Research Methodology – Market Definitions
India Non Whey Mass Gain Market Size: India Non Whey Mass Gain Market Size has been defined as the total revenue generated by the domestic sales and imports of non whey mass gaining products manufactured using non whey sources of proteins (soy, pea, potato, egg) such as non whey protein isolates and non whey blends with carbohydrates & with other nutritional supplements. The market does not include whey protein mass gain isolates, whey protein blends with carbohydrates & with other nutritional supplements’ blends and whey & non whey blends. Exports have not been considered in the market size. Additionally, the market includes product sales through various distribution channels including online and offline (MBO, EBO, supermarkets, Chemists, Pharmacies, Grocery Stores, Non Grocery Stores, Product Stall and Others) modes. The market has been evaluated at manufacturer’s price.
India Sports Nutrition Market Size: India Sports Nutrition Market Size has been defined as the revenue generated by the sales of nutritional products which improve physical endurance, increasing muscle growth/development/mass, or speeding recovery after exercise. Sports nutrition is targeted at athletes and gym-goers, and their principal purpose is to build muscle and to boost energy. Sports Nutrition tracks two types of products: Protein and Non-Protein. Sports protein include bars, powder and ready-to-drink (RTD) with equal or more of 20 grams of protein per serving (not per 100gr). Sports Non-Protein includes products that do not have protein as its core ingredient. They can be used to repair muscle or as energy/endurance booster. Note: Mainstream sports nutrition products such as sports drinks (e.g. Gatorade), energy drinks (e.g. Red Bull), or mass market energy/low protein bars (e.g. Clif Bar) are not included here. It also excludes high protein bars not specifically positioned for sports. Energy and sports drinks are tracked in the Soft Drinks system and energy/nutrition bars in the Packaged Foods system.
Total Addressable Market (TAM): The total addressable market has been defined as the total number of non-gym going population in the country (or region).
Research Methodology – Consolidated Research Approach
Hypothesis Creation: The research team has first framed a hypothesis about the market through analysis of existing industry factors obtained from magazines, journals, investor presentations, industry articles and annual reports of major companies in India and Abroad (Companies selling products in India).
Hypothesis Testing: The research team conducted computer assisted telephonic interview (CATI) with several industry professionals including decision makers in leading companies and other protein & health nutrition experts across sports nutrition industry. The industry professionals included several management executives, franchise marketing & support heads, business development managers, business development heads, key account managers, brand manager, regional managers of major non whey mass gain brands including Endura, Ayurwin Pharma, Accumass, Optimum Nutrition, Bright Lifecare, Medisys and others in the ecosystem. The analyst at Ken Research collated their insights on the market onboard and to seek justification to the hypothesis framed by the team. Additionally several nutritionists from different sectors have been interviewed to understand their perspectives, needs, pain points and the prices they are willing to pay.
Sanity Checking @ Decision Tree Analysis: Data has been collected and verified through cross-sanity checking the opinion and facts received from interview with the hypotheses framed from public databases. The team has verified the data by conducting both bottom-to-top and top-to-bottom analysis. General consensus on data collected from primary research and public and proprietary databases were formed by conducting in-house decision tree analysis of the data points available and by comparing it with overall sports nutrition industry. Secondary data sources include the analysis of existing industry factors, obtained from company reports and from magazines, journals and online articles. To cross verify the data derived from above mentioned approach, we performed CATI’s posing as mystery shoppers without disclosing actual identity. This approach has helped us to understand various company’s operational performance in unbiased manner.
Future Forecasting via Poll Opinions and Statistical Tools: Multi-Factor regression was conducted on the lag variables by identifying the independent and quantifiable variables directly affecting the market. However, due to high standard error and biasness being detected in the model we used moving average analysis as well as considered poll opinions of leading decision makers of the industry.
Interpretation and Proofreading: The final analysis was then interpreted in the research report by our expert team well versed with the Nutritional Supplement Market.
