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What Does AI Tell Us About AI Marketing Trends? An Interview by a Human.

AI Marketing Trends Header Maze of Data

By: David Pierpont
2/21/23

Background

An-individual analyzing the latest marketing trends.

Figure 1 – DALL-E 2 interpretation of the prompt “woman executive reviewing marketing data.”
Author’s note: Often found images with text or people were crude representations. It seems Midjourney’s AI image tool was a better alternative for the way I do prompts.

ChatGPT, the AI-powered next generation prototype chatbot from OpenAI, substantially funded by Microsoft and last week announced its integration with Bing search, is one example of the world buzzing with a mix of wonder and fear. The platform was hailed by the New York Times, “the best artificial intelligence chatbot ever released to the general public.” OpenAI also has DALL-E 2 for developing images and art. For marketers, we are very interested in how these tools will impact how we develop new strategies and ideas for campaigns, generate creative assets and content options for advertising, manage the buying process across channels and beyond current machine learning used in programmatic buys within specific platforms.

But any good marketer dives into these opportunities with a healthy mix of “what’s possible” and skepticism in what can it really do that is game changing for clients. Like any new technology there are important bugs that need to be addressed. Yet, Artificial Intelligence puts us in new territory and valid debates on the implications of these tools on the economy, knowledge workers, biases of its programming, education, more problems with disinformation and society itself.

One thing that is clear, these tools are still just tools and require supervision and expertise from humans. Subject Matter Experts (SMEs) that work in their fields and have a huge repository of real-world experiences to add context, filter-out the noise and apply the outputs from these new tools into something strategic and actionable is very much needed. As always, the shiny new object needs to be tempered with good ole hard work and experience. Yet, these new innovations will indeed add to our capabilities and improve productivity.

“For the vast majority of people, it’s just going to be another tool that they use and it’s going to make them more productive,” – Michael Wooldridge, computer science professor at the University of Oxford, CBC News 12/15/22

Approach

AI Marketing Trends Approach Human vs AI

Figure 2 – Photo Credit: Midjourney via Discord
Prompt: Human male in late 40s with glasses, bald head and beard interviewing a futuristic robot that runs on AI.

Every day there are numerous blog posts and YouTube videos of people posting their approaches to using AI within marketing. There are amazing techniques and combination of tools, some free and other paid, to develop content, images and videos that can be used for organic and paid marketing.

For this article I’ll be using ChatGPT and approaching the topic of “AI Marketing Trends for Artificial Intelligence” in an interview format. This is a great way for those new to using long-form question-answering AI tools like ChatGPT. By the way, GPT stands for, “generative pre-trained transformer” in sub-genre of artificial intelligence tools called Large Language Models (LLMs) and are “trained with massive amounts of data to accurately predict what word comes next in a sentence.” As amazing these tools are you will notice that the key to using them are the prompts to help navigate the conversation and lead to deeper engagements with more complex topics.

Now for the fun!

 

Top 10 AI-Informed Marketing Trends for Artificial Intelligence

Human Prompt: What are the marketing and advertising trends AI will impact in the next five years?

ChatGPT Response: Artificial intelligence is expected to have a significant impact on marketing and advertising in the next five years. Here are some of the key trends:

