How artificial intelligence is transforming marketing

• How is AI used in marketing?
• AI marketing tools: powering efficiency and precision
• Machine learning
• Task automation is foundational to AI
• AI helps analyze current market trends
• Challenges of AI in marketing

In the fast-paced world of 21st-century business, few forces have captured our imagination like Artificial Intelligence (AI). While its impact spans industries from manufacturing to healthcare, it’s in the realm of marketing where AI is sparking a true revolution. It’s not just about automation anymore; artificial intelligence in marketing is about understanding customers on a deeper level, personalizing experiences at scale, and predicting trends with uncanny accuracy.

As the lines between human creativity and machine learning blur, marketers find themselves at a thrilling crossroads. This isn’t just another buzzword; it’s a fundamental shift in how AI is used in marketing to forge connections, drive conversions, and shape the future of customer engagement.

Speculation about the long-term future of artificial Intelligence in society is at a fever pitch, receiving unprecedented attention in the news and on social media. Luminaries such as Elon Musk and the late Stephen Hawking have expressed deep concern about AI’s exponential growth with the possibility that it will eventually become self-aware.

They believe that if AI development is left unchecked, it could easily surpass human control within decades from now and create its own agenda one perhaps antithetical to the value of human life. That said, we are now witnessing fierce, heavily invested competition between Google and Microsoft to advance artificial intelligence without apparent concern for its long-term dangers.

How is AI used in marketing?

While speculation about AI’s future runs rampant, the reality is that it’s already revolutionizing marketing strategies today.

Forward-thinking companies aren’t waiting; they’re harnessing AI’s power to gain a profound understanding of their customers and fine-tune their tactics for maximum impact. It’s not just hype – studies show a staggering 91.5% of leading businesses are investing in AI on a regular basis. (1)

Here’s a glimpse into how AI is being deployed in the marketing trenches right now:

• Unveiling customer insights: AI tools act as digital detectives, sifting through mountains of customer data to uncover hidden patterns and predict future behaviors. This empowers marketers to deliver personalized content that truly resonates, boosting engagement and fostering loyalty.
• Cracking the attribution code: Say goodbye to guesswork. AI-powered attribution modeling sheds light on which marketing channels and campaigns are truly driving results, allowing marketers to optimize their budgets and strategies.
• Performance insights at your fingertips: AI provides real-time performance insights, giving marketers a clear view of what’s working and what’s not. This enables agile decision-making and continuous improvement.
• Media buying made smarter: AI takes the guesswork out of media buying, helping marketers identify the most effective ad placements to reach their target audience with laser precision.
• Hyper-segmentation for hyper-relevance: AI’s ability to process massive datasets enables the creation of hyper-segmented customer groups, allowing marketers to deliver highly targeted and relevant messages.
• Predictive analytics for a competitive edge: AI empowers marketers to anticipate future trends and customer behaviors, giving them a head start in a rapidly changing marketplace.
• Sentiment analysis for proactive engagement: AI helps marketers understand and respond to customer feedback in real-time, allowing them to address concerns and capitalize on positive sentiment.
• Keeping tabs on the competition: AI-powered competitive analysis tools provide valuable insights into market trends and competitor strategies, helping marketers stay one step ahead.

In practice, you’ll encounter AI in the form of chatbots providing instant customer service, image recognition software analyzing visual content, and recommendation engines suggesting products tailored to individual preferences.

The bottom line? AI is no longer a futuristic concept; it’s a marketing powerhouse that’s transforming the way businesses connect with their customers and achieve their goals. In fact, it’s shaping the very future of marketing as we know it.

AI marketing tools: powering efficiency and precision

AI marketing tools are rapidly becoming indispensable for marketers, enabling them to automate tasks, gain deeper insights, and optimize campaigns for maximum impact. Let’s explore some of the ways different types of AI are being leveraged in the marketing realm:

