Direct to Customer Archives - 91��

Generative AI, a New Catalyst for D2C Expansion

91�� — Mon, 12 Feb 2024 13:36:00 +0000

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. 91�� 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 91��.

Author:

Debal Chakraborty,
Principal Consultant

The post Generative AI, a New Catalyst for D2C Expansion appeared first on 91��.

Brands that Embrace Digital will Stay Ahead in the D2C Model

91�� — Wed, 21 Sep 2022 08:07:10 +0000

Sanaya woke up late on a Monday morning to discover that she had run out of her favourite skimmed milk. It was 8:30am and raining incessantly outside. She had to join an important meeting from 9:00 am. The presentation document was loading in the laptop. She quickly picked up the mobile and started typing the brand name on a retail ecommerce website. She found the product out of stock but came across other brands in that category. She went on to check the company’s D2C website but could not navigate through the multiple options toward the product ordering page. In a hurry, she returned to the retail website and found that it was already displaying all the options of alternative brands in the same category. She observed that the other brands don’t have the convenient packaging that she had been enjoying in her preferred brand. But that day she didn’t have time to decide. She quickly chose and paid for an alternative brand and reached for the laptop to look through the presentation, which she would discuss in the meeting.

It is a common situation that most shoppers face while buying packaged goods online. Due to high demand many daily used products go out of stock in retail sites. But it is more annoying to experience longer time in any shopping website due to lack of clarity about how to select and pay for a product. Direct-to-customer (D2C) is the new trend shaping the consumer-packaged goods (CPG) industry across the globe. Primary reason being low entry barrier, which is enabling private label brands to appear in the market with frequency higher than ever. However, not all brands could sustain the race of attracting consumers to their brands. It is more due to the marketing strategy they follow than the quality or features in the products. Drawing consumers to the products is the primary major challenge in this business model. Second major challenge is ensuring continuous availability of products, which means ensuring an uninterrupted supply chain process. If we introspect more into the primary challenge, we find three reasons underlying. First one is all about understanding the need of each & every customer and designing product as per their requirements. Second is keeping a tab of competitors’ offerings in the marketplace. Third is using information related to earlier two cases to develop personalised buying experience for every customer. The only solution that could help us resolve all these problems is data. Data is the ammunition in this expanding war of customer acquisition and retention. Collection of data about customers’ preferences and competitors’ new offers, storing those data and using those effectively are of primary importance in building a successful D2C business model.

If we go deeper into this, we find that next level of challenge is identification of data. It is customary for every marketer to understand and find the type of data one needs to understand customers’ requirements. Parallelly, one needs to find the data required on competitors’ offerings to strengthen the grip on the marketplace. Once understood, firms should think about the resources through which all these data can be collected and stored. And finally, how these data can be used to generate insights about customer’s behaviour.

To help firms in this journey, digital technology services are on the rise. The advent of intelligent automation has equipped the software service providers develop digital tools to understand the ongoing trend and find which areas need more focus to make the business run profitably. Robotic process automation (RPA), cloud technology, Artificial Intelligence (AI) based algorithms and machine learning (ML) programs are examples of digital tools which have paved the way for technology focused CPG firms to monitor their businesses closely and engage consumers more effectively. Every consumer has a different and unique way of shopping. Therefore, engaging with each consumer through the right channel, right promotion and right offer is undoubtedly a critical task. In top of that increasing penetration of mobile technology has brought all category of consumers at the same place and at the same time resulting in an extra level of complexity in data collection. Therefore, developing a robust data storage facility is no more a choice but a necessity for managing such increasing diversified consumer base. 91�� through its rich experience of working with multiple CPG consumers can provide both on-premises and cloud-based database solutions to manage terabytes of data on a continuous basis.

Once the data storage facility is set up, suitable data collection resources should be developed to ensure uninterrupted data feeding to the repository. Whenever a consumer engages in any purchasing activity through online channel, millions of data are transferred to the marketing firm. Multiplying this with number of available channels, nearly trillions of data are needed to be handled every day. Hence, the solution is to have resources having the capability to find relevant data in any format from any channel and incessant feeding of these data to the storage facility. 91��’s intelligent automation team can develop any customised intelligent bots using robotic process automation (RPA) for collecting data from any channel at any time with 100% efficiency. Not only from websites, but these bots can also even identify the necessary data from any document in any format. This can help the firms analyse multiple purchasing invoices to figure out average purchase value for any customer.

After collection the data, next important steps are identification of relevant KPIs and development of analytical models for the purpose of understanding the status of ongoing business and generation of insights about customer’s buying pattern. 91�� has a dedicated analytics team who has developed analytical models as per business need and has helped firms understand consumer journey at every touchpoint starting from exploration to procurement of any product.

After data management the next critical area where D2C firms should put highest focus is managing the supply chain of entire processes. If designing products as per consumer’s need is the primary challenge that D2C firms face now-a-days, then the next big challenge is taking these products to the consumer’s doorstep. The solution that addresses this concern is smart supply chain. Although most of the firms engage third parties for delivery of products, making the products available to delivery partner’s warehouses or distribution centres need a thorough monitoring of supply chain. 91��’s Industry 4.0 and Digital team together provide efficient and effective supply chain solutions with the help of Internet of Things (IoT), RPA and AIML. Not only our solutions ensure automated monitoring of entire supply chain process but also can eliminate the redundant processes, reduce the energy consumption at intermediate stages wherever possible and build models for optimising selection of packaging materials.

The problem that Sanaya faced at the beginning of this article could have easily been avoided had the brand manufacturer focussed on these issues and collected data about Sanaya’s buying pattern. Also, they should have ensured availability of the product at retailer’s site by adopting smart supply chain practices. Emerging digital technologies like robotics, artificial intelligence, cloud technology and IoT are a blessing for firms. However, leveraging these technologies to maximise the profit and capture the market share needs a blend of expertise & experience over the years. 91��’s rich experience of working with global CPG manufacturers in multiple channels and multiple regions for diversified products have helped develop suitable digital technology-based offers for D2C firms. In an industry like CPG where competition has been a paramount concern from new product perspective, emergence of D2C practice has made the situation more complex. To compete successfully and lead in the marketplace, firms must embrace the digital tools for navigating through the wave of unlimited new products.