The product lifecycle: 3 ways brands are using the power of big data and analytics

Consumer Products Writer

In the CPG industry, change is the new norm. Traditionally predictable markets such as the U.S. are becoming fragmented as consumers rely on multiple channels to discover new products, compare prices and complete purchases. According to a report by PricewaterhouseCoopers (PwC) and Strategy&, market share growth is shifting from large manufacturers to smaller firms. To succeed in this environment, CPG leaders will need to return to the basics: supporting innovation and increasing product life cycle efficiency. Brands are using big data and analytics to bridge product lifecycle gaps between market research, new product innovation and maintenance steps.

1. Navigating the data avalanche

Thanks to digital channels, CPG brands have access to a wealth of unstructured data including product browsing activity, location information and social media engagement, Adweek notes. According to a 2014 survey from Honeywell reported in SupplyChainBrain, however, these insights are leaving companies frustrated. Sixty percent of respondents reported feeling overwhelmed by the amount of available information, while 63 percent reported that growing business complexities are "impacting their ability to meet consumer and retailer demands."

Through this confusion, CPG leaders are recognizing the importance of connecting their online and offline data sources. For example, product content solution provider Gladson has prioritized the consolidation of digital and storefront product information into one database to help simplify consumers' decision cycles. The end result is a consolidated experience.

2. Getting closer to customers

CPG leaders can use big data and analytics to plan their product development and innovation strategies. As PwC and Strategy& point out, today's consumers demand products tailored to their exact needs. This trend creates pressure on CPG leaders to tailor features to specific consumer segments. Big data and analytics can help by creating a direct channel for brands to observe consumer research patterns, monitor audience sentiment and request buyer feedback. Lay's, for example, recently launched its "Do Us A Flavor" program, which invited consumers to submit and vote upon ideas for new Lay's potato chips products. Through this crowdsourcing process, the brand chose the next iteration of products to develop.

With increased market fragmentation, developing new products can feel like a guessing game. CPG leaders can counteract this challenge by incorporating buyer feedback into the research, planning and development process. Data collection and analysis can streamline product lifecycle costs by eliminating the guesswork from innovation.

3. Meeting retailers' needs

The rising diversity of sales channels is spawning new information management challenges, creating the potential for more expensive and less efficient product lifecycles. According to SupplyChainBrain, CPG leaders need improved data and analytics strategies to operate a transparent supply chain that considers customer-specific product details, including preferred ingredients, expiration dates, dimensions, weight, warnings, use cases, health details, nutrition facts and manufacturing processes. With 20 to 25 percent of CPG items being replaced or changed in a year, organizations need to house their product details in one central database, create a mechanism to scale production up and down and ensure that information is tailorable to specific retailers' needs. This flexibility, scalability and centralization will introduce new efficiencies to every product lifecycle.

Information overload, a need for innovation and market fragmentation introduce new maintenance costs to CPG leaders. With big data and analytics, organizations can seek points of optimization. By consolidating data sources, elicit product ideas from customers and meeting retailers' needs, companies are better positioned to reduce costs at every product lifecycle stage.

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