{"id":602535,"date":"2023-01-29T07:49:30","date_gmt":"2023-01-29T13:49:30","guid":{"rendered":"https:\/\/news.sellorbuyhomefast.com\/index.php\/2023\/01\/29\/why-most-publishers-cant-deliver-precise-intent-data\/"},"modified":"2023-01-29T07:49:30","modified_gmt":"2023-01-29T13:49:30","slug":"why-most-publishers-cant-deliver-precise-intent-data","status":"publish","type":"post","link":"https:\/\/newsycanuse.com\/index.php\/2023\/01\/29\/why-most-publishers-cant-deliver-precise-intent-data\/","title":{"rendered":"Why Most Publishers Can\u2019t Deliver Precise Intent Data"},"content":{"rendered":"<div>\n<ul>\n<li>January 27, 2023<\/li>\n<p>\t\t\t\t\t\t\t<span><\/p>\n<li><a href=\"https:\/\/www.techtarget.com\/blog\/content\/\">Content<\/a>, <a href=\"https:\/\/www.techtarget.com\/blog\/intent-data\/\">Intent Data<\/a><\/li>\n<p>\t\t\t\t<\/span>\n\t\t\t\t\t<\/ul>\n<div data-equalizer-watch=\"sharing\" data-equalizer=\"sharing\" data-equalizer-on=\"large\">\n<p><img loading=\"lazy\" decoding=\"async\" data-del=\"avatar\" src=\"https:\/\/cdn.ttgtmedia.com\/wp-content\/uploads\/2019\/01\/John-Steinert_2019_crop-120x120.png\" height=\"80\" width=\"80\"><\/p>\n<\/p><\/div>\n<h2><strong>Are all \u201cWalled Gardens\u201d alike?<\/strong><\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/cdn.ttgtmedia.com\/wp-content\/uploads\/2023\/01\/whymostpublisherscantdeliverprecisionintentdata.jpg\" alt=\"precision intent data\" width=\"403\" height=\"269\">Even though Google continues to push out its end-of-cookies date \u2013 for lack of any adequate replacement for advertising targeting \u2013 we\u2019ve been hearing more about the targeting data strengths and weaknesses of the big three \u201c<a href=\"https:\/\/www.kevel.com\/blog\/what-are-walled-gardens\">walled gardens<\/a>\u201d (Google, Facebook and Amazon) in the B2C space. In B2B, the concept of \u201cwalled gardens\u201d also applies specialized publishers, but it\u2019s less well understood. And while it\u2019s conceptually accurate that any walled-garden proprietor who has their users\u2019 permission could potentially offer marketers a really valuable data source, most were not conceived or designed for that purpose. The reality is that much of the so-called intent data from B2B publishers is actually an amalgam of very weak signals, leaving it up to you as B2B marketers to try and figure out the difference between a truly valuable offering and one that sounds good but can\u2019t deliver. From where I sit, I can see at least 3 important shortcomings to be aware of:<\/p>\n<ol>\n<li><strong>Business models designed for broad and shallow:<\/strong> Most online publishers were built on a model designed to maximize advertising dollars from big spenders. Think about a publication like USA Today: You get the most eyeballs by covering a lot of topics at a very high level.<\/li>\n<li><strong>Anonymous behavioral signals are not additive:<\/strong> Despite the reality that two weak signals here don\u2019t add up to a strong (do you remember the fallacy of packaging bad mortgages together and rating them good?) many providers are doing this and saying it works.<\/li>\n<li><strong>\u201cDirectional\u201d suggestions from marketing don\u2019t deliver real value to sales:<\/strong> Not only are MQA\u2019s subject to serious false-positive issues, when a supplier pairs MQAs with cold contacts \u2013 think about it \u2013 it\u2019s really no better than having a prioritized territory account list and doing cold calling.<\/li>\n<\/ol>\n<p>To provide you with better insight on the right intent data for your needs, I\u2019ll be discussing these at length using some current examples that are out there.<\/p>\n<h2><strong>Most publishers were built on an advertising-driven business model <\/strong><\/h2>\n<p>Most publisher walled gardens were built for advertising purposes, not to deliver the kind of high-quality purchase intent data necessary to greatly increase sales efficiency. This advertising-based business model compelled them to seek out the broadest possible audieences within large, general interest categories. Even in quasi-specialty categories (like \u201ctech\u201d), broad and shallow coverage was the best way to maximize ad dollars by covering a little about a whole lot.