real solution to the biggest marketing problem associated with the first phase of online monetization: passively targeted ads. In the past, brands placed banner and pop-up ads and could only hope that would be seen by consumers with buyer intent. With Google Search ads, brands could attach their ad next to content and search results viewed by people looking to buy something. For example, an alcoholic beverage brand could pay for an advertisement next to content viewed by someone who had searched for “best craft beers.” Soon, brands began targeting search keywords like “looking to buy” or “product recommendations” that expressed buyer intent. This was revolutionary for ad placement and performance.
Targeted ads based on browsing behavior-generated analytics not only benefited brands; they benefited internet users at large. Targeted search engine advertisements were less disruptive and unwelcome than non-targeted pop-ups and banner ads. Based on a study conducted by the ad agency Adlucent, 71% of respondents “said they would prefer ads that are tailored to their personalized interests and shopping habits” (Pauzer, 2016). Adlucent’s study also revealed that user preference translated to a twice as high click-through-rate versus a more passive, non-tailored banner advertisement.
Google Search not only transformed the ad space, but also transformed the content that surrounded online advertisements. Google Search became the driving force behind online content marketing, a strategy that focuses on creating and distributing valuable, relevant, and consistent content to attract and retain a clearly defined audience. The end goal is to drive profitable customer action.
Additionally, in order to increase visibility, Search Engine Optimization (SEO) was born. SEO is the process of optimizing a website to improve its visibility on search engine results pages, thereby increasing the quality and quantity of free traffic to the site, also known as organic traffic. Content producers quickly realized that if they incorporated specific terms that users were searching for, they could push their content to the top of the search results and not have to simply pay for visibility.
In the early days of Google Search, Google’s algorithm was not very sophisticated. As a result, tricks like keyword stuffing (sticking thousands of keywords onto a page) worked well to push results to the top of search results. Today, Google and content producers still play a cat-and-mouse game of optimization but with increasingly sophisticated algorithms. Google will change their algorithm, and content producers will adapt to make sure their content stays towards the top of the relevant search results (Baker 2021).
Interest around search engine optimization remains very popular and relevant today. Infegy Atlas data shows a monthly mention rate of 4,761,079 posts per month across social media in January 2018 (Figure 6, Infegy Atlas Post Volume for Search Engine Optimization, 2022).
Figure 6: Post volume for search engine optimization over the last decade, Infegy Atlas data.
While Google wanted to stop some of the more flagrant abuses of search engine optimization, they also created a new service to enable content providers and advertisers to easily gain insights into the content they were producing – Google Analytics, which they released in 2005. Together, Google Search console and Google Analytics, have become the gatekeepers of search engine optimization. Google Search Console maintains statistics on how websites rank and for which keywords, and Google Analytics records traffic through site pages (among many other functions).
Infegy Atlas linguistics reveal the proximity of search engine optimization-related hashtags in conversations around the analytics platform (Figure 7, Infegy Atlas word cloud showing Google Analytics Hashtags, 2022).
Figure 7: Infegy Atlas word cloud showing positive sentiment around Google Analytics, Infegy Atlas data.
Google Analytics also allows marketers to analyze who is visiting their websites in order to optimize advertising campaigns. AdWords and AdSense, later known as Google Ads, were Google’s two central advertising products. Their development was led by Sheryl Sandberg who later joined Facebook. AdWords is a platform where brands looking to buy search ads could bid on relevant terms that they thought would aid product discovery. AdSense, on the other hand, is a platform where web sites could sell ad real estate to advertisers. A sentiment word cloud from Infegy Atlas shows how social media marketers have been thrilled with Google Analytics’s ease of use for over 15 years. (Figure 8, Infegy Atlas word cloud for Google Analytics, 2022).
Figure 8: Infegy Atlas word cloud showing positive and negative topics relating to Google Analytics, Infegy Atlas data.
Google Search became the dominant model for online advertising for the next thirteen years until Mark Zuckerberg and Sheryl Sandberg built an entirely new user-driven ad model from scratch with Facebook and Instagram.
Facebook was founded in 2003 as a directory of friends; Zuckerberg did not give much initial thought into how the platform would be monetized. Student reporter Adam Schneider writes in a 2004 article of The Harvard Crimson, that Zuckerberg planned to launch ads just to “offset the cost of the servers,” which at that point cost only $85 per month (Schneider, 2004). Zuckerberg realized after a few years that, in order to survive, Facebook would have to become profitable.
