Snapshot juxt indian women 2010 study


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Demographic, Psychographic & Consumption Lifestyle profiling of Women Consumers in India

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Snapshot juxt indian women 2010 study

  1. 1. Indian Women 2010 Demographic, Psychographic & Consumption Lifestyle profiling of Women Consumers in India
  2. 2. <ul><li>Most recent and representative survey-based estimates of women consumers in India by their ‘occupational–marital’ status segmentation </li></ul><ul><li>Estimates based on a very large land survey conducted in Apr–May 2010 surveying over 259,000 individuals living in 37,000 households in 101 cities and 20,000 households in 1,000+ villages </li></ul><ul><li>A highly ‘comprehensive’ profiling of Indian women consumers - in their demographics, psychographics and consumption lifestyles </li></ul><ul><li>A deeper profiling of various type of women occupational and marital status segments in India and how they differ in their consumption lifestyle and preferences – includes details about their location and language preferences, socio-economic status, household and financial assets ownerships, monthly and annual household expenditure on main spend heads, personal and household level consumption of some lifestyle products along with brand preferences, psychographic profile, regular lifestyle habits and preferences, holiday and entertainment preferences, shopping orientation & preferences, media usage, ……. </li></ul><ul><li>Demographic and socio-economic profiling is based on ‘ all women individuals ’ living in the surveyed households. Psychographic and consumption lifestyle profiling is based on information of ‘ women respondents ’ who answered on behalf of their households </li></ul>Study Overview
  3. 3. Study Methodology <ul><li>A large-scale land survey was conducted to estimate and profile Indian families and their individual and household consumption behavior. The survey covered ‘towns’ and ‘villages’ of all population strata in all the mainland states and union territories in India (covering all the key, and 69 of the total 77 regions in India as classified by NSSO) </li></ul><ul><li>Though the selection of towns and villages was ‘purposive’, the sampling within the towns was done on ‘2-stage random’ basis (firstly a random selection of polling booths, and then a random selection of households from the electoral list within each of these randomly selected polling booths); within villages sampling was done on ‘systematic random’ basis (selection of every n th house in the village) </li></ul><ul><li>To make the survey findings representative of the entire Indian population (and not just of the surveyed households and individuals) appropriate state-wise, urban district/village class and SEC combination level household ‘representation weights’, as derived from the authentic ‘Govt. of India’ base-level population statistics (NSSO/Census), were applied to the survey data </li></ul>
  4. 4. Segmentation of Women Consumers (by a combination of their ‘occupational’ and ‘marital’ status) Urban Sample Rural Sample Women Students Unmarried and studying 20,709 11,929 Working Maidens Unmarried and working 1,242 522 Housewives Married and not working 5,810 2,767 Housewife Moms Married with children and not working 34,456 18,580 Working Wives Married and working 534 275 Working Moms Married with children and working 3,151 1,955
  5. 5. Topline Findings
  6. 6. <ul><li>There are only 40 million ‘working women’ in India (9% of all women) . Of the rest,148 million are ‘students’ and 260 million are ‘housewives’ </li></ul><ul><li>‘ Housewife moms’ is the largest occupational-marital segment among women (50%) – with an average age of 37 years </li></ul><ul><li>2 out of 3 working women are also ‘working moms’ </li></ul><ul><li>Half of all the gainfully employed women in India are ‘unskilled’ workers. Only 1 in 10 works in the ‘corporate world’ </li></ul><ul><li>‘ Southern’ region contributes the highest proportion of working women. Marathi and Tamil reading women form a noticeable proportion of working women </li></ul>A World of Housewives & Moms
  7. 7. <ul><li>Housewives/Housewife moms show better SEC profiles (belonging to SEC ‘A’, ‘B’ and ‘C’) than working wives/working moms </li></ul><ul><li>They have higher avg. ‘monthly incomes’ in the family (and better household asset ownership levels) than the households with working wives/working moms </li></ul><ul><li>2 out of 3 ‘urban’ working wives/moms live in the smallest ‘tier 4’ towns. A relatively higher proportion of housewives/housewife moms live in bigger cities </li></ul><ul><li>Housewife moms highlight ‘playing with children’ as their ‘favorite pastime at home’ noticeably more than the working moms </li></ul>The housewives are “better-off”!
