{"id":1886,"date":"2026-03-27T03:44:17","date_gmt":"2026-03-27T03:44:17","guid":{"rendered":"https:\/\/aaxonix.com\/resources\/?post_type=case_study&#038;p=1886"},"modified":"2026-03-27T04:27:36","modified_gmt":"2026-03-27T04:27:36","slug":"ethnic-wear-chain-dead-stock-unified-inventory","status":"publish","type":"case_study","link":"https:\/\/aaxonix.com\/resources\/case-studies\/ethnic-wear-chain-dead-stock-unified-inventory\/","title":{"rendered":""},"content":{"rendered":"<style>\n.cs-body{max-width:900px;margin:0 auto;padding:32px 0 56px;color:var(--muted);font-size:16px;line-height:1.85;}\n.cs-body h1{font-family:'Fraunces',serif;font-size:clamp(26px,3.5vw,40px);font-weight:900;color:var(--ink);line-height:1.15;margin:0 0 8px;}\n.cs-body h2{font-family:'Fraunces',serif;font-size:clamp(19px,2.4vw,26px);font-weight:800;color:var(--ink);margin:2.8em 0 .8em;line-height:1.2;}\n.cs-body 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class=\"cs-body\">\n\n<div class=\"cs-eyebrow\">Case Study &nbsp;&middot;&nbsp; Ethnic Wear Retail<\/div>\n<h1>How a 12-Outlet Ethnic Wear Chain Eliminated Dead Stock with Unified Inventory<\/h1>\n\n<div class=\"cs-snapshot\">\n  <div class=\"cs-snap-tile\"><div class=\"cs-snap-label\">Industry<\/div><div class=\"cs-snap-val\">Multi-Store Ethnic Wear Retail<\/div><\/div>\n  <div class=\"cs-snap-tile\"><div class=\"cs-snap-label\">Store Network<\/div><div class=\"cs-snap-val\">12 retail outlets across 4 cities<\/div><\/div>\n  <div class=\"cs-snap-tile\"><div class=\"cs-snap-label\">SKU Count<\/div><div class=\"cs-snap-val\">8,500+ active SKUs<\/div><\/div>\n  <div class=\"cs-snap-tile\"><div class=\"cs-snap-label\">Tools Deployed<\/div><div class=\"cs-snap-val\">Zoho Inventory, CRM, Desk, Analytics<\/div><\/div>\n<\/div>\n\n<p>This regional ethnic wear retailer operates 12 outlets across four cities in western India, selling sarees, lehengas, kurta sets, and bridal collections. With over 8,500 active SKUs spanning silk, cotton, and blended fabrics, the business faces seasonal demand swings tied to wedding seasons, Navratri, Diwali, and Eid. Store managers tracked stock in outlet-level spreadsheets, reorders were phone-based, and the head office had no consolidated view of what was sitting unsold across the network.<\/p>\n\n<h2>The Problem<\/h2>\n\n<p>Multi-store <a href=\"https:\/\/aaxonix.com\/industries\/retail\/\" class=\"sp-content-link\">retail operations<\/a> in ethnic wear depend on moving the right inventory to the right location at the right time. When each outlet operates as an inventory island, three compounding failures erode margins.<\/p>\n\n<div class=\"cs-problem-grid\">\n  <div class=\"cs-problem-card\">\n    <div class=\"cs-pc-icon\">\n      <svg viewBox=\"0 0 24 24\" aria-hidden=\"true\"><path d=\"M21 16V8a2 2 0 00-1-1.73l-7-4a2 2 0 00-2 0l-7 4A2 2 0 003 8v8a2 2 0 001 1.73l7 4a2 2 0 002 0l7-4A2 2 0 0021 16z\"\/><polyline points=\"3.27 6.96 12 12.01 20.73 6.96\"\/><line x1=\"12\" y1=\"22.08\" x2=\"12\" y2=\"12\"\/><\/svg>\n    <\/div>\n    <h3>Dead Stock Accumulation<\/h3>\n    <p>Without cross-store visibility, slow-moving sarees and lehengas piled up at outlets where local demand had shifted. At any given time, 22% of total inventory was classified as dead stock&mdash;items unsold for over 120 days. Annual carrying cost for this dead inventory was estimated at &#8377;56 lakhs across the chain.<\/p>\n  <\/div>\n  <div class=\"cs-problem-card\">\n    <div class=\"cs-pc-icon\">\n      <svg viewBox=\"0 0 24 24\" aria-hidden=\"true\"><circle cx=\"12\" cy=\"12\" r=\"10\"\/><polyline points=\"12 6 12 12 16 14\"\/><\/svg>\n    <\/div>\n    <h3>Slow Inter-Store Transfers<\/h3>\n    <p>When a store ran out of a popular design, the manager would call other outlets to check availability, negotiate quantities, and arrange courier pickup. This phone-based coordination took 5&ndash;7 days on average, by which time the customer had often moved on. An estimated 14% of walk-in customers left without purchase due to stockouts of items available elsewhere in the chain.