By Ash Patel
Today’s CPG retailers, manufacturers and marketers face a far more competitive landscape and complex path to purchase than that of just 10 years ago, as consumers enjoy a wider variety of products, along with new ways to learn about and purchase them.
Online and mobile marketing have introduced increased competition for consumer attention and loyalty, pushing decision-makers to continually seek out more effective avenues for reaching and activating shoppers.
To do so, marketers rely heavily on data, analytics and technology to gain deeper insights into shopper preferences and behavior. These insights arm them with the knowledge to create optimal products, packaging, pricing, promotions, displays and store layouts/planograms in ways that maximize revenue.
To stay relevant, the three elements that must be present in any CPG strategy are rich integrated data sets, prescriptive analytics, and robust technology that delivers insights via interactive visualization.
To truly optimize ROI and drive growth, another catalyst often overlooked is speed. What if retail decision-makers could get POS information from multiple retailers just three days after the shopping day ends, and in some cases, the next day? IRI research conducted in Europe last year revealed that faster time to information can result in promotional uplift of as much as 50 percent.
Traditionally, CPG data sets tracked basic information from annual sales data collected from the core channels, including point-of-sale terminals and panel data. Today, a truly integrated data set will include household-level purchase behavior; online, social and television exposure; consumer sentiment; frequent shopper data; unemployment rates; weather implications; and gas prices, to name just a few. Effective data accumulation must surpass the core channels to include client and expanded channels such as shipment and inventory records and census data, respectively.
As the Big Data movement shows no signs of slowing down, CPG retailers must deploy a solution that amasses data from core, client and expanded channels in real time. Faster delivery of insight has a dramatic impact on performance, including better promotional availability and planning. In the past, data would become available a minimum of seven days after the end of the shopping day. This time lag caused issues in regard to processes, such as inventory stocking, resulting in lackluster performance of promotional strategies. Manufacturer and retail decision-makers who receive the information later than a competitor, or too late, are incapable of preventing lost revenues. Thus, CPG decision-makers must implement a solution that can provide the immediacy of comprehensive data collection to leverage that information in a growth-driving strategy.
The integration of core, client and expanded data sets will make the information even more complex, which is why prescriptive analysis is crucial, as it distills actionable recommendations for retailers.
Prescriptive analytics transforms the decision-making process by identifying growth opportunities through statistical data mining, machine-learning algorithms and prioritized recommendations that are personalized to the individual decision-maker. Using algorithms and methodologies, prescriptive analytics provides the synthesis of Big Data to pinpoint specific insights that inform decision-making. The CPG retailer that can quickly gather, access and analyze these rich integrated data sets will be well positioned to act upon the actionable insights, thus increasing market share.
Data visualization is an effective method of increasing the speed at which raw data are transformed into insights. The technology required to visually display the insights derived from the data analysis is the factor most closely tied to true driver of ROI and growth, which is speed. A graphic representation of brand performance and consumer behaviors speeds up the decision-making process by which retailers evaluate and allocate the necessary resources to optimize ROI and drive growth.
Actionable Insights for CPG Retailers
As competition in the CPG landscape increases, CPG retailers must work to develop a comprehensive and thorough understanding of consumer behavior to drive growth and increase market share. Retailers must tailor the collection, analysis and display of their data to accommodate the need for immediate and insightful decision-making and concomitant consumer results. Data set accumulation methods must expand and diversify to encompass all consumer demographics and all facets of consumer behavior. As the data pool expands not only in size, but in specificity as well, data interpretation methodologies and algorithms must follow suit with prescriptive analytics.
The final catalyst for ROI optimization and growth is the ability to visually represent brand performance in a manner that best informs decision-makers. If these three elements — rich integrated data sets, prescriptive analytics, and insightful technology that allows for interactive visualization — can be delivered rapidly, CPG retailers will be well equipped to adjust pricing, promotions, displays and store layouts in ways that maximize consumer attention and loyalty.
Ash Patel is CIO for Chicago-based Information Resources Inc. For more information, visit www.iriworldwide.com.