  8. 8. <ul><li>After ‘money’ different women segments show distinct ‘second priority’ in their lives (‘self-education’ for women students, ‘status/fame’ for working maidens, ‘children’s education’ for housewife/working moms, ‘family’ for housewives and ‘health’ for working women) </li></ul><ul><li>Women without children prefer to ‘hang out with friends’ more, while women with children prefer to visit relatives/neighbors relatively more </li></ul><ul><li>‘ Working wives/moms’ see themselves as least physically fit. These segments also show the highest relative incidence of lifestyle diseases </li></ul><ul><li>‘ Working wives’ have the lowest self-perceptions of their ‘attractiveness’, and they claim to use ‘personal care/cosmetic products’ the least. They also consume ‘processed food’ the least </li></ul>Different drives, different lifestyles
  9. 9. <ul><li>Working wives are relatively the most ‘price’ conscious, working maidens and women students the most ‘brand image’ and ‘trend’ conscious </li></ul><ul><li>‘ Cookery’ is the biggest hobby among housewife moms and working wives, ‘cinema/films’ is the biggest hobby among the other women segments </li></ul><ul><li>Though ‘soap’ TV channels are most popular among all women segments, they are relatively less popular among working wives. ‘Music channels’ are relatively more popular among women students/working maidens. ‘Radio’ is most popular among the housewives </li></ul><ul><li>While Sonia Gandhi is the most admired ‘living celebrity’ among all the women segments, ‘women maidens’ look up to younger men more (Sachin, Dhoni, Rahul Gandhi) </li></ul>Different lifestyles, different likes
  10. 10. <ul><li>‘ Working maidens’ have the highest avg. monthly family income (Rs. 8,555) , and live relatively more in the metros (but they form only 2% of all women) </li></ul><ul><li>They are the most educated lot, tend to work in the corporate world relatively more, and have the highest penetration of internet at 5% </li></ul><ul><li>They also show the highest relative penetration levels of the ‘mainline’ household assets, and a noticeably higher ownership of scooters (10%) </li></ul><ul><li>They appear to be the most ‘outward-directed’ in their personality (working wives the most ‘inner-directed’) , most ‘brand image’ and ‘trend’ conscious, and claim to be the most frequent shoppers </li></ul>The ‘niche’ Women Maidens!
  11. 11. Report Details
  12. 12. <ul><li>The findings of the ‘Indian Women 2010’ study are available as query-based online datasets with data presented as tables/graphs/charts </li></ul><ul><li>They can be bought as an ‘ independent supplementary dataset ’ or as part of the larger ‘ individual consumers master dataset ’ </li></ul><ul><li>‘ Indian Women 2010’ is one of the ‘consumer segmentation’ study from Juxt and is part and parcel of its larger mega offline syndication offering called ‘India Consumer Landscape’. India Consumer Landscape incorporates many such consumer segmentation studies which are called supplementary studies or datasets </li></ul><ul><li>Each of the supplementary study or dataset presents findings at a specific ‘consumer segmentation’ level or a specific ‘product category’ level (see next slide for a detailed view of all master and supplementary datasets on offer under the umbrella of ‘India Consumer landscape’) </li></ul>Reporting Note: Reporting of any supplement dataset is subject to collection of sufficient sample responses in the survey
  13. 13. Indian Shoppers Shopping Orientation & preferences Juxt India Consumer Landscape Syndicated Study Datasets Product Category Datasets India Mobile Mobil Service & Handsets India Bytes Personal Computers India Drives Automobiles India Banks Personal Banking India Insured Life, Gen Insurance India Plugged Home Durables India Drinks Alcoholic Drinks India Smokes Cigarettes India Grooming Personal Care India Pack Foodies Processed Food Individual Consumer Master Dataset Master Datasets All Household Profile Data Household Master Dataset All Individual Profile Data Language, Community, Caste, Religion India Societal Landscape Lifestyle Diseases & Medication Preferences India Health Check India Hooked Indian Urbanites Urban SECs Indian Ruralites Rural SECs Indian Families Family composition & lifecycle stage Indian Generations Generational Age groups India Spending Powers Ability to Spend India Consumer Lifestyles Ability to Spend + Inclination to Spend India Affluents The Uppies & The Rich Indian HOH Chief Wage Earners of the Households Indian Women Women Consumers India Investing The Financial Investors Dominant & Integrated Media Usage (TV, Print, Radio, Internet) Holidays & Travel India Holidays Consumer Segment Datasets
