The rise of AI has drastically changed the way businesses connect with their customers. Here are some benefits and pitfalls of using AI in marketing.
In the age of digital marketing, artificial intelligence (AI) has emerged as a game-changer, bringing drastic changes to the way businesses interact with their audience. AI helps 21st-century businesses keep up with the fast-paced and digitally-driven market, allowing them to plan, execute, and optimise marketing campaigns faster. By leveraging this technology’s capabilities, marketers can tap into vast amounts of data, automate processes, and deliver highly personalised experiences to their target audience.
But while AI is poised to improve marketing practices for the better, it’s not without its challenges. With the promise of change also comes cause for concern — its implications on customer ethics, human labour, data collection, and more. In this article, we discuss the numerous advantages, disadvantages, and implications of using artificial intelligence in marketing.
The Advantages of Using AI in Marketing
As a tool, the role of AI is to help marketing departments make processes faster and more efficient. It allows for the automation of tasks that don’t require human intervention, leaving room for marketers to think bigger. Its limited yet robust role makes it an excellent aid, but in itself is incapable of being an adept marketer — meaning that marketing jobs are still safe.
Here are some reasons marketing departments are using AI to their benefit:
Advanced Data Analysis
AI-powered analytics tools help businesses gain meaningful insights from large and complex data sets quickly. Traditional data analysis methods often fall short due to the sheer volume and complexity of data available today. AI algorithms can uncover patterns, trends, and correlations that human analysts might otherwise miss.
Analytics allow marketers to track user behaviour faster and examine user behaviour on various metrics (engagement, conversion, time and location, etc.). Applications like Google Analytics, for instance, track all this data in real time, enabling teams to respond to changing user behaviour faster than ever before. In addition to tracking campaign progress, this kind of data also serves as comprehensive research for new campaigns.
By leveraging AI in data analysis, marketers can make data-driven decisions, optimise marketing strategies, and gain a deeper understanding of customer behavior, preferences, and market trends.
Automation of Rote Tasks
AI technology offers significant advantages in automating repetitive and time-consuming marketing tasks. Using tools for large-scale data generation and analysis, lead generation, content curation, email campaigns, and social media posting, marketing departments can save time and make their processes more efficient.
Tools like Jasper, Wordtune, Otter.ai, and Grammarly can speed up the content creation process and aid in writing, editing, and curating collaterals. Platforms like Meta Business Creator, Metricool, and Google Analytics can help you schedule social media posts or ads, while MailChimp and sendinblue can help you automate email campaigns.
Using AI for repetitive and recurring tasks allows marketers to shift their attention away from manual work and focus on creative and strategic aspects of their role. Automation also reduces human error (you’re unlikely to miss posting) and oversight (you have more time to do quality checks and the like).
Improved Customer Service
AI-powered chatbots and virtual assistants have transformed customer service in marketing. These AI systems can handle customer inquiries, provide instant support, and offer personalised recommendations. These tools use natural language processing and machine learning algorithms to understand customer queries, engage in meaningful conversations, and resolve issues efficiently.
Creating automated chatbots allows for real-time interaction with customers. Responses for common queries can be templatised and quickly dispatched to customers, while executives can address more specific or unique queries with the nuance that is required. This combination of automation and human interference allows the department to provide customer interactions that are timely and carefully tailored experiences that enhance customer satisfaction.
By providing 24/7 support and quick response times, AI-powered customer service enhances the overall customer experience, increases customer satisfaction, and reduces the workload on human customer service representatives.
Enhanced Personalisation
One of the key advantages of AI in marketing is its ability to deliver highly personalised experiences to customers. AI algorithms can analyse vast amounts of customer data such as demographics, preferences, browsing behaviour, and purchase history, to generate valuable insights.
With this information, marketers can segment their audience and create highly targeted advertising campaigns that appeal to each segment. By identifying browsing patterns and user preferences, AI algorithms can deliver personalised advertisements to specific segments or individual users — making the advertisements more relevant, immediate, and effective, leading to higher engagement and conversion rates.
Another effective way to make customer experiences more personalised is through recommendation engines. A recommendation engine uses data mining, machine learning, and artificial intelligence to understand user preferences and predict items that users are likely to engage with or find value in. They typically study data about user behaviour, browsing history, past interactions, preferences, and feedback to make personalised recommendations.
Recommendation engines are increasingly being used in a wide range of industries: online commerce, news and media, digital streaming, entertainment, social media, and more. They play a pivotal role in customising user feeds to deliver relevant experiences and eliminating irrelevant ones—ultimately helping users discover products, services, or content that aligns with their interests.
