Canonical URL: https://elacelerador.es/en/data-and-automation/connectif-email-measurement-consent/ --- description: Only opens and clicks from consenting contacts link to their profile. Other events remain in anonymized counts, and the feature does not change email delivery. title: Connectif separates individual email tracking from aggregate statistics image: https://elacelerador.es/images/social/v1/connectif-separates-individual-email-tracking-aggregate-statistics-2f91463948828bb59a9187b5a25a0790.jpg --- 1. [Home](https://elacelerador.es/en/) 2. [Data and automation](https://elacelerador.es/en/data-and-automation/) # Connectif separates individual email tracking from aggregate statistics Only opens and clicks from consenting contacts link to their profile. Other events remain in anonymized counts, and the feature does not change email delivery. By [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 12 October 2026 at 22:53 CEST 13 min read [ Add as preferred source ](https://www.google.com/preferences/source?q=elacelerador.es&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) Share [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Felacelerador.es%2Fen%2Fdata-and-automation%2Fconnectif-email-measurement-consent%2F%3Futm%5Fsource%3Dlinkedin%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on LinkedIn. 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Preview requests: 0") [ ](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Felacelerador.es%2Fen%2Fdata-and-automation%2Fconnectif-email-measurement-consent%2F%3Futm%5Fsource%3Dfacebook%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on Facebook. Preview requests: 0") ![Person working with a laptop and mobile devices at a table](https://elacelerador.es/images/variants/v1/connectif-explains-email-measurement-apart-individual-profiles-person-working-laptop-mobile-devices-w1280.webp) A workspace with a laptop and mobile devices. Archive photograph illustrating digital communication. Framing adapted. Photo: [Parker Byrd · CC0](https://commons.wikimedia.org/wiki/File:Mobile%5Fdeveloper%5Fat%5Fwork%5F%28Unsplash%29.jpg?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) [Connectif](https://elacelerador.es/en/company/connectif/) explained Sept. 22, 2026, a feature separating email opens and clicks linked to an individual from anonymised counts retained for campaign analysis. The distinction affects a routine marketing decision: who should receive the next message. A campaign can continue to show aggregate activity while part of that activity stops being available for selecting particular contacts. Information remains in the dashboard, but decisions based on individual profiles observe a different population and require a different interpretation of missing signals. The feature guide distinguishes consent granted, consent denied and no information. Only the first state associates opens and clicks with a contact; the others retain anonymised counts. Connectif says this configuration does not change which emails the person receives. It separates recording from sending rather than automatically unsubscribing every contact without individually linked tracking. ## Activity can continue without appearing in a profile The change establishes a boundary between observing a collective outcome and recognising the people who produced it. A brand can know a message's interaction total without retaining an equivalent individual history for every recipient. Confusing the two levels can produce incomplete segments or commercial decisions that incorrectly interpret an apparently silent contact profile as evidence of indifference to the brand. An absent recorded open does not establish that someone ignored a message. An absent individual click does not prove a lack of interest in the product either. In Connectif's announced design, the signal can be missing because it is not associated with the contact. The reason for that absence belongs in interpretation before the data are turned into an inactivity label. Email-activity segments therefore need review. A segment of contacts without opens does not necessarily describe all inactive readers. It can mix people with no observed response and people outside individual observation coverage. That difference is a specific measurement problem, rather than a justification for recovering through another route every signal that the person did not want linked to their profile. Nor does the feature establish that the aggregate total is a recoverable anonymous list of individuals. The count supports activity assessment under platform rules, while individual selection needs an available and appropriate association. This analysis maintains that boundary. It does not describe aggregate information as a doorway for reconstructing identities that are absent from the individual event history. The type of information also changes stated willingness to share it. In IAB Europe and Kantar’s November 2024 survey, 21% did not want purchase history processed for personalised advertising and 8% emphatically objected; the corresponding responses for precise location were 32% and 19%. These are opinions among internet users in twelve countries, not consent decisions by Connectif recipients. The study does not specifically ask about email tracking: it illustrates why general coverage cannot describe every use of data. The data behind the story ### Objection depends on the information proposed for use Two levels of objection to data use for personalised advertising, twelve-country European aggregate, November 2024. Would not want processingEmphatically objects Tap or hover for details. Select a series above to show or hide it. Expand notesCollapse notes **Sources:** Statista; Original report, p. 19; methodology, p. 40 Online survey of 10,500 internet users aged 16+ in twelve countries; Spain contributes 1,000, but these figures cover the aggregate. Two of five responses are shown without summing or normalising rounded values. Does not measure actual consent, email tracking or Connectif customers. Explore