The Pros and Cons of AI for Marketing: An In-Depth Guide

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Generative AI (artificial intelligence) has rapidly woven itself into the fabric of modern marketing, reshaping strategies and changing how businesses and affiliates engage with their audiences. We’re even using it regularly on the ClickBank marketing team now – I feel like we’d be getting behind if we didn’t!

According to Morgan Stanley, AI’s current impact stands at $2.1 trillion, affecting approximately 25% of the workforce. This figure is expected to surge to $4.1 trillion in the coming years, encompassing about 44% of the labor force.

Generative AI startups like OpenAI are attracting billions of dollars in funding from companies like Microsoft after Kevin Scott, Microsoft’s Chief Technology Officer, decided to bet on OpenAI rather than relying solely on in-house projects.

And Microsoft isn’t the only company pouring billions of dollars into generative AI! Amazon is investing $4 billion in AI startup Anthropic in a move seen as an effort to catch up with rivals like Microsoft in the AI arena and harness AI’s potential to enhance customer experiences.

So, given that AI is trending for marketers – and because ClickBank’s audience is primarily affiliate marketers and product creators/ecommerce brands – I thought it would be helpful to do a deep dive into how AI can impact marketing across the board. In this comprehensive guide, I delve into the pros and cons of AI for marketing, specifically affiliate marketing, and reveal several of AI’s real-world applications for affiliate marketers!

5 Pros of AI in Marketing

1) Enhanced Personalization

AI’s capacity to decipher intricate patterns in customer behavior is incredible. By analyzing historical data, AI algorithms can discern individual preferences and purchase histories and even predict future actions. This insight empowers marketers to craft hyper-personalized campaigns that resonate deeply with each customer individually.

According to McKinsey, companies that grow faster drive 40 percent more revenue from personalization than their slower-growing counterparts.

For example, Starbucks uses AI technology to deliver personalized customer experiences, showing how AI can enhance customer interactions and drive customer loyalty. By incorporating customer data into AI algorithms, Starbucks creates unique customer experiences that cater to individual preferences and needs.

2) Improved Customer Insights

AI-driven analytics can offer incredble depth in knowing your customers. AI not only identifies who your target audience is, but also why they make certain choices!

This knowledge helps businesses refine their products, services, and marketing messages, resulting in a more targeted approach. And just like brands and product owners will use this information, affiliates can also benefit from these insights and adjust their marketing messages to take advantage of what they learn.

In one case study, Deloitte helped a large pharmaceutical company analyze five years of data across 700,000 healthcare providers with the use of cognitive tools, increasing their customer reach. This resulted in a 50% reduction in email subscribers opting out of the email list, and that’s because the company really got to know the needs of their customers at a deeper level!

3) Increased Efficiency and Productivity

Automation lies at the heart of AI, and in marketing, it’s a game-changer.

An experiment conducted by the Boston Consulting Group (BCG) with the support of scholars from Harvard Business School, MIT Sloan School of Management, the Wharton School at the University of Pennsylvania, and the University of Warwick shows promising results.

With more than 750 BCG consultants worldwide participating, it was the first study to test the use of generative AI in a professional services setting. And the impact on productivity was remarkable!

BCG used OpenAI’s GPT-4 in the experiment for creative product innovation, a task involving ideation and content creation.

Around 90% of participants improved their performance. In addition, their level of performance was 40% higher than those working on the same task without GPT-4. 

Content creation is the backbone of many affiliate marketers’ marketing strategies. And if you can be 40% more productive than affiliates who don’t use AI tools like ChatGPT, this one move could help you become a successful affiliate marketer faster and more affordably than ever!

4) Predictive Analytics

Google defines predictive analytics as the process of using data to forecast future outcomes. It essentially attempts to answer the question, “What might happen next?”

Google explains the process as follows:

“The process uses data analysis, machine learning, artificial intelligence, and statistical models to find patterns that might predict future behavior. Organizations can use historic and current data to forecast trends and behaviors seconds, days, or years into the future with a great deal of precision.”

Based on research conducted by Forbes, many companies have seen great results using predictive analysis. Some examples include:

  • The global professional services organization EY saved 250,000 working hours of manual labor by implementing AI-enabled intelligent document automation.
  • PepsiCo used Azure Machine Learning and machine learning operations to greatly reduce the time required to model a production environment and to accelerate its ability to predict customer demand.
  • Progressive Insurance expanded digital brand trust and saw $10 million in annual savings using their AI chatbot built on Azure Cognitive Services.

You would not be wrong to think that predictive AI doesn’t directly fall into the realm of affiliate marketing.

However, although ChatGPT from OpenAI is a generative AI platform and not a predictive AI platform, it can analyze past data to generate content about future trends that digital marketers would want to know! If there’s any way to incorporate AI-based predictive analytics into your own marketing workflow, the results can be amazing.

