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Online marketing
Online marketing
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Online marketing
Online marketing
Online marketing
Online marketing
Online marketing
Online marketing
Online marketing
Online marketing
Online marketing
Online marketing
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Online marketing

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  • 1. PRESENTED BY:-GROUP 6SHAILESH KUMAR(100)RACHIT AGARWAL(101)ANSHUL BANSAL(102)S. PRIYA(103)FAHIM TALMEEZ(104)ABHA RAINA(105)
  • 2. INTRODUCTION Share of the online retail space is only 7-10 per cent, Rs 32 billion. Industry is expected to grow by triple in size by 2014-15, set to grow at a rate of 45-48 per cent to reach Rs 100 billion. Books were the first and initially the largest category to be sold online, now replaced by electronics, IT accessories, lifestyle products etc.
  • 3. HINDRANCES Poor network connectivity Credit/debit card penetration Inhibitions about security of online transactions Cash on Delivery (COD) has proved to overcome these inhibitions
  • 4. OBJECTIVES To study of inclination of consumers towards specific products for online shopping. To study the other potential products for online retailing & ways to standardise the shopping experience. To study the factors for preference of online shopping as well as to know what inhibits the consumer from online shopping.
  • 5. RESEARCH METHODOLOGYMethod to be used for collection of sample:-The data was collected through a well designed questionnaire.Sources of data:-Primary data was used for the project.Sample Design:-Sample selection was of random type.Sample size:-Sample size is of 150 people who do shopping online or would like to do it.Selection of tools for data analysis:-Available software such as MS Excel and SPSS (Statistical Package for SocialSciences) is used for analysis. Several tests such as z-test, ANOVA(Analysis ofVariance) have been applied.
  • 6. GRAPHS ANDCHARTS
  • 7. DISTRIBUTION OF AGE 8 3 14 20 to 30 yrs 30 to 50 yrs Less than 20 yrs More than 50 years 132
  • 8. DISTRIBUTION OF MONTHLY INCOME 15% 35% Less than Rs 20000 More than 1 lakh Rs Rs 20000 to Rs 50000 Rs 50000 to Rs 1 lakh 39% 11%
  • 9. DISTRIBUTION OF AVG. EXPENDITUREPER PRODUCT 7 6 18 Nil Less than 500 Rs 500 to Rs 1000 Rs 5000 to Rs 10000 More than Rs 10000 70 56
  • 10. GENDER 26% Female Male74%
  • 11. Are you a card holder160140120100 80 150 Total 60 40 20 7 0 No Yes
  • 12. Which product you want to buy in future FMCG 84 82 80 78 83 Total 76 74 76 72 No Yes
  • 13. Home appliances100 95 90 80 70 64 60 50 40 Total 30 20 10 0 No Yes
  • 14. Automobiles140 134120100 80 60 Total 40 25 20 0 No Yes
  • 15. GENDER BIAS ON FACTORS INHIBITING ONLINE SHOPPING INDEPENDENT-SAMPLES T TEST is used for determining the difference in opinion of MALE and FEMALE gender on Factors that inhibit online shopping. HYPOTHESIS NULL HYPOTHESIS (H0): There is no difference in the opinion of male and female gender on factors that inhibit them from shopping. ALTERNATE HYPOTHESIS (H1): There is a difference in the opinion of male and female gender on factors that inhibit them from shopping.
