{"id":10682,"date":"2026-01-08T18:52:56","date_gmt":"2026-01-09T00:52:56","guid":{"rendered":"https:\/\/attentionmedia.io\/?p=10682"},"modified":"2026-01-08T18:52:56","modified_gmt":"2026-01-09T00:52:56","slug":"the-data-quality-paradigm-shift-has-arrived","status":"publish","type":"post","link":"https:\/\/attentionmedia.io\/?p=10682","title":{"rendered":"The data quality paradigm shift has arrived"},"content":{"rendered":"<div><img loading=\"lazy\" decoding=\"async\" width=\"800\" height=\"450\" src=\"https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg\" class=\"attachment-large size-large wp-post-image\" alt=\"A new paradigm for data quality.\" loading=\"lazy\" \/><\/div>\n<p>If you work in martech, marketing operations or related roles, you\u2019ve surely heard colleagues and leadership complaining about data quality and their lack of trust in data.<\/p>\n<p>We often place the blame for data quality on the system, because we\u2019re not willing to fully say the quiet part out loud: The No. 1 factor in data quality is the people, the processes and the level of rigor in those processes.<\/p>\n<p>Today, we stand on the cusp of a significant paradigm shift, in which we must reevaluate how we establish and measure trust in our own platforms. The infusion of AI\u00a0capabilities in traditional platforms is growing at an unprecedented pace, and new AI-native challengers are here.<\/p>\n<p>Through 2025, I explored <a href=\"https:\/\/martech.org\/the-future-of-the-martech-stack-and-marketing-operations-is-unstructured\/\">the impact of unstructured data<\/a> on marketing. I also went back to look at the <a href=\"https:\/\/martech.org\/10-insights-for-marketing-and-mops-leaders-from-the-state-of-martech-2025-report\/\">leading trends that started the year<\/a>.\u00a0<\/p>\n<p>As 2025 went on, we saw more AI-powered capabilities appearing in leading martech platforms, many of which were turned on by default. Now is the time to consider the adjustments needed for our \u201ctrust mindset.\u201d Our historic data governance processes, which apply to both structured and unstructured data, are no longer relevant.<\/p>\n<p>The heart of the issue is this: More of our stack\u2019s processes will be based on probabilistic approaches rather than traditional deterministic rules.<\/p>\n<ul class=\"wp-block-list\">\n<li><strong>Deterministic:<\/strong> Based on exact data matches and preset rules and more rigid workflow conditions.<\/li>\n<li><strong>Probabilistic approaches:<\/strong> Context-based interpretation, based on LLM AI capabilities to infer the meaning of data, as they process both unstructured and structured data.<\/li>\n<\/ul>\n<p><strong><em>Dig deeper: <a href=\"https:\/\/martech.org\/the-future-of-the-martech-stack-and-marketing-operations-is-unstructured\/\">The future of the martech stack and MOps is \u2018unstructured\u2019<\/a><\/em><\/strong><\/p>\n<h2 class=\"wp-block-heading\">The tipping point is here<\/h2>\n<p>In October 2025, I wrote about the <a href=\"https:\/\/martech.org\/customer-sentiment-and-risk-are-hidden-in-the-emails-in-your-crm\/\">benefits and risks of extracting insights from CRM-captured email<\/a>. During that same timeframe, multiple headlines caught my attention, declaring <a href=\"https:\/\/www.thecrmisdead.com\/\">the CRM is dead<\/a>.<\/p>\n<p>While I didn\u2019t necessarily agree with the provocative headlines, I think most would agree with the underlying challenges they highlight. Rigid workflows, data silos and manual overhead typically hamper our efforts to drive growth and productivity for organizations.\u00a0\u00a0<\/p>\n<p>Perhaps the original <a href=\"https:\/\/martech.org\/topic\/customer-relationship-management-crm\/\">CRM<\/a> mission \u2014 to completely structure the unstructured \u2014 was an impossible goal to begin with. In other words, our CRM and <a href=\"https:\/\/martech.org\/topic\/marketing-automation\/\">marketing automation platform (MAP)<\/a> initiatives relied on a one-size-fits-all playbook that said properly structuring most of the underlying data was the answer.<\/p>\n<p>Even under the best set of rules and processes, we all end up dealing with edge-case exceptions that always result in our favorite fail-safe \u2014 the deterministic drop-down menu known as \u201cOther.\u201d\u00a0 Despite all prior efforts, data quality challenges are still front and center.<\/p>\n<ul class=\"wp-block-list\">\n<li>76% of respondents to <a href=\"https:\/\/www.validity.com\/resource-center\/the-state-of-crm-data-management-in-2025\/\">Validity\u2019s \u201cState of CRM Data Management in 2025<\/a>\u201d said less than 50% of their CRM data is accurate or complete.\u00a0\u00a0<\/li>\n<li>Scott Brinker and <a href=\"https:\/\/martech.org\/author\/frans-riemersma\/\">Frans Riemersma<\/a>\u2019s <a href=\"https:\/\/chiefmartec.com\/2025\/12\/heres-your-copy-of-our-martech-for-2026-report-free-and-ungated\/\">\u201cMartech for 2026<\/a>\u201d report found 56.3% of respondents indicated poor quality \u2014 missing, stale or inconsistent data \u2014 was hindering their AI implementations.<\/li>\n<\/ul>\n<p>To address these challenges, Gartner and other industry leaders suggest that new criteria are needed around \u201cAI-ready\u201d data. I recall an old yet trusted framework called CRUD: Create, Retrieve, Update, Delete,\u00a0which was ingrained in many underlying data management principles. Let\u2019s have some fun by proposing a modern version of CRUD.