5) Cost Reduction

While your initial investment in AI technology might seem substantial, the long-term cost savings are undeniable. The automation of tasks, elimination of guesswork, and increased ROI make AI a financially prudent choice for many businesses, both large and small.

Of course, with all the AI tools available on the market, it might not even be necessary to invest in AI technology. Chances are good that existing tools will meet your requirements.

From a marketing perspective:

  • AI helps reduce costs through its ability to analyze vast datasets for patterns and trends.
  • With AI-powered personalization tools, marketers can tailor their messages to specific audiences and improve targeting, minimizing wasted resources on irrelevant campaigns.
  • AI-powered marketing automation tools are adept at handling repetitive tasks such as email campaigns, social media scheduling, and content distribution. This not only saves time but also frees up valuable resources. As a result, marketing teams can achieve more with less, ultimately reducing marketing costs.

One of the best examples of how AI can reduce marketing costs is using AI-powered chatbots to handle customer inquiries and provide personalized product recommendations.

This not only reduces customer support costs but also increases conversion rates. And chatbots are typically able to handle high volumes of inquiries simultaneously, providing quick and accurate responses, which improves customer satisfaction.

At ClickBank, we’re already experimenting with an AI chatbot for our Spark education platform. This AI chatbot – which we’re calling “Ember” – can answer high-level questions related to our coursework, summarize points, and refer students to the lessons that will address their questions.

In doing so, we can provide a better product and more customer support to a wider group of people!

9 Cons of AI for Marketing

1) Data Privacy Concerns

As AI processes vast amounts of data, concerns about data privacy and security loom large. Ensuring compliance with regulations such as GDPR becomes more challenging as AI algorithms become more sophisticated. Mishandling customer data can lead to severe repercussions, including hefty fines and a tarnished reputation.

Several countries have already taken steps to safeguard consumers. For example, the European Union has made substantial progress in shaping AI regulations through the AI Act. Their goal is to balance technological advancement with individual rights and privacy.

Data privacy breaches have been rare, but remain a risk. For example, in March 2023, a bug in ChatGPT allowed some users to see data from other users. In July 2023, the Washington Post reported that the Federal Trade Commission (FTC) is investigating OpenAI over a data leak and ChatGPT’s inaccuracy.

The Biden-Harris Administration secured voluntary commitments from seven leading AI companies – Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI – in July 2023 to manage the risks posed by AI. Although not directly related to data privacy, this shows that the leading AI companies care about the impact AI might have on consumers.

2) Implementation Challenges

Implementing AI in marketing requires a comprehensive strategy and skilled personnel, both internal and external. Many organizations grapple with the complexity of integrating AI seamlessly into existing systems.

To successfully integrate AI into existing marketing processes, you’ll have to partner with AI solution providers that have significant experience and expertise. Simply incorporating new apps or plugins into your workflow isn’t always enough to see the kind of productivity gains you’lre looking for. 

It’s key to start defensively, protecting data input, storage, and infrastructure from potential adverse impacts. You should also consider compatibility with AI to ensure smooth operations. Post-transition, you’ll want to provide comprehensive training on the new system to any employees you have.

Typically, affiliate marketers do not face the same implementation challenges as large companies, though bigger e-commerce brands might! But the point stands: if you’re an affiliate marketer, implementing AI in your marketing strategy might be a steep learning curve. Consider investing in training courses and outside consulting, rather than a slow and risky trial and error approach.

3) Lack of Creativity

AI excels at data-driven decision-making, but it struggles in the realm of creativity. While it may feel like an LLM like ChatGPT is great at coming up with ideas, in reality, it’s not inventing these ideas out of nowhere – it can’t currently come up with any completely new ideas or concepts on its own. The spark of human ingenuity, emotional resonance, and the ability to think outside the box are all elusive to AI.

I like to say that generative AI is a good servant but a poor master for marketers. If you’re an affiliate marketer, AI can save you time by performing repetitive tasks, leaving you to focus on higher-value activities. But AI will not generate unique ideas or grow your affiliate marketing business on autopilot.

And you run the risk of having your content, copy, and products looking a lot like everyone else’s if you’re depending on AI to do the heavy lifting. Creativity is still a valuable piece of any successful online business, whether you’re an affiliate or a product creator.

4) Initial Costs

The initial investment in AI technology, including software, hardware, and skilled professionals, can be prohibitive for some businesses. However, it can be a smart investment that leads to productivity gains that will eventually pay for itself many times over.

According to WebFX, companies can generally pay anywhere from zero to $300,000 for AI software, depending on whether it’s a third-party solution or a custom platform developed by a team of in-house or freelance data scientists.