<\/p>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/cdn.ttgtmedia.com\/wp-content\/uploads\/2023\/01\/TTGTvsCompetition.png\" alt=\"precision intent data\" width=\"293\" height=\"267\"><\/p>\n<p>In enterprise tech, there are a handful of large walled gardens that on the surface appear similar but are actually very different from a business model, data, and value delivery perspective. IDG (now Foundry), SWZD (Spiceworks ZiffDavis), \u00a0Informa (who bought UMB), CNET, et al are all examples of the old-school advertising-driven business model. As a result, they can\u2019t deliver the precision for real Intent revenue impact. In contrast, TechTarget was purpose-built for the internet era and the very granular decision support needs of enterprise tech buyers and sellers. Evidence of the fundamental differences between the models can be seen in their respective organic search rankings on Google: TechTarget\u2019s micro-segmented approach results in far more total organic traffic (it\u2019s grown some 2X in just the past two years) and much more granular segmentation capabilities. For you as an advertiser, that\u2019s good for targeted contextual advertising (versus spray and pray programmatic). It\u2019s even better for Intent data precision, lead conversion yields, opportunity identification, and a host of other sales and related go-to-market needs. Let\u2019s take a closer look at why.<\/p>\n<h2><strong>Broad and shallow can\u2019t get you to precision intent data<\/strong><\/h2>\n<p>If you\u2019ve built your publishing model to attract very broad audiences, like say a \u00a0ComputerWorld or InformationWeek has (you can read descriptions of coverage models <a href=\"https:\/\/foundryco.com\/our-brands\/\">here<\/a>), the whole concept is to build a news-oriented media property that people can get a broad gist of \u201cwhat\u2019s happening\u201d out there. It\u2019s a model that helps you sell advertising in big chunks to big spenders, which is efficient for you, but unfortunate for more specialized advertisers with specialized targets and less budget. Even today, this model may still be \u201cworking\u201d for marketers at the very biggest companies, because they can afford to advertise at tremendous scale. But despite the low cost of programmatic advertising, smaller brands need a lot more granularity to have any hope of impacting their laser-focused niches. They need to reach those people who really care about innovative differentiators, not everyone who has a passing interest in a huge category like \u201cSecurity\u201d or \u201cCloud\u201d.<\/p>\n<p>Unfortunately for broad-based legacy publishers, the advertising-focused business model actually precludes a pivot to a more insight-rich approach. Here\u2019s why: Since their whole business model revolved around advertising, it\u2019s actually not constructed to be able to generate the granularity required to deliver precision Intent data. By design, this business model sits on an infrastructure built for generalities and scale, not for hyper-segmented accuracy and detail. By design, the editorial content and reportorial staff skills don\u2019t aim to serve the highly specific needs of tech decision-driving professionals (whose input is required in every significant enterprise tech purchase). At best, these types of publishers can only track wide account behavior surges in the broadest most general sense of the idea. They can only see broad interest trends. Which means, from the traffic they do get, they can only supply high-level data, generating insights too vague to be meaningfully useful for anything other than high-level advertising. In contrast, TechTarget\u2019s approach was built for granularity from the start, so our model is not only extremely efficient for advertising, it\u2019s incredibly powerful for sales. It has the granularity about an individual prospect\u2019s needs and more that enable a seller to personalize their outreach.<\/p>\n<h2><strong>How should you factor this into your understanding of the Intent data space as a whole?<\/strong><\/h2>\n<p>Some will argue that nearly any legitimate source of B2B targeting data is an improvement on basic programmatic ad targeting (after all, it\u2019s an adtech category struggling with nearly <u><a href=\"https:\/\/www.statista.com\/topics\/8503\/ad-fraud\/\">$65 billion<\/a><\/u> in fraud annually \u2013 50%+ of total spend!) And maybe if all you want to do is target your digital advertising a little better, such legacy-model tech publishers can improve on even broader B2B outlets like Forbes, WSJ.com and the rest. The point I want you to be very clear on here is that the Intent market is full of self-proclaimed \u201cIntent data\u201d providers \u2013 outlets that obtain their data in all sorts of ways \u2013 but because of fundamental flaws in their business models (similar to those of the legacy publishers), few of them can actually help you make substantive progress on your most pressing business objectives.