Zuckerberg brought Sheryl Sandberg on in 2008 to have her recreate her work at Google where she built both AdWords and AdSense (Chafkin, 2022). While Sandberg’s tactics at Google centered around users’ searches, the technique she and her team put into place at Facebook involved a much more intrusive tracking of user activity. Facebook placed tracking beacons involving Facebook Like buttons and login portals. These tracked how users who had Facebook accounts traversed the web. Facebook then aggregated, analyzed, and sold that information to advertisers. These dossiers became very valuable, as advertisers could put micro-targeted ads not only on users’ profiles, but also on other sites that they visited.
Facebook/Meta’s personalized advertising had two major consequences for the industry.
First, Facebook ads became extremely important for small businesses that could not afford the more expensive placements associated with Google Search. A 2009 New York Times article explained this niche with an example of a single proprietor photographer gaining almost $60,000 in new business after investing just $300 in Facebook advertisements (Pattison, 2009). The article further explains just how niche and narrow Facebook’s targeting could get, noting “a coffee shop in San Francisco can display advertisements only to local people whose profiles or group affiliations suggest they like coffee” (Pattison, 2009).
The second major significance of Facebook’s microtargeting involved nurturing prospective customers, specifically those who had displayed interest in a particular brand, but had not yet made a purchasing decision. “Interest” in this case was most commonly measured by cart abandonment: customers who fill up an online shopping cart but leave the site before buying anything. Cart-abandonment hovers at around 69.57% (Kristensen, 2022).
Through their granular tracking, Facebook/Meta enables marketers to reenage consumers who displayed buying intent, but hadn’t yet pulled the trigger on a purchase. Sandberg herself noted on a 2014 earnings call that Facebook’s ability to retarget an interested consumer was a powerful asset (Fitzgerald, 2014).
The second phase of monetization and advertising on the internet is still in full-swing. However, with content-marketing expanding and innovating at an alarming rate, it is no wonder that another phase of online marketing has emerged alongside phase two – influencer marketing.
During the time we’ve been referring to as “phase two,” Facebook and Google sold ads that were layered into organic, user-driven activity. For example, Facebook would show ads that appeared next to status updates and friends’ photos and Google placed relevant ads next to the organic search results for which users searched. Users benefited by receiving the social media or search provider’s services without any sort of subscription fee. Up until this point, companies had not been paying individuals on social media for their content.
This exchange of free online services for advertising space began to change in the 2000s as individuals began aggregating large, influential followings. Brands realized that the massive subscriber counts of content creators served as “captive audiences” and potential customers. The third phase of internet advertising allowed for brands to pay influential social media content creators, individuals who had access to audiences the brands needed to expand, for access to their audiences.
YouTube created the first iteration of influencer marketing with their 2007 Partnership Program. This program directly paid content creators a percentage of the advertising revenue they earned from the platform. In the next iteration, brands themselves, not just platforms, began paying and sponsoring content creators directly.
When YouTube was founded in 2005, its founders, much like those at Facebook and Google, did not prioritize how the site would make money. Users uploaded videos for free for anyone in the world to watch. That changed in 2007 when YouTube announced its Partner Program: it would pay its content creators 55% of the ad revenue that YouTube earned from advertising on their video channel (Sweatt, 2020). While paying social media users for the content they were producing seems commonplace now, at the time it was a novel idea.
The YouTube Partnership Program was met with near-universal acclaim by content creators. Historical data from Infegy Atlas consumer intelligence shows that social media users have discussed the program with 84% positivity over the last 15 years. This captures social conversations going all the way back to when the program launched. (Figure 9, Infegy Atlas sentiment analysis for YouTube Partner Program, 2022). Additionally, Infegy Atlas analyzed that a massive 54% of posts emoted Joy and Trust while discussing the program (Figure 10, Infegy Atlas Emotional analysis for YouTube Partner Program, 2022).
Figure 9: Sentiment trend graph for the YouTube Partnership Program from 2007 - present; Infegy Atlas data.
Figure 10: Infegy Atlas Emotional trend graph for YouTube Partner Program, Infegy Atlas data.
YouTube’s partnership program achieved two key breakthroughs.
First, on the individual user level, it made a creative, video-based career accessible for anyone with a video camera and an internet connection. Prior to YouTube, creative video producers and filmmakers had to go to film school, then get jobs at creative ad agencies or Hollywood studios. In short, there was no easy way for their work to be distributed without the aid of a gigantic creative studio. YouTube Partnerships made it possible to make a living as a video-based content creator.
