More than 80 percent of the world’s consumers reside in emerging markets, and they account for nearly 65 percent of the world’s spending on fast-moving consumer goods (FMCG). What’s remarkable is that 60 percent of these consumers are located in rural or smaller towns. In addition, many of these markets have maintained their footing during the economic downturn.
In India, GDP growth has slowed from a high of more than 8-9 percent to the current rate of 5 percent as a result of the downturn. The country’s FMCG has also taken a hit, as growth has fallen to 10 percent this year from 18 percent in 2012. Growth isn’t slumping everywhere, however. In fact, the country’s rural areas are growing by leaps and bounds when compared against the metros.
India’s rural markets are massive, and the opportunity is unmistakable. Tapping into these areas, however, isn’t without its challenges. There are more than 600,000 villages, and granular data for many of them doesn’t exist, making the task of reaching the ones that offer the highest return more difficult. So the need of the day is market prioritization.
Not all brands, however, are benefitting from this huge opportunity. When Nielsen analysed more than 39,000 brands across the FMCG industry, we found that less than 10 percent were successful in the market. Upon closer examination, we found that one of the key factors behind the successful brands was a focus on the rural areas. And that focus led to 4x rural growth compared with metro growth.
So how do marketers make the most of these markets, create effective go-to-market strategies and effectively tap the bottom of the pyramid?
Enter Big Data and Data Fusion
The biggest challenge in front of marketers and researchers today is getting their heads around the dearth of data on these emerging market hotspots. The task lies in procuring data that sales teams can leverage and recognizing where marketers can set up distributor branches or deploy sub-distributor networks.
Big data is the new normal, and our research shows that strategies like data fusion can effectively identify these hotspots and help marketers effectively tap them.
The first step in coping with big data involves evaluating all available data sets. The second step involves bridging the gaps across the data sources. Enter data fusion, a stop-gap process that estimates and integrates data across various sources. For example, Nielsen conducted a shop census to assess the FMCG potential of across 7,000 villages across India. There are more than 600,000 villages in India, and we can use the results from our shop census and statistical techniques to estimate the FMCG potential for all of these markets.
Make Big Data a Big Answer
While rural regions of emerging markets are a low hanging fruit for the FMCG industry, marketers need to deal with the absence of data on these localities. To address this, marketers need to develop new ways to enhance their reach into these markets, such as data fusion, market prioritisation and technology integration.
The fact is that 65,000 villages (i.e., 10% of the total number of villages) are driving 60 percent of the total FMCG business in rural India. Market prioritisation can help marketers identify prospective buyers, bring down costs significantly and reduce uncertainty. This technique and tool can be applied across industries, markets and categories, making it an ideal way to effectively tap these hotspots in the global bazaar.
For additional insights on tapping India’s local hotspots, click here.