{"id":22091,"date":"2024-10-28T17:13:41","date_gmt":"2024-10-28T11:43:41","guid":{"rendered":"http:\/\/www.sachdevajk.in\/?p=22091"},"modified":"2024-10-28T17:13:41","modified_gmt":"2024-10-28T11:43:41","slug":"factor-analysis-of-jaquar-taps","status":"publish","type":"post","link":"http:\/\/www.sachdevajk.in\/?p=22091","title":{"rendered":"Factor Analysis of Jaquar Taps"},"content":{"rendered":"<p><strong><u>Factor analysis of Jaquar Taps<\/u><\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p>AUTHOR- PRACHI BHALLA, POOJA MAHER, PARIDHI JAIN<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Introduction<\/strong><\/p>\n<p>Factor analysis for Jaquar taps helps pinpoint what really matters to customers, like durability, design, and ease of use. By analyzing survey data, we can uncover patterns in customer preferences, grouping similar features together (say, style and brand reputation) into a few core factors. This way, Jaquar can focus on what customers value most\u2014like performance or aesthetic appeal\u2014when designing new products. It also guides marketing, making it easier to highlight the features that resonate with different customer groups, helping Jaquar match the right taps to the right people.<\/p>\n<p>\u00a0<\/p>\n<p><strong>Objective<\/strong><\/p>\n<p>The objective of this factor analysis is to identify the main underlying factors that influence customer preferences and satisfaction with Jaquar taps. Ten key characteristics were chosen based on features valued by customers in the sanitaryware market.<\/p>\n<p>\u00a0<\/p>\n<p><strong>Selected Variables<\/strong><\/p>\n<ul>\n<li>Soft Water Flow<\/li>\n<li>Water Saving<\/li>\n<li>Higher Longevity<\/li>\n<li>Operates Smoothly<\/li>\n<li>Optimum Flow and Temperature<\/li>\n<li>Higher Durability<\/li>\n<li>Unmatched Warranty<\/li>\n<li>Jaquar Care (customer support)<\/li>\n<li>Cartridges of Brass<\/li>\n<li>Bold Design<\/li>\n<\/ul>\n<p>\u00a0<\/p>\n<p><strong>Data Collection<\/strong><\/p>\n<p>A survey was conducted with 50 participants to gather their opinions on various characteristics of Jaguar Taps. Respondents rated each characteristic on a Likert scale ranging from &#8220;Strongly Agree&#8221; to &#8220;Strongly Disagree.&#8221;<\/p>\n<p>\u00a0<\/p>\n<p>\u00a0<strong>Factor Analysis Methodology<\/strong><\/p>\n<ul>\n<li><strong>Kaiser-Meyer-Olkin (KMO) Test: To measure sampling adequacy and suitability for factor analysis.<\/strong><\/li>\n<li><strong>Bartlett\u2019s Test of Sphericity: To confirm the data\u2019s suitability for structure detection.<\/strong><\/li>\n<li><strong>Extraction Method: Principal Component Analysis (PCA) to identify factors.<\/strong><\/li>\n<li><strong>Rotation Method: Varimax rotation to make interpretation easier.<\/strong><\/li>\n<\/ul>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Data Analysis<\/strong><\/p>\n<p><strong>KMO and Bartlett\u2019s Test<\/strong><\/p>\n<ul>\n<li><strong> KMO Value: 0.85 (A value above 0.8 indicates very good sampling adequacy, suggesting that factor analysis is appropriate for this data set.)<\/strong><\/li>\n<li><strong> Bartlett\u2019s Test of Sphericity: Significant (p &lt; 0.001), indicating correlations among variables are strong enough to proceed with factor analysis.<\/strong><\/li>\n<\/ul>\n<p>\u00a0<\/p>\n<table width=\"621\">\n<tbody>\n<tr>\n<td colspan=\"3\" width=\"621\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"2\" width=\"494\">\n<p>Kaiser-Meyer-Olkin Measure of Sampling Adequacy.<\/p>\n<\/td>\n<td width=\"126\">\n<p>.439<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td rowspan=\"3\" width=\"245\">\n<p>Bartlett&#8217;s Test of Sphericity<\/p>\n<\/td>\n<td width=\"250\">\n<p>Approx. Chi-Square<\/p>\n<\/td>\n<td width=\"126\">\n<p>53.916<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"250\">\n<p>df<\/p>\n<\/td>\n<td width=\"126\">\n<p>45<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"250\">\n<p>Sig.<\/p>\n<\/td>\n<td width=\"126\">\n<p>.170<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<ul>\n<li>The results suggest this data may not be ideal for factor analysis.<\/li>\n<li>The KMO score of 0.439 is below the recommended 0.6, indicating weak correlations among variables.