{"id":1593,"date":"2026-08-21T12:40:48","date_gmt":"2026-08-21T10:40:48","guid":{"rendered":"https:\/\/indusmart.digital\/?p=1593"},"modified":"2026-10-19T11:57:13","modified_gmt":"2026-10-19T09:57:13","slug":"predict-customers-ready-to-buy","status":"publish","type":"post","link":"https:\/\/indusmart.digital\/en\/blog\/predict-customers-ready-to-buy\/","title":{"rendered":"How to use AI to predict which customers are ready to buy"},"content":{"rendered":"<div class=\"wp-block-group alignfull ind-pagehead is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-wrap is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-crumb ind-contenidor wp-block-paragraph\"><a href=\"\/en\/\">Home<\/a> \u203a <a href=\"\/en\/blog\/\">Blog<\/a> \u203a <a href=\"\/en\/blog\/topics\/ai-applied-to-industry\/\">AI &amp; automation<\/a><\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><span class=\"ind-eyebrow\">AI &amp; automation<\/span><\/p><h1 class=\"ind-ph wp-block-heading\">AI for B2B sales: how to predict <span class=\"ind-hl\">which customers are ready to buy<\/span><\/h1><p class=\"ind-metaline ind-contenidor wp-block-paragraph\"><span><span class=\"ind-av\">CM<\/span> By <b>Cesc Marsal<\/b><\/span><span>\u00b7 Mar 17, 2026<\/span><span>\u00b7 9 min read<\/span><span>\u00b7 Updated 2026<\/span><\/p><\/div><\/div>\n\n<section class=\"wp-block-group alignfull is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-wrap ind-artwrap is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-prose is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-answer is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-lab ind-icona-abans ind-icona-pin ind-contenidor wp-block-paragraph\"> Quick summary<\/p><p class=\"wp-block-paragraph\">Your sales team is tracking <b>50 to 200 accounts<\/b> at once, and there's no humanly possible way to know which ones are really about to buy. AI lead scoring, also known as <b>predictive lead scoring<\/b>, does know: it learns from your sales history and gives each account a likelihood to close that's <b>75-85% accurate<\/b> over 90 days, compared to 25-35% for human intuition. Best of all, you probably already have the data it needs, scattered across your CRM. A serious project takes <b>90 days, in phases<\/b>, not a year. And it doesn't replace your sales reps: it takes cold accounts off their plate so they can focus on the hot ones.<\/p><\/div><p class=\"wp-block-paragraph\">Even at a well-run industrial company, every sales rep juggles dozens of active accounts, each with its own sales cycle, contacts, and unanswered emails. Staying focused on who's genuinely close to buying isn't a matter of talent: it's <strong>mathematically impossible<\/strong> for one person. AI for B2B sales changes that at the root, and it's not science fiction: it's already happening at Spanish manufacturers in 2026. Here's how it works, what you need to get started, and why the first company in your industry to get it right will have the edge for years.<\/p><h2 class=\"wp-block-heading\" id=\"a1\">Why your sales intuition is no longer enough<\/h2><p class=\"wp-block-paragraph\">This is the stat that hits industrial leadership teams hardest: a high-performing B2B sales rep spends <strong>73% of their time on accounts that never close<\/strong>. Not for lack of skill, but because they have no systematic way to tell which deals will close and which won't. If they manage 30 active accounts in a month, their typical close rate is around 10%: three sales, and 27 opportunities that drain time, energy, and motivation with no return.<\/p><p class=\"wp-block-paragraph\">The problem isn't productivity. It's that <strong>no human can process the hundreds of signals each account sends every week all at once<\/strong>. An algorithm can. That's where the difference begins.<\/p><h3 class=\"wp-block-heading\" id=\"a1a\">The buying signals your team misses (but algorithms catch)<\/h3><p class=\"wp-block-paragraph\">As a B2B customer nears a decision, their behavior changes and leaves a digital trail that no person could process in time, but that's obvious to AI. These are the signals that best predict a purchase:<\/p><ul class=\"wp-block-list\"><li><strong>A sudden spike in website visits<\/strong> from the customer's domain: someone inside is doing research.<\/li><li><strong>Repeated downloads<\/strong> of spec sheets, comparisons, or case studies from their industry.<\/li><li><strong>Opening old emails<\/strong> that had sat untouched for months: classic re-engagement.<\/li><li><strong>Visits to high-intent pages<\/strong> like pricing or terms.<\/li><li><strong>LinkedIn activity<\/strong> related to your product category.