With the rapid rise of conversational AI platforms like chatbots and virtual assistants, such as Amazon Lex and Dialogflow, a new era of digital advertising is emerging. Conversational AI simulates human conversation through machine learning and NLP software, so the ads targeted against these chat queries are starting to make their way into the PPC ecosystem. However, while this brings possibilities for more relevant advertising, it may lead to questions about data privacy. Here, we’ll dive into how ads can target Conversational AI search queries and what this means for the current PPC landscape.
what is conversational Ad Targeting?
Conversational AI enables businesses to engage customers in human-like conversations through solutions like chatbots, voice bots, and voice assistants.
Google and MIcrosoft (Bing)
While its integration into Google Ads is still evolving, conversational AI can personalize interactions, improve ad targeting, and assist with bidding strategy. Conversational responses are incorporated into search engines like Microsoft Bing and Google, where ads appear as links in response to user queries. These links aren’t always flagged as ads to preserve user engagement and conversational flow. This contrasts with Google’s traditional search model, which relies heavily on clicks and user engagement to drive ad revenue. In Bing Chat, advertisers don’t bid for specific chat placements. Bing simply takes links from existing ad campaigns. In Google, chatbots are providing interactive ad experiences where users can ask questions and receive personalized recommendations within the ad.
Perplexity
Although founded in 2022, Perplexity has been dominating the Conversational AI space this year and is taking on Google by implementing brand-sponsored queries as responses to AI conversations. It now positions itself as an answer engine, combining Google with ChatGPT-esc conversational abilities. They recently announced that they will monetize this feature by allowing brands to sponsor specific suggested questions, influencing follow-up questions, and guiding users towards their products or services. Perplexity stands out for its ability to pull from live internet sources and provide links for them; however, with sponsored search integration, users have been advised to be cautious when trusting response information.
Issues with Conversational AI Ad Targeting
While this new targeting sounds exciting, it comes with issues.
- Impressions on traditional search ads could decline as users get used to the AI-generated responses. Consider AI a complete disruption to PPC advertising as we know it, as it reduces the need to visit external websites, impacting traffic and ad-generated revenue.
- There needs to be more explicit control and reporting on ad placements within chat responses for those advertising on Bing.
- Concerns around data privacy are valid, as chat queries can reveal more specific information about users than traditional keyword searches. There is also concern surrounding how these interactions will be stored and used and who will have access to their information for ad targeting. This could lead to a need for more transparency and trust for users, who may avoid using conversational AI.
- Managing ad relevance is much more challenging in chat than in traditional search, as questions can be nuanced or open-ended. Ads need to maintain conversational flow without feeling forced or irrelevant.
- Ad fatigue could be a problem if users begin to see ads in every interaction.
- Nuanced questions or complex queries can easily be misunderstood by Conversational AI, leading to irrelevant responses and user frustration.
benefits of Ad Targeting in Conversational AI
Ad targeting in conversational AI allows advertisers to reach users in more personalized and contextually appropriate ways without relying on keywords, search history, and user behavior. Advertisers can target based on user questions or intents expressed within chats. These ads can be more accurately matched to user intent, allowing for hyper-relevant content, aligning with what users are actively searching for, and potentially increasing click-through rates (CTR) and conversions. Conversational AI also allows for real-time responses, creating an opportunity for immediate ad engagement and extending the PPC model beyond traditional search engines.
Shifts in the PPC Landscape
Conversational ad targeting represents a significant shift in the PPC landscape, where keywords and search engine algorithms have traditionally been the primary tools. Instead of just bidding on keywords, advertisers can now consider chat phrases or user intents. This change could diversify the PPC market, providing a fresh wave of competition and new pricing structures as advertisers navigate the balance between keyword-based PPC and query-based ad targeting within chat systems.
Entering the conversational AI space requires new strategies and approaches. Marketers must develop a different approach to keyword research that considers natural language and intent. Understanding common user phrases or questions will be crucial for effective ad targeting in chat interfaces. Brands may need to invest in tools that enhance contextual understanding, such as machine learning, to determine the appropriate timing and type of ad based on user intent.
Final thoughts
Ad targeting against chat queries in conversational AI can revolutionize PPC advertising by making ads more personalized and contextually relevant than ever before. However, it also brings new responsibilities for advertisers to handle user data responsibly and to design advertisements that enhance rather than interrupt user experiences. With privacy concerns on the rise and user expectations evolving, success in this space will depend on transparency and a focus on user satisfaction.
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