  • 16. INDEPENDENT-SAMPLES T TEST COMPARISION BETWEEN MALE AND FEMALE ON FACTORS INHIBIT THEM TO SHOP ONLINEGender N Mean Std. Deviation Std. Error MeanWhat Factors inhibit you Male 116 3.3966 1.28455 .11927from online shopping Female 41 4.1463 .96335 .15045[Security]What Factors inhibit you Male 116 3.5431 1.13744 .10561from online shopping Female 41 3.7805 .93574 .14614[Damage]What Factors inhibit you Male 116 3.7328 1.21839 .11312from online shopping[Inconvenience in Returning Female 41 4.1951 .92789 .14491]What Factors inhibit you Male 116 3.8621 1.22933 .11414from online shopping [Lack Female 41 4.0488 .99878 .15598of Touch & Feel Experience]What Factors inhibit you Male 116 3.3879 1.19979 .11140from online shopping [Delay Female 41 3.3171 1.03535 .16169in Delievery]What Factors inhibit you Male 116 3.2845 1.22869 .11408from online shopping Female 41 3.1220 1.20820 .18869[Unavailability of stock]What Factors inhibit you Male 116 2.2414 1.19142 .11062from online shopping Female 41 2.2439 1.28024 .19994[Others]
  • 17. Independent Samples Test Levenes Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed)What Factors inhibit you Equal variances 10.308 .002 -3.411 155 .001from online shopping assumed[Security] Equal variances -3.905 93.261 .000 not assumedWhat Factors inhibit you Equal variances 4.637 .033 -1.200 155 .232from online shopping assumed[Damage] Equal variances -1.317 84.658 .192 not assumedWhat Factors inhibit you Equal variances 4.565 .034 -2.212 155 .028from online shopping assumed[Inconvenience in Equal variances -2.515 91.756Returning ] .014 not assumedWhat Factors inhibit you Equal variances 3.453 .065 -.875 155 .383from online shopping assumed[Lack of Touch & Feel Equal variances -.966 85.753 .337Experience] not assumedWhat Factors inhibit you Equal variances 2.035 .156 .336 155 .737from online shopping assumed[Delay in Delievery] Equal variances .361 80.662 .719 not assumedWhat Factors inhibit you Equal variances .320 .572 .731 155 .466from online shopping assumed[Unavailability of stock] Equal variances .737 71.275 .463 not assumedWhat Factors inhibit you Equal variances 1.161 .283 -.011 155 .991from online shopping assumed[Others] Equal variances -.011 66.083 .991 not assumed
  • 18. ANOVA Preference of Online shopping with Age group as a factor Preference of online shopping Sum of F over real time shopping Squares Mean Square (Sig. Value) Between Groups 5.317 1.772 3.3809 80 (.020) Within Groups 79.677 .524 60 Total 84.994 40 68 57 Total ANOVA 20 32 Preference of Online shopping with Monthly Income as a factor 0 May be No Yes F Sum of Squares Mean Square (Sig. Value) Between 2.844 .948 1.7538 Groups (.158) Within Groups 82.150 .540 Total 84.994 Row Labels May be No Yes Grand Total ANOVA 20 to 30 yrs 26 54 52 132 Preference of Online shopping with Gender as a factor 30 to 50 yrs 3 9 2 14 F Less than 20 yrs 3 3 Sum of Squares Mean Square (Sig. Value)Between Groups 1.896 1.896 3.5142 (.063) More than 50 years 3 5 8Within Groups 83.097 .540Total 84.994 Grand Total 32 68 57 157
  • 19. ANOVA Average Frequency of Online Shopping with Age Group as a factor Avg. Frequency F 60 Sum of Squares Mean Square (Sig. Value) 50 Between Groups 10.237 3.412 1.4866 (0.220) 40 30 53 Within Groups 348.910 2.295 20 39 10 26 22 Total 359.147 0 6 11 ANOVA Average Frequency of Online Shopping with gender F Sum of Squares Mean Square (Sig. Value) Between Groups 22.421 22.421 10.2542 (.002) Within Groups 336.726 2.187 Total 359.147 ANOVAAverage Frequency of Online Shopping with Monthly Once in 6 Once in a Twice in a Grand income as a factor Row Labels months month month Total Female 10 13 4 27 F Sum of Squares Mean Square (Sig. Value)Between 11.571 3.857 1.6867Groups (0.1722) Male 29 40 22 91Within Groups 347.576 2.287 Grand Total 39 53 26 118Total 359.147