<\/p>\n  <\/div>\n  <div class=\"cs-problem-card\">\n    <div class=\"cs-pc-icon\">\n      <svg viewBox=\"0 0 24 24\" aria-hidden=\"true\"><path d=\"M17 21v-2a4 4 0 00-4-4H5a4 4 0 00-4-4v-2\"\/><path d=\"M23 21v-2a4 4 0 00-3-3.87\"\/><path d=\"M16 3.13a4 4 0 010 7.75\"\/><\/svg>\n    <\/div>\n    <h3>Blind Replenishment Decisions<\/h3>\n    <p>Purchase orders were placed based on store manager intuition rather than data. Seasonal spikes around weddings and festivals caught procurement off guard, while over-ordering of off-season categories tied up working capital. The buying team had no SKU-level velocity data across the chain, resulting in &#8377;24L wasted annually on excess procurement of slow categories.<\/p>\n  <\/div>\n<\/div>\n\n<h2>The Solution Stack<\/h2>\n\n<p>Four Zoho modules were configured to create unified inventory visibility across all 12 outlets with demand-driven replenishment and structured inter-store transfer workflows.<\/p>\n\n<div class=\"cs-solution-stack\">\n  <div class=\"cs-sol-row\">\n    <div class=\"cs-sol-badge\">\n      <div class=\"cs-sol-product\">Zoho<\/div>\n      <div class=\"cs-sol-module\">Inventory<\/div>\n    <\/div>\n    <div class=\"cs-sol-body\">\n      <h3>Multi-Location Stock Ledger<\/h3>\n      <ul>\n        <li>Each of the 12 outlets mapped as a separate warehouse with barcode-based stock receipts, sales deductions, and transfer logging<\/li>\n        <li>Real-time central dashboard showing current quantity, ageing, and reorder status per SKU per location<\/li>\n        <li>Automated reorder points set per SKU per outlet using 90-day rolling sales velocity with seasonal adjustment factors<\/li>\n        <li>Draft purchase orders auto-generated when stock dips below threshold, sent to procurement queue for review<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <p><a href=\"https:\/\/aaxonix.com\/products\/zoho-inventory\/\" class=\"sp-content-link\">Zoho Inventory multi-location tracking<\/a> served as the central stock ledger, giving the head office a single view of 8,500+ SKUs across all 12 outlets in real time.<\/p>\n  <div class=\"cs-sol-row\">\n    <div class=\"cs-sol-badge\">\n      <div class=\"cs-sol-product\">Zoho<\/div>\n      <div class=\"cs-sol-module\">CRM<\/div>\n    <\/div>\n    <div class=\"cs-sol-body\">\n      <h3>Walk-In Capture and Loyalty Pipeline<\/h3>\n      <ul>\n        <li>Walk-in customers captured at billing counter with phone number, occasion type, and fabric preferences<\/li>\n        <li>Automated WhatsApp alerts for new arrivals matching recorded preferences and past purchase categories<\/li>\n        <li>Loyalty tier tracking based on annual spend with tier-specific discount rules pushed to POS<\/li>\n        <li>Wedding-season campaign pipelines triggered 6 weeks before peak periods using regional calendar data<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <p><a href=\"https:\/\/aaxonix.com\/products\/zoho-crm\/\" class=\"sp-content-link\">Zoho CRM contact capture<\/a> turned anonymous walk-ins into profiled repeat buyers, enabling targeted campaigns ahead of wedding and festival seasons.