the data table Scroll left or right to see all columns __Objection depends on the information proposed for use (%)__ | Category | Would not want processing | Emphatically objects | | -------------------------------- | ------------------------- | -------------------- | | Previous purchases | 21% | 8% | | Social media activity | 28% | 15% | | Location within about 500 metres | 32% | 19% | ## Digital commerce's scale explains why coverage matters For market context, Spain's INE found in 2025 that 59.6% of people aged 16 to 74 had bought online in the three months before interview , compared with 56.7% in 2024\. The Spanish survey uses three-stage stratified sampling; its theoretical sample was 26,862 dwellings, with collection from March 31 to July 13, 2025. The published series differs by 2.9 percentage points. These are self-reported purchases by people, rather than campaign conversions or Connectif contacts. The window precedes each interview. The figure establishes the scale of the market in which commercial communication is used, without measuring tracking acceptance or the feature's effect on sales. Those questions need their own observations and denominators. Within a broad population of buyers, businesses can have relationships with people whose preferences and observation conditions differ. Commercial evaluation should not assume that those offering more individual signals represent everyone else. Coverage bias can particularly affect teams using interaction histories to decide follow-up intensity or campaign spending. More detailed records can describe a selected audience rather than a more representative one. The national indicator and email statistics have different denominators. Connecting them explains context but cannot calculate how many buyers will receive a message or what share will accept tracking. That estimate requires actual audience data and collection conditions. This publication does not turn ecommerce penetration into a fictional consent rate or imply that an official household survey measured the platform's users. Willingness to receive useful communication asks a different question. In Customer Experience Trends, EAE recorded 28.9% of Spanish consumers saying they liked notifications about relevant products, while 56.9% valued advice from a real person. Statements can overlap. This interaction preference establishes neither permission to link opens to a profile nor which message will generate a purchase; it indicates the usefulness communication should offer even when individual observation is absent. The data behind the story ### Wanting communication does not establish agreement to tracking Statements about personalisation and brand interaction, consumers in Spain; report published February 2024. Select the statement Tap or hover for details. All values are also available in the data table. Expand notesCollapse notes **Sources:** Statista; EAE: original report, pp. 52 and 62 EAE: 1,000 consumers aged 18–70\. February 2024 is publication date; fieldwork period, interview mode and sampling frame are not detailed in the report. Statements can overlap; not an additive distribution or consent or purchase rates. The 9.1% refers to AI recording preferences for personalised advertising, not consent to any AI use. Explore the data table Scroll left or right to see all columns __Wanting communication does not establish agreement to tracking (%)__ | Category | Select the statement | | ---------------------------------------------- | -------------------- | | Advice from a real person | 56.9% | | Relevant product notifications | 28.9% | | Dislikes personalisation | 12.9% | | Does not mind history or name use | 10.8% | | Does not mind AI recording preferences for ads | 9.1% | | Does not know | 7.1% | ## Three populations a report should keep separate A programme review can distinguish eligible recipients, delivered messages and contacts with available individual tracking. The first population answers who could receive communication. The second describes delivery under the channel's technical definition. The third determines which profiles can supply associated signals for later segmentation. These populations can overlap, but none can be substituted for the others without changing the measurement question. Every rate should state its corresponding population. Dividing linked opens by all sends can describe observed coverage; dividing them only by contacts with tracking available describes response in a restricted population. Both can be useful, but their labels must prevent one being presented as if it represented behaviour across the whole audience. A clear denominator makes the difference visible to decision-makers. A configuration change can move those denominators without changing customer behaviour. Comparing an earlier campaign with a later one requires marking the change and explaining its scope. Otherwise, lost individual links can resemble deterioration in the content, or expanded coverage can resemble a commercial improvement that never happened. A measurement series needs its configuration history alongside the response figures. Events and people should also remain separate. One person can generate several opens or clicks; an event total does not establish how many distinct recipients participated. Aggregate data may limit deduplication, and the definition of each report should explain those limits. The announcement supplies no study measuring these differences, so this revision does not invent a percentage of individually observable contacts. ## Opening an email remains an imperfect signal The limitations do not begin with this feature. Apple explains that its privacy protection can download remote content in the background . Loading a resource used to record activity therefore does not always represent deliberate reading. That technical limit can exist even when a platform is able to associate the recorded event with an individual contact profile. A serious report should distinguish an observed signal from the behaviour it is intended to