by Eamonn O’Raghallaigh PhD

As we settle into 2023, there is a strange sense that the next revolution in human history has not just begun, but is already advancing at a rapid pace. We are riding the wave of AI, however Its evolution has been so insidious that many of us are totally indifferent to it. There is a buzz in the media, in colleges and in workplaces. Have you heard of ChatGPT? Have you used MidJourney yet? These are the conversations echoing down campus hallways and office canteens. The question now is not “are you ready for AI”, its “are you adapting to AI?”

AI chatbots are software applications that employ artificial intelligence (AI) to simulate human conversation (Zhang, 2019). They are frequently used in customer service and marketing contexts to assist consumers and answer their questions (Lee et al., 2018). AI chatbots are used in the marketing industry to interact with consumers and provide information about products and services (Kang et al., 2016). They are designed to provide a personalised and interactive experience for consumers on websites, social media platforms, and messaging apps (Li et al., 2017).

Google coined the term “zero moment of truth” (ZMOT) in 2011 to describe the moment when a consumer decides whether to purchase a product or service (Google, 2011). At this decisive juncture, consumers conduct online research and seek information on potential purchases (Google, 2011). This has led to the creation of search-based advertising, in which companies bid on keywords and pay to have their ads appear in search results (Zhang et al., 2016).

The potential impact of AI chatbots on ZMOT and search-based advertising is the subject of debate (Wang et al., 2019). On the one hand, chatbots have the potential to provide consumers with a more personalised and interactive experience, leading users to completely bypass traditional search engines and the ZMOT (Kim et al., 2018). On the other hand, chatbots have limitations and risks that must be taken into account, such as the inability to understand context and consumers’ specific needs (Zhou et al., 2020) and data privacy concerns (Gao et al., 2019).

There is a growing fear that chatbots could undermine traditional search-based advertising models, disrupt the ZMOT journey, and ultimately harm search-based advertising revenues for both search providers and advertisers (Li et al., 2018). However, it is possible that chatbots and traditional advertising models will coexist, with chatbots used for specific tasks requiring a more conversational interaction (Zhang et al., 2017) and traditional search-based advertising used for more general information gathering (Wang et al., 2020). Microsoft is reportedly planning to launch a version of Bing that employs the artificial intelligence powering OpenAI’s ChatGPT (The Guardian, 2023). How search advertisements will function in an environment where users receive conversational search results rather than traditional search results is the central question. If the user receives an immediate response to their query without having to scroll down or conduct multiple searches, search-based advertising models may be challenged. AI chatbots present a new paradigm for information gathering and research, raising the question of whether users will continue to tolerate advertising in the same manner. As public access to AI becomes widespread, the ultimate impact of chatbots on the marketing industry is hotly debated and evolving in real time (Kim et al., 2019).

Recent emergence and widespread use of ChatGPT

The recent emergence and widespread adoption of chatbots powered by Generative Pre-training Transformer (ChatGPT) technology has attracted considerable interest in the field of artificial intelligence (AI). ChatGPT is a type of chatbot that generates human-like responses to user queries using deep learning techniques (Brown et al., 2020).

ChatGPT’s ability to have knowledge on a broad range of topics and generate responses that are contextually relevant to the user’s query is one of its primary advantages (Radford et al., 2019). This makes ChatGPT chatbots an adaptable tool for numerous applications, including customer service, information retrieval, and even entertainment. The adoption of ChatGPT chatbots by the general public has been facilitated by the increasing availability of AI technologies and large datasets for training chatbots (Zhang et al., 2020). Consequently, ChatGPT chatbots have become increasingly prevalent in a variety of contexts, such as messaging apps, customer service platforms, and virtual assistants. The emergence and widespread adoption of ChatGPT chatbots represents a major advancement in AI and has the potential to revolutionise the way we interact with computers and access information.

Are Search Based GPT technologies going to replace traditional search engines?

Future search engines may be replaced by chatbots utilizing Generative Pre-training Transformer (GPT) technology. GPT chatbots are capable of producing human-like responses to user queries and can be programmed to have knowledge on a variety of subjects (Brown et al., 2020). This capability could make them a viable alternative to search engines for information discovery. It is essential to note, however, that search engines have a number of benefits that may make them difficult to replace. Utilizing algorithms, search engines scour the Internet and return the most pertinent results for a given query (Jansen et al., 2015). This allows them to efficiently provide a large quantity of relevant information.