<\/p>\n  <div class=\"cs-sol-row\">\n    <div class=\"cs-sol-badge\">\n      <div class=\"cs-sol-product\">Zoho<\/div>\n      <div class=\"cs-sol-module\">Desk<\/div>\n    <\/div>\n    <div class=\"cs-sol-body\">\n      <h3>Inter-Store Transfer Ticketing<\/h3>\n      <ul>\n        <li>Store manager raises a transfer request ticket specifying SKU, quantity, and urgency level<\/li>\n        <li>System auto-identifies nearest outlet with available stock and routes the ticket for dispatch confirmation<\/li>\n        <li>SLA timers enforce 24-hour dispatch and 48-hour delivery with escalation to regional manager on breach<\/li>\n        <li>Goods receipt logged via barcode scan at receiving store, closing the ticket and updating both warehouse ledgers<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <p><a href=\"https:\/\/aaxonix.com\/products\/zoho-desk\/\" class=\"sp-content-link\">Zoho Desk ticketed workflows<\/a> replaced phone-based coordination with structured transfer requests, cutting average transfer time from 5&ndash;7 days to 1.5 days.<\/p>\n  <div class=\"cs-sol-row\">\n    <div class=\"cs-sol-badge\">\n      <div class=\"cs-sol-product\">Zoho<\/div>\n      <div class=\"cs-sol-module\">Analytics<\/div>\n    <\/div>\n    <div class=\"cs-sol-body\">\n      <h3>Demand Intelligence and Dead Stock Alerts<\/h3>\n      <ul>\n        <li>SKU velocity heatmaps showing sell-through rate by outlet, category, fabric type, and price band<\/li>\n        <li>Dead stock alerts triggered at 90 days with recommended markdown or transfer-out actions<\/li>\n        <li>Seasonal demand forecasting using prior-year sales data overlaid with regional festival calendars<\/li>\n        <li>Procurement recommendations generated weekly with suggested quantities per category per outlet<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n<\/div>\n\n<h2>Before vs. After<\/h2>\n\n<table class=\"cs-ba-table\">\n  <thead>\n    <tr>\n      <th>Process Area<\/th>\n      <th class=\"before\">Before<\/th>\n      <th class=\"after\">After<\/th>\n    <\/tr>\n  <\/thead>\n  <tbody>\n    <tr>\n      <td>Inventory visibility<\/td>\n      <td class=\"before\">Outlet-level spreadsheets, no central view<\/td>\n      <td class=\"after\">Real-time dashboard across 12 locations<\/td>\n    <\/tr>\n    <tr>\n      <td>Dead stock (% of inventory)<\/td>\n      <td class=\"before\">22% of total inventory aged 120+ days<\/td>\n      <td class=\"after\">Under 15%&mdash;32% reduction<\/td>\n    <\/tr>\n    <tr>\n      <td>Inter-store transfer time<\/td>\n      <td class=\"before\">5&ndash;7 days via phone coordination<\/td>\n      <td class=\"after\">1.5 days average via ticketed workflow<\/td>\n    <\/tr>\n    <tr>\n      <td>Reorder decisions<\/td>\n      <td class=\"before\">Store manager intuition, no velocity data<\/td>\n      <td class=\"after\">Auto-generated POs based on 90-day rolling sales<\/td>\n    <\/tr>\n    <tr>\n      <td>Carrying cost (dead stock)<\/td>\n      <td class=\"before\">&#8377;56L\/year estimated<\/td>\n      <td class=\"after\">&#8377;38L\/year&mdash;&#8377;18L annual saving<\/td>\n    <\/tr>\n    <tr>\n      <td>Stockout-driven walkouts<\/td>\n      <td class=\"before\">~14% of walk-ins left due to stockouts<\/td>\n      <td class=\"after\">Under 5% with cross-store fulfilment<\/td>\n    <\/tr>\n    <tr>\n      <td>Customer re-engagement<\/td>\n      <td class=\"before\">No systematic follow-up or profiling<\/td>\n      <td class=\"after\">WhatsApp alerts based on preferences and occasion<\/td>\n    <\/tr>\n  <\/tbody>\n<\/table>\n\n<h2>Implementation Phases<\/h2>\n\n<p>The project followed a phased rollout managed by our <a href=\"https:\/\/aaxonix.com\/services\/zoho\/\" class=\"sp-content-link\">Zoho implementation<\/a> team, completing full deployment across all 12 outlets in ten weeks.