  1. Personalization: AI algorithms can analyze vast amounts of data to create highly personalized experiences for individual customers. This will lead to more targeted advertising and marketing campaigns, tailored to the specific interests and preferences of each customer.
  2. Predictive analytics: AI can be used to predict consumer behavior and purchasing patterns, allowing companies to create more effective marketing strategies.
  3. Chatbots and virtual assistants: AI-powered chatbots and virtual assistants will become increasingly sophisticated, allowing companies to engage with customers in real-time and provide them with immediate assistance.
  4. Influencer marketing: AI can be used to identify and analyze social media influencers, helping companies to choose the most effective influencer marketing campaigns.
  5. Programmatic advertising: AI algorithms will automate the process of buying and selling advertising space, making it possible to deliver highly targeted ads in real-time.
  6. Augmented reality and virtual reality: will play a significant role in the development of augmented and virtual reality technologies, which will be used to create immersive advertising experiences that can engage customers on a deeper level.
  7. Voice search optimization: As voice-powered virtual assistants become more popular, companies will need to optimize their marketing strategies for voice search, including developing content that is easily discoverable through voice searches.
  8. Customer experience management: AI can be used to monitor and analyze customer feedback in real-time, allowing companies to quickly respond to customer needs and improve the overall customer experience.
  9. Content creation: AI algorithms can be used to generate high-quality content, such as blog posts and articles, that can be used for marketing purposes. This will make it easier for companies to produce engaging and relevant content for their target audience.
  10. Fraud detection: AI algorithms can be used to detect and prevent fraudulent activity in the advertising industry, such as click fraud and ad fraud, ensuring that companies’ marketing budgets are being spent effectively.

Human: Using the previous answer. How can AI-informed personalization help lead to more targeted advertising and marketing campaigns as more privacy laws like General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) are enforced?

Customer Personalization

Figure 3 – Photo Credit: Midjourney
Prompt: Using a woman featured in the image develop a targeting persona to illustrate AI-informed personalization help led to more targeted advertising and marketing campaigns.

AI: AI-informed personalization can help companies to create more targeted advertising and marketing campaigns even as privacy laws like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) are enforced, by using alternative sources of data that are not subject to these regulations.

For example, AI can use data from public sources, such as social media profiles and online behavior, to infer information about customers’ interests and preferences. This information can then be used to create highly personalized experiences for each customer, without requiring access to their personal data.

Additionally, AI algorithms can analyze large amounts of data to identify patterns and relationships that would be difficult for a human to detect. This can be used to create predictive models that help companies to understand the likelihood of a customer taking a particular action, such as making a purchase.

By using AI to create more targeted advertising and marketing campaigns, companies can ensure that they are reaching their target audience with relevant and engaging content, even as privacy laws make it more difficult to access personal data.

It’s important to note, however, that companies must still comply with privacy laws and ensure that they are using data in a responsible and ethical manner. AI can help to make the process of targeting advertising and marketing campaigns more efficient, but it cannot be used to bypass privacy regulations.

Human: Expand on the following, AI can be used to predict consumer behavior and purchasing patterns, allowing companies to create more effective marketing strategies.

Predictive Modeling

Figure 4 – Photo Credit Midjourney
Prompt: A team of diverse individuals collaborating around a large reporting dashboard of marketing data.

AI: By using machine learning algorithms, AI can identify patterns and relationships in this data that would be difficult for a human to detect.

For example, AI can analyze a customer’s purchase history to determine the products or services they are most likely to purchase in the future. This information can then be used to create targeted marketing campaigns that offer personalized recommendations to each customer.

Similarly, AI can analyze a customer’s online behavior, such as the websites they visit and the searches they perform, to understand their interests and preferences. This information can be used to target advertising campaigns that are more likely to be of interest to each customer.

By using AI to predict consumer behavior and purchasing patterns, companies can create more effective marketing strategies that are better aligned with the needs and preferences of their target audience. This can lead to increased customer engagement and loyalty, as well as higher conversion rates and sales.

It’s important to note that while AI can provide valuable insights into consumer behavior, it should be used in conjunction with other data sources and human expertise. AI is a tool that can support decision-making, but it should not be relied upon exclusively. Companies must also consider factors such as cultural differences, customer preferences, and market trends when creating marketing strategies.

Human: What tools need to be used to allow AI to predict consumer behavior and purchasing patterns? How can these tools interface with a consumer’s online behavior such as visiting websites and searches?