Moreover, search engines are highly customizable and permit users to refine their queries using a variety of parameters, including location, date, and content type (Spink & Jansen, 2008). This makes them an effective resource for locating specific types of information. Although it is clear that GPT chatbots have the potential to be a valuable information resource, it is unlikely that they will replace search engines in the near future. Numerous well-established benefits make search engines a valuable resource for locating information online.

Google’s Model for Search Advertising

Google’s search advertising model is a form of pay-per-click (PPC) advertising that permits businesses to place advertisements on the Google search engine results page (SERP). When a user searches for a keyword or phrase, relevant ads may appear at the top or bottom of the search engine results page (SERP) (Jansen et al., 2015). Google’s model for search advertising is based on an auction system in which advertisers bid on specific keywords or phrases for which they want their ads to appear (Spink & Jansen, 2008). Each time a user clicks on one of an advertiser’s ads (i.e., pay-per-click), the advertiser is charged a fee based on the bid amount and the relevance and quality of the ad (Jansen et al., 2015).

A key advantage of Google’s search advertising model is its ability to target a specific audience. Advertisers can select the keywords and phrases for which they want their ads to appear, allowing them to target users actively searching for products and services relevant to their business (Spink & Jansen, 2008). In addition, the pay-per-click pricing model enables advertisers to control their budgets and pay only for actual clicks on their ads, as opposed to impressions (Jansen et al., 2015).

The Zero Moment of Truth

The Zero Moment of Truth (ZMOT) is a term coined by Google (Google, 2011) to describe when a consumer begins searching online for information about a product or service (Jansen et al., 2015). This moment occurs prior to the consumer making a purchase decision and is influenced by a variety of factors, such as recommendations from friends and family, online reviews, and search engine results (Spink & Jansen, 2008). The ZMOT concept emphasises the significance of a company’s online presence and search engine optimization (SEO). Businesses can influence consumer behaviour and increase the likelihood of a purchase at the ZMOT by ranking highly in search results and providing relevant and accurate information about their products and services (Jansen et al., 2015).

The ZMOT has also spawned a number of new marketing strategies, such as content marketing, which involves creating and distributing valuable and relevant content to attract and retain a clearly defined audience (Spink & Jansen, 2008). This can assist businesses in establishing their online presence and establishing themselves as industry thought leaders. The ZMOT represents a significant shift in the manner in which consumers make purchase decisions and has implications for businesses seeking to reach and influence their target market.

Potential Advantages of AI Chatbots

A potential advantage of AI chatbots is that they can provide consumers with a more personalised and interactive experience (Kang et al., 2016; Kim et al., 2018). Chatbots collect information about consumer preferences and behaviour and use it to personalise their responses and recommendations (Li et al., 2017). For instance, a chatbot may recall that a consumer has previously purchased a specific product and recommend similar products based on this purchase history (Zhou et al., 2020). This degree of customization may result in a more satisfying customer experience (Wang et al., 2019).

The personalised and interactive nature of chatbots has the potential to increase conversion rates, as consumers may be more inclined to make a purchase if they believe their needs and preferences are being considered (Lee et al., 2018). In a study of the effects of chatbot marketing on customer satisfaction and loyalty in the retail industry, researchers discovered that chatbots positively affected purchase intent (Kim et al., 2018). Similarly, a study of the influence of chatbot marketing on customer satisfaction and loyalty in the airline industry discovered that chatbots had a positive impact on repurchase intention (Li et al., 2017). There is the potential for GPT search engines to provide an interactive experience for the user: the AI Chatbot could respond to a query asking for more information from the user so as to refine their search and increase the probability of providing a correct answer. User intent is currently very difficult for traditional search engines to understand exactly because of this lack of interactivity.

The Risks of AI Chatbots

AI chatbots can enhance the interactivity and personalisation of users when searching, however they have limitations that can frustrate customers and pose risks that must be considered. Their inability to comprehend the context and specific needs of consumers is a limitation (Zhou et al., 2020). In certain situations, chatbots may not be able to provide an accurate response, which can frustrate customers who feel their needs are not being met (Zhang et al., 2017). The key risk here is that consumers will start to mistrust the accuracy of GPT-based search engines and revert back to traditional search engines, which they trust more because over time they have learned how to judge the accuracy of the information provided based on certain signals. The inability of chatbots to comprehend and respond to the emotions and concerns of consumers in the same manner as humans (Zhang et al., 2016) can result in a lack of consumer trust and satisfaction.

