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The Emergence of AI
We have come a long way in the last 50 years when just a few computers and less than a megabyte of storage were considered adequate for human needs. Today, we view technology as an accelerator and enabler in the pursuit of opportunity, and we openly appreciate its limitless possibilities.
In this journey, the web has advanced at a rapid pace. From the early 90s’ read-only web to the late 90s’ that introduced a read-and-write web, we have now entered the 3.0 era, where we can share and interact with rich media content such as audio, video, and images. Today, we are in the early days of Web 3.0, which is poised to evolve further and become more intelligent and adaptable to meet user needs, powered by Artificial Intelligence (AI)-computer systems that can replicate human cognitive functions.
Although humans are proficient in data analysis, machines demonstrate even greater capabilities. And while AI continues to break new ground, some of its applications are already inextricably linked to our everyday lives. From finding optimal routes on maps to matching drivers and commuters in ride-sharing apps, and from facial recognition to real-time gaming analytics, traditional AI has been around for years. At Castrol, we have harnessed the power of traditional AI by offering consumers real-time predictive analytics in gaming environments, contextual advertising based on interests, and advanced deterministic and probabilistic models. These models help identify the right audiences for serving ads and offers, ensuring both efficiency and effectiveness.
Gen AI - A Gamechanger
Then came generative AI, where machines create something new rather than just analysing existing data. This marks a historic milestone in artificial intelligence—one that Bill Gates has compared to the invention of the microprocessor, the personal computer, the Internet, and the smartphone. The possibilities for creation are endless, but early adoption centres around content creation and personalisation, which means that generative AI will deliver engaging experiences that were unimaginable just a few years ago.
For large brands, early use cases of generative AI include the creation of content – ranging from videos to text – with both speed and scale. Language models that incorporate brand essence and tone of voice that fits multi-market cultural contexts will help shape platform solutions, overcome marketing challenges, and facilitate adoption. Once the big idea is in place, the sheer volume of manual work involved in campaign creation will start to diminish rapidly, enabling the single-point creation of global campaigns that are both effective and most importantly efficient in terms of time and money.
The marketer of tomorrow will be able to focus on creative and strategic tasks, free from mundane, repetitive work—an incredibly powerful shift. Gen AI will also enable micro-personalisation at scale, splitting cohorts into micro-segments and customising creatives to drive engagement and eventually consumption.
A good way to understand the power of this technology is to start by experimenting, learning and then scaling. The effectiveness of generative AI hinges on the quality of data input into the models, hence focusing on this aspect becomes crucial.
At Castrol, we have been experimenting as well. In a recent campaign targeting enthusiast bikers, we leveraged Gen AI for creative development, resulting in a significant boost in engagement and brand scores. By implementing mass personalisation with interest-based customised ads, we observed notable increases in video viewership and brand recall. As we continue to use Gen AI for creating social posts, we anticipate reduced costs, accelerated content growth and improved quality.
A survey conducted by the MMA in India with 100 marketing executives found that over 50% of them were already testing or scaling creative optimisation and content production using AI in late 2023. This represents encouraging progress, and we will see the adoption rate rise rapidly from here.
AI’s influence extends well beyond content creation to significantly enhance customer engagement. Chatbots powered by AI are becoming ubiquitous in customer service, offering real-time support and personalised interactions. Companies can deploy AI-driven chatbots to provide instant responses to customer inquiries, troubleshoot issues, and offer product recommendations based on individual vehicle specifications. At Castrol, we have used interactive advertising with a built-in AI-enabled chatbot that addresses customer queries and facilitates service bookings. This innovation has led to a notable increase in redemptions compared to previous methods.
While these are exciting applications at play today, the future holds even greater promise. One of the applications for the automotive industry is training. Gen AI can support upskilling for sales, service and customer support staff at scale, across multiple languages and through digital mediums to reach large audiences instantly. This capability will make it easier to sell, service, and buy new technology and vehicle models in a rapidly growing market filled with traditional, hybrid, and electric vehicles.
Another promising area is predictive maintenance and automated communication with vehicle owners. By analysing data and leveraging an integrated ecosystem, AI can ensure vehicle uptime, enhance performance, and boost business productivity. Imagine a car that never breaks down, because of intelligent real-time monitoring and seamless communication between a manufacturer, a service workshop and a customer. Or consider reaching a consumer who is actively considering a new vehicle at just the right moment with the right offer coupled with active nurturing to close the sale.
Data Privacy and Ethical Considerations
As we embrace the potential of AI, it is crucial to navigate the ethical considerations and data privacy concerns that come with it. Web 3.0 emphasises a decentralised web where users have greater control over their data. For brands, this means ensuring that AI-driven marketing practices are both transparent and respectful of user privacy.
Building trust through ethical data practices not only complies with regulations but also strengthens the brand's reputation. Companies must prioritise data security and provide clear information about how customer data is used, thereby fostering a relationship of trust with its audience.
The Role of Blockchain and Decentralisation:
Web 3.0 also introduces blockchain technology and decentralised systems, which can enhance transparency and security in digital marketing. Blockchain can be used to verify the authenticity of digital ads, ensuring that marketing budgets are not squandered on fraudulent activities. For brands, integrating blockchain offers a new level of accountability and efficiency in digital advertising.
Decentralisation, a core principle of Web 3.0, encourages a shift away from centralised control by major platforms. This shift opens up new avenues for direct engagement with consumers, bypassing traditional intermediaries. Companies can explore decentralised platforms to build more authentic and direct relationships with their audience, thereby enhancing engagement and loyalty.
Looking Ahead - Embracing the Future
As brands chart their course through the Web 3.0 era, the integration of AI and other emerging technologies presents a myriad of opportunities. Embracing AI-driven personalisation, leveraging generative AI for content creation, and adhering to ethical data practices will be crucial in navigating this new landscape.
Web 3.0 promises a more interactive, personalised, and transparent digital experience. For forward-thinking brands like Castrol India, this is not just a technological shift but an opportunity to redefine marketing strategies, enhance customer relationships, and drive innovation. By strategically harnessing the power of AI and other Web 3.0 technologies, companies can position themselves at the forefront of modern marketing, ready to meet the evolving needs of their customers and lead the industry into its next chapter.
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