AI: To allow AI to predict consumer behavior and purchasing patterns, a variety of tools can be used, including:

    1. Customer Relationship Management (CRM) systems: These systems can be used to store and manage customer data, including demographic information, purchasing history, and online behavior.
    2. Data warehousing and analytics tools: Data warehousing and analytics tools can be used to process and analyze large amounts of data from a variety of sources, including CRM systems, e-commerce platforms, and web analytics tools.
    3. Machine learning algorithms: Machine learning algorithms can be used to identify patterns and relationships in the data, and to make predictions about consumer behavior and purchasing patterns. Common algorithms used in this context include decision trees, random forests, and neural networks.
    4. Web analytics tools: Web analytics tools can be used to track a consumer’s online behavior, such as the websites they visit and the searches they perform. This data can be combined with other data sources to create a comprehensive view of each customer.
    5. Predictive modeling tools: Predictive modeling tools can be used to create predictive models based on the data analyzed by machine learning algorithms. These models can be used to make predictions about consumer behavior and purchasing patterns, and to create more effective marketing strategies.

To interface with a consumer’s online behavior, these tools can use technologies such as cookies, tracking pixels, and browser extensions to collect data about the websites the consumer visits and the searches they perform. This data can then be combined with other data sources, such as CRM systems and e-commerce platforms, to create a comprehensive view of each customer.

It’s important to note that companies must comply with privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), when collecting and using data to predict consumer behavior and purchasing patterns. Companies must obtain consent from customers for the collection and use of their data and must ensure that the data is stored and processed securely.

Human: What about Customer Data Platforms (CDPs) to understand current and perspective customers to personalize their consumer journey? Added this follow-up: Using the last explanation. In 150 words, how can Customer Data Platforms (CDPs) use AI to understand current and perspective customers to personalize their consumer journey? (Note: edited both responses to summarize)

AI: Customer Data Platforms (CDPs) is a centralized system that collects and integrates customer data from multiple sources, such as website interactions, purchasing history, and engagement with marketing campaigns. This data is then organized and segmented to create a single view of each customer.

For example, using AI, a CDPs can analyze large amounts of customer data, such as website interactions, purchasing history, and engagement with marketing campaigns, to identify patterns and relationships in the data that would be difficult for a human to detect. This information can be used to create predictive models that help companies to understand the likelihood of a customer taking a particular action, such as making a purchase.

CDP flowchart from TreasureData

Figure 5 – Photo Credit: Treasure Data (CDP platform)
Example of data collection to customer profile enrichment to campaign output.
Note: Treasure Data is a partner for Brain Trust + Partners, sister agency of RocketSauce Media Labs

Human: Are Customer Data Platforms (CDPs) a good option for automation to use AI to infuse first-party data into programmatic advertising planning and buying?

AI: Yes, Customer Data Platforms (CDPs) can be a good option for automation to use AI to infuse first-party data into programmatic advertising planning and buying.

The centralized data is then organized and segmented to create a single view of each customer, making it easier to use in programmatic advertising.

By integrating AI algorithms into the CDP, brands and marketing agencies can use the customer data stored in the CDP to inform their programmatic advertising strategies. AI algorithms can be used to analyze the data in real-time, and to make automated decisions about which advertising spaces to buy and sell, based on factors such as cost, target audience, and campaign goals and which digital channels that are most likely to reach that target audience.

Human: How can AI make chatbots and virtual assistants more useful compared to the current technologies?

Chatbots and virtual assistants

Figure 6 – Photo Credit MidJourney
Prompt: AI chatbot talking with an online customer about a new pair of shoes.

AI: Currently, chatbots and virtual assistants are often limited by the number of pre-written responses they are programmed with, which can make them less effective at handling complex or unexpected customer requests.

By incorporating AI algorithms, such as natural language processing (NLP) and machine learning, chatbots and virtual assistants can understand the intent behind customer requests and provide more relevant and accurate responses. For example, AI algorithms can be used to analyze customer requests in real-time, identify the most appropriate response, and generate a response on the fly.

Additionally, AI can be used to make chatbots and virtual assistants more proactive, by anticipating customer needs and making recommendations based on their individual preferences and behavior. For example, a chatbot powered by AI could suggest a product or service to a customer based on their past purchases or interests.

 

Human: Give an example of using AI for influencer marketing. What will the impacts be to companies that require a subscription to access curated lists of social media influencers?