<\/p>\n<p><strong><em>Dig deeper: <a href=\"http:\/\/customer%20sentiment%20%E2%80%94%20and%20risk%20%E2%80%94%20are%20hidden%20in%20the%20emails%20in%20your%20crm\/\">Customer sentiment \u2014 and risk \u2014 are hidden in the emails in your CRM<\/a><\/em><\/strong><\/p>\n<h2 class=\"wp-block-heading\">CRUD 2.0: A mindset shift for AI-ready data<\/h2>\n<h3 class=\"wp-block-heading\">C = Context<\/h3>\n<p>Brinker and Riemersma\u2019s year-end report provided new terminology to help us navigate these changes. For me, the emergence of \u201ccontext engineering\u201d was the lead story. The key metaphor the report explored was the Goldilocks principle of data: Evaluating the \u201cjust right\u201d amount of data needed for our embedded AI agents and workflow processes to be efficient and effective.\u00a0\u00a0<\/p>\n<p>Instead of asking whether we can trust the output, we\u2019ll shift to determining if we can trust the underlying context the AI algorithm is operating on. Martech engineers will become data curation and context engineers.<\/p>\n<h3 class=\"wp-block-heading\">R = Review by the \u2019human in the loop\u2019<\/h3>\n<p>Probabilistic, AI-based algorithms require us to shift the team\u2019s input capacity for coordinated \u201chuman-in-the-loop\u201d review processes. We\u2019ll need to retrain teams and introduce new internal fact-checking procedures so that the appropriate subject matter experts are pulled in, depending on the context of the data.\u00a0<\/p>\n<p>We\u2019ll also need to expand our <a href=\"https:\/\/martech.org\/mops-leaders-as-scientists-embracing-the-scientific-method\/\">data-scientist mindsets<\/a> to introduce new sampling processes and develop data confidence levels. Most importantly, while traditional processes typically relied on project-based milestones to rally cleanup efforts, the \u201cMarTech for 2026\u201d report forecasts a shift to a continuous review mindset, since many of these embedded capabilities will be running around the clock.<\/p>\n<h3 class=\"wp-block-heading\">U = Upgrade\u00a0<\/h3>\n<p>We\u2019ll shift more attention from updating data fields to analyzing whether the overall process and decision quality are actually improving. Does the inclusion of AI provide significant business value, given the costs of the process?<\/p>\n<p>AI-processing costs will become the rising tide in utilization metrics, not just account and contact data storage. Brinker had already predicted earlier in 2025 that we would need to move beyond counting users and learn new utilization-based systems, as <a href=\"https:\/\/www.mi-3.com.au\/14-07-2025\/martechs-agentic-age-is-rising-says-scott-brinker\" target=\"_blank\" rel=\"noopener\">AI\/SaaS cloud vendors are already introducing usage-based consumption models<\/a> to replace the cost-per-seat, tiered-feature models.<\/p>\n<h3 class=\"wp-block-heading\">D = Declutter<\/h3>\n<p>In a strange twist, the potential risk of <a href=\"https:\/\/martech.org\/ai-trust-is-the-new-growth-engine\/\">AI hallucinations<\/a> \u2014 either in inaccurate reporting or mismatched content \u2014 from AI agents operating on poor data quality may be the key to unlocking time and capacity for long-overdue cleanup initiatives. More than 60% (62.1%) of respondents in Brinker and Riemersma\u2019s survey indicate they\u2019re already using built-in agents embedded in existing platforms. The time to act is now.<\/p>\n<p>The risk of highly visible, inaccurate or automated campaigns may be the fuel necessary to make the business case to declutter our legacy systems.\u00a0<\/p>\n<p>Implementations that are active for more than six to 12 months don\u2019t have their setups and workflows revisited as frequently as needed. However, the impact of this tech debt was likely hidden, as long as your teams maintained solid documentation and processes that clearly identified which fields were actively used. In the new probabilistic world operating across the entire CRM\/MAP ecosystem, these historical data fields and workflows will introduce noise, impacting the reliability of your output and increasing errors at a higher rate.<\/p>\n<h2 class=\"wp-block-heading\"><strong>Applying CRUD 2.0<\/strong><\/h2>\n<p>Because most teams will start by revisiting their traditional CRM processes, I believe our organizations will need to bridge the gap in a step-wise fashion, by first retrofitting more minor use cases and then scaling those efforts more broadly. To illustrate this, I will revisit my simplified example from March \u2014 classifying a key contact correctly into the appropriate persona category when their job title included keywords such as \u201ccontract.\u201d<\/p>\n<h3 class=\"wp-block-heading\">Context<\/h3>\n<ul class=\"wp-block-list\">\n<li>If based solely on deterministic rules, using the word \u201ccontract\u201d in job titles may be properly classified into Legal\/Compliance.<\/li>\n<li>However, based on the contact\u2019s involvement with RFP processes or terms and conditions <a href=\"https:\/\/martech.org\/customer-sentiment-and-risk-are-hidden-in-the-emails-in-your-crm\/\">captured through deal emails and related context<\/a>, a probabilistic AI agent could determine that a key member of a buying group is functioning instead in a sourcing\/procurement role.