Use of Data and Analytics to Drive E-commerce Growth in CPG Post-COVID

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Jayant Pandit is director of marketing at Sigmoid.

A turning point for CPG companies

The COVID-19 pandemic has compelled businesses to shift to virtual marketplaces and CPG has been no different. During the pandemic, CPG brands enjoyed rapid growth, with a more absolute increase in 2020 than in four years from 2016 to 2019. Consumers are increasingly preferring online portals over brick-and-mortar stores, and the trend shows no indications of slowing down. Consumer polls conducted by McKinsey showed that US customers intend to continue spending more money online even after the COVID-19 situation has stabilized.


Before the coronavirus pandemic, e-commerce accounted for approximately 4% of all grocery sales, a tiny portion of the overall volume. But during the pandemic, the share of grocery spend on online platforms has increased to as high as 20% according to Sigmoid analysis. The figure is expected to settle at about 10-12% by the end of 2022. A boost in digital sales of essential goods and personal care products, which were purchased more frequently online during the pandemic, has driven the growth in CPG spend. It is estimated that almost 35% of US shoppers new to e-commerce plan to continue making grocery purchases online after COVID-19.

Unlock the true value of e-commerce data

With the surge in online grocery shopping, copious amounts of user data is getting generated presenting online CPG businesses with unique opportunities. The utilization of e-commerce analytics will glean significant benefits and surely be a game-changer for CPG companies in a highly competitive market. However, they also need to plan and execute their data strategy carefully. The first step toward unearthing actionable data insights is to outline the data type to be considered. Datasets can be broadly categorized into product-based data and consumer behavior data. Product-based data includes tracking and logging product-specific trends and statistics. Some product-specific datasets are:

  • Individual product sales trends
  • Sales analysis of products within a category
  • Distribution
  • Price analytics

Customer behavior data points, on the other hand, would include tracking and logging purchase behavior, preferences, and trends of online shoppers. Customer-specific datasets are:

  • Frequency of making purchases
  • Cart abandonment to transaction completion analysis
  • Brand/Store loyalty
  • Consumer demographics

Once the required data has been made available, the next step is to glean insights out of the available data. Specific analysis needs to be done keeping the end goal in mind. The data obtained can be utilized in various ways, such as:

  • Personalized marketing: This involves understanding consumer behavior to determine preferences and generate recommendations. CPG companies should pivot their marketing strategies to create more personalized brand experiences for consumers.  Point of sale data, loyalty data, promotions performance, engagement data from its website, social and digital paid media data should be analyzed.
    • Personalized marketing can enable more than 10% growth in revenue from targeted campaigns by analyzing customer profiles.
    • Recommending products based on buying patterns can drive 25% growth in revenue for CPG companies.
  • Order fulfillment: The surge in online CPG retails is redefining the traditional order fulfillment process. With online retail, CPG players are now able to cater to a wider demographic as well as a larger geographic footprint while short-term trends such as bulk buying behavior are also compelling them to mold their business approach. In this new business paradigm, they need to build on capabilities to capture data from omnichannel sources and create data lakes to ingest and analyze data from disparate sources.
  • Product launches: Today CPG companies mostly depend upon retailers for consumer data generated from POS transactions and sales performance figures. In a new normal, the proliferation of online retail will generate significantly larger and substantially more diverse data streams which will provide the CPG companies with newer opportunities to leverage user data. This will help them redefine personalized recommendations with newer perspectives and offerings.
  • Category-specific decision making: CPG analytics output can objectively highlight strengths, weaknesses, inefficiencies, and opportunities within a particular product category giving granular visibility into each product type. Businesses that have successfully adopted data analytics-enabled decision-making have seen up to a 22% increase in demand for specific products.

How CPG firms can build e-commerce strategy

Data culture and automation: The most important step is to build on the culture of data, and embed predictive analytics and AI into day-to-day operations to swiftly address shifts in e-commerce demand, supply chain, and consumer preferences. Automating processes across functionalities for demand forecasting to reduce manual labor.

Digital infrastructure: Connected data platforms, IT, and infrastructure can enable full visibility of the customer’s path to purchase, and e-commerce dashboards can provide real-time insights into changes in demand. Prioritizing customer-centricity across critical touchpoints can improve conversion rates and drive revenue growth.

Partnerships and ecosystem: Forge strategic alliances to establish ecosystems that differentiate customer services. CPGs partnering with 3 PLs and digital natives is a vital element in the exploration of new revenue streams and operating models. Acquire or partner with digital specialists to contain costs by expediting and optimizing processes.


Customer demands and preferences are evolving as they adjust to the new normal post COVID-19. E-commerce sales are accelerating as CPG firms focus on business sustainability and customer engagement. CPG companies should expand their e-commerce capabilities to increase customer outreach. They must invest more in analytics to align their strategies and business models with the evolving consumer trends and requirements. To boost online sales CPG companies should improve conversion rates and revenue growth by prioritizing customer-centricity across critical touchpoints. Data and analytics can play a pivotal role in better understanding, analyzing, and approaching customers.

About the Author
Jayant Pandit is Director of Marketing at Sigmoidand is passionate about applying data and analytics to solve business problems. In his earlier roles with leading technology service providers, he has consulted many CPG and Retail companies globally to leverage information technology for business transformation.