• Chatbots: AI-powered chatbots provide instant customer support, answer frequently asked questions, and even qualify leads. Natural Language Processing (NLP) enables these chatbots to understand and respond to customer queries in a human-like manner, improving customer satisfaction and engagement.
• Content creation: AI-powered tools can assist in generating blog posts, social media captions, and product descriptions. While they may not replace human creativity entirely, they can be a valuable aid in overcoming writer’s block and improving content productivity.
• Maintenance and quality checks: Machine learning algorithms excel at identifying patterns and anomalies in large datasets. In digital marketing, this translates to powerful quality checks for websites, ad campaigns, and content. For example, AI can automatically detect broken links, grammatical errors, or inconsistencies in branding, ensuring a polished and error-free online presence.
• Standardization of marketing tasks: AI-powered automation tools are streamlining repetitive marketing tasks, such as social media scheduling, email marketing, and data entry. This frees up marketers to focus on strategic planning and creative ideation. Robotic Process Automation (RPA) is particularly effective for standardizing tasks that involve structured data and rule-based processes.
• Personalization engines: AI analyzes customer data to deliver personalized product recommendations, email content, and website experiences. This level of personalization enhances the customer journey, increasing conversions and fostering loyalty.
• Predictive analytics: AI can analyze historical data to predict future trends, such as customer churn or product demand. This empowers marketers to make proactive decisions and optimize their strategies for better results.

Machine learning

At the heart of AI’s marketing prowess lies Machine Learning (ML), the technology enabling those “guided experiences” that seem to read customers’ minds.

ML, a cornerstone of artificial intelligence marketing, has revolutionized big data analytics, allowing marketers to anticipate customer desires and proactively deliver tailored solutions. It’s the secret sauce behind those eerily accurate product recommendations and personalized emails that make you feel truly understood.

While we may envision ML as the path to machines conversing like humans (and that future is certainly on the horizon), its current impact on marketing is already profound.

Today’s ML-powered tools are laser-focused on specific tasks: optimizing ad placements, crafting persuasive email subject lines, and generating content that resonates. It’s about intelligent automation, not just brute force repetition.

Yet, even these seemingly “basic” applications are yielding remarkable results. Organizations awash in data and hungry for sophisticated personalization have been leveraging these foundational AI capabilities for years.

Healthcare and financial services may have initially led the charge, but the marketing world is swiftly catching up, recognizing the immense potential of AI to forge deeper connections and drive unparalleled results.

Machine learning continually improves all aspects of marketing

By contrast, CMOs and their teams rely on AI and machine learning to iteratively test and improve their marketing campaigns and strategies. This requires a new level of data quality which isn’t possible using conventional platforms The most popular use of AI and machine learning in organizations is delivering personalization at scale across all digital channels. There’s also increasing adoption of predictive analytics based on machine learning to fine-tune models to improve up-sell and cross-sell results. (2)

There is such a vast amount of data that platforms like Google and Amazon handle that is impossible to analyze by humans. Also, an artificially intelligent system stores multiple information about large numbers of people captured within multiple machines from multiple sources. All of this appears in the system asynchronously or simultaneously.

AI-enabled systems perceive the environment and take action, accordingly, remembering the situations that may come up again. With the help of historical data, AI can predict future data trends, alerting marketers to proactively take action. (3)

According to a recent study (4), 87% of companies that have adopted AI were using it to improve email marketing. 61% of marketers were also planning to use artificial intelligence in sales forecasting.

Using AI tools like robotic analytics, CRM, and social data, a marketer can quickly boost the ROI of marketing initiatives. Thanks to the increasing amount of data gathered from customers, businesses’ marketing strategies have become more data-driven. (5)

Task automation is foundational to AI

Task automation: These applications perform repetitive, structured tasks that require relatively low levels of intelligence. They’re designed to follow a set of rules or execute a predetermined sequence of operations based on a given input, However, they can’t handle complex problems such as nuanced customer requests.

Machine learning: ML employs algorithms that learn how to use large quantities of data to make relatively complex predictions and decisions. Such models can recognize images, decipher text, segment customers, and anticipate how customers will respond to various initiatives.

Machine learning already drives programmatic buying in online advertising, e-commerce recommendation engines, and sales direction models in customer relationship management (CRM) systems.

It and its more sophisticated variant, deep learning, are the most exciting technologies in AI. That said, it’s important to clarify that most existing ML applications still just perform narrow tasks and need to be ‘trained’ using voluminous amounts of data.

Other AI differentiators

Stand-alone applications: Stand-alone applications are best understood as clearly demarcated, or isolated, AI programs. They’re separate from the primary channels through which customers learn about, buy, or get support for using a company’s offerings- -or the channels employees use to market, sell, or service those offerings.