<\/li><\/ul><p class=\"wp-block-paragraph\">No single signal means anything on its own. What a good model flags as a \u201cbuying alert\u201d is a <strong>weighted combination of several signals within a short period<\/strong>. That's when your sales rep gets the alert to call before the competition does.<\/p><h3 class=\"wp-block-heading\" id=\"a1b\">What's changed in AI lead scoring over the past 18 months<\/h3><p class=\"wp-block-paragraph\">Until recently, lead scoring was manual: marketing and sales set rules like \u201cdownloads the ebook = 10 points, requests a quote = 50 points.\u201d It worked, but it was rigid, slow to update, and not very accurate: it was right <strong>30-40%<\/strong> of the time.<\/p><p class=\"wp-block-paragraph\">What's changed is that platforms now use <strong>machine learning that learns from your historical data<\/strong>. The model analyzes the patterns shared by customers who did close, compares them with current leads, and returns a real probability of closing. Well-trained models reach <strong>75-85% accuracy in predicting closes within the next 90 days<\/strong>. For a pipeline of 50 opportunities, that means knowing with reasonable certainty which 35 will close and which won't.<\/p><h2 class=\"wp-block-heading\" id=\"a2\">How predictive analytics for sales really works<\/h2><p class=\"wp-block-paragraph\">Everything you hear about AI sounds complicated, but this <strong>isn't magic: it's advanced statistics, neatly packaged<\/strong>. Understanding the three components underneath takes the fear out of it and helps you decide whether it's right for your company: the data, the model, and the integration with your CRM.<\/p><div class=\"wp-block-group ind-threecol is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-stepblock is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-t ind-contenidor wp-block-paragraph\">01<\/p><h3 class=\"ind-as-h4 wp-block-heading\">The data<\/h3><p class=\"wp-block-paragraph\">Website behavior, email engagement, CRM history, firmographic data, and, above all, your history of won and lost deals. You already have most of it.<\/p><\/div><div class=\"wp-block-group ind-stepblock is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-t ind-contenidor wp-block-paragraph\">02<\/p><h4 class=\"wp-block-heading\">The model<\/h4><p class=\"wp-block-paragraph\">Algorithms designed for small datasets that learn your closing patterns and apply them to every new lead, with no coding on your part.<\/p><\/div><div class=\"wp-block-group ind-stepblock is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-t ind-contenidor wp-block-paragraph\">03<\/p><h4 class=\"wp-block-heading\">The integration<\/h4><p class=\"wp-block-paragraph\">A 0-100 score that lives inside your CRM and prioritizes your sales rep's list, plus automatic alerts when an account heats up.<\/p><\/div><\/div><h3 class=\"wp-block-heading\" id=\"a2a\">The data your AI needs (data you already have)<\/h3><p class=\"wp-block-paragraph\">Here's the good news: you probably already have most of the data AI needs, scattered across your CRM, marketing platform, and web analytics. The job isn't creating new data; it's <strong>connecting what you already have<\/strong>. A good model cross-references website behavior (pages, frequency, downloads), email engagement (opens, clicks, replies), CRM history (meetings, proposals, stages), and firmographic data. But the most valuable input is your <strong>history of won and lost deals<\/strong>: that's what lets the model learn which patterns led to wins and which didn't.<\/p><p class=\"wp-block-paragraph\">A midsize industrial company typically <strong>already generates 70-90% of this data<\/strong>; it's just stuck in silos. That's why the first phase of any serious project is consolidating it into a single clean repository the model can learn from.<\/p><h3 class=\"wp-block-heading\" id=\"a2b\">The models that work best in industrial B2B<\/h3><p class=\"wp-block-paragraph\">Not every model works here. Many are built for very high-volume B2C (e-commerce, retail) and need millions of transactions. In manufacturing, where you handle <strong>hundreds of deals a year, not millions<\/strong>, <em>gradient boosting<\/em> models and small neural networks tuned for limited data work better. Some platforms come with them prepackaged, so you don't need an in-house data science team, and they deliver visible results in <strong>6-8 weeks<\/strong>.