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Users' Choice 2013: Survey Methodology

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PANKAJ
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The Users' Choice Awards this year have been decided after conducting a survey of enterprises having 100 to 999 employees across the top 8 Indian cities. As this is a fairly wide universe in which the IT needs and brand preferences can vary, we further sub-divided it into two parts. The break-up of this along with sample size achieved is as follows:

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1. Organizations with 100-499 employees: 220 respondents

2. Organizations with 500-1000 employees: 211 respondents

The results have also been reported separately for each category in the pages to follow. It was a field survey where face to face interactions were held with CIOs and IT Managers of these organizations. These respondents were from 7 industry verticals i.e. Discrete Manufacturing, Process Manufacturing, BFSI, IT/ITeS, Healthcare, Education and Services (Logistics, Hospitality, and Professional services).

Awards Categories

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The survey was conducted to identify the top IT brands that users were likely to buy in the next six months across 32 different categories. These were broadly classified into 4 sections i.e. Hardware, Software, Network Hardware and Internet & WAN Services. AMC consciously has been kept out of any of these categories; and has been carried as a stand-alone element called IT Support & Services. However, after we received the results, we had to knock off one category due to insufficient votes, leaving us with 31 total categories.

Based on the survey, the winners have been declared across the following categories:

1. Overall Best IT Brand

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2. Best IT Brands across Hardware, Software, Networking, and Services

3. Best IT Brands across 31 categories in organizations with 100-499 employees

4. Best IT Brands across 31 categories in organizations with 500-999 employees

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Survey Methodology

The survey questionnaire sought information on six basic areas:

1. TOM (Top of Mind) recall: Here, the respondents were asked to say the first brand that comes to their mind across each category. This was recorded in the questionnaire.

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2. Primary brand owned: The respondents were asked which IT brand did they currently own in each category. In case they owned multiple brands of a category, they were asked to mention the dominant brand.

3. Brand preference for future purchase: Here, the respondents were asked which brand were they likely to buy in the near future (six months) across each category. In case they planned multiple brands of a category, they were asked to mention the dominant brand.

4. Satisfaction on Current Primary Brand: Here, the respondents were asked to rate on a five-point scale where 5 means Very Satisfied and 1 means Very dissatisfied.

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5. Reason for satisfaction on current brand: Here, the respondents were asked to choose a single reason from a set of four reasons for being satisfied with a brand in each category.

6. Reason for preference of future brand: Here, the respondents were asked to choose a single reason from a set of four reasons that they were likely to buy a particular brand in the future.

To identify the Users' Choice for each product category, all above six parameters were considered. Of these, the brand preference for the future was further divided into two data points:

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Brand Loyalty: This is the percentage of respondents who said they were likely to stay with the same brand that they were currently using, out of the total respondents who gave a response in a particular category.

Brand shift in: The percentage of respondents who said that they were likely to shift into a particular brand from some other brand.

Factor 2 and 4 i.e. ‘primary brand owned' and ‘satisfaction on current primary brand' were clubbed by multiplying them and the resultant factor was termed as Brand Strength.

Factor 5 and 6 i.e. ‘reason for satisfaction on current brand' and ‘reason for preference of future brand' were clubbed and average % of each reason was estimated.

How we decided the winners

The value of each parameter was standardised to represent all the parameters in one scale. Each of those was assigned certain weigthage based on an internal discussion between CMR and PCQuest. Further, the weighted score was calculated and then indexed to the highest as 100.

Finally on the basis of derived Index score, the users' choice was identified for each brand category.

For arriving at the overall best brands across hardware, software, services, and networking, as well as the overall best IT brand, we took the weighted score of all brands under every major category in a single sheet and then we indexed them based on the maximum weighted score. These were then ranked according to their index.

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