{"id":20716,"date":"2025-01-27T16:09:14","date_gmt":"2025-01-27T16:09:14","guid":{"rendered":"https:\/\/www.equalexperts.com\/?p=20716"},"modified":"2025-02-26T13:43:30","modified_gmt":"2025-02-26T13:43:30","slug":"how-bad-data-hinders-good-personalisation","status":"publish","type":"post","link":"https:\/\/www.equalexperts.com\/blog\/data\/how-bad-data-hinders-good-personalisation\/","title":{"rendered":"How bad data hinders good personalisation"},"content":{"rendered":"<p>E-commerce leaders know that personalisation is key to increasing conversions, improving customer loyalty, and standing out in a crowded market. But despite heavy investment in personalisation technologies\u2014AI-driven recommendations, behavioural targeting, and dynamic content\u2014many retailers still struggle to deliver meaningful personalisation.<\/p>\n<p>The reason? <strong>Bad data.<\/strong><\/p>\n<p>If your data is incomplete, inconsistent, or outdated, your personalisation efforts won\u2019t just underperform\u2014they\u2019ll actively frustrate your customers. Instead of feeling understood, they\u2019ll experience <strong>irrelevant recommendations, broken journeys, and missed opportunities.<\/strong><\/p>\n<p>Let\u2019s explore how bad data hinders good personalisation\u2014and what you can do to fix it.<\/p>\n<p><center><a href=\"https:\/\/www.equalexperts.com\/ecommerce-personalisation-john-lewis-partners\/\"><img decoding=\"async\" class=\"wp-image-20727 size-full aligncenter\" src=\"https:\/\/www.equalexperts.com\/wp-content\/uploads\/2025\/01\/EE_Blog_JLP_ADcreative_500x250-1.jpg\" alt=\"Case study: John Lewis &amp; Partners How an extra \u00a330m in revenue was generated in the first 12 months \u2014 all with data-driven personalisation\" width=\"550\" height=\"250\" srcset=\"https:\/\/www.equalexperts.com\/wp-content\/uploads\/2025\/01\/EE_Blog_JLP_ADcreative_500x250-1.jpg 550w, https:\/\/www.equalexperts.com\/wp-content\/uploads\/2025\/01\/EE_Blog_JLP_ADcreative_500x250-1-300x136.jpg 300w\" sizes=\"(max-width: 550px) 100vw, 550px\" \/><\/a><\/center><\/p>\n<h1>Personalisation is only as good as your data<\/h1>\n<p>&nbsp;<\/p>\n<p>Every personalised experience\u2014whether it\u2019s a product recommendation, an email offer, or a homepage layout\u2014depends on accurate, timely, and well-structured data. When that data is unreliable, the experiences you deliver won\u2019t make sense to your customers.<\/p>\n<p>Consider these common failures caused by bad data:<\/p>\n<ul>\n<li>A returning customer sees recommendations for products they\u2019ve already purchased, making the site feel impersonal and irrelevant.<\/li>\n<li>A high-spending VIP customer is shown generic discounts instead of exclusive loyalty rewards.<\/li>\n<li>A long-time customer receives a \u201cWelcome back\u201d email as if they were a first-time shopper.<\/li>\n<li>A shopper adds an item to their cart but receives a promotion for a competing product, leading to confusion.<\/li>\n<\/ul>\n<p>Each of these errors creates friction in the customer journey. Instead of reinforcing trust and engagement, they undermine the very purpose of personalisation.<\/p>\n<h1>The cost of bad data in personalisation<\/h1>\n<p>&nbsp;<\/p>\n<p>The impact of poor data quality isn\u2019t just theoretical\u2014it directly affects revenue, efficiency, and brand perception. Here\u2019s how:<\/p>\n<h2>1. Wasted marketing spend<\/h2>\n<p>Personalisation depends on accurate customer segments, but bad data leads to irrelevant targeting:<\/p>\n<ul>\n<li>Customers receive discounts on products they don\u2019t want.<\/li>\n<li>Email campaigns are based on outdated preferences.<\/li>\n<li>Retargeting ads chase customers who have already made a purchase.<\/li>\n<\/ul>\n<p>This results in lower engagement, higher unsubscribe rates, and wasted budget.<\/p>\n<h2>2. Lost revenue opportunities<\/h2>\n<p>Good personalisation should drive higher average order value (AOV) and repeat purchases. But when data is unreliable:<\/p>\n<ul>\n<li>Cross-sell and upsell recommendations fail because the system doesn\u2019t recognise a customer\u2019s purchase history.<\/li>\n<li>Abandoned cart reminders go to customers who already checked out.<\/li>\n<li>Product recommendations are generic, making them easy to ignore.<\/li>\n<\/ul>\n<p>Bad data means customers miss out on relevant products\u2014and businesses miss out on revenue.<\/p>\n<h2>3. Operational inefficiencies<\/h2>\n<p>Duplicate, inconsistent, or inaccessible data slows down your teams and creates internal friction. Consider the challenges:<\/p>\n<ul>\n<li>Customer service teams can\u2019t access accurate order histories, making issue resolution slower.<\/li>\n<li>Marketing teams waste time manually cleaning data before launching campaigns.<\/li>\n<li>Developers struggle with inconsistent data across platforms, leading to poor automation.<\/li>\n<\/ul>\n<p>Instead of focusing on innovation and optimisation, teams are stuck fixing data issues.