Going D2C: Data-Driven Transformations for the CPG Industry

The direct-to-consumer (D2C/DTC) approach marks a significant turning point for CPG businesses, owing to the consistent customer engagement—and the possibility of bringing in long-term shoppers—it makes possible. Before 2020, CPG players were also actively entering the DTC space, for instance, with a CPG giant buying out a personal grooming business for $1 billion.^[1]

However, the disruptions created by the pandemic have made it clear that the DTC dream can no longer remain so. Instead, what has become apparent is “a rapid transition, one in which the only rule is to digitize or get left behind”.^[2] Given the need to move away from purely brick-and-mortar setups, reduce dependence on third-party sales, and keep pace with the emerging consumer-centric model, DTC appears to be a natural step for CPG. However, there are several questions to be explored at this point.

The problems with going DTC:

Lack of data: As CPG companies typically do not have access to first-party data, and often face delays while obtaining data, data latency and incomplete data pose major challenges. With the lack of historical data, regulatory restraints, and the increasingly popular cookie-less online experience exacerbating this problem, what kind of data do CPG brands need, and how can it be effectively obtained and leveraged?

Unwieldy supply chains: With traditional CPG supply chain models geared towards wholesale and retail distribution, how can businesses be equipped to deal with customer-facing sales?

Channel conflicts: While DTC opens up the possibilities of new revenue streams, how can businesses manage potential conflicts with retailers while ensuring a consumer focus?

Ensuring customer satisfaction: With limited experience in catering to consumers, what value proposition can CPG brands offer to ensure enhanced customer engagement, and importantly, customer loyalty?

Leveraging data-driven approaches here can help CPG businesses navigate the uncertainties of the DTC market and build a sustained presence. Let’s take a look at a few key steps to this process:

Testing the market waters: Exploring the possibility of developing a DTC presence, chalking out the strategies required for differentiation, and identifying the products/services that will become the focus of the new model are important considerations for DTC hopefuls. Often, customers who opt for a DTC channel have unique requirements and expectations, including convenience, personalization, brand aspiration, and a seamless journey—and this needs to be effectively mapped.

Reorienting R&D and Supply Chains: Going DTC may require new product types tailored to markets, to achieve differentiation as well as capture niche segments that existing products do not tap into. Packaging, durability, temperature, transportation, handling, eco-friendliness, and appeal therefore become important variables to consider during R&D.

Moreover, supply chains become a major consideration here. From bulk sales to smaller quantities, from retail-focused distribution to more personalized delivery, and from established supply schedules to fluctuating, faster shipments for consumers—businesses will have a lot to contend with. As reorienting the supply chain is both resource and finance-intensive, several factors, including slow- and fast-moving SKUs, outsourcing, and in-house manufacturing and distribution, need to be considered.

Building new Touchpoints and Channels: While creating a digital store is a common approach for DTC brands, this must be complemented by omnichannel strategies to ensure a high level of flexibility and choice. In addition, the number of touchpoints available to consumers, and strategic partnerships with retailers and market entrants, should be carefully considered.

Personalization—The next wave: A renowned footwear manufacturer in the DTC space was able to completely reorient its entire business model to ensure customer-centricity. As “content, community and customization”^[3] have been touted as the ingredients to its roaring success, it is evident that personalization is another essential for CPG businesses looking to implement DTC approaches.

Here’s how you can mobilize data to optimize your DTC efforts:

Accelerate market research: Creating a DTC roadmap involves sourcing varied types of data including those from structured and unstructured sources, competitors’ sales data, social media, marketing, and governmental data. Following this, they can be streamlined into a central AI & ML-powered interface to obtain real-time feedback and actionable insights. The best paths to implementing DTC approaches can thus be quickly identified using AI.