Research Methodology – Market Sizing and Limitation
Market Sizing:
- To estimate the market size for non whey mass gain products in India, our team has followed bottom to top approach. Our team has tapped specific product sales for major non whey mass gain product manufacturing companies (both domestic and international) through their financial statements reported to Company Registrar & thereby, performing various trade desk interviews to cross validate.
- The research team has then identified other financial and operating parameters for international and local companies from the management.
- To understand the classification of market by offline and online sales, we have conducted various CATI’s across all major manufacturers and importers of the industry to analyze their revenue split from online & offline sales channels. We then cross checked & cross verified the data so obtained by various other industry experts. This helped our team to assess the online sales for non whey mass gain products in India.
Limitation:
- Number of offline stores covered for all the non whey mass gain brands are considered from industry articles/annual reports/company website/through management interviews, which sometime might include the stores that have been closed or the ones which might not have opened yet.
- Some data points have been collated from Primaries opinion which may or may not match the actual number. The analysts at Ken Research have run a sanity check and the margin of error should not be more than 5-10%.
- Future Growth model has been built on the basis of future developments and opinions received from key industry veterans of the market followed by subjective analysis with margin of error not more than 5-10%.
- There could be a case that there would be a mismatch between product information obtained regarding product ingredients from product labels and that obtained through Industry experts. In this case, we have considered a product as non whey mass gainer primarily through identification of ingredients at the back of each product’s packaging.
- The online & offline sales split has been evaluated at the manufacturer’s level due to lack to information however, this should have ideally be calculated at retailers level.
Research Methodology – Variables (Dependent and Independent)
Variables Considered:
Sports Nutrition Market: An increase in sales of sports nutrition products including non whey mass gaining bars, powder and tablets & capsules and other products, would directly increase the demand and the market size of India non whey mass gain market.
Urban Population: An increase in the number of people living in urban cities would make a higher proportion of population being exposed to non whey mass gain company’s aggressive marketing strategies. Living in the developed regions would also make people adopt healthier lifestyle and join fitness centers, yoga, Pilates and other non-gym activities. Thus with increase in awareness and marketing exposure, demand for non whey mass gainers would proportionally increase.
Protein Consumption: Since major non whey mass gain products have proteins (non-whey) in their ingredients, an expansion in protein consumption would influence higher demand for non whey mass gain products constituting pea, potato, egg & soy protein. This would directly increase market sales.
Non Gym Going Population: Non gym going population is the largest target audience for non whey mass gain products. An increase in this variable would proportionally increase our market size.
Forecast Modelling:
Multi-Factor regression was conducted on the lag variables by identifying the independent and quantifiable variables directly affecting the market. The report applies this analysis to forecast the future of India Non whey mass gain market. However, the capabilities of SPSS and predictive analytics software have not been leveraged to determine the relevant indicators used for forecasting this industry due to high biasness & standard error of results. Moreover, the results underestimated the future market size when compared to the data collaborated through CATI’s and industrial analysis. Moreover aggressive company expansion plans, robust growth expected in number of offline stores, growth in non gym going & urban population and increase in sports nutrition market size are other extraneous variables which would have tremendous impact on the future market size.
In the present case, India non whey mass gain market revenue has been taken as the dependent variable and other variables such as sports nutrition market size, urban population, protein industry & non gym going population have been taken as independent variables.
Research Methodology – India Non Whey Mass Gain Market
A multiple regression model has been used through SPSS statistical tool that analyzes the multiple correlation coefficients, R, its square, and an adjusted version of this coefficient as summary measures of model fit. Further, R-Square is used to explain the validity of the independent variables. R Square, also known as the coefficient of determination, represents the proportion of total variation in the dependent variable explained by the variation in the independent factors.
Applying multiple regression analysis to a set of data leads to regression coefficients, one for each explanatory variable. These coefficients give an estimated change in the response variable associated with a unit change in the corresponding explanatory variable, conditional on the other explanatory variables remaining constant.
For more information on the research report, refer to below link:
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