By Manish Sinha
Indian American economist Arvind
‘Free Trade, a concept so grand,
A force that moves goods from land to land.
No tariffs or barriers to impede,
A free market, a global economy to lead.’
The former vice-chairman of the government-backed think-tank NITI Aayog was amused. “Capabilities of the latest AI software (are) truly amazing,” said the senior academic and the Professor of Indian Political Economy at Columbia University on the social media platform, Twitter.
As we enter 2023, upcoming technologies like AI, Metaverse, and others will clock consumer behavior and preferences changes. To stay competitive and reach customers effectively, new ideas and approaches will define the effectiveness of marketing strategies. These will also place businesses in a better position to succeed in an ever-changing marketplace. Some of these ideas are likely to blow your mind.
Turning to AI for Creativity
Artificial intelligence (AI) and creativity may seem like opposing concepts, but they can work together in powerful ways. As we enter a new phase of machine learning, AI will play a crucial role in creating content, product designs, surveys, art, and others.
AI in content creation: Software like ChatGPT and Notion AI has shown that AI can create impactful content in seconds. Some of this AI-created content have even found appreciation from prominent economists, scientists, and senior academics.
AI-generated art: Algorithms can train on large datasets of existing artwork to generate new pieces of unique and original art. AI can also generate art by using generative models. These models, trained on a large dataset of artwork, are used to generate new art. For example, a generative model could be trained on a dataset of paintings by a particular artist and used to create new works following the styles of the artist. Another way that AI can generate art is by using neural style transfer. For instance, an AI algorithm can transfer the style of a painting by Vincent van Gogh onto a photograph (of a landscape).
AI models such as GANs (Generative Adversarial Networks) have achieved impressive results in generating photorealistic faces, scenes, and other forms of art. In this case, one AI generates random variations from seed images while another checks and rejects the results as per the desired parameters. Some examples of working models include Mid journey, Stable Diffusion, and DALL-E, a GPT3 art variant from the Open AI foundation.
AI in product design: AI has the potential to greatly enhance the efficiency and effectiveness of product design. Many companies are already using AI in their design processes. There are several ways in which AI can be used to aid in product design. These include –
Generative design: AI algorithms can be used to generate design options based on specified design criteria, such as aesthetics, functionality, and manufacturing constraints.
Material optimization: AI can be used to help designers choose the most appropriate materials for a product based on its intended use and other factors such as cost, weight, and environmental impact.
Simulation and analysis: AI can be used to simulate and analyze the performance of a product under various conditions, such as stress, wear, and temperature.
Personalization: AI can be used to create personalized product designs based on the preferences and needs of individual customers. It can be relevant for fashion and home decor, where customers may want products tailored to their specific tastes.
AI in surveys: AI can help analyze and interpret surveyed data in ways that are faster and more accurate than would be possible with manual analysis alone. AI in surveys uses natural language processing (NLP) algorithms. These algorithms analyze the responses to open-ended survey questions and identify key themes and patterns in the data. AI in surveys also involves the use of machine learning algorithms. These algorithms can run on large datasets of survey responses and predict how respondents will answer future questions. AI is also used to automate the survey process itself. For example, AI-powered chatbots conduct surveys with users (in real time).
Tuning into Metaverse for next-gen customer experience
A concept used to describe a shared virtual space that is created and maintained by computer algorithms, Metaverse has gained increasing attention with the advancement of virtual reality (VR) technology and faster Internet speed. The metaverse has the potential to revolutionize the way we interact with each other and with the digital world.
Creating Virtual Experiences 2.0: Creating a virtual experience 2.0 involves designing and building immersive, interactive digital environments that are accessed and experienced through technologies like virtual reality (VR) or augmented reality (AR) technology. These can be used for a wide range of purposes, including entertainment, education, training, and marketing.
Virtual and AI freelance teams driving creativity and innovation: Virtual and AI freelance teams are groups of individuals who work remotely and use technology such as virtual reality (VR) and artificial intelligence (AI) to collaborate and create new products and services. These teams are increasingly being used to drive creativity and innovation in a variety of industries. This offers several benefits over traditional in-person teams like flexibility, and the ability to scale up or down quickly, apart from facilitating collaboration and communication.
Understanding the customer mood, and mindset through granular Data analysis
This refers to the process of collecting and analyzing data at a very detailed and specific level. This can involve collecting data on individual transactions, interactions, or behaviors, rather than just aggregating data at a higher level. Tools such as data lakes, data warehouses, and big data analytics platforms help collect and store large amounts of granular data from customers to analyze it in real-time.
Implicit passive data is the key: Implicit passive data refers to data that is collected from an individual without their explicit knowledge or consent. This type of data is often collected through the use of sensors and tracking devices, such as those found in smartphones, wearable devices, and internet of things (IoT) devices. By collecting and analyzing data at a very detailed and specific level, organizations can better understand their customers, processes, and operations, and use that knowledge to drive innovation and improve performance.
Customers’ mood is the new data: It’s used to understand and improve the customer experience. This data can be collected through various means, including surveys, social media analysis, and facial recognition technology. Understanding the mood of customers can be particularly useful for businesses looking to improve the customer experience and increase customer satisfaction.
Social and professional personas: By analyzing data from social and official personas, organizations can gain a comprehensive understanding (of their customers) and use this information to inform their marketing strategies and improve their overall performance. This data can provide insights into customer preferences, behaviors, and attitudes. It can be targeted for marketing campaigns, tailored products, and services to meet customer needs.
Precision targeting by B2B Marketing
Precision targeting is a marketing strategy that involves identifying and targeting specific, well-defined market segments over attempting to appeal to a large audience. This strategy is increasingly used in B2B (business-to-business) marketing as it allows businesses to focus their efforts on the needs and characteristics of their audience.
Virtually customizing B2B solutions: This can be an effective approach in the current era of remote work and social distancing, as it allows businesses to continue to deliver solutions without having to be present in person. You can customize such solutions using online collaboration tools, offering online demos and product trials, using AR (augmented reality) and VR (virtual reality), and leveraging data and analytics.
Low-cost physical and digital solutions with 3D printing: As it eliminates the need for tooling and other costly setup costs, 3D printing enables businesses to produce low volumes of customized products at lower costs than traditional manufacturing methods. 3D printing can produce parts and products much faster than traditional manufacturing methods. It can produce various products, from simple plastic objects to complex metal parts. It can also be a more sustainable manufacturing method as it eliminates the need for many materials and processes used in traditional manufacturing.
As the marketing landscape evolves, it is critical to stay updated on the latest trends and technologies. By embracing new developments like artificial intelligence, personalization, interactive marketing, and much more, businesses can position themselves for success in 2023 and beyond.
The author is the chief marketing officer at sterlite technologies
Follow us on Twitter, Instagram, LinkedIn, Facebook