<\/p><p class=\"wp-block-paragraph\">Your selection should be vendor-agnostic: if you already use a CRM, it makes sense to evaluate its built-in predictive layer first; if you want something more independent or sophisticated, there are specialized tools. What matters isn't the brand but the balance between what you'll invest and what that platform can do with your actual data volume.<\/p><h3 class=\"wp-block-heading\" id=\"a2c\">How it fits into your CRM and your current team<\/h3><p class=\"wp-block-paragraph\">The most reasonable concern we hear is, \u201cWill my team have to change everything they do?\u201d The answer is no. When it's implemented well, the sales rep <strong>doesn't even notice the AI working behind the scenes<\/strong>: the only change is that their account list arrives intelligently prioritized. Each account gets a score from 0 to 100 that updates in real time, and when they log into the CRM in the morning, they see accounts sorted by likelihood to close: red for urgent (&gt;80), yellow for follow-up (50-80), green at the bottom.<\/p><p class=\"wp-block-paragraph\">AI can also <strong>trigger automatic alerts<\/strong>: if an account jumps from 40 to 75 in 48 hours because someone has been browsing your website heavily and opening emails, the sales rep gets an instant alert to reach out. It's the support every good industrial sales rep has always wanted, without turning them into a software operator.<\/p><h2 class=\"wp-block-heading\" id=\"a3\">How to launch a project without wasting money<\/h2><p class=\"wp-block-paragraph\">You don't need to be Tesla or have an astronomical budget to implement predictive AI. It's well within reach for midsize companies with a well-designed, phased project. What it does require is an honest approach: <strong>start small, validate with real data, and scale what works<\/strong>. Here's how we structure these projects at induSmart.<\/p><h3 class=\"wp-block-heading\" id=\"a3a\">The 3 phases of a realistic project (90 days, not 12 months)<\/h3><p class=\"wp-block-paragraph\">Most profitable projects get done in 90 well-structured days, not a year:<\/p><ul class=\"wp-block-list\"><li><strong>Phase 1 (weeks 1-4): data consolidation.<\/strong> We connect your CRM, marketing, website, and email; remove duplicates; and standardize critical fields to create a single, clean data repository.<\/li><li><strong>Phase 2 (weeks 5-8): training and validation.<\/strong> We load your history of won and lost deals, the model learns the patterns, and we validate it against recent accounts with known outcomes until it reaches at least 70-80% accuracy.<\/li><li><strong>Phase 3 (weeks 9-12): integration and training.<\/strong> We turn on the scores in your CRM, set up the alerts, and train your sales team to interpret them.<\/li><\/ul><p class=\"wp-block-paragraph\">From day 90 on, <strong>the system runs on its own and improves every month<\/strong> as new data comes in.<\/p><h3 class=\"wp-block-heading\" id=\"a3b\">Human prediction vs. predictive AI<\/h3><p class=\"wp-block-paragraph\">The difference is operational, and it translates into opportunities that used to slip away and now close on time:<\/p><figure class=\"wp-block-table ind-cmp\"><table><thead><tr><th>Criteria<\/th><th>Sales intuition<\/th><th>Predictive AI<\/th><\/tr><\/thead><tbody><tr><td>90-day close accuracy<\/td><td>25-35%<\/td><td>75-85%<\/td><\/tr><tr><td>Signals processed per account<\/td><td>Whichever they remember<\/td><td>All of them, in real time<\/td><\/tr><tr><td>Prioritization criteria<\/td><td>Recency and gut feeling<\/td><td>Likelihood to close<\/td><\/tr><tr><td>Hot account alert<\/td><td>Whenever they remember<\/td><td>Automatic alert within 48 hours<\/td><\/tr><\/tbody><\/table><\/figure><div class=\"wp-block-group ind-takeaways is-layout-flow wp-block-group-is-layout-flow\"><h4 class=\"wp-block-heading\">What you take away from this article<\/h4><ul class=\"wp-block-list\"><li>No sales rep can process every signal from 50-200 accounts: AI can, which is why it can predict who's going to buy.<\/li><li>Predictive lead scoring correctly predicts 75-85% of 90-day closes, compared to 25-35% for intuition.<\/li><li>You probably already have 70-90% of the data you need; the work is connecting it, not creating it.<\/li><li>A serious project takes 90 days, in phases: data, model, integration.<\/li><li>AI doesn't replace sales reps: it takes cold accounts off their plate so they can spend their time on hot ones.<\/li><\/ul><\/div><h2 class=\"wp-block-heading\" id=\"a4\">Frequently asked questions<\/h2><div class=\"wp-block-group ind-faq is-layout-flow wp-block-group-is-layout-flow\"><details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\" open><summary>How much does it cost to implement predictive AI at my company?