Ideas That Generate Results
Russian Food and Non Food Retail Forecast (2007-2011)
The retail industry is the most developing one around the world and sensing this trend, RNCOS has come up with a latest report "Russian Food and Non Food Retail Forecast (2007-2011)” on the Russian retail industry. The report is an extensive research and rational analysis on the Russian Retail Industry and helps clients to analyze the opportunities and factors critical to its success. It underlines the key issues the industry is facing and provides a prudent analysis on its various aspects. The overview on opportunities and future forecast helps the clients to analyze the future course of direction and major growth areas of the industry.
Russia was ranked as the second most attractive retail market in Global Retail Development Index 2006. Russia saw an increased consumer spending and demand for consumer products that ultimately led to increased retail sales from 2001 to 2006 at a CAGR of 25%, which is a good sign for the retail companies. The central region that includes Moscow and St Petersburg had the dominant share (38%) of the retail market.
In 2006, retail food sales accounted for more than 46% of Russian retail sales. Though the percentage of food retail sales in total retail sales have decreased in the past six years, there is a visible sign of growth in the retail food sector as it has increased with a CAGR value of over 24% during 2001 to 2006 and reached the value US$ 144.62 Billion. Revenue from retail sales of non-food items reached US$ 172.57 Billion in 2006.
The steady growth in personal incomes and ongoing real Ruble appreciation is believed to swell the retail market to expected US$ 769.40 Billion by 2011. But the Russian food retail industry is predicted to decelerate from its current CAGR to 13.72% in 2011. Non-food retail sector is predicted to increase with CAGR value of 19% spanning from 2007 to 2011.
Altogether, the retail growth in the coming years is expected to be stronger than GDP growth. But some factors may disturb the growth trend, including inefficient distribution network, and poor infrastructure, resulting in high logistics costs (as a proportion of GDP), and inventories. It’s a lot easier to cut manufacturing costs than it is to cut distribution costs. But this also is an opportunity for existing retailers to keep a check on their competitors.
Also, the government has relatively less regulations for consumer-based economy, and Russia’s political stability and low maturity makes Russia all the more attractive for players.
- The strong growth areas in consumer purchasing in terms of CAGR value include cosmetics and toiletries, household cleaning products, furniture, computers and washing machines while in terms of market value, the clothing segment will dominate non-food retail sales during the forecasted period.
- Organic food, baby food, diet food, and packed and processed food are the fast growing areas in the food sector.
- Food expenditure in Russia is being replaced by increased expenditure on household facilities, recreation, education and cultural services.
- Cities with the population of more than one million will be the next big retail markets for the retailers.
- Discount and convenience stores are the fastest growing retail formats in Russia.
Key Issues and Facts Analyzed
- What is the market size and scope of the Organized Retailing in Russia?
- What are the factors driving growth in this sector?
- What is the size of organized market segment-wise and what are their growth prospects?
- What and where are the growth prospects and challenges in the industry?
- What are the emerging trends in the market?
- Who are the major players of the industry, and what are their strategies and market
Research Methodology Used
Information has been sourced from books, newspapers, trade journals, and white papers, industry portals, government agencies, trade associations, monitoring industry news and developments, and through access to more than 3000 paid databases.
The analysis methods include ratio analysis, historical trend analysis, linear regression analysis using software tools, judgmental forecasting and cause and effect analysis.