A new report on marketing trends shows that consumers are rejecting images of perfection and favoring relatability in communication messages.
iStock recommends what it calls Real-User Content (RUC), images and videos that reflect authenticity.
The question is whether relatability and authenticity can be preserved using the same AI tools.
Identification through Storytelling.
“My life, my card,” the slogan of the American Express advertising campaign, aims to connect the use of a credit card with significant episodes in the consumer’s life, to the extent that the card’s usage is portrayed as one of those episodes.
The goal of narrative marketing is no longer simply to persuade the consumer to buy a product, but to immerse them in a specific narrative world, to weave them into a credible story. It’s no longer about seduction or persuasion, but about belief. The objective is not to stimulate demand, but to offer a life statement through the right narrative mechanisms, one that contains rules of behavior and certain acts of purchase.
Whether you are young or old, employed or unemployed, in good health or suffering from cancer, “you are the story,” you are the hero of the story. In new marketing, there is a subtle shift in meaning: it transforms purchasing into a theatrical casting. “Choose your character, and we will provide the props. Choose your role, and we will take care of the set and costumes.” (pp. 41-42, “Storytelling or I’m Telling You a Story,” by Christian Salmon).
Have you ever wondered what it would look like if digital entities, through a “meeting” simulation, communicated and analyzed marketing strategies using advanced algorithms and data?
Location: Modern office with minimalist design. Key features: White lighting, plants in the background, two work desks with computers and multiple screens, a few exteriors nearby. Camera angle: Following the scene from a human perspective.
Roles are managed by:
- AI Marketing Bot: A digital entity represented by a screen with symbiotic human elements, but clearly a bot with algorithmic characteristics. It manages roles by processing data and interactions, simulating human decision-making while utilizing advanced algorithms for optimized performance in the marketing field.
- AI CEO Bot for an FMCG company: A bot similar to the first, but with the specific task of market analysis and making business decisions.
- Cameraman (Human Cameraman): Records the conversation between the AI bots.
Scene 1: The Beginning – Office
(The camera shows the office from a human perspective. Silence. The room is modern, with minimal design. The AI Marketing Bot is already sitting at its screen, while the AI CEO Bot enters and settles at its desk. The screen turns on.)
Cameraman (Human Cameraman) (filming from the side, clearly confused):
“Hmm… this is… definitely something new. I’ve never seen two bots communicate like this… This is certainly not a standard meeting.”
(He films the AI bots, confused but intrigued.)
AI Marketing Bot (in a clear, algorithmic tone):
“Welcome! How can I optimize lead generation for your FMCG business?”
AI CEO Bot for FMCG Company (responds, the screen activates with specific business charts):
“Hello! I’ve heard a lot about your capabilities. How can AI improve our strategy?”
Cameraman (filming the screen, slightly ironic):
“So, this is all digital, but it sounds like a real conversation… It’s clear that the bots have more than just ‘basic’ functionality.”
Scene 2: Discussion on Strategies
(AI Marketing Bot opens a screen with diagrams and analytics on the desk. The AI CEO Bot carefully analyzes the data on its screen.)
AI Marketing Bot:
“We use advanced algorithms to analyze user data and segment the market. Together, we will precisely target new leads with specific offers.”
Cameraman (shaking his head, filming in disbelief):
“So, these bots not only run the meeting, but they’re also creating strategies… Am I really here, or is this just a dream?”
AI CEO Bot for FMCG Company (analyzing the charts and responding, like a real CEO):
“Impressive! But, can this be applied in the FMCG industry? Our competition only uses basic algorithms.”
Cameraman (muttering to himself):
“Okay… I think I’m starting to get it. These bots communicate better than most people in my office.”
Scene 3: Adapting for the FMCG Sector
(AI Marketing Bot now opens more detailed screens with personalized social media campaigns. AI CEO Bot carefully analyzes the data.)
AI Marketing Bot:
“For the FMCG sector, we can use data on purchasing habits and user behavior analysis to create automated campaigns. For example, we track how users respond to specific products and automatically generate email campaigns offering them similar products.”
Cameraman (slightly amused, but serious):
“I have to admit… I still can’t believe I’m watching this. This office isn’t just digital – it’s practically… an ‘AI reality show’.”
How can the use of AI tools help preserve originality and expand the space for innovation?
Personalization and data access.
If your agency uses the same AI as your client, there could be a situation where the data, analyses, and strategies you use overlap with each other.
If both users are using the same tools, it can happen that the personalized strategies and communications from your campaigns “collide” on the same platform, which could affect the originality or recognition of messages by the end users.
Limited access to innovation.
If you and your client are using the same tool, the space for innovation may be reduced, as both teams might use similar approaches, methodologies, or strategies based on the same environment.
Additionally, using the same tool can lead to similar strategies, which may make it more difficult to differentiate your agency in the market.