One example is the color-discovery app created by Behr, the paint company. Using IBM Watson’s natural language processing and Tone Analyzer capabilities, the application delivers several personalized Behr paint-color recommendations that are based on the mood consumers desire for their space. Customers use the app to short-list two or three colors for the room they intend to paint. (6)

Integrated AI applications: the unsung heroes of marketing automation

Often working behind the scenes, integrated AI applications are seamlessly woven into existing marketing systems. These subtle yet powerful tools, fueled by machine learning, make split-second decisions that impact customer experiences without anyone even noticing. Think of the lightning-fast algorithms that determine which digital ads to serve you as you browse the web – that’s integrated AI in action.

Data scientists and developers are pushing the boundaries even further, creating general-purpose learning algorithms. This means AI isn’t just limited to mastering one specific task; it’s gaining the ability to adapt and learn across a range of marketing functions, unlocking new levels of efficiency and innovation.

AI-powered decision making: empowering marketers at every level

The integration of AI into Customer Relationship Management (CRM) systems is a game-changer. AI marketing tools are now embedded within these platforms, offering intelligent recommendations to marketers and salespeople in real-time.

Whether it’s suggesting the perfect upsell opportunity or predicting which customer segments are most likely to convert, AI empowers data-driven decision-making at every touchpoint.

This shift towards automation allows businesses to streamline routine tasks, freeing up human talent to focus on strategic initiatives that require creativity and critical thinking. It’s about striking the perfect balance between machine efficiency and human ingenuity.

Navigating the AI adoption maze: challenges ahead

While the potential of AI in marketing is undeniable, the journey toward successful implementation is not without its hurdles, presenting a unique set of marketing manager challenges.

Stand-alone task automation, while less technically complex, still requires careful configuration to align with specific workflows. Companies must proactively invest in acquiring the necessary AI skills and expertise to ensure smooth deployment.

Integrating AI into existing marketing workflows demands a delicate balancing act. The goal is to augment human skills, not replace them. Achieving seamless collaboration between humans and machines requires thoughtful planning and execution.

For instance, while AI-powered chatbots can handle routine customer inquiries, less capable bots can lead to frustrating customer experiences. In such cases, it may be wiser to position chatbots as assistants to human agents, ensuring a seamless and satisfying customer journey.

The buzz surrounding AI and marketing can sometimes lead to inflated expectations. It’s crucial to recognize that AI is not a magic bullet that will instantly solve all marketing challenges. Setting realistic goals and understanding the limitations of current AI capabilities is essential for successful implementation.

As marketing artificial intelligence becomes increasingly sophisticated, ethical considerations come to the forefront. Issues such as data privacy, algorithmic bias, and transparency must be carefully addressed to ensure that AI is used responsibly and ethically.

Marketers must navigate the fine line between leveraging AI’s potential for innovation and upholding ethical standards that protect consumers and maintain trust.

AI helps analyze current market trends

Digital marketers can adopt AI technology to find the most attractive business growth opportunities for brand expansion. Innovative AI tools can scan a vast quantity of data to derive and analyze current market trends. This helps marketers to create strategies that help to uncover new ideas for rebranding marketing and innovative marketing campaigns.

While most marketers are increasingly comfortable regularly using AI tools, they’re often executed in an ad-hoc manner. Many marketing departments still lack a coordinated, strategy-focused approach to implementing major projects. And many are lagging when it comes to fostering an AI-friendly, data-first culture as well. This includes developing competencies and requisite skills. (7)

AI and ad placement

Facebook and Google are the biggest online advertising platforms. They both offer AI tools that work by combining audience segmentation with predictive analytics.

Segmentation splits customers into groups according to demographic characteristics – gender, age, income level, interests–and an infinity of other potential variables. In short, predictive analytics calculates which groups a particular product or service is most likely to appeal to. (8)

Facebook, Google, and all of the other platforms that offer advertising functions allow businesses to target thousands of potential customers with multiple versions of advertising materials. This is critical in measuring and assessing their relative effectiveness with different demographic groups.

AI-driven advertising tools are most effective when used as part of a coordinated AI marketing strategy By comparison, with traditional methods of advertising such as television, newspapers, and magazines, it’s very difficult to attribute sales growth to any specific advertising content, or venue,

Content marketing

“Content is king” has been accepted wisdom in marketing departments since the twentieth century, the dawn of Web 2.0, and the rise of user-generated content platforms, especially social media. AI content marketing is a term that describes the inclusion of AI and machine learning programs into content tools. “Content marketing tools can help with content planning, creation, distribution, analysis, and reporting. AI helps improve the quality of content marketing.(9)

As AI continues to evolve, the future of content will increasingly rely on advanced technologies to enhance personalization and engagement.