  • 20. FACTOR Sum of Squares Mean Square F Sig.Flipkart Between Groups 2.448 2.448 1.059 .305 Within Groups 356.141 2.313 Total 358.590Ebay Between Groups .394 .394 .240 .625 Within Groups 252.504 1.640 Total 252.897Snapdeal Between Groups 8.382 8.382 5.257 .023 Within Groups 245.535 1.594 Total 253.917Jabong Between Groups 10.842 10.842 9.038 .003 Within Groups 184.747 1.200 Total 195.590Inkfruit Between Groups 1.615 1.615 1.488 .224 Within Groups 167.128 1.085 Total 168.744Yebhi Between Groups 3.271 3.271 2.490 .117 Within Groups 202.287 1.314 Total 205.558Homeshop18 Between Groups 6.725 6.725 5.374 .022 Within Groups 192.711 1.251 Total 199.436Futurebazaar Between Groups 2.926 2.926 2.512 .115 Within Groups 179.401 1.165 Total 182.327Letsbuy Between Groups .751 .751 .848 .358 Within Groups 136.243 .885 Total 136.99470mm Between Groups 2.097 2.097 4.330 .039 Within Groups 74.595 .484 Total 76.692Indiatimes Shopping Between Groups .005 .005 .005 .941 Within Groups 152.322 .989 Total 152.327
  • 21. WEBSITE PREFERENCE WITH GENDER AS AFACTOR Sum of Sum of Sum of Sum of Sum ofRow Labels Homeshop18 Flipkart Ebay Snapdeal Jabong Max SumFemale 91 137 98 115 98 205Male 206 419 291 263 207 580 80 70 60 50 Homeshop18 Flipkart 40 Ebay 30 Snapdeal Jabong 20 10 0 Female Male
  • 22. WEBSITE PREFERENCE WITH AGE AS A FACTOR Sum of Squares Mean Square F Sig.Flipkart Between Groups 23.022 7.674 3.476 .018 Within Groups 335.567 2.208 Total 358.590Ebay Between Groups .189 .063 .038 .990 Within Groups 252.708 1.663 Total 252.897Snapdeal Between Groups 2.747 .916 .554 .646 Within Groups 251.170 1.652 Total 253.917Jabong Between Groups 11.817 3.939 3.258 .023 Within Groups 183.772 1.209 Total 195.590Inkfruit Between Groups 7.892 2.631 2.486 .063 Within Groups 160.851 1.058 Total 168.744Yebhi Between Groups 17.263 5.754 4.645 .004 Within Groups 188.295 1.239 Total 205.558Homeshop18 Between Groups 4.933 1.644 1.285 .282 Within Groups 194.503 1.280 Total 199.436Futurebazaar Between Groups 1.508 .503 .423 .737 Within Groups 180.819 1.190 Total 182.327Letsbuy Between Groups 1.914 .638 .718 .543 Within Groups 135.080 .889 Total 136.99470mm Between Groups .862 .287 .576 .631 Within Groups 75.830 .499 Total 76.692Indiatimes Shopping Between Groups 1.529 .510 .514 .673 Within Groups 150.798 .992 Total 152.327Infibeam Between Groups .742 .247 .264 .851 Within Groups 142.200 .936 Total 142.942Others Between Groups 9.691 4.846 1.812 .171 Within Groups 179.180 2.674 Total 188.871
  • 23. PREFERENCE OF PRODUCTS WITH AGE AS A FACTOR ANOVA age group F (Sig. Value) Sum of Squares Mean SquareClothing Between Groups 8.246 2.749 1.2656 (.288) Within Groups 330.113 2.172 Total 338.359Books Between Groups 6.709 2.236 0.9813 (.403) Within Groups 346.368 2.279 Total 353.077Electronic Item Between Groups 10.735 3.578 1.8626 (.138) Within Groups 292.009 1.921 Total 302.744Footwear Between Groups 5.112 1.704 1.0367 (.378) Within Groups 249.831 1.644 Total 254.942FMCG Between Groups .434 .145 0.1276 (.944) Within Groups 172.156 1.133 Total 172.590Electric Appliance Between Groups 7.641 2.547 1.9257 (.128) Within Groups 201.045 1.323 Total 208.686Gifts & Flowers Between Groups 2.959 .986 0.5174 (.671) Within Groups 289.810 1.907 Total 292.769Others Between Groups 5.263 2.632 1.5843 (.216) Within Groups 76.410 1.661 Total 81.673
  • 24. PREFERENCE OF PRODUCTS WITH MONTHLY INCOME AS A FACTOR ANOVA monthly income F Sum of Squares Mean Square (Sig. Value)Electronic Item Between Groups 10.518 3.506 1.8236 (.145) Within Groups 292.226 1.923 Total 302.744Clothing Between Groups 16.787 5.596 2.6449 (.051) Within Groups 321.572 2.116 Total 338.359Books Between Groups 13.052 4.351 1.9449 (.125) Within Groups 340.025 2.237 Total 353.077Footwear Between Groups 7.540 2.513 1.5442 (.205) Within Groups 247.402 1.628 Total 254.942FMCG Between Groups 5.947 1.982 1.8081 (.148) Within Groups 166.643 1.096 Total 172.590Electric Appliance Between Groups 4.733 1.578 1.1758 (.321) Within Groups 203.953 1.342 Total 208.686Gifts & Flowers Between Groups .444 .148 0.07696 (.972) Within Groups 292.325 1.923 Total 292.769Others Between Groups 2.834 .945 0.5392 (.658) Within Groups 78.839 1.752 Total 81.673