represent. Opens can help identify patterns but do not prove understanding or purchase intention. Content decisions need other observations when they are available and appropriate, such as resolved questions or confirmed purchases, without automatically crediting any single observation as the cause of the customer's decision. Tracking configuration and email-client privacy protection operate at different levels. One can restrict association with a contact while the other changes how content loads. Combining both phenomena under a single label of reduced interest conceals their mechanisms. Reviewing signal provenance helps explain why it is missing or why it appears without an individual deliberately reading the message. The creative consequence is concrete. Optimising subject lines exclusively for opens can reward an indicator whose coverage or technical meaning has changed. Content needs a clearer commercial question: what useful information it offers and which relevant step it should enable. That question maintains focus when part of individually associated tracking is no longer available to guide follow-up decisions. ## Automation needs review according to its dependencies A team using the feature should identify journeys depending on an associated open or click. An inventory can reveal an entry condition, an exit condition or a waiting period based on those signals. This is a proposed operational review, not a claim that Connectif automatically adjusts every journey in every store when the configuration is activated. The guide documents a transition detail: creation of the consent field is asynchronous, and the field is unavailable to workflows and segments until that process finishes. Duration depends on contact volume rather than a published universal deadline. This wait differs from a person's no-information state: an unavailable definition and an unknown value within an existing definition describe different situations. A campaign owner needs to recognise which is occurring before interpreting an empty selection as lack of interest or applying another rule to an audience whose information is still changing during the configuration process. Missing signals can have different effects depending on their position. If the signal starts a message sequence, someone may never enter it; if it permits exit, the person could remain longer. Both possibilities should be examined against reasonable communication rules. Looking only at the number of contacts in the final dashboard segment does not explain how a dependency changed the journey. The no-information state needs explicit treatment within the business. It is not an unknown positive preference that can be completed by intuition. The announced guide treats it as absence of consent for event association. Proposed data governance should preserve that meaning and prevent an import from translating it into a different state without evidence supporting the change in the underlying preference. The documentation describes separate settings for existing and new contacts. That capability provides a review point before changes are applied. Marketing and the data owner need to understand the population affected by each choice and the evidence supporting its state. The tool offers a technical capability; deciding the actual configuration remains the responsibility of the company using that capability. ## Replacing a signal does not remove interpretation requirements A website visit, purchase and email click are different events, with different origins and uses. Replacing a missing signal with another can change a segment's purpose. Someone buying without a recorded click is not equivalent to someone showing interest in technical content. The revised rule must describe the behaviour it actually observes rather than preserving an old label with a new meaning. Campaign parameters on a link can help identify where a visit originated when that information is observed. They cannot turn an unlinked open into a verified identity or establish which sale was additional. A commercial review should assess their specific role without presenting a traffic label as a universal solution to every loss of individually associated tracking coverage. Choosing another channel also needs to begin with the actual customer relationship. A restriction on email tracking should not be interpreted as permission to increase communication elsewhere. Planning can consider different routes when they make sense for users, while keeping preferences, purposes and available information separate for each channel. The absence of one measurement does not resolve those other decisions. These are design and measurement considerations. This article does not turn a product announcement into a general legal conclusion for every market or certify any particular deployment. Anonymisation is attributed to the provider's description. Its full technical scope and the choices of a business activating the feature have not been independently audited as part of this revision. ## Comparing outcomes without selecting only observable people A programme can appear more effective when measured only among contacts offering more signals. Those people may already have a more active relationship with the brand. Excluding everyone else reduces the ability to understand effects across the eligible audience. Selection by observability must therefore be distinguished from selection by behaviour before the results are used to justify larger communication budgets. For a proposed evaluation, assignment to a promotional action should precede observation of results and use comparable criteria between groups. When purchasing outcomes are appropriate to measure, the primary result could use a transactional source and a defined purpose without requiring an open history for every person. This does not assume universal access or automatically legitimate use of all transactional data. The comparison should include non-buyers. Calculating contribution only among purchasers answers another question and can