<\/p>\n<h2><strong>What you should understand about weak Intent + cold contact data<\/strong><\/h2>\n<p>As Intent started to draw attention, many data providers rushed to offer additional \u201cIntent\u201d feeds on top of the contact information that is their bread and butter. Finding themselves with gaps in both areas (contacts and Intent), many legacy publishers have pursued this approach as well, through a combination of point-solution acquisitions and both 2<sup>nd<\/sup> and 3<sup>rd <\/sup>party external sourcing. After cobbling together a solution, such approaches now lead publishers to say things like: [We now provide] \u201cmultiple intent sources combined to capture buying behavior\u201d, even though that doesn\u2019t add up. They make claims that are hard to understand like: [We] \u201ccapture the signals that drive buying decisions \u2026 and layer intent signals from diverse buying channels\u201d.\u00a0 <strong>My belief is that potential buyers like you should be careful to parse such verbiage very carefully. Let\u2019s discuss some of the issues in more depth:<\/strong><\/p>\n<p>Many providers say they layer in data from the \u201cpublic web\u201d, but that data is public precisely because it has little precision targeting value. The content that generates it is either too general, too widely available or both. <strong>This turns out to be the fundamental weakness of both advertising-based publisher data and all 3<sup>rd<\/sup> party Intent alike: it\u2019s derived from low value original sources. Furthermore, unlike with contact data where different sources added together can help clean up missing fields or verify latest known account affiliations, weak sources of intent data can\u2019t be strengthened like this. Most accounts are big, diverse groups of anonymous people generating lots of different signals all the time. If you don\u2019t know much about the signals or who they\u2019re from, you can\u2019t determine if they are truly additive. Thus instead of actually strengthening the signal, if you do this with behavioral data, you\u2019re often just layering two false positives on each other..<\/strong><\/p>\n<p>A lot of providers talk up their selection of \u201cIndustry content\u201d. But any B2B and lots of B2C properties cover \u201cindustry\u201d stories. Unless that content\u2019s been built to help differentiate between highly granular topics, it can\u2019t actually support the highly specific information requirements and concerns of enterprise tech buying teams. And thus, as a marketer, you can\u2019t actually tell if their needs are relevant to what you sell. Like many Intent providers, legacy publisher-style data can neither differentiate between false-positive surges nor help buyers navigate within the highly complex, highly differentiated solution areas inside big categories like Cloud, \u00a0Security, DevOps, and so on.<\/p>\n<p>Many publishers are talking more about their \u201cOpted in\u201d audiences. While that\u2019s good in theory, in practice, in order for it to be valuable to you, you need to have the behavior of <em>this specific person<\/em>. If the behavior is only available at the account level, it tells you nothing about any specific contact. When the behavioral data being tracked is general-interest oriented, and only at the account level, then it makes you as a marketer essentially no better off than you continue targeting your efforts on role and function alone.<\/p>\n<p>Some legacy publishers specifically recognize the challenges they face and openly describe their attempts to overcome it with messaging like this: [We\u2019ve] \u201cmatched [our account intent] to the buying team at the contact level\u201d. I had to read this one closely, and you should too. Here, they\u2019re actually explaining that they don\u2019t have precision intent about those opt-in people they mentioned, so instead, they\u2019re supplying cold contacts that they think you might want to try. This is super common now in the buyer-beware Intent space. Many of the \u201cpop-up\u201d intent players are offering exactly the same thing, because they can buy both surge data and contact data, massage it together, and make it sound special to you. If you were to buy in, rather than helping your sales colleagues, you\u2019d be asking them to spend substantial energy sorting through all these cold names using expensive, brute force sales development resource. This is the exact situation that <a href=\"https:\/\/www.forrester.com\/b2b-marketing\/say-goodbye-to-mqls-webinar\/\">Forrester<\/a> has described at length in discussing the inherent weaknesses in the MQA (marketing qualified concept).