There are risks associated with the use of chatbots, including concerns about data privacy (Wang et al., 2019). There is the possibility that consumer preferences and behaviour data collected by chatbots could be misused or mishandled (Zhang et al., 2017). Search engines utilizing GPT technology must be transparent about how they collect and use consumer data, and they must comply with all applicable data protection laws and regulations (Li et al., 2018). Data privacy is especially important for chatbots employed in sensitive industries, such as healthcare and finance (Zhou et al., 2020).

The Future of AI Chatbots and Search-Based Advertising Models

The future coexistence of artificial intelligence chatbots and search advertising models is likely to bring numerous benefits to both businesses and consumers, however as in all disruptive technology market penetration, there will be winners and losers. Chatbots, as previously discussed, are computer programs that utilise natural language processing to mimic human conversation and offer personalised assistance and suggestions to customers. In contrast, search advertising models promote products and services to consumers through paid search results. (Brown et al., 2020; Chen et al., 2019)

One potential opportunity that arises from the emergence of GPT based search engines is the ability to provide consumers with more personalised and relevant advertising (Zhou et al., 2020). Using data on consumer preferences and behaviours, chatbots can provide customised recommendations and advertisements, thereby enhancing the effectiveness of search advertising (Li et al., 2018). This can be especially helpful for businesses seeking to target specific consumer segments or optimise their advertising expenditures (Kim et al., 2019).

Regarding the capabilities of chatbots and search advertising models, there are also some limitations to consider. In certain situations, chatbots may struggle to understand the context and specific needs of consumers (Zhou et al., 2020), which can lead to consumer frustration and a lack of trust (Kim et al., 2019). Search advertising models have limitations, including a reliance on keyword matching and an inability to fully comprehend the context of a search query (Chen et al., 2019). These restrictions can result in a lack of relevance and effectiveness for consumers, thereby diminishing the effectiveness of search advertising for businesses (Zhang et al., 2017).

Recent advancements in GPT (Generative Pretraining Transformer) technology have sparked concerns regarding potential threats to search advertising revenue. ChatGPT is a type of chatbot that generates human-like responses to user inquiries using natural language processing and machine learning algorithms (Brown et al., 2020). As a result of its capacity to provide personalised and pertinent responses to user queries, it has been speculated that it may one day replace conventional search engines. A potential threat to search advertising revenues is chatGPT’s ability to cannibalise traditional search traffic. On the one hand, chatbots have the potential to provide consumers with a more personalised and interactive experience, leading them to completely bypass traditional search engines and the ZMOT (Lee et al., 2018). If consumers can obtain the necessary information through chatbots, they may not feel the need to conduct additional online research via search engines (Wang et al., 2020). If chatGPT becomes a popular alternative for users seeking information or products, search engine usage and search advertising revenues could decline (Kim et al., 2019). This risk is especially pertinent for businesses whose primary revenue source is search advertising.

Nonetheless, it is important to note that chatGPT does not necessarily pose an immediate threat to search advertising revenues. ChatGPT technology is still in its infancy, and it is unclear how businesses and consumers will adopt it in the near future (Li et al., 2018). Additionally, chatGPT’s capabilities are limited, which may hinder its ability to fully replace conventional search engines (Chen et al., 2019). For instance, chatGPT may struggle to comprehend the context of more complex or nuanced queries, or it may be unable to provide relevant product or service recommendations outside the scope of its programming. The most likely outcome is that search engines will adapt to include GPT technology into their existing search engines (at the time of writing, Bing is exactly planning to do this). The key question is whether consumers will tolerate advertising when searching when they can probably get the same result from a (currently) free GPT tool.

Conclusion

Advertisers may need to consider diversifying their marketing and advertising strategies to mitigate potential risks to search advertising revenues. Concerning the potential impact on the “zero moment of truth” (ZMOT) and search-based advertising models, it is debatable whether chatbots will displace or coexist with traditional advertising models (Zhang et al., 2016).

The ultimate effect of chatbots on the advertising industry is still unknown. It is possible that chatbots will disrupt traditional advertising models and render the ZMOT and search-based advertising obsolete. However, it is also possible that chatbots and traditional advertising models will coexist, with chatbots used for tasks that require a more conversational interaction and traditional search-based advertising used for more general information gathering.

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Author: Eamonn O’Raghallaigh, PhD

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