<\/p>\n\n<div class=\"cs-timeline\">\n  <div class=\"cs-tl-item\">\n    <div class=\"cs-tl-badge\">1<\/div>\n    <div class=\"cs-tl-content\">\n      <div class=\"cs-tl-title\">Inventory Master and Warehouse Setup <span class=\"cs-tl-dur\">Weeks 1&ndash;3<\/span><\/div>\n      <ul>\n        <li>Imported 8,500+ SKU records with category, fabric, colour, size, cost, and MRP attributes<\/li>\n        <li>Mapped 12 outlets as separate warehouses with opening stock captured via physical audit and barcode tagging<\/li>\n        <li>Configured reorder points per SKU per outlet using historical sales data from POS exports<\/li>\n        <li>Built real-time inventory dashboard for head office showing stock levels, ageing, and reorder queue<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <div class=\"cs-tl-item\">\n    <div class=\"cs-tl-badge\">2<\/div>\n    <div class=\"cs-tl-content\">\n      <div class=\"cs-tl-title\">CRM and Customer Profiling <span class=\"cs-tl-dur\">Weeks 3&ndash;5<\/span><\/div>\n      <ul>\n        <li>Configured walk-in capture workflow at billing counters to record phone, occasion, and fabric preferences<\/li>\n        <li>Imported 18,000+ existing customer records from loyalty cards and POS history<\/li>\n        <li>Built loyalty tier rules with automated discount push to POS based on annual spend thresholds<\/li>\n        <li>Created WhatsApp campaign templates for new arrivals, seasonal collections, and occasion-based recommendations<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <div class=\"cs-tl-item\">\n    <div class=\"cs-tl-badge\">3<\/div>\n    <div class=\"cs-tl-content\">\n      <div class=\"cs-tl-title\">Transfer Ticketing and Desk Workflows <span class=\"cs-tl-dur\">Weeks 5&ndash;7<\/span><\/div>\n      <ul>\n        <li>Built transfer request form in Desk with SKU lookup, quantity, and urgency fields<\/li>\n        <li>Configured auto-routing logic to identify nearest outlet with available stock<\/li>\n        <li>Set SLA timers: 24-hour dispatch, 48-hour delivery, with regional manager escalation on breach<\/li>\n        <li>Deployed barcode-based goods receipt at receiving outlets to close tickets and update ledgers<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n  <div class=\"cs-tl-item\">\n    <div class=\"cs-tl-badge\">4<\/div>\n    <div class=\"cs-tl-content\">\n      <div class=\"cs-tl-title\">Analytics, Training, and Go-Live <span class=\"cs-tl-dur\">Weeks 8&ndash;10<\/span><\/div>\n      <ul>\n        <li>Built Analytics dashboards: SKU velocity heatmaps, dead stock alerts, seasonal forecasting, procurement recommendations<\/li>\n        <li>Conducted outlet-level training for store managers and billing staff across all 12 locations<\/li>\n        <li>Ran three-week parallel period comparing spreadsheet records against system output<\/li>\n        <li>Full go-live with legacy spreadsheets archived and quarterly review cadence established<\/li>\n      <\/ul>\n    <\/div>\n  <\/div>\n<\/div>\n\n<h2>Results<\/h2>\n\n<p>Within the first full year on the unified system, the retailer measured significant improvements across dead stock reduction, transfer speed, and carrying cost savings. The numbers below compare the first full year on Zoho against the prior year.<\/p>\n\n<div class=\"cs-stats-grid\">\n  <div class=\"cs-stat-card\">\n    <div class=\"cs-stat-num\" id=\"cs-counter-1\" data-target=\"32\" data-suffix=\"%\">0<\/div>\n    <div class=\"cs-stat-lbl\">Reduction in Dead Stock<\/div>\n  <\/div>\n  <div class=\"cs-stat-card\">\n    <div class=\"cs-stat-num\" id=\"cs-counter-2\" data-target=\"3\" data-suffix=\"&times;\">0<\/div>\n    <div class=\"cs-stat-lbl\">Faster Inter-Store Transfers<\/div>\n  <\/div>\n  <div class=\"cs-stat-card\">\n    <div class=\"cs-stat-num\" id=\"cs-counter-3\" data-target=\"18\" data-prefix=\"&#8377;\" data-suffix=\"L\">0<\/div>\n    <div class=\"cs-stat-lbl\">Annual Carrying Cost Saved<\/div>\n  <\/div>\n<\/div>\n\n<div