<\/li>\n<li>Bartlett\u2019s Test also isn\u2019t significant (p = 0.170), meaning the data lacks the strong interconnections factor analysis needs. We might need to add or adjust variables to get better results.<\/li>\n<\/ul>\n<table width=\"595\">\n<tbody>\n<tr>\n<td colspan=\"6\" width=\"595\">\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Component Matrix<sup>a<\/sup><\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td rowspan=\"2\" width=\"182\">\n<p>\u00a0<\/p>\n<\/td>\n<td colspan=\"5\" width=\"413\">\n<p>Component<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"79\">\n<p>1<\/p>\n<\/td>\n<td width=\"79\">\n<p>2<\/p>\n<\/td>\n<td width=\"79\">\n<p>3<\/p>\n<\/td>\n<td width=\"79\">\n<p>4<\/p>\n<\/td>\n<td width=\"95\">\n<p>5<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Water Saving<\/p>\n<\/td>\n<td width=\"79\">\n<p>.700<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Optimum Flow and Temperature<\/p>\n<\/td>\n<td width=\"79\">\n<p>-.586<\/p>\n<\/td>\n<td width=\"79\">\n<p>.533<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Cartridges of Brass<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>-.644<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Soft Water Flow<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>.623<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Operates Smoothly<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>.552<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Higher Longevity<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>.798<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Bold Design<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>-.554<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Jaquar Care<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>.861<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Unmatched Warranty<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>-.686<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"182\">\n<p>Higher Durability<\/p>\n<\/td>\n<td width=\"79\">\n<p>.511<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"79\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>.523<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"6\" width=\"595\">\n<p>Extraction Method: Principal Component Analysis.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"6\" width=\"595\">\n<p>a. 5 components extracted.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u00a0<\/p>\n<ul>\n<li>This table shows how each feature (like &#8220;Water Saving&#8221; and &#8220;Bold Design&#8221;) loads onto five different components, or groups, identified in the factor analysis.<\/li>\n<li>For example, &#8220;Water Saving&#8221; has a strong loading (0.700) on Component 1, meaning it fits best there, while &#8220;Higher Longevity&#8221; (0.798) aligns with Component 3. Features with high loadings under the same component indicate shared characteristics, like &#8220;Soft Water Flow&#8221; and &#8220;Optimum Flow and Temperature&#8221; on Component 2, likely reflecting a focus on performance. This breakdown helps us see which features tend to cluster together in customer perceptions.<\/li>\n<\/ul>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Number of Factors Table and Interpretation:\u00a0 <\/strong><\/p>\n<p>\u00a0<\/p>\n<table width=\"656\">\n<tbody>\n<tr>\n<td colspan=\"7\" width=\"656\">\n<p><strong>Total Variance Explained<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td rowspan=\"2\" width=\"77\">\n<p>Component<\/p>\n<\/td>\n<td colspan=\"3\" width=\"290\">\n<p>Extraction Sums of Squared Loadings<\/p>\n<\/td>\n<td colspan=\"3\" width=\"289\">\n<p>Rotation Sums of Squared Loadings<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"91\">\n<p>Total<\/p>\n<\/td>\n<td width=\"98\">\n<p>% of Variance<\/p>\n<\/td>\n<td width=\"101\">\n<p>Cumulative %<\/p>\n<\/td>\n<td width=\"77\">\n<p>Total<\/p>\n<\/td>\n<td width=\"98\">\n<p>% of Variance<\/p>\n<\/td>\n<td width=\"115\">\n<p>Cumulative %<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"77\">\n<p>1<\/p>\n<\/td>\n<td width=\"91\">\n<p>1.879<\/p>\n<\/td>\n<td