Email marketing

A large number of AI-powered tools help with email marketing, “AI-based email marketing is a form of machine learning. In an email program, It’s the set of rules and processes that allows programs to analyze hundreds or thousands of inboxes to create better, more personalized content for subscribers.(10)

Challenges of AI in marketing

The marketing manager’s challenges in implementing AI technology for their marketing campaigns are not to be underestimated. While the potential rewards of AI marketing are revolutionary, there are real obstacles to overcome.

From securing buy-in from skeptical executives and team members to maintaining brand quality amidst the allure of generative AI, marketing leaders must navigate a range of concerns. Additionally, the lack of AI skills among employees poses a significant hurdle, requiring training and education to fully leverage the power of automated campaigns and content creation.

Furthermore, ensuring compliance with privacy regulations and effectively prioritizing AI initiatives and solutions add further complexity to the marketing manager’s role. Despite these challenges, with a strategic approach and a solid case for implementation, the transformative potential of AI marketing can be realized.

While the potential rewards of AI marketing are revolutionary, there are real challenges. If you’re planning on adding additional AI software to your marketing, be aware of these common pitfalls:

• Securing buy-In: Some executives, managers, and team members will be all in on AI. Others, not so much. Depending on your industry, you might have to fight an uphill battle just to gain acceptance for a new AI solution or feature. So, make sure you come prepared with a solid case for implementing new marketing AI.
• Maintaining brand quality: With everyone excited about the seemingly magical potential of generative AI, (self-learning) content creators neglect off-brand elements, like outlier designs. As you begin to include generative AI in your marketing, make sure the AI you’re using isn’t negatively impacting your brand.
• Lack of employee AI skills: AI offers great potential to increase productivity, but you’ll need marketers with AI skills to set up your automated campaigns, as well as to edit and implement content. For marketing leaders, a lack of training and education was cited as the top challenge to adopting AI.
• Privacy and data utilization: Browsers, phone manufacturers, and governments are cracking down on the use of third-party data, which means your AI will have to comply with all data regulations in the regions you operate in.
  Prioritizing AI initiatives and solutions: Only 29% of marketing leaders feel confident in their ability to evaluate AI marketing technology. This deficit is a major barrier to AI adoption. To stay focused, prioritize the biggest problems your marketing department and customers face before incorporating AI enhancements.(11)

The near future of AI marketing

Most marketing departments outside of large companies won’t have dedicated, specialist data scientists. As a company goes through the ongoing process of developing a data-and-AI-literate culture, it must enable people who are already experts in their particular field to gain training in AI skills.

OWDT understands the importance of staying ahead in a rapidly evolving digital landscape. Our Marketing and SEO services are designed to leverage data-driven insights and AI technology to optimize your website for search engines effectively.

The rise of Generative (learning) AI within software platforms

Many commonly used marketing tools are adding generative (learning) AI capabilities. For example, the content collaboration platform StoryChief lets you use generative AI to write content briefs.

And the SEO optimization platform Frase offers AI for drafting blogs. Expect to see hundreds of different marketing platforms adding AI into the mix. It will be up to you and your marketing team to determine which features are worth your time. (12)

We can expect to see research AI get much more sophisticated. AI tools make researching and strategizing much easier and faster. So, we can expect to see more AI tools dedicated to customer research and marketing strategy.

Emerging roles and responsibilities

In the near future, new AI-related marketing team roles will emerge. For example, there might be new positions for AI Marketer, AI Marketing Manager, AI Content Editor, etc.

Some AI marketing tasks don’t require a whole new hire, but there will be an augmenting of team marketing competencies to include specific AI-related skills.