  14. 14. Pricing* * 10.3% service tax extra * Key Findings PowerPoint Report for any dataset (only on order) – Rs. 50,000 per dataset Single Supplementary Datasets Combo Datasets Note: Reporting of any segment level dataset is subject to collection of sufficient sample responses at that segment level in the survey +  Rs. 700,000 Individual Consumer Master Dataset Rs. 600,000 (All available data on women consumers individually) (All available data on individual consumers) (At all geographic levels – all India, urban, rural, state-wise, town class-wise, village class-wise, urban district-wise for top 25 urban districts) ‘ Indian Women’ Segmentation Dataset Rs. 60,000 per Women Segment (all relevant individual level data but only for one ‘women segment’) ‘ Indian Women’ Segmentation Dataset 3 Women Segments - Rs. 150,000 (all relevant individual level data but only for 3 ‘women segments’) ‘ Indian Women’ Segmentation Dataset All 6 Women Segments Rs. 200,000
  15. 15. <ul><li>Payment Terms : 50% advance, 50% after delivery of all datasets/reports </li></ul><ul><li>Delivery Timeline : ‘Indian Women’ Segmentation Datasets </li></ul><ul><li> 3 days from date of order after 15 th September 2010 </li></ul><ul><ul><ul><ul><ul><li>: Individual Consumers Master Dataset </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li> Anytime on order after 15 th September 2010 </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>: PowerPoint Report </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li> 1 week per dataset report each from date of order after 30 th August 2010 </li></ul></ul></ul></ul></ul><ul><li>Reporting Format : Query access based o nline dataset </li></ul>Payment Terms & Delivery
  16. 16. <ul><li>Size estimates of ‘Occupational-Marital Status’ Women Segments </li></ul><ul><li>(All India, Urban/Rural, Zone-wise, State-wise, City-type wise, Village-type wise, For top 25 urban districts ) </li></ul><ul><li>Size estimates of total women in India, Size estimates of each of the 6 ‘occupational-marital status’ women segments (Women Students, Working Maidens, Housewives, Housewife Moms, Working Women, Working Moms), Their proportion in the total women population </li></ul><ul><li>Geographics </li></ul><ul><li>Region, State, Urban/Rural area, City Type/Village Type, Top 25 individual urban districts </li></ul><ul><li>Personal Profile (only demographic profile based on all women members of the household, other profile details based on profile of only the women respondent answering for the household) </li></ul><ul><li>Personal Demographics: Gender, Age, Marital Status, Generational classification by age, Status in the household (CWE or other earning member or dependent member of the household), Occupation, Education, Medium of Education, Preferred language of reading </li></ul><ul><li>Personal Psychographics: Self perception of own physique (physical fitness and looks), Most important priorities in life currently, Current hobbies and interests, Living celebrity currently identify with the most, Favorite indoor entertainment activities, Favorite outdoor entertainment activities, Parameter that defines ‘status in the society’ for them </li></ul><ul><li>Buying Orientation: Price-quality orientation, Attributes give weight-age to when buying, Factors give weight-age to when deciding place of buying, whether responded to a marketing/advertising stimulus in the past </li></ul>Indian Women 2010 (Information Coverage)
  17. 17. <ul><li>Personal Consumption Lifestyle Orientation </li></ul><ul><li>Consumption Lifestyle Classification </li></ul><ul><li>Level of socialization/social influence (how inclined to interact with others in spending spare time at home, outside, in party/get-together, in deciding to buy products/services) </li></ul><ul><li>Level of consumption Impulse (how inclined to keep abreast with lifestyle trends, buy what’s latest & trendy, frequency of replacing things at home, frequency of shopping, enthusiasm towards shopping, whether to consume or save if income increases, whether to consume or save if income declines) </li></ul><ul><li>Personal Consumption Lifestyle </li></ul><ul><li>Vehicle : type of vehicle driven (car, scooter, motorcycle) along with the brand used </li></ul><ul><li>Mobile Phone : whether a mobile user, no. of connections, no. of handsets used, handset price, type of connection plan, service subscribed to on the most used connection, features present on the most used handset, whether listens to music on a mobile device </li></ul><ul><li>Computer : whether a computer user, place from where accessing computer, type of computer if used at home </li></ul><ul><li>Internet : whether an internet user, place from where accessing internet, whether uses internet on mobile phone </li></ul><ul><li>Alcohol : whether drink alcohol, with what frequency, type of alcohol consumed, brand consumed </li></ul><ul><li>Insurance : whether has a life insurance policy and how many </li></ul><ul><li>Banking :  whether has a saving account, how many accounts and with which type of institution (bank/coop bank/post office), whether owns a credit card, no. of credit cards owned, card types, card brands, card issuing banks </li></ul><ul><li>Personal Care Products : whether uses and brand used (Face cream, Deodorant, Body lotion/Moisturizer, Lipstick, Hair color, Face wash, Fairness cream, Shampoo, Conditioner, Hand wash, Hair oil, Hair cream/gel, Toilet Paper) </li></ul>Indian Women 2010 (Information Coverage)
