{"id":74498,"date":"2025-02-07T22:06:06","date_gmt":"2025-02-07T22:06:06","guid":{"rendered":"https:\/\/peraltafinancing.com\/analytics\/hyper-relevance-a-solution-to-answer-customers-needs-in-personalisation\/"},"modified":"2025-02-07T22:06:06","modified_gmt":"2025-02-07T22:06:06","slug":"hyper-relevance-a-solution-to-answer-customers-needs-in-personalisation","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=74498","title":{"rendered":"Hyper relevance, a solution to answer customers needs in personalisation"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div id=\"wtr-content\" data-bg=\"#0cacf8\" data-fg=\"#0cacf8\" data-width=\"5\" data-mute=\"\" data-fgopacity=\"1.00\" data-mutedopacity=\"1.00\" data-placement=\"top\" data-placement-offset=\"48\" data-content-offset=\"0\" data-placement-touch=\"top\" data-placement-offset-touch=\"0\" data-transparent=\"1\" data-shadow=\"1\" data-touch=\"\" data-non-touch=\"1\" data-comments=\"0\" data-commentsbg=\"#0cacf8\" data-location=\"page\" data-mutedfg=\"#0cacf8\" data-endfg=\"#f44813\" data-rtl=\"\">\n<p>According to an Accenture study (available <a href=\"https:\/\/www.relationclientmag.fr\/Thematique\/data-room-1252\/Breves\/etude-hyper-personnalisation-nouvel-imperatif-consommateurs-fran-ais-329863.htm#jUdgDpOF3lvXjMsZ.97\">here<\/a> in French), 44% of French consumers switched over to competitors in 2017 because their shopping experience was not personalised enough \u2013 and 66% of them are more likely to buy from companies that personalise customer experiences (based on their location, past interactions or preferences). This demand for ultra-personalisation, combined with highly volatile Internet users, is pushing digital marketing into the era of <em>hyper-relevance<\/em>. Consumer loyalty to a brand is becoming almost obsolete. Online shoppers increasingly take advantage of the best opportunity, regardless of where it comes from \u2013 and expect companies to offer them exactly what they need, at the right price and at the right time. So how do companies approach this modern conundrum? Welcome to <em>Hyper relevance\u2026<\/em> And the most effective way to obtain it is to collect and analyse analytical data of impeccable quality.<\/p>\n<p class=\"has-larger-font-size\"><strong>In practice\u2026<\/strong><\/p>\n<p>From experience, we have seen that many companies are still light years away from grasping the extent of the modern shifts in online marketing. Internet users often find themselves pursued by the advertising of a product they have already bought, and whose price goes down over time. This type of inconsistency fuels customers\u2019 mistrust and is often caused by a lack of data quality which undermines a brand\u2019s credibility and harms their business.<\/p>\n<p class=\"has-larger-font-size\"><strong>It\u2019s all<br \/>\nabout trust<\/strong><\/p>\n<p>In<br \/>\npractical terms, for marketers, it is a question of restoring relevance in<br \/>\ntheir every action, campaign and in the relationship they create with the<br \/>\nconsumer. The challenge is to increase the level of trust in the brand over<br \/>\ntime. <strong>Only quality data<\/strong> (accurate, complete, clean, timely, consistent<br \/>\nand compliant) <strong>can guarantee that errors are kept to a minimum<\/strong> during<br \/>\nits use (there is no such thing as zero risk).<\/p>\n<p>Paradoxically,<br \/>\n<a href=\"https:\/\/www.accenture.com\/_acnmedia\/pdf-69\/accenture-global_dd_gcpr-hyper-relevance.pdf#zoom=50\" rel=\"nofollow\">47% of French people are concerned<br \/>\nthat the new digital services will know too much about them<\/a> and their family\u2026 82% also say<br \/>\nthat it is extremely important for companies to protect the confidentiality of<br \/>\ntheir personal information. <\/p>\n<p>In addition<br \/>\nto advanced personalisation, corporate transparency and ethics also become a<br \/>\nweapon of persuasion, and therefore a necessary condition for restoring trust.<\/p>\n<h2><strong>Hyper-relevance analytics<\/strong><\/h2>\n<p>What can be<br \/>\noffered, for example, to a customer affected by a natural disaster? Or to a<br \/>\nuser whose flight has been significantly delayed? These situations require a<br \/>\nhigh degree of relevance in the response you need to provide. With a highly<br \/>\nadvanced knowledge of user expectations, it is possible to target precisely and<br \/>\nat the right time. You can achieve this by:<\/p>\n<ul>\n<li>Obtaining a perfect<br \/>\nunderstanding the customer\u2019s entire digital ecosystem, and not just their<br \/>\nsite-centric performance, which tends to be generalised by all their online devices<br \/>\n(mobile activity can often reveal specific, often varying behaviour). <\/li>\n<li>Detecting a strong<br \/>\ninterest in particular content through the analysis of requests made by the<br \/>\nInternet user in an engine, or by studying the frequency of their visits. <\/li>\n<li>Measuring<br \/>\nunderperformance: visitors\u2019 exposure to error pages, queries without results,<br \/>\netc.