Influencer Management

Figure 7 – Photo Credit Midjourney
Prompt: Curating the best group of online influencers.

AI: An example of using AI for influencer marketing is in the selection and management of influencer partnerships. AI algorithms can analyze large amounts of data, such as an influencer’s social media following, engagement rates, and audience demographics, to identify the most appropriate influencers for a particular brand or product. This information can then be used to create a shortlist of influencer candidates, reducing the time and effort required to manually review and evaluate potential influencers.

The impact of AI on companies that require a subscription will depend on how they adapt to the changing landscape. Companies that continue to rely solely on manual curation may find it increasingly difficult to compete with AI-powered solutions, which can process and analyze data at a much faster and more accurate rate.

However, companies that are able to incorporate AI into their offering and offer additional value-added services, such as campaign management and performance analysis, will be better positioned to succeed in the market.

Human: Give an example on how AI will play a role in the development of augmented and virtual reality technologies?

Virtual and Augmented Reality

Figure 8 – Photo Credit Dall-E
Prompt: An advanced AI-brain using customer data to build new landscapes in virtual reality game.

AI: Using AI algorithms, virtual environments can be made to respond to the actions of users in real-time, creating a more immersive experience. For example, AI algorithms can be used to analyze the movements of users and adjust the virtual environment accordingly, creating a more responsive and dynamic experience.

Another example is in the use of AI to create more lifelike virtual characters and objects. AI algorithms can be used to generate realistic animations and behaviors for virtual characters, making them more believable and engaging. Similarly, AI algorithms can be used to generate highly detailed and accurate virtual objects, such as furniture and landscapes, that can be used in virtual and augmented reality applications.

This has the potential to revolutionize a wide range of industries, from gaming and entertainment to education and training.

 

 

Human: How will AI support Voice search optimizations? Which voice search companies should marketers focus on in 2023?

Voice Search Google vs Amazon

Figure 9 – Photo Credits: Dall-e, David Pierpont
Prompt: Two advanced anime monster robots fighting in a ring.
Added in company logos and “VS” using Wikimedia commons.

AI: AI will support voice search optimization by helping companies to understand the language and intent behind voice search queries, and to create content that is easily discoverable through voice searches.

AI algorithms can be used to analyze large amounts of data, such as search queries and customer feedback, to identify the keywords and phrases that are most commonly used in voice searches. This information can then be used to optimize websites and content for voice search, making it easier for customers to find the information they need through voice-powered virtual assistants.

As for which voice search companies marketers should focus on in 2023, the two most prominent players are Amazon’s Alexa and Google’s Assistant. These virtual assistants are integrated into a wide range of devices, from smart speakers to smartphones, and have become increasingly popular in recent years.

Marketers who want to optimize for voice search should focus on creating content that is easily discoverable through these virtual assistants, by using keywords and phrases that are commonly used in voice searches and by providing clear and concise answers to common questions. Additionally, marketers should consider integrating voice search capabilities into their own websites and apps, making it easier for customers to find the information they need through voice search.

Human: What are the top 5 tools for customer experience management that incorporate AI?

AI:

    1. Salesforce Einstein: A platform that uses AI to help companies personalize and optimize their customer interactions. It includes features such as predictive lead scoring, sentiment analysis, and intelligent recommendations.
    2. Zendesk AI-powered chatbots: A chatbot platform that uses AI to help companies provide quick and accurate responses to customer inquiries. It includes features such as natural language processing (NLP), machine learning, and real-time analytics.
    3. KAI by Cognitivescale: An AI-powered customer engagement platform that helps companies to personalize their customer interactions and optimize their customer experience. It includes features such as NLP, machine learning, and predictive analytics.
    4. IBM Watson Customer Engagement: An AI-powered customer engagement platform that helps companies to understand and respond to customer needs in real-time. It includes features such as NLP, machine learning, and predictive analytics.
    5. Verint AI-powered customer service: An AI-powered customer service platform that helps companies to provide quick and accurate responses to customer inquiries. It includes features such as NLP, machine learning, and real-time analytics.

