Abstract

Big Data is changing and revolutionizing marketing. CPG Big Data includes data sources like social media, point of sale, CRM, web IoT (Internet of Things), sensors, apps, store credit cards, etc. This paper explores key challenges Consumer Packaged Goods (CPG) marketers face, how Big Data can be leveraged to transform marketing, opportunities to scale with Big Data, and the approaches for leveraging it to yield higher revenue.

About the CPG Industry

CPG industry is the largest manufacturing employer, contributing $2T GDP in the U.S., representing 10% of the nation's GDP (Consumer Brands Association, 2017). Besides, it contributes $1.5T+ to exports, 7% of the national exports. It produces everyday use items which have constant demand and need to be frequently replenished like food, beverages, personal and household goods. It supports other industries like fishing, agriculture, forestry, transportation, warehousing, manufacturing, real estate, packaging, etc.

Marketing and Big Data

Big retail giants and now CPG leaders like Amazon and Walmart have capitalized on changing consumer behavior, tapped into emerging channels and customer-centric digital brands ("CPG, Big Data", 2020). Leading companies have leveraged Big Data insights to fine-tune their marketing approach. Big Data can be applied to answer — Which distribution channels should we pick? What should be the price across channels? How can routine pricing decisions be streamlined? Which discounts should we offer? Which promotional campaigns to run? Which relationships should be most nurtured? Which markets are untapped and promise potential profitability? Which markets should we exit? Which unmet needs in segments should we cater to? What should the seasonal messaging strategy be? Should we offer variations of products like organic, Kosher, non-GMO, gluten-free? How can we optimize marketing spend? What are the new behavior trends? Which cultural dimensions impact purchase decisions? Which categories of snack products are an impulse buy?

Key challenges facing CPG company marketers

Marketing practices are constantly evolving with changing customer behaviors. Technological advances are impacting how consumers research, shop, and make purchase decisions. With tighter budgets, increased need for ROI on spend, CPG marketers face a challenging set of dynamics in reaching, connecting with, and influencing consumers. Challenges include:

• Rapidly & sometimes radically changing consumer needs with a focus on value.
• Lack of seamless access to in-store retailers' data.
• The entrance of hard discounters and online pricing wars.
• Intensified pressure from retail consolidation.
• Harder to achieve breakout differentiation and brand positioning in a saturated market ("A tight race", 2016).
• Competition from low-priced, high-quality private-labels posing a risk of loss to generics. CPG industry grew 2% last year and private labels grew by 4% ("CPG, Big Data", 2020). In-store sales of private-label constitute 19% of sales (Wilson, 2020).
• A rise of the digital consumer, growing eCommerce, and shift to online shopping and blurring lines with the physical shopping experience.
• Availability of online reviews at fingertips influencing and sometimes overriding what the brand has to say about itself.
• Need for demographic and age-appropriate messaging to appeal to all consumer segments, requiring penetration and brand awareness in varied segments (Misra, 2016).
• Diminishing shelf space, fighting for in-store attention ("CPG, Big Data", 2020), and a larger share of shopper's mind, heart, and wallet ("Anticipated shift", 2007).
• Consumers demanding ethical & corporate responsibility (Wilson, 2020). E.g., biodegradable packaging, avoiding water wastage, reduced environmental impact, plant-based ingredients, healthier options, sustainable energy sources, etc.
• Retailers holding the reins of what to stock.
• Brand loyalty is weak with Millennials.

A case for Big Data for CPG companies

We live in a world where the consumer is king, a world where consumers have choices and choose where and with whom they want to do business. In this fast-changing world predicting consumer behavior is hard. With an ever-growing competitive landscape, it is a challenge to influence consumers with the brand alone. CPG companies have struggled with growth, growing 0.3% per year as compared to 3.8% which is the average for midsize companies and 10% for small-sized ones (Alldredge et al., 2016). The backdrop of political and economic pressures, value-conscious consumers, and the need to convince retailers to stock products, makes a compelling case for mining Big Data. In today's era, knowledge is not only power, it is profit too!

Leveraging Big Data to drive marketing

In marketing, it is important to know who your customers are, "where to play?" and "how to win?." Big Data provides the opportunity for CPG manufacturers to analyze vast data volumes data and extract meaningful insights. Positive impacts include enhanced ROI, speed of advertising, and boosting the shopping experience.

• Optimizing pricing

70% of the company revenue comes from standard products, the remaining 30% from the thousands of pricing decisions made throughout the year (Columbus, 2016). Pricing right is key to reducing brand switch. Big Data can be used to define daily shelf prices, propagate pricing through channels and streamline routine pricing decisions. Using sophisticated analytical tools for rules-based price-setting, simulating war-games, analyzing product assortment/mix impact can provide a leading edge (Alldredge et al., 2016).

• Driving product design, innovation, packaging, and reducing brand switch

Mining data can yield insights into changing consumer behaviors, guide product/package design, innovation, and messaging. Walmart found that household-level purchases between 2000–2013 showed declines in calories, sugar, fat, and sodium density (Tallie, 2015). These trends were consistent with other major retailers. Insights like these can aid in managing SKU portfolios and product development guided by required outcomes e.g., eliminate trans-fat, reduce sodium by 25%, reduce sugar by 10%, etc. Products like Gatorade G2, Coke Mini, and Charmin Ultra Strong have been results of innovation, extending the brand.