Thirty-two percent of marketers and agency professionals were using AI to create ads, including digital banners, social media posts, and digital out-of-home ads, according to a recent study by Advertiser Perceptions. (13)

• AI and Customer Data Platforms are being combined to drive greater personalization at scale.
• High-performing marketing teams were 25% more likely to increase their use of AI in 2022.
• Marketers use AI-based demand sensing to better predict unique buying patterns across geographic regions and alleviate stock-outs and back-orders. Combining all available data sources, including customer sentiment analysis using supervised machine learning algorithms, it’s possible to improve demand sensing and demand forecast accuracy.
• ML algorithms can correlate location-specific sentiment for a given product or brand and a given product’s regional availability. Having this insight alone can save the retail industry up to $50B a year in obsolete inventory.
• Minimizing inventory risk and fine-tuning product demand forecasts are ideal use cases for AI source: ai can help retailers understand the consumer, phys.org. January 14, 2019.
• Forty-one percent of marketers say that AI and machine learning make their greatest contributions to accelerating revenue growth and improving performance. Marketers say that getting more actionable insights from marketing data (40%) and creating personalized consumer experiences at scale (38%) round out the top three uses today. The study also found that most marketers, 77%, have less than a quarter of all marketing tasks intelligently automated and 18% say they haven’t intelligently automated any tasks at all. Source: Drift and Marketing Artificial Intelligence Institute, 2021 State of Marketing AI Report.

Use of artificial intelligence in pricing management

Pricing involves factoring in multiple aspects in the finalization of price. Real-time price variation based on fluctuating demand adds to the complexity of the pricing task. Artificial intelligence-based multiarmed bandit algorithms can dynamically adjust prices in real-time scenarios (Misra et al., 2019).

In a frequently changing pricing scenario like an e-commerce portal, machine learning algorithms can quickly adjust the price points to match the competitor’s price (Bauer & Jannach, 2018).

Use of artificial intelligence in place management

Product access and product availability are essential components of a marketing mix for heightened customer satisfaction. Product distribution relies on networked relationships, logistics, inventory management, warehousing, and transportation problems–which are largely mechanical and repetitive in nature.

Artificial intelligence is the ideal solution in the case of place management by offering robots for packaging, drones for delivery, and IoT for order tracking and order refilling (Huang & Rust, 2020).

Standardization and mechanization of the distribution process add convenience to both suppliers and customers. Besides utility in distribution management, AI also offers customer engagement opportunities in a service context.

Use of artificial intelligence in the marketing company

The best marketing agencies like OWDT (marketing and web design Houston company)  are constantly updating their strategies to incorporate artificial intelligence (AI) as it has the potential to transform the industry.

AI can analyze vast amounts of consumer data to provide insights into customer behavior and preferences, allowing marketers to personalize their messaging and offerings. It can also automate tasks such as ad targeting and optimization, freeing up marketers to focus on more strategic initiatives.

Additionally, AI-powered chatbots and virtual assistants can improve customer service and engagement. As AI technology continues to advance, marketing agencies that embrace it will have a significant competitive advantage in delivering effective and efficient campaigns that drive results.

There are, of course, challenges in adapting to AI marketing. But it’s important to understand and act upon the many advantages that it provides.

Summary of benefits of AI in marketing

• AI accelerates and improves business and customer interaction.
• AI improves ROI.
• AI advances revenue growth and improves performance.
• AI generates more actionable insights from marketing data.
• AI creates personalized customer experience to scale.
• AI reduces the time spent on repetitive tasks.
• AI drives down costs and improves efficiency.
• AI provides personalized content to users based on their search history
• AI and predicts customer needs and behaviors with greater accuracy.
• AI shortens the sales cycle.
• AI increases operational excellence and optimizes the user experience.
• AI offers continuous customer services with AI chatbots and Live Chat.
• AI helps brands cut costs and increase revenues.
• AI targets the right audience
• AI helps businesses use the advantages of going global

Sources

[1] contentbot.ai/blog/news/is-ai-the-future-of-ecommerce-heres-what-we-know.

[2] snowflake.com/guides/prediction-analytics-or-predictive-analytics

[3] research.aimultiple.com/ai-stats/#marketing

[4] https://research.aimultiple.com/ai-stats/#marketing

[5] /venturebeat.com/ai/why-ai-is-the-differentiator-in-todays-experience-market/

[6] researchgate.net/publication/349635531_Enhancing_Marketing_Strategies_and_Analytics_Through_Artificial_Intelligence

[7] marketingaiinstitute.com/blog/ai-in-advertising

[8] rockcontent.com/blog/ai-content-marketing

[9] googleadservices.com

[10] imeanmarketing.com/blog/ai-marketing-statistics

[11] storychief.io/blog/ai-content-marketing-storychief-vs-chatgpt

[12] advertiserperceptions.com

[13] businessoffashion.com/opinions/retail/the-cost-of-dead-inventory-retails-dirty-little-secret/