<\/summary><p class=\"wp-block-paragraph\">For a midsize industrial company, a realistic project requires an initial investment of <strong>\u20ac15,000 to \u20ac45,000<\/strong> (data consolidation, model training, CRM integration, and team training). On top of that, there's a platform license of <strong>\u20ac300 to \u20ac1,500 a month<\/strong>, depending on volume and tool. Compared to the cost of a sales rep spending 73% of their time on accounts that don't close, the payback usually comes within 4-6 months.<\/p><\/details><details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Do I need a lot of data for it to work?<\/summary><p class=\"wp-block-paragraph\">Less than you think. A decent model needs a <strong>minimum of 100-200 historical closed deals<\/strong> to start learning useful patterns, and almost any company with more than three years in business has that. Quality matters more than quantity: 150 well-documented deals outperform 500 poorly labeled ones.<\/p><\/details><details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>What accuracy can I realistically expect?<\/summary><p class=\"wp-block-paragraph\">Well-trained models in industrial B2B reach <strong>75-85% accuracy<\/strong> in predicting 90-day closes: if one tells you an account has an 85% chance of closing, it's right 8 times out of 10. Human intuition, according to benchmark studies, tops out at 25-35%.<\/p><\/details><details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Does it replace the sales team?<\/summary><p class=\"wp-block-paragraph\">Not at all: it amplifies it. AI prioritizes, alerts, and suggests, but the sales rep is still the one who builds the relationship, negotiates, and closes. What it eliminates is time wasted on cold accounts. Human conversation and personal trust are still decisive in closing industrial deals.<\/p><\/details><details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>What types of platforms are available?<\/summary><p class=\"wp-block-paragraph\">There are several types, and your choice should be vendor-agnostic: predictive layers built into the CRM itself (convenient if you already use one), more independent specialized tools, and full AI-powered ABM platforms (more powerful, with bigger budgets). For midsize companies, we recommend prioritizing the best value for the money and the support to get started without a data science team.<\/p><\/details><details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>How long does it take to deliver results?<\/summary><p class=\"wp-block-paragraph\">Operational results (scores your team uses every day) start on <strong>day 90<\/strong>, when the initial project wraps up. Measurable revenue results take another 3-6 months, because industrial sales cycles are long. The first metric to move is your pipeline opportunity conversion rate, which typically rises 20-40% in the first two quarters.<\/p><\/details><\/div><div class=\"wp-block-group ind-authorbox is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-av ind-contenidor wp-block-paragraph\">CM<\/p><p class=\"ind-contenidor wp-block-paragraph\"><b>Cesc Marsal<\/b><small>Digital solutions architect at induSmart. He builds robust, scalable infrastructure that turns each industrial company's needs into precise, practical technology.<\/small><a href=\"\/en\/blog\/authors\/cesc-marsal\/\" class=\"ind-lk\">See the author&#x27;s profile \u2192<\/a><\/p><\/div><p class=\"ind-u11 ind-contenidor wp-block-paragraph\"><a href=\"\/en\/free-audit\/\" class=\"ind-btn ind-btn-primary\">Request your free assessment \u2192<\/a><a href=\"\/en\/consulting\/\" class=\"ind-btn ind-btn-ghost\">See how we apply AI<\/a><\/p><h2 id=\"a5\" class=\"ind-u16 wp-block-heading\">Related articles<\/h2><div class=\"wp-block-group ind-grid3 is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-post ind-u04 ind-amb-enllac is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-ph ind-contenidor wp-block-paragraph\"><span class=\"ind-t\">Acquisition<\/span><\/p><div class=\"wp-block-group ind-bd is-layout-flow wp-block-group-is-layout-flow\"><h3 class=\"ind-as-h4 wp-block-heading\">Industrial B2B lead generation: 15 tactics that work in 2026<\/h3><div class=\"wp-block-group ind-author is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-av ind-contenidor wp-block-paragraph\">CB<\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><small>Carles<\/small><\/p><\/div><\/div><p class=\"ind-contenidor wp-block-paragraph\"><a class=\"ind-estirat\" href=\"\/en\/blog\/\" aria-label=\"Industrial B2B lead generation: 15 tactics that work in 2026\"><\/a><\/p><\/div><div class=\"wp-block-group