• Localized, granular insights into shopper attributes and a 360-degree view

Today companies need a 360-degree view of their customers and context. Aggregate patterns do not apply in local contexts. Analyzing consumer spending patterns, demographics, the occasion of purchase (fill-up or impulse) is key. Big Data helps gain granular insights at the national, regional, city, store, and channel levels for segments. It provides a holistic view of all touchpoints and guides strategies for distribution, pricing, product mix. These insights allow CPGs to quickly shift marketing efforts and respond to market trends (Keating, 2020). It is a win-win for retailers, benefitting from research.

• Building on "power-partnerships" with retailers

As once-average performers have upped their games, top performers are investing in securing exhaustive data from retailers in areas of the market basket, shopper panel data, loyalty cards, coupon redemption data. With the potential to expand into high-growth areas, data from the manufacturer website, multichannel grocers, pure-play online grocers, regional grocers, club stores, discount stores, dollar stores, and marketplaces can be mined. Manufacturers are partnering with retailers to stay in frequent contact. 75% of the retailers share data weekly and 25% real-time ("A tight race", 2016).

• Optimizing distribution strategies based on GeoAnalytics, weather & social sentiments

Big Data can help leverage weather and social sentiments to predict demand and for promotions. (Hays, 2004). In 2004, when Hurricane Frances was about to hit Florida's Atlantic coast, Walmart decided to leverage sales data from Hurricane Charley and stock up on pre-hurricane items like pop-tarts 7X more than normal inventory levels. CPGs can use demand-sensing analytics to forecast resurging sales, increase potential customer loyalty, and influence lifestyle.

• Tapping into cultural "hotspots"/contextual targeting with ethnic marketing strategies

By now all the corporations realize that their primary source of new growth will come from ethnic groups like Hispanics, African Americans, and Asian Americans. 40% of the Millennial market is also multi-cultural. These and other multicultural groups comprise 30% of the U.S. population. It is projected that by 2032, people of color will become a majority of the working class and by 2045 become a majority (Misra, 2016). Big Data analytics can help apply cultural dimensions to marketing strategies and develop culturally-nuanced advertising (Shavitt et al., 2020). It can help address — What impact does culture have on the purchase-decision journey? How are decision-making patterns different from mainstream customers? Are attitudes different?

• Gain better ROI from trade promotions for household penetration

CPGs invest 20% of their revenues in trade promotions, and 72% of the US companies lose money (Hwang et al., 2019). Conversely, top-class promotions yield 5X better returns than least effective. Most promotions provide short-term gains and not long-term growth, as they do not account for new shopping habits and shopping environments. Big Data analytics can help in designing targeted promotions for customer segments, offer geo-targeted ads and store-specific promotions.

• Guiding retailers on shopper marketing strategies

Shopper marketing involves enhancing the shopping experience to drive in-store and online sales by studying shopper behavior in shopping mode and focuses on making last-minute appeals at the very moment customers are considering buying by setting up sounds, lighting, layout, demos. CPGs can guide retailers by unearthing actionable insights (Keating, 2018).

• Delivering personalized outcomes via persuasive messaging

Customers are looking for value, however, the perception of value is changing with overall price, quality, and trust being driving factors. Customer perception of value could be better understood and shifts in behavior addressed by crafting clear, persuasive messaging to increase brand loyalty.

Key approaches for CPG marketers to strategize & leverage Big Data

The four key marketing strategies revolve around increasing customer acquisition, reducing customer churn, increasing revenue per customer, and improving existing products. To power, these strategies with Big Data organizations need to embrace a data-driven culture. A few guidelines (Grocery Manufacturers Association/McKinsey, 2016):

• Formulate customer-centric, long-term marketing plans while catering to short-term needs.
• Identify pockets of growth, align resources to specific investments in building channels and products. Align marketing efforts and cross-functional teams across the value stream.
• Garner executive support for sustaining data-driven culture, create a sense of urgency, and aid in data literacy. Continue to invest in building lean processes, data governance, and infrastructure to maintain Big Data environments and turn model outputs into business actions (Fitzgerald, 2015).
• Identify measures of success (ROI, net sales, funnel conversion rate, brand awareness, lifetime value), impact, and influence of spend. Publish dashboards to enable better decision-making.
• Engage in frequent top-to-top conversations with top retailers.
• Forge partnerships with customers and retailers linking channel management practices (Bellefonds, 2020).

Conclusion

Guesswork is no longer the norm in anticipating customer's expectations and behaviors. Big Data is the most powerful source to make informed decisions and offers immense opportunities to proactively strategize marketing efforts and drive overall business performance. It is imperative that CPG players leverage the power of Big Data in how they do business, or they risk downfall. Big Data enables CPG companies to not only sustain and survive but gain a competitive advantage. CPG companies can leverage Big Data insights to power marketing strategies, differentiate themselves, and stay profitable.

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