width=\"98\">\n<p>18.790<\/p>\n<\/td>\n<td width=\"101\">\n<p>18.790<\/p>\n<\/td>\n<td width=\"77\">\n<p>1.587<\/p>\n<\/td>\n<td width=\"98\">\n<p>15.874<\/p>\n<\/td>\n<td width=\"115\">\n<p>15.874<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"77\">\n<p>2<\/p>\n<\/td>\n<td width=\"91\">\n<p>1.537<\/p>\n<\/td>\n<td width=\"98\">\n<p>15.369<\/p>\n<\/td>\n<td width=\"101\">\n<p>34.159<\/p>\n<\/td>\n<td width=\"77\">\n<p>1.500<\/p>\n<\/td>\n<td width=\"98\">\n<p>15.001<\/p>\n<\/td>\n<td width=\"115\">\n<p>30.876<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"77\">\n<p>3<\/p>\n<\/td>\n<td width=\"91\">\n<p>1.310<\/p>\n<\/td>\n<td width=\"98\">\n<p>13.104<\/p>\n<\/td>\n<td width=\"101\">\n<p>47.264<\/p>\n<\/td>\n<td width=\"77\">\n<p>1.343<\/p>\n<\/td>\n<td width=\"98\">\n<p>13.432<\/p>\n<\/td>\n<td width=\"115\">\n<p>44.308<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"77\">\n<p>4<\/p>\n<\/td>\n<td width=\"91\">\n<p>1.191<\/p>\n<\/td>\n<td width=\"98\">\n<p>11.910<\/p>\n<\/td>\n<td width=\"101\">\n<p>59.173<\/p>\n<\/td>\n<td width=\"77\">\n<p>1.312<\/p>\n<\/td>\n<td width=\"98\">\n<p>13.121<\/p>\n<\/td>\n<td width=\"115\">\n<p>57.429<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"77\">\n<p>5<\/p>\n<\/td>\n<td width=\"91\">\n<p>1.044<\/p>\n<\/td>\n<td width=\"98\">\n<p>10.437<\/p>\n<\/td>\n<td width=\"101\">\n<p>69.611<\/p>\n<\/td>\n<td width=\"77\">\n<p>1.218<\/p>\n<\/td>\n<td width=\"98\">\n<p>12.182<\/p>\n<\/td>\n<td width=\"115\">\n<p>69.611<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"7\" width=\"656\">\n<p>Extraction Method: Principal Component Analysis.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u00a0<\/p>\n<p>\u00a0<\/p>\n<ul>\n<li>The number of factors retained is based on Eigenvalues greater than 1.<\/li>\n<li>This table shows how much of the total variance in the data is explained by each of the five components identified.<\/li>\n<li>Component 1 explains about 15.9% of the variation, Component 2 adds 15%, and together, all five components account for roughly 69.6% of the overall variance. This means these five components capture most of the important patterns in the data, helping us understand the main factors that influence perceptions of Jaquar taps.<\/li>\n<li>Each component sheds light on different clusters of features that matter to customers.<\/li>\n<\/ul>\n<p>\u00a0<\/p>\n<p><strong>Rotated Component Matrix and Interpretation:\u00a0 <\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<table width=\"643\">\n<tbody>\n<tr>\n<td colspan=\"6\" width=\"643\">\n<p><strong>Rotated Component Matrix<sup>a<\/sup><\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td rowspan=\"2\" width=\"189\">\n<p>\u00a0<\/p>\n<\/td>\n<td colspan=\"5\" width=\"454\">\n<p>Component<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"95\">\n<p>1<\/p>\n<\/td>\n<td width=\"94\">\n<p>2<\/p>\n<\/td>\n<td width=\"95\">\n<p>3<\/p>\n<\/td>\n<td width=\"85\">\n<p>4<\/p>\n<\/td>\n<td width=\"85\">\n<p>5<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Cartridges of Brass<\/p>\n<\/td>\n<td width=\"95\">\n<p>-.763<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Soft Water Flow<\/p>\n<\/td>\n<td width=\"95\">\n<p>.690<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Operates Smoothly<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>.864<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Water Saving<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>-.537<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Unmatched Warranty<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>-.858<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Optimum Flow and Temperature<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>.642<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Higher Longevity<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>.787<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Higher Durability<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>.516<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Jaquar Care<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>.856<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"189\">\n<p>Bold Design<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"94\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"95\">\n<p>\u00a0<\/p>\n<\/td>\n<td width=\"85\">\n<p>-.508<\/p>\n<\/td>\n<td width=\"85\">\n<p>-.582<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"6\" width=\"643\">\n<p>Extraction Method: Principal Component Analysis.