However, if you’re new to affiliate marketing, there’s good news: you don’t need to significant money to take advantage of AI technology. ChatGPT-3.5 from OpenAI is totally free, and ChatGPT-4 is only $20 monthly. Many other AI-powered tools – such as AI copywriting tools – are also modestly priced, usually less than $100 per month.

5) Dependence on Technology

Relying too heavily on AI systems can create vulnerability in your business. Technical glitches or system failures can disrupt marketing efforts and leave businesses scrambling for alternatives!

AI technology can also impair your ability to be efficient and productive without it if you become dependent on it. I would recommend only using AI technology after you can perform core tasks yourself or successfully outsource them. This will serve as a fallback for you if crucial AI services are ever down or you find their output start to degrade in quality.

Strike a balance between letting AI do what it is best at and building on your core strengths, experience, and expertise that AI can’t replicate!

6) Hallucinations

IBM defines AI hallucinations as follows:

“A phenomenon wherein a large language model (LLM) – often a generative AI chatbot or computer vision tool – perceives patterns or objects that are nonexistent or imperceptible to human observers, creating outputs that are nonsensical or altogether inaccurate.”

There are many possible causes for hallucinations. It includes bias (more about that later), poor or insufficient training data, incorrectly decoded data, and sometimes outputs that are not based on training data.

After chatting with ChatGPT about why it sometimes hallucinates and generates incorrect or fictional information, it appears this likely occurs due to one or more of the following reasons:

  • Pretraining on diverse data: ChatGPT is pre-trained on a vast amount of data from the internet that includes both accurate and inaccurate information. This broad exposure to diverse data means that it may have learned patterns from unreliable sources or fictional content, leading to the generation of erroneous information.
  • Lack of fact-checking: ChatGPT does not have access to real-time fact-checking capabilities or external databases to verify the accuracy of the information it generates. It relies solely on the knowledge acquired during training, which may contain inaccuracies.
  • Ambiguity and context: ChatGPT generates responses based on the input it receives and the context provided. If the input is ambiguous or the context is unclear, it may make educated guesses or fill in gaps with information that may not be accurate.
  • Over-optimization: Some AI models, including ChatGPT, are prone to generating information that is coherent within the context of a conversation but not necessarily factually correct. It can happen because the model is designed to optimize for fluent and contextually relevant responses and may prioritize fluency over factual accuracy.
  • Limited world knowledge: While GPT-3.5 (the free version of ChatGPT) has access to a vast amount of information, its knowledge is still limited to what was available up to its last knowledge cutoff date (September 2021). It may not be aware of recent events or developments that have occurred after that date.
  • Based on the above, it is essential that you not rely blindly on the accuracy of AI tools like ChatGPT. Instead, always verify the accuracy of any responses you receive, especially statistics or facts that you can easily look up.

    Here is how ChatGPT phrases it:

    “It’s crucial to use ChatGPT and similar AI models with an awareness of their limitations and to verify the information they generate, especially when it comes to critical decisions or factually accurate content. Incorporating human oversight and fact-checking mechanisms can help mitigate the risk of hallucinations and ensure the reliability of the information provided by these models.”

    7) Bias

    In 2018, MIT researchers introduced Norman, which they refer to as the “world’s first psychopath AI.” They created Norman as an experiment to examine Rorschach tests and describe what it saw.

    Trained solely on graphic content from the darkest corners of Reddit, Norman exhibited extreme bias, offering disturbing interpretations compared to a standard AI trained on diverse data. Five years later, Norman’s legacy remains a reminder of the consequences of biased training data in AI.

    Generative AI apps like ChatGPT and image generation tools like Midjourney face increasing scrutiny for inherent bias. For example, research has uncovered gender bias in ChatGPT’s output professions, showing biases in the training data.

    Identifying and resolving bias in AI can be challenging due to a lack of transparency in algorithm development. Similar to the consequences of sharing hallucinations or factual errors, you can suffer reputational harm if you share AI output with bias.

    8) Google and E-E-A-T

    If you’re a content marketer and rely on Google for free organic traffic, AI might pose a challenge for you.

    According to Google, their ranking algorithm systems aim to reward original, high-quality content that demonstrates E-E-A-T: expertise, experience, authoritativeness, and trustworthiness.

    Google has also confirmed that they focus on the quality of content, rather than how content is produced to deliver reliable, high-quality results to users.

    In addition, Google Search’s helpful content system generates a signal used by its automated ranking systems to better ensure people see original, helpful content created for people in search results.

    Based on the above, Google does not, in principle, discriminate against helpful, high-quality AI-generated content that demonstrates expertise, experience, authoritativeness, and trustworthiness.

    However, complying with all of the above using a generative AI tool like ChatGPT is easier said than done. Expecting ChatGPT to show experience, for example, might be stretching its capabilities.

