The consumer goods industry has seen decades of glorious growth based on proven age-old strategies of providing innovative product solutions to the ever-growing array of consumer needs, rapid expansion in emerging markets, scaling up brands and operations to meet mass-appeal and leveraging this scale at every node of the value chain to generate profits. In recent times, the same companies have struggled to deliver sustainable growth with their scaled mass-branding approaches and increasingly diverse consumer profiles to cater to. While technology has played a crucial role in the growth of the consumer goods industry to-date, the future landscape promises disruptive changes with the explosive growth of e-commerce shoppers in markets like China and India and the inevitable adoption of the Internet of Things. With rapid growth of Internet penetration and digitization of consumer and shopper habits, FMCG players will need to adapt and innovate much faster to stay relevant and competitive.
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'Investing in Data Analytics is Crucial to Staying Competitive in Fmcg'
To stay competitive, companies are adopting new ways of analyzing data about their consumers and retailers through the growing array of applications of big data analytics across marketing, finance, sales & supply chain. Business discussions are fast moving away from diagnostic analysis (root-cause) to predictive and prescriptive analytics to drive business insights. These insights enable companies to be more relevant and react faster to changing consumer behaviors and needs. Without doubt, companies with the right predictive business insights have a competitive advantage – making it imperative to have the right data analytics systems and processes in place to succeed. The right consumer insights can be very powerful and the key to unlocking these insights is acquiring the right set of data as organically as possible. Companies need to equip themselves with relevant tools to collect complete, relevant data sets and provide quick and efficient analytics to drive business decision-making.
One of the most useful types of data is that which is acquired in-store as these can quickly provide insights on consumer behavior and their purchase journey to help drive sales growth. This data can be used to influence sales and channel strategies as well as joint-business plans with retailer partners. Below are just a few ways analyzing in-store data can provide a better understanding of consumers and translate into improved sales strategies:
in-store purchase path and areas that consumers spend most time in,
shelf related data to drive shopper-based shelf refresh,
which shelves or merchandising devices are more effective to drive awareness,
what kinds of products sell better at each store,
the variations of consumer in-store behavior with seasonality.
In addition, analyzing visitor volume (traffic) and purchase frequency over time at each distribution point can help stores optimize their staffing, inventory and promotion plans. Businesses can also choose to analyze out-of-store data like neighborhood demographics of each store, socio-economic background and life-stage related data to tailor their offering to their customer base. Analytics and insights using this kind of data can help businesses customize their marketing and sales plans, even pricing strategy, to provide a more relevant consumer experience as well as enable their partners to optimize their operations (suppliers, retailers etc.).
Implementing analytics is not always easy in the business world as companies struggle with prioritization of use-cases or hiring the right expert skill-sets to drive this transformation in their decision making processes. A common pitfall is getting stuck in endless iterations of analysis after gathering too much data. Identifying the right use-cases and prioritizing clear business problems to solve are the primary steps. Thereafter, gathering the right data and providing simple, quick analysis and insight through the right statistical models and visualization can enable quick business decision making and speed-to-market. The competitive edge that analytics can bring to the playing field is undeniable but it is crucial to build this capability with the right talent and the right tools.
Apps like ‘Collect’ aim to enable companies stay competitive using relevant data analytics capabilities by providing a platform for easy form creation and a customized approach to data collection. They are particularly useful in complex emerging markets where reach and distribution are challenges as the app can be used offline in remote areas where internet connectivity might be an issue and across many languages.
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Furthermore, the app can even generate relevant visuals to enable efficient data-based decision-making. Not so long ago the consumer goods industry was dominated by global giants and their megabrands. Recent industry trends show the rapid growth of local players across the globe, increased consumer focus on value and an explosive growth of the e-commerce channel – all contributing to an increasingly challenging environment for today’s consumer goods players to stay competitive. These trends have changed the way consumers interact with brands and challenge the effectiveness of age-old business models. With the tremendous growth of e-commerce giants like Amazon & Ali Baba Group in the last 5 years, FMCG companies of today need to rethink their channel strategies – right from designing the right product & packaging for selling in a virtual “store” to re-inventing how they price, promote and merchandize across channels. Despite the fast-paced change in landscape, there are high returns for companies that are willing to adapt and rise to the opportunities of tomorrow.
