Despite all the hype about AI coming for our jobs, for most of us there’s little need to worry – at least for now. We need to shift our perspective from seeing AI as a threat to understanding it as a device to improve personal efficiency and business management. AI is a technological tool to be leveraged by professionals, rather than a replacement for them.

This is particularly evident in the marketing sector, which can greatly benefit from the additional processing power that AI delivers to analyze large swaths of data and draw conclusions from it. In fact, 85 percent of marketers believe AI will help them better reach and target consumers.

However, in order to maintain customer loyalty, marketers need to preserve brand authenticity and relatability. You can’t simply launch a 100 percent AI-developed marketing campaign devoid of human oversight or creativity and expect it to be successful. To be sure, it’s time to embrace AI, but first we need to understand how to use it properly.

Analyzing real-time trends

One of the biggest advantages of AI in marketing is its ability to analyze current trends, customer preferences, and consumer behavior to shape marketing campaigns in real-time. AI can automate and adjust factors like ad placement, timing, and messaging based on current performance data. In essence, it knows what’s going on – in the world, in markets, and in a customer’s mind – and can respond accordingly. This leads to better ROI on marketing spend.

Imagine for instance an e-commerce company that sells a wide range of products. AI algorithms can analyze customer browsing, history, and purchasing behaviors on the website. By tracking what products customers view, add to their carts, and ultimately buy, the AI system can identify patterns such as frequently purchased combinations and even the typical sequence of actions before making a purchase. This information helps optimize product placements, suggest complementary items, and target advertisements to push individuals towards more sales and fuller carts.

Besides tracking and responding to trends, AI can also enable smart customer segmentation, dividing a larger target audience into smaller, more homogeneous groups based on shared characteristics. AI can perform sophisticated segmentation by considering numerous variables simultaneously, allowing marketers to tailor their campaigns to specific customer segments.

Consider a cosmetics brand launching a new line of skincare products. Instead of using broad demographic categories like age and gender, AI-driven segmentation can consider a combination of factors such as age, gender, skin type, lifestyle, and purchasing history. This can result in segments like “Young professionals with oily skin seeking anti-acne treatments” or “Mature women interested in anti-aging products.” With these refined segments, marketers can create targeted content and offers that resonate with each group’s particular needs and preferences.

But the AI can also shift a customer from one segment to another and display different ads based on their behavior during the current visit. It’s this real-time responsiveness that can really turbocharge marketing campaigns.

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Embedding creativity

While AI can process data to generate content, it lacks the empathy, creativity, and discernment that humans bring to the table. So ideally, marketers would use AI to collect and analyze data from diverse sources, and then human professionals would figure out how to best make use of it. People infuse data-driven campaigns with authenticity, relatability, and emotional appeal, factors that are crucial for building lasting connections with consumers. As of yet, those are factors that AI has struggled to replicate.

Consider how some global brands already use AI in marketing. Advertising agencies Hello Monday and DEPT® collaborated to launch digital ads in empty store windows that analyze what passersby are wearing, find shoes that match their outfits, and place them on their feet through augmented reality. This was intended to show the potential of empty storefronts in advertising and revenue-generation.

What’s more, BMW now uses AI in predictive analytics to design new vehicle models based on data about changing consumer preferences and tastes. And Nutella used AI to create seven million different labels available for one month only, with each being marketed as a collector’s item, in an extraordinarily successful marketing campaign.

The point is the sheer number of possibilities here, and the ability to launch creative campaigns based on rich data and sophisticated data analytics. But, at the end of the day, the AI didn’t create or develop the campaign – it just provided the data that set the campaign in motion.

Handling unstructured data

One reason that the “human factor” is so crucial in marketing is that marketers are working with so much unstructured data, information that doesn’t have a predefined format, which makes it more challenging to analyze. This often includes text data from social media posts, customer reviews, and email content, as well as images and videos. Unlike structured data listed in databases or spreadsheets, unstructured data lacks a clear organization and can vary widely in content and context.

AI struggles with reading and interpreting unstructured data because it comes in various formats, languages, and writing styles. AI models are trained on structured data and often struggle to handle the diversity of unstructured content, while also contending with the emotional nuances of it that require a human perspective.

Despite these challenges, AI has made significant advancements in handling unstructured data through technologies like natural language processing (NLP) and computer vision. NLP techniques enable AI to create a sense of structure in otherwise unruly textual data and to analyze the results, while computer vision allows AI to interpret visual data like images and videos. By training AI models on vast amounts of diverse data and fine-tuning them for specific tasks, AI can gradually improve its ability to handle unstructured data.

However, human expertise remains essential in interpreting the nuances of unstructured data. Humans can grasp the broader context and emotional clues that AI algorithms can’t understand. Even if AI learns to read social media comments across platforms and catalog them by the charge of the sentiment – funny, sarcastic, critical, etc. – it will still require humans to interpret the nuances of responses and determine which feedback is useful and how to respond.

Final thoughts

Ultimately, integrating human expertise with AI creates a powerful combination that leverages the strengths of both. AI brings data processing, pattern recognition, and automation capabilities, while human expertise contributes creativity, empathy, strategic thinking, and nuanced decision-making.

AI isn’t after your job. In fact, it’s here to make your job easier.

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