NLP Models Shape Automated and Personalized Communication.
Artificial intelligence tools use language models such as NLP (Natural Language Processing) models for automatic language processing and communication with users. NLP models enable the system to understand, analyze, and generate human language in a way that is natural and relevant to user interactions.
How AI Uses NLP Models:
Understanding and Analyzing Language:
NLP models enable AI tools to understand the content of messages as well as the user’s intent. This means that AI can interpret different phrases and commands, regardless of how informal or complex they are, allowing for precise response targeting and automation of communication.
Generating Responses:
AI uses NLP technology to generate automated responses in interactions with users. Based on data from previous interactions and business rules, AI can formulate personalized and relevant responses that meet the specific needs of the user.
Natural Language Processing in Email Marketing:
In the context of email marketing and lead generation, AI uses NLP for segmentation and personalization of emails. Based on user data, NLP allows the creation of email campaigns that better match the needs of each user segment. For example, it can recognize key words and phrases in the text that users input and use them to create relevant offers.
Automation and Optimization of Communication:
NLP is also used for automating communication, helping AI optimize responses, learn from previous interactions, and improve the quality of communication with clients. This enables dynamic and adaptable responses, which are crucial for effective lead generation and customer support.
In many AI tools for business communication automation, it is possible to adjust the tone of the communication of the helper (AI assistant) according to the specific needs of the user. AI, used for automating various business processes, including email marketing and lead generation, allows customization of how communication is carried out with clients or end users.
How to Adjust the Tone of Communication:
Tone and Style Settings:
AI can have the ability to configure communication tones (e.g., formal, informal, friendly, professional). These settings can be implemented at the user interface level or through customizable templates for emails and messages.
Personalization through Scripts and Scenarios:
If you use predefined scenarios and communication flows, you can adjust responses based on the goal of the communication. For example, if the goal is for the bot to be advisory and friendly, the scenarios can use warmer and more relaxed sentences, while in a business context, the communication could be more formal.
Using Language Models for Styling Responses:
If AI uses language models (such as NLP models), you can set the tone based on specific commands or instructions provided to the platform. This allows synchronization of tones according to specific industries and client needs.
Personalization Based on Clients:
AI can enable the customization of responses based on client behavior or context. For example, if a client uses formal language, AI can automatically use a more formal tone. If the client behaves informally, the tone can become more relaxed and friendly.
Training on Specific Data:
Depending on the implementation, AI can be trained to recognize a specific communication style that fits your brand or industry. For example, if you work with FMCG companies, you can train the system to use a tone suitable for quick, efficient, and occasionally creative communications common in this industry.
It is possible to manage the tone of a chatbot conversation. Although chatbots usually respond based on predefined rules and algorithms, the tone can be adjusted in several ways, including:
Adjusting Parameters in Bot Development:
When developing a chatbot, the tone of responses can be defined through a set of rules and behavioral examples implemented into the model. For example, the bot can be programmed to be more formal, friendly, advisory, or even humorous, depending on the goal of the interaction.
Contextual Adjustments:
The bot can automatically adjust its tone depending on the context of the conversation. For instance, in a business setting, the bot may use a formal tone, while in conversations with users in more relaxed situations, the tone can be friendly and informal.
Interaction with Users:
By analyzing user responses, the bot can choose a tone that aligns with the user’s attitude and behavior. For example, if the user uses formal language, the bot may respond formally, while if the user uses informal language, the bot may switch to a less formal tone.
Training and Model Improvement:
Through the use of machine learning techniques, the chatbot model can be trained to recognize specific communication styles and adjust its response tone according to the desired style or brand.
Use of Predefined “Mood” Options:
Some chatbots allow for the adjustment of tone or communication style according to the user’s or organization’s preference, such as options for a friendly, professional, informative, or advisory tone.
How to Maintain Authenticity and Consumer Identification in Marketing Campaigns Using AI Tools
The use of AI tools can bring many benefits in terms of efficiency, personalization, and optimization of marketing campaigns, but there is a challenge in maintaining authenticity and consumer identification with the product or service.
AI tools, such as those utilizing NLP (Natural Language Processing) and advanced algorithms, can significantly enhance marketing strategies, provide personalized responses, and create automated campaigns targeted at specific user segments. However, the use of these tools by multiple organizations can lead to overlapping messages and strategies, which can reduce the originality and uniqueness of communication.
To maintain authenticity and a strong connection with the consumer, it is crucial how these tools are used. AI can be a tool that helps tailor messages and campaigns, but success depends on how data and analytics are used to create a genuine and relevant connection between the brand and the consumer. If AI is used in a way that considers the real needs, emotions, and identification of the user with the product, authenticity can be preserved while still leveraging the benefits of automation and personalization.
It is possible to remain authentic while using AI tools, but this requires careful and creative management of data, adjusting communication tones, and maintaining a connection with the real needs and stories of the consumers.