The study examined the relationship between product testing and customer satisfaction/return rates in the cosmetic industry. Surveys were administered to 120 customers in San Francisco. Results showed: 1) Product testing had a large, positive effect on customer satisfaction. 2) Product testing had a small, negative effect on return rates. 3) No significant difference was found between genders in return rates. 4) A significant relationship was found between high return rates without testers and past returns. The findings suggest making testers available could increase satisfaction and reduce costs from returns, though more research is needed. Managers should consider offering testers to evaluate impact on profits.

1. Research: The effect of testers on return rate and
customer satisfaction in the cosmetic fieldBY
ANGELA SINGH
SOPHIA ATTAF
ANDREA VERESS

2. Introduction
▶ Cosmetic industry: $56.63 billion in US
▶ By 2016: total revenue will exceed about $ 62 billion and employ about 63,816
people
▶ Large rate of returns in this industry: 8.60% (according to the consumer returns
survey, which included 60 companies)
▶ Products that have been returned cannot be sold to another customer

3. Secondary research
▶ Product return rate might attain 25% in some cases ($100 billion per year in lost
and it decreases the company’s profits by 3.8%)
▶ Dissatisfaction with a product is the consequence of an emotional dissonance that
has a positive relationship with product returns
▶ The reasons for high product return according to this research are:
▶ The client found a better product at a lower price
▶ The expectations of the customer were not met
▶ Even if males had a high dissatisfaction level, their rate of return was lower than
for females.
▶ The rate of product returns varies according to the nature of the product and the
period of the year

4. Problem definition
▶ In drugstores and other retail stores (Walgreens, CVS, Rite Aid, Target, Walmart)
customers cannot try out cosmetic products before the purchase
▶ If customers could try cosmetic products would that decrease return rates and
increase customer satisfaction?

5. Research questions
▶ Is there any relationship between product testing and customer satisfaction?
▶ Is there any relationship between prior product testing and return rate?
▶ Is there any relationship between gender and reaction to testers regarding
satisfaction level?

6. Hypothesis
▶ H1: There is a positive correlation between product testing and customer
satisfaction regarding the tested product.
▶ H2: There is a relationship between prior product testing and return rate
▶ H3: The rate of return is different according to the gender of the customer.
▶ H4: There is a relationship between rate of return and level of education.
▶ H5: There is a relationship between satisfaction level when testers are available
and gender.
▶ H6: There is a relationship between rate of return in the last 6 months and the
return frequency when testers are not available.

7. Research methodology
-T-test

8. Primary
Research
Pilot
Survey
Online
Survey
Mall
Intercept

9. Quantitative Research Plan
▶ Total- 12 questions
▶ Specific research questions- 9
▶ Demographic questions- 3

10. Questionnaire Design
▶ Non-comparative scaling technique 'Likert scale’
▶ Other questions consist of nominal, interval and scales
which provides data about the respondent's demographic
information

11. Sampling population
▶ Target Audience
▶ Number of respondents
▶ Sampling techniques

12. Sampling Size
120
Respondents
Male
41
Female
79

13. Results

14. First Hypothesis
▶ Our first hypothesis: There exists a positive correlation between product testing
and customer satisfaction regarding the tested product.
▶ Used test: Wilcoxon Signed Rank Test
▶ We used a seven-level Likert scale to collect these data where 1 represents
“extremely dissatisfied” and 7 represents “extremely satisfied”.

15. First Hypothesis
H0: The difference between the pairs follows a
symmetric distribution around zero.
P value is below 0.05, so we can reject the null
hypothesis.
Effect size: r= Z/ √n. The effect size in this case is
0.49 which is considered a large effect size.
Testers have a statistically significant effect on
customer satisfaction.

16. Second Hypothesis
▶ Our second hypothesis: There is a relationship between prior product testing and
return rate
▶ Test method: Wilcoxon Signed Rank test
▶ We used a five-level Likert scale to collect these data where 1 represents “never”
and 5 represents “very often”.

17. Second Hypothesis
H0: The difference between the pairs follows a symmetric
distribution around zero.
P value is below 0.05, so we can reject the null
hypothesis.
r= Z/ √n. The effect size in this case is 0.24 which is
considered a small/weak effect. According to this test, we
can say that testers have a small effect on the returns.

18. Third Hypothesis
▶ Our third hypothesis: Different gender return cosmetic products with different
frequency.
▶ Test method: Cross tabulation with Chi-square

19. Third Hypothesis
H0: There is no difference between
woman and man on whether they
returned a cosmetic item in the last
6 months.
Our P value (0.079) was higher
than our significance, so we
couldn’t reject the null hypothesis.
According to the test, there is no
statistically significant difference
between women and men
regarding their returns.

20. Fourth Hypothesis
▶ Fourth hypothesis: There is a relationship between return of products and level of
education.
▶ We wanted to test whether education level and return frequency has any relationship.
▶ Test method: Independent Samples T-test
▶ Grouping variable: returned a product in the last 6 months
▶ Independent variable: education level
▶ We measured the education level on a 7-level scale where 1 was equal with “less than
high school” and 7 was equal “doctorate”.