<\/p>\n<h2><strong>You can see these weaknesses clearly by looking closely at flashy generic web demos<\/strong><\/h2>\n<p>While it\u2019s fundamentally a good idea to offer a demonstration of your product on the web, a bad generic demo can actually hurt. Coming from the enterprise tech perspective, I\u2019ve experimented with a variety of Intent providers\u2019 on-page demos and have not been impressed. In most, a look at the topic drop down actually illustrates many of the shortcomings we\u2019ve been discussing. I immediately notice that the topic choices are super-limited, i.e. not granular enough to help. They can\u2019t provide insights that differentiate between solutions and they show duplicate accounts that are supposedly in market across many categories. This is again because the data they\u2019re using comes from an editorial model that is too broad and shallow (whether it\u2019s their own data source or a feed that they are reselling). I\u2019ve noticed frequently that, even when these sites claims tech expertise, their choices go no deeper than whole categories of software. What I want is the <em>real people<\/em> within accounts who care about <em>the real<\/em> <em>differences<\/em> between particular solutions. What they give me instead is a list of companies to go after that\u2019s actually worse than if I used ICP targeting based on firmographics alone. In a number of these demos, it even seems as if the data model is based simply on a top-level extract from G2 or TrustRadius\u2019 category definitions, leaving out all the actual value in those providers\u2019 deeper features!<\/p>\n<h2><strong>Choosing the best Intent data source for your company and use cases<\/strong><\/h2>\n<p>Like some other newer RevTech categories, Intent data has generated a ton of interest quickly, first among marketers and more recently with sellers and other members of the GTM organization. Naturally, this attracted a host of new supplier entrants, which has complicated things for practitioners like you. Unlike late entrants, TechTarget was an early pioneer in the space because we had a data foundation that works for our clients: Our business model was specifically conceived to serve the granular decision support needs of tech buyers (and the vendors looking to sell to them). Our Priority Engine\u2122 platform leverages a uniquely powerful, transparent 1<sup>st<\/sup> party \u201cwalled garden\u201d methodology (2<sup>nd<\/sup> party to you) to deliver the highest quality, most actionable insights available. For additional information and to fully understand what your company can gain from precision intent data that you can\u2019t get anywhere else, please arrange a <a href=\"https:\/\/reg.techtarget.com\/general-product-walkthrough.html\">demonstration<\/a> customized to your specific needs.<\/p>\n<p><a href=\"https:\/\/www.techtarget.com\/tag\/b2b-publishing\/\">B2B publishing<\/a>, <a href=\"https:\/\/www.techtarget.com\/tag\/priority-engine\/\">Priority Engine<\/a>, <a href=\"https:\/\/www.techtarget.com\/tag\/purchase-intent-data\/\">purchase intent data<\/a>, <a href=\"https:\/\/www.techtarget.com\/tag\/techtarget\/\">TechTarget<\/a><\/p>\n<\/p><\/div>\n<p><a href=\"https:\/\/www.techtarget.com\/why-most-publishers-cant-deliver-precise-intent-data\/\" class=\"button purchase\" rel=\"nofollow noopener\" target=\"_blank\">Read More<\/a><br \/>\n John Steinert<\/p>\n","protected":false},"excerpt":{"rendered":"<p>January 27, 2023 Content, Intent Data Are all \u201cWalled Gardens\u201d alike? Even though Google continues to push out its end-of-cookies date \u2013 for lack of any adequate replacement for advertising targeting \u2013 we\u2019ve been hearing more about the targeting data strengths and weaknesses of the big three \u201cwalled gardens\u201d (Google, Facebook and Amazon) in the<\/p>\n","protected":false},"author":1,"featured_media":602536,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[706,1461,46],"tags":[],"class_list":{"0":"post-602535","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-cant","8":"category-publishers","9":"category-technology"},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts\/602535","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/comments?post=602535"}],"version-history":[{"count":0,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts\/602535\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/media\/602536"}],"wp:attachment":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/media?parent=602535"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/categories?post=602535"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/tags?post=602535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}