  18. 18. <ul><li>Processed Food Products : whether uses and brand used (Packaged vegetables, Noodles, Ketchup/Sauce, Cold drinks, Bottled/Mineral water, Packaged Fruit Juice, Chocolates, Packaged snacks like chips & namkeen, Cornflakes/Processed cereals, Chyawanprash, Cheese, Milk additive/ supplement, Eating Fast Food, Home delivery of food) </li></ul><ul><li>Lifestyle Products : whether uses and brand used (Jeans, Sports shoe, Readymade shirt & trouser, Watch, Air Travel, 3 star+ hotel stay) </li></ul><ul><li>Some Products in rural households only (Packaged Biscuits, Refined Oil, Butter, Jam, Packaged Pickles, Battery/Cell, Travel by train, Stays in a hotel, Battery/Cell, Travel by train, Stays in a hotel) </li></ul><ul><li>Holidaying - whether holiday in India, frequency of taking such holidays, favorite destinations, Whether holidays abroad, frequency of taking such holidays, favorite destinations </li></ul><ul><li>Personal Health Profile </li></ul><ul><li>Whether suffers from any serious lifestyle disease and which one (Low Blood Pressure, High Blood Pressure, Diabetes, Thyroid Problem, Arthritis, Chronic Bronchitis/Asthma, Spondylitis, Obesity, Piles) , Preference for type of treatment for these lifestyle disease </li></ul><ul><li>Preference for type treatment/medication and brands used for some casual lifestyle diseases when they occur (Cough & Cold, Head ache, Muscular pain, Indigestion, Acidity, Acne/Pimples, Fever, Allergy, General weakness, Toothache) </li></ul><ul><li>Personal Media Usage (of only women respondents answering for the household and not of all women members of the household) </li></ul><ul><li>Type of TV content watched and the most watched TV channels for each type (Entertainment/Serials/Reality Shows, News, Movies, Music, Business News & Info, Spiritual/Devotional, Sports, Cartoon) </li></ul><ul><li>Type of newspaper/magazine read and the most read brands for each type (Regular Newspaper, Business Newspaper, Regular Magazine, Business Magazine), Most listened to radio channels </li></ul>Indian Women 2010 (Information Coverage)
  19. 19. Indian Women 2010 (Information Coverage) <ul><li>Household’s Socio-Economic Profile </li></ul><ul><li>Family size, Family classification by lifecycle stage, Highest occupation and education level in the household, Neo-SEC Classification, CWE Occupation, CWE Education, Conventional SEC classification </li></ul><ul><li>Monthly Household Income (MHI), Sources of Household Income, No. of earning members in the family, Average per capita household income, Spending power classification, Ownership status and size (carpet area) of house living in </li></ul><ul><li>Asset owned in the household (House, Land, Car, Motorcycle, Scooter, Bicycle, B/W TV, Color TV, TV Connection, Fridge, Washing Machine, Air Conditioner, Microwave, Music system, Portable music player, VCD/DVD player, Regular Camera, Digital Camera, Video Camera, Computer, Video Games, Food processor, Water purifier, Toaster/Sandwich maker, Power backup, Landline phone, Tractor, Tube well/Pump, Transistor/Radio) </li></ul><ul><li>Type of asset owned in the household and brand owned for the following assets (Fridge, Water purifier, Color TV, TV Connection, Washing Machine, Car, Motorcycle, Scooter, Computer) </li></ul><ul><li>Financial asset ownerships (Saving Bank Account, Fixed Deposit, RBI/Govt. Bonds, Demat Account, Medical Insurance, Accidental Insurance, House Insurance, Mutual Funds, Company Shares/Stocks, Chit Fund Deposits, Crop Insurance) </li></ul><ul><li>Total monthly household expenditure (MHE) with allocation on main spend heads (Rent, Telephone Bill, Electricity Bill, Kitchen Fuel, Daily Transport/Conveyance, Loans & other liability payments, Basic Food/Grocery, Basic Toiletries, Processed Food & Snacks, Cosmetics/Grooming products, Indoor entertainment, Outdoor entertainment, Farm Equipment maintenance, Cattle Fodder/Feed) , MHE as % of MHI </li></ul><ul><li>Annual consumption expenditures on main spend heads (Clothing, Footwear, Watches, Fashion accessories, Gold/Precious Jewelry, Durables/Appliance purchase, Vehicle maintenance, Holidays, Financial investments, Savings, Farm Equipment purchase and repair, Seed purchase, Cattle purchase, Fertilizer/Pesticide Purchase, House/Roof repairing) </li></ul>
  20. 20. <ul><li>Address : 3, Kehar Singh Estate, 1st Floor, Westend </li></ul><ul><li> Marg, Lane 2, Said-ul-Ajaib, New Delhi – 110030 </li></ul><ul><li>Telephone : +91-11-29535098, +91-9811256502 </li></ul><ul><li>Contact Person : Sanjay Tiwari </li></ul><ul><li>Email : [email_address] </li></ul><ul><li>Website : </li></ul>Contact Details
  21. 21. Thank You!