  • 25. PREFERENCE OF PRODUCTS WITH GENDER AS A FACTOR ANOVA Sum of Squares Mean Square F Sig.Electronic Item Between Groups 6.191 6.191 3.215 .075 Within Groups 296.552 1.926 Total 302.744Clothing Between Groups 8.606 8.606 4.019 .047 Within Groups 329.753 2.141 Total 338.359Books Between Groups 1.551 1.551 .679 .411 Within Groups 351.526 2.283 Total 353.077Footwear Between Groups .587 .587 .355 .552 Within Groups 254.355 1.652 Total 254.942FMCG Between Groups 7.381 7.381 6.880 .010 Within Groups 165.209 1.073 Total 172.590Electric Appliance Between Groups .299 .299 .221 .639 Within Groups 208.387 1.353 Total 208.686Gifts & Flowers Between Groups 15.902 15.902 8.845 .003 Within Groups 276.867 1.798 Total 292.769Others Between Groups 1.916 1.916 1.129 .293 Within Groups 79.757 1.697 Total 81.673
  • 26. REGRESSION Multiple Regression is used to: Find the relationship of One dependent variable which may be affected by two or more independent variables. Here we are trying to predict what factors for preference of Online shopping will affect the consumers behavior of frequency of Online shopping. Hypothesis: Null Hypothesis (Ho): Average frequency of Online shopping is not dependent on Factors which contribute to Online shopping. Alternate Hypothesis (H1): Average frequency of Online shopping is dependent on Factors which contribute to Online shopping.
  • 27. INPUT ADDED DEPENDENT VARIABLE :Average Frequency of Online shopping INDEPENDENT VARIABLE:Why you prefer Online Shopping? Save Time Discounts Home Delivery Vast Collection Anytime Shopping Exotic Collection Brand Availability Convenience Guidance Social Influence Otherso METHOD: STEPWISE
  • 28. SIGNIFICANT MODELS IDENTIFIED Variables Entered/Removeda Variables Variables Model Entered Removed Method 1 Why you prefer Stepwise Online (Criteria: Shopping? Probability-of-F- [Save Time] to-enter <= .050, Probability-of-F- to-remove >= .100). 2 Why you prefer Stepwise Online (Criteria: Shopping? Probability-of-F- [Guidance] to-enter <= .050, Probability-of-F- to-remove >= .100). a. Dependent Variable: Average Frequency of Online Shopping
  • 29. Model Summary Adjusted R Std. Error of Durbin-Model R R Square Square the Estimate Watson a1 .228 .052 .046 1.48706 b2 .297 .088 .076 1.46319 1.828a. Predictors: (Constant), Why you prefer Online Shopping? [Save Time]b. Predictors: (Constant), Why you prefer Online Shopping? [Save Time], Whyyou prefer Online Shopping? [Guidance]c. Dependent Variable: Average Frequency of Online Shopping
  • 30. ANOVA Sum of MeanModel Squares df Square F Sig. b1 Regression 18.600 1 18.600 8.411 .004 Residual 340.548 154 2.211 Total 359.147 155 c2 Regression 31.585 2 15.793 7.376 .001 Residual 327.562 153 2.141 Total 359.147 155a. Dependent Variable: Average Frequency of Online Shoppingb. Predictors: (Constant), Why you prefer Online Shopping? [Save Time]c. Predictors: (Constant), Why you prefer Online Shopping? [Save Time],Why you prefer Online Shopping? [Guidance]
  • 31. Coefficients Standardized Unstandardized Coefficients CoefficientsModel B Std. Error Beta t Sig.1 (Constant) 5.016 .500 10.039 .000 Why you -.344 .118 -.228 -2.900 .004 prefer Online Shopping? [Save Time]2 (Constant) 5.550 .537 10.330 .000 Why you -.298 .118 -.197 -2.525 .013 prefer Online Shopping? [Save Time] Why you -.247 .100 -.193 -2.463 .015 prefer Online Shopping? [Guidance]a. Dependent Variable: Average Frequency of Online Shopping Multiple Regression Equation: Y a b1 X 1 b2 X 2 b3 X 3 ....... bk X K Referring the table a=5.550, b1= -0.298 and b2= -0.247 X1= Rating given for Save Time X2= Rating given for Guidance