class=\"cs-chart-wrap\">\n  <div class=\"cs-chart-title\">Inventory Health: Before vs. After<\/div>\n  <canvas id=\"cs-chart-1\" height=\"220\"><\/canvas>\n<\/div>\n\n<div class=\"cs-doughnut-row\">\n  <div class=\"cs-chart-wrap\">\n    <div class=\"cs-chart-title\">Stock Age Distribution &mdash; Before<\/div>\n    <canvas id=\"cs-chart-2a\" height=\"200\"><\/canvas>\n  <\/div>\n  <div class=\"cs-chart-wrap\">\n    <div class=\"cs-chart-title\">Stock Age Distribution &mdash; After<\/div>\n    <canvas id=\"cs-chart-2b\" height=\"200\"><\/canvas>\n  <\/div>\n<\/div>\n\n<div class=\"cs-takeaway\">\n  <h3>What This Means for Multi-Store Retailers<\/h3>\n  <p>Ethnic wear retail runs on seasonal timing and regional taste. A saree that sits unsold for four months at one outlet may be the top seller at another location 200 kilometres away. When inventory lives in disconnected spreadsheets, every store becomes a silo&mdash;overstocked in some categories, starving in others. Unified visibility does not just reduce carrying costs; it turns the entire chain into a single, responsive inventory pool where stock flows to wherever demand exists. The result is fewer markdowns, fewer walkouts, and procurement decisions driven by data instead of guesswork.<\/p>\n<\/div>\n\n<h2>Frequently Asked Questions<\/h2>\n\n<div class=\"cs-faq\">\n  <div class=\"cs-faq-item\">\n    <div class=\"cs-faq-q\">How does unified inventory work across multiple retail outlets?<\/div>\n    <p class=\"cs-faq-a\">Each outlet is mapped as a separate warehouse in the inventory system. Every sale, return, and stock receipt updates the central ledger in real time via barcode scanning. The head office sees a single dashboard showing current quantities across all 12 locations.<\/p>\n  <\/div>\n  <div class=\"cs-faq-item\">\n    <div class=\"cs-faq-q\">What made inter-store transfers faster after implementation?<\/div>\n    <p class=\"cs-faq-a\">Transfers shifted from phone-based coordination to a ticketed workflow with SLA timers. The requesting store raises a ticket, the sending store confirms and dispatches, and goods receipt is logged via barcode scan, replacing a 5&ndash;7 day cycle with 1.5 day average.<\/p>\n  <\/div>\n  <div class=\"cs-faq-item\">\n    <div class=\"cs-faq-q\">How were reorder points calculated for ethnic wear SKUs?<\/div>\n    <p class=\"cs-faq-a\">Reorder points were set per SKU per outlet using 90-day rolling sales velocity, accounting for seasonal spikes like wedding and festive periods. When stock dips below threshold, a draft purchase order auto-generates for procurement review.<\/p>\n  <\/div>\n  <div class=\"cs-faq-item\">\n    <div class=\"cs-faq-q\">Can this approach work for retailers with fewer than 12 outlets?<\/div>\n    <p class=\"cs-faq-a\">Yes. The same architecture applies to chains with as few as 3&ndash;4 outlets. Smaller chains often see faster ROI because per-store setup effort is lower and inventory imbalances are easier to correct once visibility exists.<\/p>\n  <\/div>\n<\/div>\n\n<\/div>\n\n<script>\n(function(){\n  var CU=(typeof countUp!=='undefined'&&countUp.CountUp)?countUp.CountUp:(typeof CountUp!=='undefined'?CountUp:null);\n\n  function initCounters(){\n    if(!CU) return;\n    document.querySelectorAll('[id^=\"cs-counter-\"]').forEach(function(el){\n      var cu=new CU(el.id,parseFloat(el.dataset.target)||0,{\n        duration:2.2,useEasing:true,useGrouping:true,\n        prefix:el.dataset.prefix||'',\n        suffix:el.dataset.suffix||'',\n        decimalPlaces:parseInt(el.dataset.decimals||'0',10)\n      });\n      if(!cu.error) cu.start();\n    });\n  }\n\n  function initCharts(){\n    if(typeof Chart==='undefined') return;\n\n    var c1=document.getElementById('cs-chart-1');\n    