Generative AI, a new catalyst for D2C expansion

No one will argue with the fact that the technology that has created the most intense ripple effect across industries in recent times is Generative AI. The progressive penetration of this technology into the workforce of organisations is posing a threat to the companies which are still evaluating its potential applications. Traditional Artificial Intelligence (AI) has been predominant in multiple areas of business transformation for quite some time. However, introduction of generative AI has added a new dimension to the transformation process across industries like CPG. CPG industry has long been a prime user of AI technologies like Machine learning & Predictive analytics to resolve the mystery of consumer behaviours. In last few years this industry has seen manifold increase in adoption of digital technologies due to emergence of D2C (Direct to Customer) business model. The aspirational journey of D2C could be further accelerated by the features of generative AI through proper applications. Potential of this technology could generate significant value in areas like Sales & Marketing, Customer operations and Product R&D. As McKinsey report highlights that ~75% of total annual value from generative AI use cases are accounted for in above areas along with Software engineering. Functions like supply chain & logistics, which are at the core of D2C business model, are also not far behind from reaping benefits of this technology.

Following benefits are lying ahead for the CPG & D2C players who aspire to become game changers in the industry.

Marketing & Sales:

• Content creation: Generative AI is undoubtedly a useful tool for potential savings in time and effort for content creation. Primary use could be preliminary idea generation. Even this tool could be used to create content out of collective ideas generated by different team members.
• Consumer preference: Ability of generative AI to read through texts, videos and photos to retrieve useful information and analyse those to generate insights within short period could help D2C firms create vast number of individual consumer profiles with higher accuracy. Based on individual preferences this tool could be used to draft engaging campaigns and advertisements to increase the probability of conversions.
• Market research: This is the area that is receiving increasing focus in D2C firm because of the rising competition. Generative AI could be deployed to understand overlapping areas of feedbacks received from consumer researches, social media views, academic research outcomes and responses from online campaigns.
• Customised offerings: Customisation is at the core of D2C business model wherein firms have already deployed traditional AI tools and analytics models. Generative AI could prove effective in this space by its ability to convert text-to-image for visualisation of offerings through interplay of colour, textures, ingredients, tastes etc.
• Synthetic customers: Unique value proposition of generative AI is mimicking human actions based on analysis of responses. D2C firms could utilise this facility to analyse customer feedbacks and generate ‘Synthetic Customer’ which is a digital replica of actual customer exhibiting purchasing preferences. This could help companies revisit their existing strategies of getting closure to any customer and improve the chances of lead generation.

Products & Services:

• Product Innovation: Product conceptualisation might become easier with generative AI through analysis of market research data, consumer preferences, competitors’ activities and consumers’ browsing history. Moreover, simulation of product formulations considering combinations of ingredients, their pricing and attributes could help create improved product variants with increased monetary savings.
• Packaging Design: An attractive and appealing packaging that provides relevant information within shorter viewing span is always preferable in CPG industry. Generative AI could add value to packaging design by processing & recognising consumer preferences and market needs from texts, photos, videos, research articles and social media views.
• Product portfolio & pricing: Generative AI could analyse the pricing of competitors products, sales data, market trends and consumer preferences to suggest optimised pricing. Sales trajectory, stock movement, consumer demands and market demands are useful information which could assist this tool identify low performing products that need replacement with a more effective solution.
• Customer service: Generative AI could improve the quality of interactions by engaging in more emotional dialogue through analysis of previous interactions. The tool could also be deployed for answering multiple customers at a time. Its ability to retrieve historical data about similar problems and suggest probable solutions could help human representatives in dealing with customers.

Supply chain & logistics:

• Inventory management: The advanced algorithms used in generative AI enable it to continuously learn through texts, images and videos and derive insightful patterns and trends out of consumer demands and market dynamics. Such a feature is crucial to recommend stock planning at factory outlet and warehouses within shorter time span as faster delivery has now become the driving force for the success of D2C business model.
• Demand forecasting: Accuracy of demand forecasting is a function of consumer buying behaviour which is the foundation for any D2C business. Firms that have higher accuracy in forecasting are set to win more than half the battle of customer acquisition. Generative AI with its advanced analytical engine could easily enhance the existing models with more accurate predictions made out of multiple factors.
• Route optimisation: By reviewing the probable routes from geographical map and analysing historical trends of traffic conditions along these routes, generative AI could recommend the fastest delivery route to consumers. Generative AI could also create convenience to customers by recommending customised schedule of delivery based on previous choices and take the firm one step closer towards a trusted relationship.

Although above benefits are going to make generative AI tempting in the long run, there is a note of caution while using this tool. Generative AI works primarily on the set of data fed into the model. Hence, relevance and authenticity of data is a concern for generating output from this technology. Moreover, there is always risk of plagiarism, copyright infringement, violation of property rights and erosion of brand value when contents are generated from publicly available information. Further, D2C firms must take note that rising adoption of generative AI will only provide a level playing field among competitors. It’s the vision and strategy of any firm to find the right avenue of application of this technology so that it could convert itself as a mere facilitator to a generator of business in the long run. ITC Infotech being an experienced digital solution provider in CPG industry is geared up to help D2C firms accelerate their business with right applications of generative AI.

For more information, contact ITC Infotech.

Author:

Debal Chakraborty,
Principal Consultant