These tools use AI to help companies understand their customers and personalize their interactions, leading to improved customer experiences and increased customer satisfaction. By incorporating AI into their customer experience management strategies, companies can stay ahead of the competition and drive business growth.

Human: For advertisers what are some AI tools to help manage Fraud detection in paid search, programmatic display and social channels like Twitter, Meta, LinkedIn, Snapchat and TikTok?

AI: Some of the most popular AI tools for fraud detection include:

Checkout these companies:

These AI tools can help advertisers to detect and prevent fraud in paid search, programmatic display, and social channels, and to ensure that their ad budget is being spent effectively and efficiently. By using these tools, advertisers can increase the transparency and accountability of their ad spend and can take steps to protect their brand from the negative effects of fraud.

Human Note: It is important to note this is a perfect example of ChatGPT answers feeling comprehensive and confident but not fully accurate or complete in the answer. It did not answer the second part of the question on fraud detection on paid search and social channels. The five companies listed above are primarily used to manage fraud on programmatic display and video auctions across SSPs and DSPs. For social media channels like Meta, they use their own AI tools, which creates some concerns about having a third party verifying the process. Some 3rd party tools like ClickCease have processes for fraud detection on both Google & Meta ads.

Human: What are some resources for how to use ChatGPT for content creation?

AI: Here are some resources:

OpenAI API Documentation: OpenAI provides extensive documentation on how to use its API, including how to use ChatGPT for content creation. This resource is a great starting point for anyone looking to get started with using ChatGPT for content creation.

OpenAI Community: OpenAI has a vibrant community of developers and users who share their experiences and knowledge on how to use the API, including how to use ChatGPT for content creation. This resource is a great place to ask questions, share your own experiences, and learn from others.

OpenAI Blog: OpenAI regularly publishes articles and tutorials on its blog, covering a wide range of topics related to AI and machine learning, including how to use ChatGPT for content creation.

GitHub Repositories: There are many GitHub repositories that provide code examples and tutorials on how to use ChatGPT for content creation. These resources are a great way to see how others are using the API, and to learn from their experiences.

AI & NLP Conferences & Meetups: Attending AI and NLP conferences and meetups is a great way to learn about the latest developments in the field, including how to use ChatGPT for content creation. These events provide opportunities to network with other professionals, learn from experts, and see demos of the latest AI technologies.

Overall, there are many resources available for learning how to use ChatGPT and other AI tools for content creation.

End Note

We have definitely entered a new age of incredible opportunities with the latest developments in AI. With all the news and marketing organizations pummeling the industry with content, our organization included, it can be overwhelming. But fear not, everyone is trying to figure out how to use these tools and this adventure is just really starting to have direct impacts into the marketing and advertising industry.

What is critical and not going away are the needs for humans to have vision, strategize, provide context (organizational goals, history, data). Above all develop digital transformation-based cultures and structures that will allow for pivoting when adding in artificial intelligence capabilities as part of your organization’s efforts.

“AI won’t replace marketers, but marketers who use AI will replace marketers who don’t.” – Marketing Artificial Intelligence Institute

The tools will only get you so far, if you can’t address the business problems or goals, it’s just another tactic. As inspiration, highly recommend this Brené Brown’s Podcast, Dare to Lead episode with Dr. Linda Hill, researcher, professor of business administration, and chair of the Leadership Initiative at Harvard Business School.

The Plug

For advertising efforts to have effective ROI, the entire ecosystem of prospective and current customer data needs to be unified and managed properly. AI tools will be a key capability to improving operations from safeguarding privacy, mitigating fraud to knowing your most valuable customers and decreasing friction in their experiences with your brand. RocketSauce goes beyond just placing media but digging into your business and working as a partner to improve the entire marketing experience. We can leverage our key sister agencies to handle everything from data analytics, data-informed consumer journeys through CDPs and any development needs from your site to mobile app to cloud services to cyber security.