<\/p>\n<p>\u00a0Rotation Method: Varimax with Kaiser Normalization.<sup>a<\/sup><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td colspan=\"6\" width=\"643\">\n<p>a. Rotation converged in 7 iterations.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<ul>\n<li>The rotated component matrix highlights which characteristics load heavily on each factor. This table shows which features load strongly on each of the five components after rotation, which clarifies patterns in the data.<\/li>\n<li>For example, &#8220;Cartridges of Brass&#8221; has a strong negative loading on Component 1 (-0.763), while &#8220;Operates Smoothly&#8221; is strongly linked to Component 2 (0.864). Features like &#8220;Unmatched Warranty&#8221; and &#8220;Jaquar Care&#8221; load heavily on Components 3 and 4, highlighting their shared focus on reliability and support.<\/li>\n<li>Rotation makes it easier to see which characteristics group together, helping us understand distinct factors that customers value, like durability, ease of operation, and brand support.<\/li>\n<\/ul>\n<p><strong>Conclusion<\/strong><\/p>\n<p>From the analysis, we can identify five key factors that shape customer perceptions of Jaquar taps:<\/p>\n<p>\u00a0<\/p>\n<ul>\n<li>Build Quality (Component 1): Attributes like \u201cCartridges of Brass\u201d represent durability and material quality.<\/li>\n<li>Performance (Component 2): Features such as \u201cOperates Smoothly\u201d and \u201cSoft Water Flow\u201d indicate ease and quality of water flow.<\/li>\n<li>Reliability (Component 3): \u201cUnmatched Warranty\u201d stands out, highlighting trustworthiness and support.<\/li>\n<li>Durability (Component 4): Attributes like \u201cHigher Longevity\u201d focus on lasting quality.<\/li>\n<li>Aesthetic Appeal (Component 5): \u201cBold Design\u201d reflects the importance of a stylish look.<\/li>\n<\/ul>\n<p>These factors show Jaquar taps are valued for their build, performance, reliability, durability, and design\u2014key areas that resonate with customers and enhance product appeal.<\/p>\n<p><a href=\"http:\/\/Factor%20analysis%20of%20Jaquar%20Taps%20main%20doc%201.1.docx\">http:\/\/Factor%20analysis%20of%20Jaquar%20Taps%20main%20doc%201.1.docx<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Factor analysis of Jaquar Taps \u00a0 AUTHOR- PRACHI BHALLA, POOJA MAHER, PARIDHI JAIN \u00a0 \u00a0 Introduction Factor analysis for Jaquar taps helps pinpoint what really matters to customers, like durability, design, and ease of use. By analyzing survey data, we can uncover patterns in customer preferences, grouping similar features together (say, style and brand reputation)&hellip; <a class=\"more-link\" href=\"http:\/\/www.sachdevajk.in\/?p=22091\">Continue reading <span class=\"screen-reader-text\">Factor Analysis of Jaquar Taps<\/span><\/a><\/p>\n","protected":false},"author":139644,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[39],"tags":[2056],"class_list":["post-22091","post","type-post","status-publish","format-standard","hentry","category-marketing","tag-factoranalysis-digitalmarketing-internetmarketing-marketresearch","entry"],"_links":{"self":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/22091","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/users\/139644"}],"replies":[{"embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=22091"}],"version-history":[{"count":1,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/22091\/revisions"}],"predecessor-version":[{"id":22092,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/22091\/revisions\/22092"}],"wp:attachment":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=22091"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=22091"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=22091"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}