if(c1) new Chart(c1,{type:'bar',data:{labels:['Dead Stock (% of Inventory)','Inter-Store Transfer (Days)','Carrying Cost (\u20b9L\/Year)','Stockout Walkouts (%)'],datasets:[{label:'Before',data:[22,6,56,14],backgroundColor:'#94A3B8',borderRadius:4},{label:'After',data:[15,1.5,38,5],backgroundColor:'#E8650A',borderRadius:4}]},options:{indexAxis:'y',responsive:true,animation:{duration:1200},plugins:{legend:{position:'bottom',labels:{font:{family:'Poppins',size:12},color:'#64748B'}}},scales:{x:{grid:{color:'rgba(0,0,0,.06)'},ticks:{font:{family:'Poppins',size:11},color:'#64748B'}},y:{grid:{display:false},ticks:{font:{family:'Poppins',size:12},color:'#334155'}}}}});\n\n    var c2a=document.getElementById('cs-chart-2a');\n    if(c2a) new Chart(c2a,{type:'doughnut',data:{labels:['0\u201330 days','31\u201360 days','61\u201390 days','91\u2013120 days','120+ days'],datasets:[{data:[28,20,16,14,22],backgroundColor:['#0F172A','#1E293B','#475569','#94A3B8','#E8650A'],borderWidth:0}]},options:{responsive:true,cutout:'55%',animation:{duration:1200},plugins:{legend:{position:'bottom',labels:{font:{family:'Poppins',size:11},color:'#64748B',padding:12}}}}});\n\n    var c2b=document.getElementById('cs-chart-2b');\n    if(c2b) new Chart(c2b,{type:'doughnut',data:{labels:['0\u201330 days','31\u201360 days','61\u201390 days','91\u2013120 days','120+ days'],datasets:[{data:[35,25,15,10,15],backgroundColor:['#0F172A','#1E293B','#475569','#94A3B8','#E8650A'],borderWidth:0}]},options:{responsive:true,cutout:'55%',animation:{duration:1200},plugins:{legend:{position:'bottom',labels:{font:{family:'Poppins',size:11},color:'#64748B',padding:12}}}}});\n  }\n\n  var grid=document.querySelector('.cs-stats-grid');\n  if(grid&&'IntersectionObserver' in window){\n    var done=false;\n    new IntersectionObserver(function(entries,obs){\n      if(entries[0].isIntersecting&&!done){done=true;obs.disconnect();initCounters();initCharts();}\n    },{threshold:0.1}).observe(grid);\n  } else {\n    initCounters(); initCharts();\n  }\n})();\n<\/script>","protected":false},"excerpt":{"rendered":"<p>A regional ethnic wear retailer with 12 outlets replaced disconnected spreadsheets with unified inventory visibility, cutting dead stock by 32% and saving&#8230;<\/p>\n","protected":false},"featured_media":1892,"template":"","meta":{"cs_card_title":"How a 12-Outlet Ethnic Wear Chain Eliminated Dead Stock with Unified Inventory","cs_result_num":"32%","cs_result_label":"Reduction in Dead Stock","cs_stat2_num":"3\u00d7","cs_stat2_label":"Faster Inter-Store Stock Transfers","cs_stat3_num":"\u20b918L","cs_stat3_label":"Annual Inventory Carrying Cost Saved","cs_challenge":"Disconnected store inventories caused overstocking at some locations and stockouts at others.","cs_solution":"Unified inventory visibility and demand-based replenishment across 12 retail outlets.","cs_tools":"Zoho Inventory, Zoho CRM, Zoho Desk, Zoho Analytics"},"cs_industry":[435],"class_list":["post-1886","case_study","type-case_study","status-publish","has-post-thumbnail","hentry","cs_industry-retail"],"_links":{"self":[{"href":"https:\/\/aaxonix.com\/resources\/wp-json\/wp\/v2\/case_study\/1886","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aaxonix.com\/resources\/wp-json\/wp\/v2\/case_study"}],"about":[{"href":"https:\/\/aaxonix.com\/resources\/wp-json\/wp\/v2\/types\/case_study"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aaxonix.com\/resources\/wp-json\/wp\/v2\/media\/1892"}],"wp:attachment":[{"href":"https:\/\/aaxonix.com\/resources\/wp-json\/wp\/v2\/media?parent=1886"}],"wp:term":[{"taxonomy":"cs_industry","embeddable":true,"href":"https:\/\/aaxonix.com\/resources\/wp-json\/wp\/v2\/cs_industry?post=1886"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}