<\/li>\n<\/ul>\n<h3 class=\"wp-block-heading\">Review\u00a0<\/h3>\n<ul class=\"wp-block-list\">\n<li>A probabilistic-based workflow could suggest that the human in the loop create a new sourcing\/procurement persona.\n<ul class=\"wp-block-list\">\n<li>If the answer is Yes, the AI agent could set that new persona appropriately<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>and\/or\u2026\u00a0<\/p>\n<ul class=\"wp-block-list\">\n<li>Notify an appropriate CRM operations leader to flag the related use case for a more thorough review (e.g., determining whether to retrospectively re-classify other contacts\u2019 personas).<\/li>\n<\/ul>\n<h3 class=\"wp-block-heading\">Upgrade<\/h3>\n<ul class=\"wp-block-list\">\n<li>Furthermore, if an automated campaign and content operations process were in place, new follow-up to that procurement audience could be drafted and only sent after the human in the loop reviews it.<\/li>\n<\/ul>\n<h3 class=\"wp-block-heading\">Declutter\u00a0<\/h3>\n<ul class=\"wp-block-list\">\n<li>Outdated job title and persona-based automations could be flagged for cleanup if a review indicates that former persona workflows were no longer needed, or those workflows could be cloned as templates for the new procurement persona.<\/li>\n<\/ul>\n<h2 class=\"wp-block-heading\">Taking advantage of this moment<\/h2>\n<p>Based on all indicators, the data quality and AI-agent tipping point is here. If these new capabilities are just turned on by default, it would actually be appropriate to say, \u201cI can\u2019t trust the tool!\u201d But with a proactive mindset that accounts for this paradigm shift, we may uncover hidden opportunities to finally address these challenges.<\/p>\n<p><!-- START INLINE FORM --><\/p>\n<div class=\"nl-inline-form border py-2 px-1 my-2\">\n<div class=\"row align-items-center justify-content-center nl-inline-container\">\n<div class=\"col-12 pb-1\">\n<p class=\"inline-form-text text-center mb-0\">Fuel up with free marketing insights.<\/p>\n<\/div>\n<div class=\"col-12 col-lg-auto pb-2 pb-lg-0\">\n<p class=\"inline-form-text text-center mb-0\">Email:<\/p>\n<\/div>\n<div class=\"col-12 col-lg-8 pe-lg-0\">\n<div class=\"form-nl-inline\"><\/div>\n<\/div>\n<div class=\"col-12 col-lg-auto\">\n<p class=\"text-center mb-0\"><a class=\"nl-terms\" href=\"https:\/\/martech.org\/terms-of-service\/\" target=\"_blank\" aria-label=\"opens in a new tab\">See terms.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<p><!-- END INLINE FORM --><\/p>\n<p>The post <a href=\"https:\/\/martech.org\/the-data-quality-paradigm-shift-has-arrived\/\">The data quality paradigm shift has arrived<\/a> appeared first on <a href=\"https:\/\/martech.org\/\">MarTech<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"<p>If you work in martech, marketing operations or related roles, you\u2019ve surely heard colleagues and leadership complaining about data quality and their lack of trust in data. We often place the blame for data quality on the system, because we\u2019re not willing to fully say the quiet part out loud: The No. 1 factor in &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/attentionmedia.io\/?p=10682\" class=\"more-link\">Read more<span class=\"screen-reader-text\"> &#8220;The data quality paradigm shift has arrived&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-10682","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"featured_media_urls":{"thumbnail":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"medium":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"medium_large":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"large":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"1536x1536":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"2048x2048":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"inspiro-featured-image":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"inspiro-loop":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"inspiro-loop@2x":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-thumbnail":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-thumbnail@2x":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-masonry":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-masonry@2x":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-thumbnail_cinema":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-thumbnail_portrait":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-thumbnail_portrait@2x":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false],"portfolio_item-thumbnail_square":["https:\/\/martech.org\/wp-content\/uploads\/2026\/01\/retro-data-quality-800x450.jpeg",0,0,false]},"_links":{"self":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/posts\/10682","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=10682"}],"version-history":[{"count":0,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/posts\/10682\/revisions"}],"wp:attachment":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10682"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10682"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10682"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}