<\/p>\n<h2>4. Damaged customer trust<\/h2>\n<p>Customers expect seamless, relevant experiences. When they encounter:<\/p>\n<ul>\n<li>Conflicting messaging across different channels (e.g. different promotions in emails vs the website)<\/li>\n<li>Repeated requests for information they\u2019ve already provided<\/li>\n<li>Misaligned recommendations that don\u2019t reflect their behaviour<\/li>\n<\/ul>\n<p>They lose trust in the brand. Frustration leads to lower engagement, fewer purchases, and, ultimately, churn.<\/p>\n<p><center><a href=\"https:\/\/www.equalexperts.com\/ecommerce-personalisation-john-lewis-partners\/\"><img decoding=\"async\" class=\"wp-image-20727 size-full aligncenter\" src=\"https:\/\/www.equalexperts.com\/wp-content\/uploads\/2025\/01\/EE_Blog_JLP_ADcreative_500x250-1.jpg\" alt=\"Case study: John Lewis &amp; Partners How an extra \u00a330m in revenue was generated in the first 12 months \u2014 all with data-driven personalisation\" width=\"550\" height=\"250\" srcset=\"https:\/\/www.equalexperts.com\/wp-content\/uploads\/2025\/01\/EE_Blog_JLP_ADcreative_500x250-1.jpg 550w, https:\/\/www.equalexperts.com\/wp-content\/uploads\/2025\/01\/EE_Blog_JLP_ADcreative_500x250-1-300x136.jpg 300w\" sizes=\"(max-width: 550px) 100vw, 550px\" \/><\/a><\/center><\/p>\n<h1>How to fix your data for better personalisation<\/h1>\n<h2><\/h2>\n<p>To unlock the full potential of personalisation, businesses must focus on <strong>data quality, accessibility, and real-time capabilities.<\/strong> Here\u2019s how:<\/p>\n<h2>1. Unify data for a single customer view<\/h2>\n<p>One of the biggest barriers to personalisation is <strong>siloed data<\/strong> across platforms\u2014marketing tools, CRM systems, analytics dashboards. When these systems don\u2019t communicate, personalisation efforts become fragmented.<\/p>\n<p>Solution: Implement a data platform that brings together purchase history, browsing behaviour, and customer interactions into a single, accessible profile. We recommend one a <a href=\"https:\/\/www.equalexperts.com\/blog\/our-thinking\/what-is-you-build-it-you-run-it\/\">You Build It, You Run It (YBIYRI) platform<\/a>.<\/p>\n<h2>2. Build data quality into your pipelines<\/h2>\n<p>Bad data is often the result of inconsistent data entry, duplicate records, or missing information. Instead of cleaning up later, prevent errors from happening in the first place.<\/p>\n<p>Best practices:<\/p>\n<ul>\n<li>Standardise data collection across all systems.<\/li>\n<li>Use automation to deduplicate and validate customer records.<\/li>\n<li>Regularly audit your data for gaps and inconsistencies.<\/li>\n<\/ul>\n<h2>3. Enable real-time data access<\/h2>\n<p>Batch-processing delays mean personalisation often relies on stale data. If a customer makes a purchase but still sees ads for the same product, it\u2019s a sign that personalisation is working with outdated information.<\/p>\n<p>Solution: Refactor batch-processes or implement streaming so that recommendations, promotions, and messaging reflect current customer behaviour.<\/p>\n<h2>4. Prioritise data governance &amp; compliance<\/h2>\n<p>With the rise of GDPR and data privacy concerns, businesses must manage data responsibly. A lack of governance leads to security risks, compliance failures, and unreliable personalisation.<\/p>\n<p>Best practices:<\/p>\n<ul>\n<li>Define clear data ownership across teams.<\/li>\n<li>Ensure compliance with privacy laws and customer consent.<\/li>\n<li>Regularly review data retention and accuracy policies.<\/li>\n<\/ul>\n<p>Personalisation isn\u2019t just about having the right tools\u2014it\u2019s about having the right data foundation. If your personalisation strategy isn\u2019t working, the problem isn\u2019t your AI or your CRM. It\u2019s your data.<\/p>\n<p>Fix that, and true, scalable, high-impact personalisation becomes possible.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>E-commerce leaders know that personalisation is key to increasing conversions, improving customer loyalty, and standing out in a crowded market. But despite heavy investment in personalisation technologies\u2014AI-driven recommendations, behavioural targeting, and dynamic content\u2014many retailers still struggle to deliver meaningful personalisation. The reason? Bad data. If your data is incomplete, inconsistent, or outdated, your personalisation efforts [&hellip;]<\/p>\n","protected":false},"author":133,"featured_media":20719,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[179],"tags":[],"location":[],"class_list":["post-20716","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How bad data hinders good personalisation | Equal Experts<\/title>\n<meta name=\"description\" content=\"Improve your ecommerce personalisation strategy for better conversions and customer loyalty by avoiding these pitfalls.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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