Additionally, such data also helps marketers deliver personalised offers and increase customer engagement and loyalty.
The Disadvantages of Using AI in Marketing
The benefits of using AI in marketing come with its own set of risks, challenges, and considerations for marketers. Data privacy and security breaches are at the forefront, along with an overdependence on user data and a risk of strategies lacking the human touch. It’s crucial that marketers be cognizant of these pitfalls so they can make well-informed decisions about how AI contributes to their strategies. Here are some considerations marketers should know about:
Data privacy and safeguards
The use of AI in marketing heavily relies on collecting and analysing vast amounts of customer data. This raises concerns about data privacy and security. The onus is on the marketers to be abreast of data regulation policies in the regions they are in and comply with them. It’s also crucial that they obtain consent from users in a transparent way by clearly stating data collection processes and providing accessible opt-in/out mechanisms. As netizens become increasingly savvy, disclosing data collection practices is a crucial way to maintain customer trust.
Storing and processing large volumes of data also increases the risk of data breaches and cyberattacks. While implementing AI tools, marketers must also implement security measures to protect (sensitive) customer information. Some commonly adopted measures include encryption during customer interactions, secure data storage, cybersecurity measures to prevent data leaks, etc.
Bias from existing data
Given that AI primarily learns from historical data, it’s unlikely to provide up-to-date information on emerging trends or unforeseen events. Its reliance on existing information also means it’s susceptible to the biases perpetrated in existing data and discourse. If machine learning continues to operate on erroneous information or biases, it may end up making recommendations that are irrelevant, exclusionary, or even harmful to its users.
Rectifying these biases usually requires human intervention, which may (depending on the severity of the bias) render the whole process counterproductive. It’s essential for marketers to evaluate algorithmic data and regularly assess for biases that may be discriminatory or negatively impact customers.
Risk of generic (or insensitive) responses
While AI automation can streamline marketing processes, it presents a risk of having customer interactions that are generic and lack a human touch. It serves a limited purpose in customer relationships, especially in instances when personalised assistance or support beyond what AI is programmed to do is required. While AI fares well with routine or commonly asked queries, it lacks the empathy needed to handle more complex or sensitive matters.
Moreover, marketing as a discipline relies on emotional connections with customers. AI-driven interactions run the risk of being too detached from human behaviour and may lack the empathy and understanding that normally comes with customer interactions. AI may also be unable to pick up subtle and contextual clues that human marketers can spot. If customers can easily recognise they are engaging with a machine, their experience with the business may not be as fulfilling or memorable.
Overreliance of data
In addition to biases, an overreliance on data can lead to a narrow perspective and overlook important qualitative insights and intuition. Using historical data as primary research can limit marketers’ perspective of emerging trends and may miss out on evolving customer expectations. Numbers also fail to capture subjective customer experiences, which marketers often draw on to create compelling campaigns. It’s humans who ultimately bring contextual understanding, creativity, and empathy that can complement data-driven approaches and lead to more well-rounded strategies.
Another concern is that AI algorithms also may not pick up on rapidly changing market dynamics and consumer behaviors. AI models typically make predictions assuming that historical patterns will always continue to hold true. If changes in market conditions and consumer behaviour are shifting faster than ever, then data collection must also evolve rapidly to keep up with these changes. Marketers should regularly evaluate and update their AI systems so they provide updated data that reflect evolving market trends and consumer preferences.
(You can also check out this blogpost ‘The Truth Behind AI Text Generators‘)
Summing up: the implications of using AI in marketing
Even as we scratch the surface of artificial intelligence and its role in business, its implications remain vast and reaching. It has increasingly gained traction as businesses recognize its potential to enhance marketing strategies and drive results. Companies are increasingly adopting AI technologies, more so after the COVID-19 pandemic, to create personalised marketing campaigns to cater to a global audience.
In large-scale campaigns, AI can be used for personalized recommendations, automated customer service, and data analysis.
The increase of AI in marketing also raises questions about the division of labour within marketing departments, since there are overlaps between its functions and what marketers have traditionally been doing. With many routine and repetitive tasks automated through AI tools, marketers have more opportunities to upskill and learn to work alongside these tools.
Marketers must be aware and critical of AI’s role in marketing processes. They must create strategies that leverage AI’s strengths but retain the human elements of marketing processes. Moreover, evolving trends, employee training, cost of implementation, and other factors must be considered while marketers implement AI in their strategies.