ind-post ind-u04 ind-amb-enllac is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-ph ind-contenidor wp-block-paragraph\"><span class=\"ind-t\">AI &amp; automation<\/span><\/p><div class=\"wp-block-group ind-bd is-layout-flow wp-block-group-is-layout-flow\"><h4 class=\"wp-block-heading\">Building AI agents for industrial companies<\/h4><div class=\"wp-block-group ind-author is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-av ind-contenidor wp-block-paragraph\">CM<\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><small>Cesc<\/small><\/p><\/div><\/div><p class=\"ind-contenidor wp-block-paragraph\"><a class=\"ind-estirat\" href=\"\/en\/blog\/\" aria-label=\"Building AI agents for industrial companies\"><\/a><\/p><\/div><div class=\"wp-block-group ind-post ind-u04 ind-amb-enllac is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-ph ind-contenidor wp-block-paragraph\"><span class=\"ind-t\">Conversion<\/span><\/p><div class=\"wp-block-group ind-bd is-layout-flow wp-block-group-is-layout-flow\"><h4 class=\"wp-block-heading\">Marketing automation: sequences that convert in industrial B2B<\/h4><div class=\"wp-block-group ind-author is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-av ind-contenidor wp-block-paragraph\">CB<\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><small>Carles<\/small><\/p><\/div><\/div><p class=\"ind-contenidor wp-block-paragraph\"><a class=\"ind-estirat\" href=\"\/en\/blog\/\" aria-label=\"Marketing automation: sequences that convert in industrial B2B\"><\/a><\/p><\/div><\/div><\/div><aside class=\"wp-block-group ind-aside is-layout-flow wp-block-group-is-layout-flow\"><div class=\"wp-block-group ind-toc is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-toc-h ind-contenidor wp-block-paragraph\">Content<\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><a href=\"#a1\">Why intuition isn&#x27;t enough<\/a><\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><a href=\"#a2\">How predictive AI works<\/a><\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><a href=\"#a3\">How to start the project<\/a><\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><a href=\"#a4\">FAQ<\/a><\/p><\/div><div class=\"wp-block-group ind-authorbox ind-u17 is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-av ind-contenidor wp-block-paragraph\">CM<\/p><p class=\"ind-contenidor wp-block-paragraph\"><b>Cesc Marsal<\/b><small>Digital solutions architect<\/small><\/p><\/div><div class=\"wp-block-group ind-card is-layout-flow wp-block-group-is-layout-flow\"><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><b class=\"ind-u10\">Is your pipeline ready for AI?<\/b><\/p><p class=\"ind-u13 wp-block-paragraph\">In 30 minutes, we'll tell you what data you have and what results you can realistically expect.<\/p><p class=\"ind-contenidor ind-embolcall wp-block-paragraph\"><a href=\"\/en\/free-audit\/\" class=\"ind-btn ind-btn-accent ind-btn-sm ind-u14\">Free assessment<\/a><\/p><\/div><\/aside><\/div><\/section>","protected":false},"excerpt":{"rendered":"<p>Home \u203a Blog \u203a AI &amp; automation AI &amp; automation AI for B2B sales: how to predict which customers are ready to buy CM By Cesc Marsal\u00b7 Mar 17, 2026\u00b7 9 min read\u00b7 Updated 2026 Quick summary Your sales team is tracking 50 to 200 accounts at once, and there's no humanly possible way to ... <a title=\"How to use AI to predict which customers are ready to buy\" class=\"read-more\" href=\"https:\/\/indusmart.digital\/en\/blog\/predict-customers-ready-to-buy\/\" aria-label=\"Read more about How to use AI to predict which customers are ready to buy\">Leer m\u00e1s<\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"ind_cls":"page ind-pg-blog-ia-predecir-clientes","footnotes":""},"categories":[61],"tags":[],"class_list":["post-1593","post","type-post","status-publish","format-standard","hentry","category-ai-applied-to-industry"],"acf":[],"_links":{"self":[{"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/posts\/1593","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/comments?post=1593"}],"version-history":[{"count":5,"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/posts\/1593\/revisions"}],"predecessor-version":[{"id":2570,"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/posts\/1593\/revisions\/2570"}],"wp:attachment":[{"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/media?parent=1593"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/categories?post=1593"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/indusmart.digital\/en\/wp-json\/wp\/v2\/tags?post=1593"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}