YouTube did not stop innovating after their initial announcement. YouTube continues to introduce monetization features like enabling users to pay content creators directly for well publicized comments, monetizing YouTube Shorts, and introducing Channel Memberships which allow YouTube viewers access to exclusive creator content (Brownlee, 2022). Infegy Atlas data shows these innovations, like YouTube’s initial partnership program, have also been met with near-universal acclaim by YouTube’s user base (Figure 11, Infegy Atlas Emoji word cloud for YouTube Channel Memberships, 2022).
Figure 11: Linguistic analysis- emoji word cloud showing positive emojis in the conversation around YouTube Channel Memberships; Infegy Atlas data.
The second major breakthrough associated with YouTube’s partnership program was how quickly compensating content creators with an ad-revenue share spread to other platforms. Entire platforms like Twitch, Medium, and Substack, built their content-engines on supporting their creators with ad-revenue. This has also spread to advertising giants like Meta with Instagram’s Reels now matching YouTube’s 55% creator pay rate (Bary, 2022). This model has created a feedback loop, according to Marques Brownlee, a YouTuber with 16.4 Million subscribers. Creators make videos which perform well. Platforms like YouTube or Twitch sell advertisements to be viewed alongside those videos. Finally, platforms fund creators with a share of that ad revenue to convince them to create more videos (Brownlee, 2022).
While popular YouTubers and other content creators enjoyed their newfound share of revenue, influential creators began to realize that building a business solely dependent on advertising dollars was a risky proposition. Having ads as their only source of revenue meant that their income is entirely dependent on view counts.
Journalist Chris Stokel-Walker of Time Magazine notes, “almost two-thirds of YouTube channels now try to make money from selling their content elsewhere, by linking out to crowdfunding platforms, selling merchandise such as t-shirts, or directing audiences to their OnlyFans accounts” (Stokel-Walker, 2022). This need for diversification, brought about by YouTube’s finicky, yet powerful algorithm, opened up an opportunity for brands to supplement or supplant platform-sourced advertising dollars.
Brands began to recognize the power of the parasocial relationship that influencers had developed with their fans, and stepped in to help fill the advertising-dependent revenue gaps. In this phase, influencer marketing, brands cut out the platform middlemen (e.g. YouTube or Instagram), and paid influencers directly with sponsorships, products, or advertising slots directly in videos. This coincided with a dramatic surge in the popularity and social consciousness of the term “Influencer.”
Infegy Atlas noted a 650% increase in the post volume of the term in the last 10 years (Figure 12, Infegy Atlas Influencer Post Volume, 2022). Using Infegy Atlas’ built-in Entity-detection, we found that Instagram is the platform most associated with the term, followed by Twitter, Linkedin, and YouTube (Figure 13, Infegy Atlas Entities Most Associated with Influencers, 2022). TikTok had the lowest overall association by post volume (due to its relatively recent emergence in the social space), but had over 1000% growth over the last few years. This strongly suggests that influencer momentum is indeed moving from “traditional” social media networks to newer players in the space.
Figure 12: Post volume around the term "Influencer" over the last 10 years, Infegy Atlas data.
Figure 13: Entities most associated with the term "Influencer," Infegy Atlas data.
Paying influencers directly solved two key issues.
Firstly, it reduces the friction between advertising dollars and purchasing decisions. One of the traditional obstacles associated with marketing is building trust with your potential customers over the initial hurdle of sponsored content. By sponsoring influencers directly, marketers and brands were able to tap directly into the parasocial relationships developed over the years between a creator and his or her audience. This resulted in significantly less friction between advertisements and their efficacy, as customers were much more likely to make purchasing decisions based on people they trusted. Professor Fine F. Leung, Assistant Professor at Hong Kong Polytechnic University, notes this increased influencer-backed efficacy. Writing in The Journal of Marketing, she notes that each 1% in additional influencer marketing spend returned a .5% increase in engagement (Leung, 2022). Since engagement is used as a marker for greater spending and purchase intent, this ratio of spend to engagement indicated very successful marketing!
Second, influencer marketing enabled advertising investment that could scale with business sizes. This report previously discussed just how expensive Google Search ads would be to small businesses, and how Facebook advertisements opened up an entirely new, small-business focused advertising space. Influencer marketing works in the same way, where smaller businesses could target, sponsor, and grow as influencers’ audiences grow.
Paradoxically, research actually notes that smaller, less expensive influencer ad-buys are actually more successful than macro-influencers. New York Times journalist Sapna Maheshwari notes in a 2018 article that brands have now extended the practice of influencer marketing to “nano-influencers.” Nano-influencers are content creators with 1000 or fewer followers on social media (Maheshwari, 2018). This not only allows for cheaper marketing campaigns, but also injects brands into relationships where the influencer has fostered an even greater deal of trust because of the intimate size of their audience community.
