CIOInsider India Magazine

Personalized marketing has long become a thing, thanks to big data analytics. But what really is this big data, and how is it collected? While tracking online browsing patterns and navigations of users contribute, around 90 percent of the data is collected via smart phones. Most of the time, the smartphone user feeds the data without even knowing it. Let's put it this way: if someone responds when we call their name, they must listen to everything in their surroundings. The same logic can be applied to the voice assistants on your phone. It listens to everything you say during the course of the day. As a consumer, that's the price you have to pay to enjoy AI-powered personalized suggestions from your favorite brands online.

AI in Marketing Delivery

A few months ago, the clothing brand Levi's faced significant backlash for incorporating AI-generated models into its online marketing campaigns. The controversy stemmed from the company's partnership with Lalaland.ai, a firm specializing in creating AI-generated fashion models. Levi's aimed to "create a more inclusive, personal, and sustainable shopping experience" by showcasing diverse body types and skin tones. However, critics quickly labeled the company as "lazy," "problematic," and even "racist," arguing that Levi's could have employed real models from diverse backgrounds instead of artificial ones. This incident underscores the profound impact of social media in shaping public opinion over night.

It’s beyond any reasonable doubt that the influence of the online world and social media means that even a minor oversight can severely damage a brand's reputation. Marketing professionals can no longer rely on assumptions or gut feelings. Instead, they must turn to the most reliable source of information: customer data. This approach goes beyond simply doing the right thing or being politically correct; it ensures that advertisements resonate effectively with the target audience.

It is beyond any reasonable doubt that data provides valuable insights into the target audience, enabling organizations to forge stronger connections with potential customers. This results in higher conversion rates, greater customer loyalty, an influx of new customers, and increased customer satisfaction.

AI Beyond Marketing

However, marketing is not the only department in which AI has made its interventions. e-Commerce largely depends on the manufacturing industry - for everything from quality products to better pricing and enabling faster delivery (or faster manufacturing).

Infusing the shop floor with AI technologies, such as machine learning, computer vision & natural language processing (NLP), transforms production processes from multiple coordinates. AI can embrace bulk data from diverse sensors, equipment and production lines. Thanks to analyitcs, the collected data can produce information that will help optimize efficiency, improve quality and reduce downtime. Using this actionable information, organizations can automate anticipating potential issues, improvement suggestions and even process adaptation in real time.

In truth, when it comes to manufacturing, one of AI’s most impactful applications is predictive maintenance. AI systems embedded in sensors and machinery can forecast failures before they occur, reducing unexpected downtimes and maintenance costs. On the other hand, AI also enables advanced quality control when computer vision systems are integrated. It allows scanning products in real time to identify defects. Additionally, computer vision systems can also be integrated into the already installed CCTV infrastructure to collect information ranging from shop floor dynamics to employee behavior.

Dismantling Counterfeit Industry

The global counterfeit industry is more than a trillion-dollar menace. From electronic gadgets to fashion, the global online and offline markets are flooded with counterfeit products. Today, organizations are fighting counterfeit products with automated X-ray scanning systems. These systems store the details of the original products and compare them with the X-ray data of products fed into the system. This automated AI-powered system enables faster and more pragmatic counterfeit detection.

AI is Revolutionizing Warehouse Management

e-Commerce companies have been leveraging AI in warehouse management for quite a while now. However, the number of applications is increasing and encrusting more aspects. While it started with robots used for packing and picking, today, AI is involved in everything from automating ordering and reordering based on variables to order fulfillment, Logistics planning, and predictive analytics. This leads to reduced human errors, improvement in overall efficiency, and better worker safety. In addition, AI can also help ensure the integrity of transaction records throughout global supply chains.