Personalization 2.0: Leveraging Generative AI for Tailored Customer Experiences

By Shiva Singh, Director, Moglix

“Personalize or Perish.” One of the leading newspapers aptly summarizes the critical nature of personalization 2.0, or hyper-personalization for businesses.

We live in an era where customers expect businesses to understand their wants and needs. Today, companies must meet customers’ needs and anticipate and exceed them. And for this, they must pivot to a digital-first mindset to create stronger, more authentic customer interactions.

How do they do this? Through a hyper-personalized, AI-powered business strategy where products, ads, and interactions are tailor-made for each customer or a group of customers.

Having said that, manually creating customized ideas for each user is difficult and impractical due to complexity and scale. Enter generative AI—a technology that can produce hyper-personalized advertisements, content, and promotions tailored precisely to individual tastes in almost real time.

Generative AI: Unleashing New Possibilities
Generative AI is ubiquitous in today’s industries, encompassing prominent examples like ChatGPT and Dall-E, among numerous other tools. Supply Chain is no exception.

The global supply chain keeps changing, always trying to be more efficient, cut costs, and make customers happy. But it’s not easy, especially with customers wanting more, markets changing so fast, and everyone wants things to be more sustainable.
With generative AI, supply chain professionals can analyze tons of data, and make smarter decisions. For example, a major European industrial manufacturing company is leveraging generative AI in factory automation and product lifecycle management to streamline product development timelines and enhance efficiency.

Tailored Customer Experiences in the Supply Chain
The world of the supply chain is a goldmine for generative AI solutions delivering tailored user experiences through:
a. Demand forecasting: Accurate demand forecasting is crucial for effective supply chains, and generative AI models play a pivotal role in achieving this. These models combine historical sales data, market trends, and seasonal variations to optimize inventory levels, minimize costs, and decrease wastage.

Walmart employs AI and predictive analytics to manage its inventory efficiently. Using the technology, Walmart stocks items accurately, mitigating the need for costly last-minute corrections to address fluctuations in supply and demand.

b. Product development: AI analyzes market data, feedback, and competition to identify market gaps. Thus helping businesses create tailored products aligned with trends and customer satisfaction.

Sephora, a global beauty products retailer, employs AI-driven personalization to enhance customer shopping interactions. The company analyzes customers’ facial features through machine learning algorithms to suggest suitable makeup products. The technology has notably boosted customer satisfaction and trust, resulting in higher user purchase rates.

c. Price optimization: Generative AI models analyze customer demand, rival prices, and market status to formulate ideal pricing tactics to keep customers happy and competitive. Hopper’s travel app stays ahead by forecasting upcoming price trends and notifying travelers about the most affordable times to purchase flights for their chosen destinations.

d. Customer feedback: As AI-driven chatbots advance, they are gaining greater proficiency in handling customer queries and responding quickly to reduce customer churn. Generative AI tools can enhance customer support by leveraging statistics, customer profiles, and customizable attributes. These tools offer insights, personalized experiences, and a more profound comprehension of your customers.

e. Customer-Centric Logistics: Real-time routing poses a significant challenge for logistics operations. However, by leveraging generative AI, delivery or pickup routes can be continually optimized and updated based on factors such as traffic conditions, weather, and delivery priorities. This ultimately leads to enhanced efficiency, reduced fuel consumption, and improved customer satisfaction.
Personalization in Procurement Processes

Customizing the procurement process presents challenges, yet it’s vital for retaining corporate customers. By adapting experiences to individual preferences, lasting bonds are formed, cultivating loyalty and recurrent business. Methods to achieve this include:

a. Optimizing supplier selection through AI-driven insights: Generative AI enhances supplier selection through comprehensive analysis of supplier data and insight generation. AI algorithms assess supplier performance, capabilities, pricing, and risk, furnishing recommendations or rankings for well-informed decision-making.

b. Tailoring procurement strategies to match specific business needs: Generative AI models can generate customized procurement strategies for specific business needs by curating personalized negotiation approaches, risk mitigation techniques, and inventory management methods.

c. Tailored procurement platform: AI can offer personalized experiences in procurement. For example, a big retailer in the US created AI bots. These bots talk to suppliers and work out quick deals. The entire bidding process is streamlined and cost-effective now. Fun fact: It turns out that the suppliers like dealing with these bots more than talking to people from the company – more than 65% of them prefer it!

d. Demand-driven procurement: AI empowers demand-driven procurement through accurate personalized forecasting, enabling just-in-time practices. It offers real-time insights, dynamic reordering, supplier collaboration, and cost efficiency to enhance agility.

Future trends in AI in supply chain
AI will gain significant traction in the supply chain and manufacturing sectors. By 2025, more than 35% of executives anticipate AI becoming pivotal for their enterprises. The AI market for supply chains is projected to reach $10.1 billion, doubling between 2017 and 2025.

An IBM report on AI adoption offers these insights:
● AI is utilized to elevate customer experiences, aligning with the objective of 48% of surveyed respondents.
● 25% of companies are actively considering the integration of NLP (Natural Language Processing) solutions, specifically in the domains of supply chain and procurement.
● AI adoption focuses on enhancing supply chain transparency, fostering responsible sourcing practices and better labour conditions.
Navigating challenges and retaining the human touch

As the technology continues to evolve, supply chain and procurement leaders must embrace the new opportunities offered by generative AI. However, they must stay vigilant to the challenges posed by generative AI, such as privacy concerns, algorithmic bias, and operational efficiency.

Generative AI provides an irreplaceable tool for personalization that is key for keeping up with evolving market conditions. Companies that embrace and adopt this technology now will remain agile in the face of disruption to stay poised at the cutting edge of their industry. Customers present a challenge to businesses, but generative AI offers unique opportunities to satisfy their needs.

Now is the time for supply chain and procurement leaders to recognize generative AI as a valuable tool for personalization and enhanced customer experience.