<\/li>\n<li>Identifying consumer<br \/>\ntrends and behaviours, the best buyers or the most volatile.<\/li>\n<li>Anticipating traffic<br \/>\nvariations influenced by external factors such as news, weather, etc.<\/li>\n<\/ul>\n<h2><strong>Machine learning \u2013 the key to value<\/strong><\/h2>\n<p>The most<br \/>\nmature companies already use enhanced analytical technologies. They use machine<br \/>\nlearning algorithms to detect and anticipate anomalies or precisely segment<br \/>\ncustomer profiles according to various parameters. Investing in predictive and<br \/>\nprescriptive technologies is one way to address the issue of hyper-relevance. <strong>But<br \/>\nwithout ensuring data quality, all efforts are meaningless, and above all<br \/>\nrisky.<\/strong><\/p>\n<p><a href=\"https:\/\/www.information-age.com\/gartner-data-and-analytics-technology-trends-123479234\/\">Gartner<\/a> refers to increased analytics as<br \/>\nthe number one trend and priority for CDOs in 2020. Built using mathematical<br \/>\nalgorithms and models, these tools must make it possible to describe and<br \/>\npredict the behaviour of Internet users. One of the Machine Learning<br \/>\napplications to improve data quality is to offer an automatic anomaly-detection<br \/>\nservice. The idea is to record the time trends and any suspicious or abnormal<br \/>\nfluctuations in the metrics (human beings are unable to do this by themselves<br \/>\non a large scale). These analyses help to explain the probable causes of these<br \/>\nanomalies. <\/p>\n<p>For example:<br \/>\nif a robot passes over a site and causes a significant peak in traffic, an<br \/>\nanomaly is detected on the number of pages viewed. By automatically exploring a<br \/>\nwhole set of related dimensions (source, device, browser, etc.), a causality<br \/>\nanalysis can be established, and it can be concluded that this anomaly was<br \/>\ncaused by an abnormal increase in traffic on the direct traffic segment in<br \/>\nCanada on the chrome 55 version. This type of tool makes it possible to deliver<br \/>\na preliminary analysis, to better understand behaviours and to guarantee the<br \/>\nreliability of your analyses.<\/p>\n<p>If you are<br \/>\nkeen to find out more about Data Quality, please don\u2019t hesitate to download our<br \/>\nlatest free guide: <\/p>\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter\"><a href=\"https:\/\/content.atinternet.com\/data-quality-in-digital-analytics\/?xtatc=PUB-[DQ_guide_2019]-[inpost]-[EN]\" target=\"_blank\" rel=\"noreferrer noopener\"><img decoding=\"async\" loading=\"lazy\" width=\"790\" height=\"250\" src=\"https:\/\/blog.atinternet.com\/wp-content\/uploads\/2019\/09\/In-post-banner-Data-Quality-EN.jpg\" alt=\"Data Quality in Digital Analytics updated in 2019\" class=\"wp-image-15173\" srcset=\"https:\/\/blog.atinternet.com\/wp-content\/uploads\/2019\/09\/In-post-banner-Data-Quality-EN.jpg 790w, https:\/\/blog.atinternet.com\/wp-content\/uploads\/2019\/09\/In-post-banner-Data-Quality-EN-300x95.jpg 300w, https:\/\/blog.atinternet.com\/wp-content\/uploads\/2019\/09\/In-post-banner-Data-Quality-EN-768x243.jpg 768w\" sizes=\"auto, (max-width: 790px) 100vw, 790px\"\/><\/a><\/figure>\n<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>According to an Accenture study (available here in French), 44% of French consumers switched over to competitors in 2017 because their shopping experience was not personalised enough \u2013 and 66% of them are more likely to buy from companies that personalise customer experiences (based on their location, past interactions or preferences). This demand for ultra-personalisation, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":74499,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12033],"tags":[4970,11717,24410,35685,28337,3080],"dealstore":[],"offerexpiration":[],"class_list":["post-74498","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","tag-answer","tag-customers","tag-hyper","tag-personalisation","tag-relevance","tag-solution"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Hyper relevance, a solution to answer customers needs in personalisation - Som2ny Network<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fivemor.com\/?p=74498\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hyper relevance, a solution to answer customers needs in personalisation - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"According to an Accenture study (available here in French), 44% of French consumers switched over to competitors in 2017 because their shopping experience was not personalised enough \u2013 and 66% of them are more likely to buy from companies that personalise customer experiences (based on their location, past interactions or preferences). 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