    As a blogger myself, I would recommend you always edit any output from tools like ChatGPT and make sure the content reflects what you would say if you were writing from scratch. Incorporate personal stories and opinions, cite reputable sources, and provide quality original data and images to ensure your content will still meet Google’s standards – even if you got help from AI along the way!

    9) Copyright Restrictions

    A federal judge in Washington, D.C., ruled in August 2023 that artwork generated by artificial intelligence is not eligible for copyright protection.

    Judge Beryl A. Howell of the US District Court for the District of Columbia stated that “courts have uniformly declined to recognize copyright in works created absent any human involvement,” reaffirming a decision of the United States Copyright Office’s guidance.

    The ruling is the first in the US to establish boundaries on legal protections for AI-generated art and has widespread implications for digital marketing images created using AI image-generation tools. If you want your videos, blog posts, books, podcasts, music, and other creative work to be copyrightable, it’s important for you to still have substantial input in the process of creating these works.

    Relying on AI could undermine the value of your business’s intellectual property, and you odon’t want that!

    AI Marketing and Machine Learning in the Real World

    AI in marketing is not a hypothetical concept. It’s a powerful tool currently reshaping industries.

    Companies like Amazon, Netflix, and Spotify all use AI to recommend products, movies, and music in their algorithms, creating personalized user experiences that keep customers engaged and loyal. In e-commerce, AI chatbots offer real-time customer support, enhancing the overall shopping experience.

    Here are a few more specific examples of companies that are leveraging AI:

    Ello

    Ello uses AI to listen to your child read from real books, teaches and motivates them, and transforms them into enthusiastic readers. The company raised $15 million in September 2023 to combat childhood illiteracy with AI and child speech recognition technology.

    Ello is a subscription-based service designed for children from kindergarten through Grade 3. For a monthly fee of $24.99, Ello delivers five carefully curated books, fostering a love for reading from an early age.

    With over 10,000 families embracing the platform, children have collectively read more than 300,000 books through the app.

    Mayo Clinic

    The Mayo Clinic is incorporating Microsoft 365 Copilot, a transformative generative AI service, to redefine healthcare workflows.

    By leveraging Microsoft 365 Copilot the clinic endeavors to streamline operations and elevate patient care.

    SAP

    SAP, the German technology giant, is entering the AI space with the launch of Joule, an AI-powered copilot tool. 

    Joule is designed to simplify and expedite critical decision-making processes and is set to debut on selected SAP tools and services in November 2023.

    Future Trends with AI in Marketing

    AI has grown exponentially in 2023, and there is no end in sight as companies invest billions of dollars into AI development.

    It is clear that AI is not a passing trend, and the earlier marketers learn to embrace AI, the further ahead they will be of their competitors and the higher the reward.

    Although nobody can predict future trends with AI in marketing with absolute certainty, the following is likely to occur:

    • Marketers will embrace AI due to productivity gains that might see them working fewer hours every week, improving the quality of their life – or at least allowing them to spend their working hours on more interesting and productive tasks.
    • More companies will block OpenAI’s GPTBot or bots from other generative AI companies from accessing their content, citing copyright concerns.
    • OpenAI’s ChatGPT will lose its dominant position in the market as companies like Google gain ground.
    • New international regulations will safeguard consumer rights and mitigate privacy concerns.
    • Many new players will enter the market, and AI technology will become a part of daily life like the internet has become.
    • Getting training in the implementation of AI technologies will be a must and become a standard requirement by companies.

    Pros and Cons of AI for Marketing Wrap-up

    AI in marketing is a double-edged sword, with its pros promising unparalleled efficiency and productivity increases while its cons pose challenges related to privacy, creativity, bias, implementation, and cost.

    To harness AI’s full potential, businesses must strike a balance between automation and human creativity, all while navigating the evolving landscape of data privacy and regulation. 

    As technology continues to advance, AI’s role in marketing will undoubtedly grow, and those who master its intricacies will enjoy a competitive edge in the ever-evolving digital marketplace.

    Generative AI presents a golden opportunity for affiliate marketers who wish to leverage AI to boost their digital marketing efforts and success.

    For more information on how AI might boost your affiliate marketing results, have a look at the following articles:

    AI in affiliate marketing is only one component that might save you time and help you earn more commissions. There is much more to affiliate marketing than AI alone – and it can be a steep learning curve!

    That’s why you should work with people who know this industry inside and out. With 25+ years in business and more than $6 billion paid out in commissions, ClickBank is the world’s leading affiliate marketplace!

    If you are serious about making money online with affiliate marketing and furthering your education, we encourage you to check out our affiliate education platform, Spark by ClickBank.

    Spark by ClickBank can help you significantly shorten the time to earn your first affiliate commission and grow your affiliate marketing business on a solid foundation!



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