Social activity has always been a magnet for marketing and commerce. With the internet becoming essentially a global, digital town-square, it is no wonder that brands have spent nearly thirty years and trillions of dollars devising ways to monetize online behavior and activity. However, every technology-driven monetization and marketing effort that has emerged since 1994, preserves a historic expectation: the internet and social networking platforms as a whole remain a free space.
With this expectation in place, brands capitalized on browsing and social networking behavior – for audiences, analytics, and even content channels. While brands have become increasingly creative at selling their products and services online, data and technology has been at the heart of how companies have generated content-based revenue.
References:
Bary, E. (2022, October 4). Get ready for more ads on Instagram. MarketWatch. https://www.marketwatch.com/story/get-ready-for-more-ads-on-instagram-11664893936#:~:text=A%20Meta%20spokesperson%20added%20that
Brownlee, M. (2022, November 9). Dear Twitter! Www.youtube.com; Marques Brownlee. https://www.youtube.com/watch?v=I1qsF0WQy8c
Cook, K. (2021, November 28). A Brief History of Online Advertising. Hubspot.com. https://blog.hubspot.com/marketing/history-of-online-advertising
Elliott, S. (1996, December 3). Banner Ads On Internet Attract Users. The New York Times. https://www.nytimes.com/1996/12/03/business/banner-ads-on-internet-attract-users.html
Fitzgerald, B. R. (2014, January 29). Recap: Facebook’s Earnings Conference Call. Wall Street Journal. https://www.wsj.com/articles/BL-DGB-32440
Howe, W. (2022, August 26). Walt’s Internet History | Walt’s World. Walthowe.com. https://walthowe.com/history/#:~:text=The%20Internet%2C%20then%20known%20as
Johnson, J. (2021). Search engine market share worldwide | Statista. Statista; Statista. https://www.statista.com/statistics/216573/worldwide-market-share-of-search-engines/
Kirschman, L. (2019, October 19). These factors have the biggest impact on influencer marketing effectiveness. UW News. https://www.washington.edu/news/2022/10/19/these-factors-have-the-biggest-impact-on-influencer-marketing-effectiveness/#:~:text=Researchers%20found%20that%20if%20firms
Kristensen, E. (2022, May 24). 15 Cart Abandonment Statistics You Must Know in 2022. Drip. https://www.drip.com/blog/cart-abandonment-statistics#:~:text=They%20calculated%20data%20from%2041
Loren Baker, & 65kreads. (2021, February 27). 20 Years of SEO: A Brief History of Search Engine Optimization. Search Engine Journal. https://www.searchenginejournal.com/seo-guide/seo-history/
Maheshwari, S. (2018, November 11). Are You Ready for the Nanoinfluencers? The New York Times. https://www.nytimes.com/2018/11/11/business/media/nanoinfluencers-instagram-influencers.html
Pattison, K. (2009, November 11). How to Market Your Business With Facebook. The New York Times. https://www.nytimes.com/2009/11/12/business/smallbusiness/12guide.html
Pauzer, H. (2016). 71% of Consumers Prefer Personalized Ads. Adlucent. https://www.adlucent.com/resources/blog/71-of-consumers-prefer-personalized-ads/
Schneider, A. (2004, March 1). Facebook Expands Beyond Harvard | News | The Harvard Crimson. The Harvard Crimson. https://www.thecrimson.com/article/2004/3/1/facebook-expands-beyond-harvard-harvard-students/?print=1#
Singel, R. (2010, October 27). Oct. 27, 1994: Web Gives Birth to Banner Ads. Wired. https://www.wired.com/2010/10/1027hotwired-banner-ads/
Sloane, G. (2019, October 27). Love It Or Hate It, The Banner Ad Turns 25. AdAge.com. https://adage.com/article/digital/love-it-or-hate-it-banner-ad-turns-25/2210521#:~:text=AT%26T’s%20banner%20was%20slightly%20more,through%20rate%20by%20today’s%20standards
Stokel-Walker, C. (2022, April 14). Why So Many YouTube and TikTok Stars Want to Sell You a Shirt (And Maybe a Burger). Time. https://time.com/6167196/youtube-tiktok-creators-new-income-streams/
Sweatt, L. (2020, November 30). YouTube Partner Program: How to Monetize Your Channel. VidIQ. https://vidiq.com/blog/post/youtube-partner-program-guide/
Zuckerman, E. (2014, August 14). The Internet’s Original Sin. The Atlantic. https://www.theatlantic.com/technology/archive/2014/08/advertising-is-the-internets-original-sin/376041/