  • 32. SOLVING THE EQUATION Assuming the consumer give 5 rating to both the factors Than, Y= 5.550-0.298*5-0.247*5 = 5.550-1.49-1.235 = 5.550-2.725 = 2.825From the values which we have given for Average frequency for online shopping is:Rating 2= Twice in a monthRating 3= Once in a monthSo to conclude Consumer will probably do online shopping if Save time and Guidance are Most important factors for him
  • 33. LIMITATIONS OF THE SURVEY The sample size was small; the generalization of the whole of the population could not be done. Most of people surveyed were in the age group 20-40, so the perception of the people above 40 years could not be captured properly The numbers of females surveyed were less (27.3%); hence the perception of the women could not be captured. Only convenience sampling technique could be used for data collection The survey conducted depends upon the opinion of the people surveyed in the sample.
  • 34. CONCLUSION Age is a major factor which affects consumer’s choice of doing online shopping over real time shopping. Whereas, monthly income and gender does not effect this choice of consumer. The average frequency of online shopping depends on the gender of the consumer but it does not depend on age of the consumer. It was found that sites like Snapdeal, Jabong and Home shop 18 were preferred by females over male .
  • 35. CONTINUED….. Itwas found that 70mm was preferred by males over females. Flipkart site is popular amongst the age group of 20-30 years. Products like Clothing, FMCG & Gifts & flowers are found to be more appealing to women as a choice of shopping. Security and inconvenience to return came out to be the major factors deterring people from doing online shopping.
  • 36. RECOMMENDATIONS Online Service provider should try to provide quality services to the buyer. The websites/portals providing this service should work towards improving and expanding their network so, that timely and efficient delivery is made. For things like apparels the delivery person should carry one size smaller and one size bigger along with the chosen size. Before dispatching the products they should be properly checked so, that the product is not returned back by customers.
  • 37. CONTINUED….. Products should be properly and carefully packed before dispatching them to avoid damage of products in transit. Proper technical steps should be taken to ensure buyer’s information by the service providers. All the service providers should have system of cash on delivery as this is the preferred mode of payment by buyers.
  • 38. REFERENCES Keisidou, Ellisavet1, Sarigiannidis, Lazaros1, Maditinos, Dimitrios1. Consumer characteristics and their effect on accepting online shopping, in the context of different product types. International Journal of Business Science & Applied Management; 2011, Vol. 6 Issue 2, p31- 51, 21p, 1 Diagram, 9 Charts Jam, Sanjay K.1, Jam, Manika2.Exploring Impact of Consumer and Product Characteristics on E-Commerce Adoption: A Study of Consumers in India. Journal of Technology Management for Growing Economies; Oct2011, Vol. 2 Issue 2, p35-64, 30p, 2 Diagrams, 11 Charts Theetranont, churee1, haddawy, peter1, krairit, donyaprueth2.Integrating visualization and multi-attribute utility theory for online product selection. International Journal of Information Technology & Decision Making; Dec2007, Vol. 6 Issue 4, p723-750, 28p, 9 Color Photographs, 4 Charts, 1 Graph Eppright,David R.1,Hawkins,Richard R.1.Determinants of Emerging e-Commerce Markets: A Developmental Perspective. Journal of Internet Commerce; 2009, Vol. 8 Issue 1/2, p113-134, 22p, 4 Charts Cash on Delivery Doesn’t Work for Companies. Forbes India Independence day special. 31 st August 2012 issue. https://www.crisilresearch.com/CuttingEdge/industryasync.jspx?serviceId=2&State=null#storyId #1329978091321#sectionId#1

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