For instance, market-specific characteristics, such as the ease of implementing DTC approaches in Asia as compared to Europe and U.S.,^[4] can be incorporated while developing AI-driven simulations to gauge services’ viability. Granular drivers, including demographics, market trends, predicted demand, and product characteristics, can be incorporated into simulations as well. This data can then inform an essential starting point: DTC positioning—whether product- or service-based, and premium offerings or cost-effective products/services.

Moreover, as developing pilots in limited geographies before scaling is an oft-adopted DTC strategy, data becomes crucial for businesses adopting a test-and-learn approach. For instance, conjoint analysis and social media listening can be used to understand customer feedback/sentiment, identify efficiencies and shortcomings, and map a tried-and-tested course of action.

In cases where a DTC presence has already been established, data can be instrumental in driving flexibility and continuous innovation, aiding decision-making on resource allocation, acquisitions, and developing in-house resources, among others.

Strengthen R&D and supply chains: AI can help not only design and test various product prototypes but also analyze product features, packaging, and consumer responses to determine potential reception in the market—this can go a long way in helping businesses optimize R&D for DTC.

Further, while there are numerous challenges surrounding supply chains, these can be effectively resolved using data. Digital twin technology can be utilized to examine the viability of various alterations to supply chains. Since such changes cannot be made overnight, and supply chain transformations can be disruptive and risky when not handled right, data can help indicate the path of least resistance, allowing for a seamless transition as well as supply chain agility.

Diversify channels and consumer touchpoints: Analytics can help identify optimal channels for customer traffic, sales, and distribution. For instance, it can drive a combination of online and physical sales through BOPIS, help turn brick-and-mortar stores into micro-warehouses, and identify the best partners for last-mile deliveries, shipping, and fulfilment, thus mitigating channel conflict.

Further, as the online customer experience is vastly different from the in-store one, a greater variety in products, detailed product information, and high-quality services are the core differentiators to making online DTC presences attractive. Here, AI-driven personalized diet plans, product recommendations, customization options, and tutorials can bolster the online experience, enabling better brand recognition, loyalty, and engagement across touchpoints such as websites and mobile apps.

Leverage personalization: As a starting point to developing tailored services, existing consumer data, including demographic information, app and location data, and transaction histories, though limited, can be leveraged for advertising and personalized recommendations.

Following data collated from multiple touchpoints, AI & ML can be employed to ensure end-to-end personalization, build customer profiles for targeted recommendations, and offer predictive insight into customer preferences and consumption patterns. Customer data platforms—centralized databases where data from different sources can be sourced, stored, and analyzed—can further improve conversion rates, tailor pricing, messaging, and loyalty initiatives, while ensuring regulatory compliance.

Data in action: The industry impact.

Here’s how a few CPG businesses have effectively leveraged data to bolster their DTC strategies and make an impact:

• A well-known seltzer brand used data to develop a comprehensive omnichannel strategy, increasing sales by 400% and 200% MoM in the U.K. and U.S., respectively.^[5]
• A cereal brand used personalization as a core DTC strategy, allowing customers to order their own customized cereals. With QR codes available on packaging, order mixes could be saved and repeated with a single scan on mobile devices, enabling ease of purchase.^[6]
• The world’s largest F&B company forayed into the DTC space with a Chocolatory, where customers could design chocolates and choose from multiple flavor combinations and customized packaging. A similar initiative in Japan saw great popularity and brought in more customers, with the resultant data allowing for R&D on even more innovative flavors.^[7]

From the increasing use of data in the move towards DTC, it is clear that the CPG industry is on the brink of change. Ranging from MNCs to smaller businesses, the value of direct interactions with customers has become clear for everyone to see. With an increasing number of businesses showing interest in this space, data is set to become a key advantage: enabling differentiation and innovation, contextualizing business applications for rapid decision-making, and paving the way for unprecedented customer engagement in the market. Using a data-driven DTC approach, CPG businesses can now gain greater visibility and relevance in the market, all while forging greater connections with their end consumers and unlocking new avenues of innovation and information.