21. Fourth Hypothesis
H0: There is no relationship between
return of products and level of
education.
The Sig (2-tailed) value is 0.21,
because this value is not less than
0.05, we cannot reject the Null
Hypothesis.
We couldn’t prove any significant
relationship between education level
and whether returns happened in the
last 6 months.

22. Fifth Hypothesis
▶ Fifth hypothesis: There is a relationship between satisfaction level when testers are present and
gender.
▶ Test method: Independent Samples T-test
▶ Grouping variable: gender
▶ Independent variable: satisfaction level if testers are available in stores
▶ We measured the satisfaction level on a 7-level Likert scale where 1 was equal with “extremely
dissatisfied” and 7 was equal “extremely satisfied”.

23. Fifth Hypothesis
H0: There is no relationship between
satisfaction level when testers are present
and gender.
The Sig (2-tailed) value is 0.115, because
this value is not less than 0.05, we cannot
reject the Null Hypothesis.
We couldn’t prove any statistically
significant relationship between
satisfaction level when testers are placed
and gender.

24. Sixth Hypothesis
▶ Sixth hypothesis: There is a relationship between return of products in the last 6 months
and the return frequency when testers are not available.
▶ Test method: Independent Samples T-test
▶ Grouping variable: returned a product in the last 6 months
▶ Independent variable: return frequency when testers are not available

25. Sixth Hypothesis
H0: There is no relationship between
return of products in the last 6 months
and the return frequency when testers
are not available.
The Sig (2-tailed) value is 0.00, because
this value is less than 0.05, we can reject
the Null Hypothesis.
This proves that there is a significant
positive correlation between high return
rate when testers are not available and
returning a product in the last 6 months.

26. Other findings
▶ According to the results of this question, samples
and testers could decrease the return intention of
a customer.
▶ When we asked respondents whether they would
feel more comfortable buying a new product if
testers were available at the store. We got a
response rate of 89.2%

27. Limitations
▶ Convenience sampling was used to gather the data.
▶ The survey has been conducted in the city of San
Francisco only.

28. Managerial Implications
▶ The results from our study have some
implications:
▶ Testing the product before purchase has
a large effect on customer satisfaction.
▶ From our study, about 70% of respondents
showed increased satisfaction when they
were able to test the product before
purchase.
▶ Managers should therefore, explore the idea
to incorporate samples for cosmetic product
categories as these products also have a
very high margin.

29. ▶ In addition, after a cosmetic item is
returned, the product cannot be resold. This
will lead to wastage and thereby reduce
revenue of the company.
▶ In the short-run it may cost companies to
make testers/samples available in stores
but in the long-run it will help them to get
more customers and thereby increase their
profitability.
ManagerialImplications

30. ▶ Although small in effect, there appears to be a
negative relationship between the presence of
testers and the rate of return of products.
▶ Based on our sample, it was found that there is no
statistical significance in difference between gender
and return rates.
▶ However, we saw in our sample that women tend to
return more often than men. However, more research
can also be done with a bigger sample size to see if
there will be any statistical significance between
gender and return rates.
ManagerialImplications

31. References
▶ Insaf, B. A., & Guilbert, F. (2009). Influences on free samples usage within the luxury cosmetic market.
Direct Marketing, 3(1), 67-82. doi:http://0-dx.doi.org.library.ggu.edu/10.1108/17505930910945741
▶ Wood, S. L. (2001). Remote purchase environments: The influence of return policy leniency on two-stage
decision processes. JMR, Journal of Marketing Research, 38(2), 157-169. Retrieved from http://0-
search.proquest.com.library.ggu.edu/docview/235214703?accountid=25283
▶ Mittal, V., & Kamakura, W. A. (2001). Satisfaction, repurchase intent, and repurchase behavior:
Investigating the moderating effect of customer characteristics. JMR, Journal of Marketing Research,
38(1), 131-142. Retrieved from http://0-
search.proquest.com.library.ggu.edu/docview/235239123?accountid=25283
▶ Petersen, J. A., & Kumar, V. (2009). Are Product Returns a Necessary Evil? Antecedents and
Consequences. Journal Of Marketing, 73(3), 35-51. doi:10.1509/jmkg.73.3.35
▶ Chandrashekaran, M., Rotte, K., Tax, S. S., & Grewal, R. (2007). Satisfaction Strength and Customer
Loyalty. Journal Of Marketing Research (JMR), 44(1), 153-163. doi:10.1509/jmkr.44.1.153
▶ Fiore, A. M., & Yu, H. (2001). Effects of imagery copy and product samples on responses toward the
product. Journal of Interactive Marketing, 15(2), 36-46. Retrieved from http://0-
search.proquest.com.library.ggu.edu/docview/229656911?accountid=25283