conceal the audience receiving messages without converting. Observation duration and return treatment should be fixed beforehand so differences are not merely explained by one group having more time. Consistent rules allow the commercial outcome to remain interpretable even when email-event coverage differs between recipients. Aggregate activity would provide a complementary channel measure. It could show whether a message still generates response under its definition but could not identify alone which people should receive a continuation. Separating campaign evaluation from individual activation preserves analytical usefulness without demanding that a count perform an identification function it no longer has in the announced configuration. ## A data change needs owners and an interpretable history Deployment can document the date, configuration and affected population to keep later series understandable. A precise annotation is more useful than a generic privacy-change warning. It identifies when an indicator movement might arise from recording changes and when content, acquisition or commercial conditions deserve investigation. It does not attribute every subsequent movement automatically to the new feature. An owner is also needed for correspondence between systems. A state imported from another form must retain its meaning and provenance. Synchronisation turning missing information into acceptance can create a data-quality problem even when the transfer finishes without a technical error. The proposed review examines semantic consistency as well as whether an update successfully reaches the receiving application. Retaining less individual detail can reduce information available for certain segments while leaving enough context for other tasks. Assessing that difference requires identifying decisions that depended on the history. The source provides no quantified sales loss or performance gain allowing the feature to be converted into a calculated financial return. Its commercial consequences need observation rather than assumptions about the value of every recorded signal. Internal reports should explain limitations in a form useful to the person deciding budgets. A clear coverage label prevents fewer linked opens being treated immediately as proof that creative work stopped performing. It also prevents spending from expanding simply because a rate calculated within a more selected population appears artificially higher than the earlier, broader measurement series. ## What the announcement establishes and what evidence comes next The source confirms a three-state feature and an announced separation between associated events and anonymised counts. Its commercial explanation appeared in September; the guide existed from August and was edited in September. That chronology describes product documentation and communication rather than a sales experiment proving the profitability of activating the feature. The original article date remains unchanged by this revision. Useful next evidence would include precise definitions of unique and total events, coverage by period and consequences for existing journeys. A business assessing the change needs to know which measures remain comparable and which require a new series. The measurement examples proposed here cannot substitute for that documentation or be presented as results observed at a particular Spanish client. This revision retains Connectif's original documents and legal identity, adds INE statistical context and Apple's content-loading documentation, and claims no nonexistent interviews or private data access. The commercial effect remains unknown. The analysis distinguishes three questions a single dashboard cannot answer: whether activity occurred, who can be observed individually and which commercial decision that evidence actually supports. ## In this article ### Companies * [Connectif](https://elacelerador.es/en/company/connectif/) ### Sources and documents * [Connectif: anuncio de seguimiento](https://connectif.ai/blog/privacidad-del-seguimiento-de-emails/?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Connectif * [Connectif: identidad legal](https://connectif.ai/aviso-legal/?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Connectif * [Connectif: función de seguimiento](https://support.connectif.ai/hc/es/articles/29425203027356-Privacidad-del-seguimiento-de-emails?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Connectif * [INE: 2025 household ICT survey and methodology](https://www.ine.es/dyngs/Prensa/TICH2025.htm?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Instituto Nacional de Estadística * [Apple: privacy protection and remote-content loading](https://support.apple.com/en-us/102289?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Apple * Statista * [Original report, p. 19; methodology, p. 40](https://iabeurope.eu/wp-content/uploads/IAB-Europe-Ad-Funding-Online-Services-Report-2025-FINAL.pdf?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · iabeurope.eu * [EAE: original report, pp. 52 and 62](https://marketing.eae.es/Informes%202024/EAE%5FCustomer%20Experience%20Trends%5F.pdf?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · marketing.eae.es Share [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Felacelerador.es%2Fen%2Fdata-and-automation%2Fconnectif-email-measurement-consent%2F%3Futm%5Fsource%3Dlinkedin%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on LinkedIn. 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His work spans product marketing, SEO, paid advertising and deep online tracking, including behavioral analytics and attribution. ## Related articles [Data and automation](https://elacelerador.es/en/data-and-automation/) Analysis ### [Automate marketing with clear accountability](https://elacelerador.es/en/data-and-automation/automate-marketing-with-clear-accountability/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 5 min [Data and automation](https://elacelerador.es/en/data-and-automation/) Analysis ### [Reduce the effort of joining a platform](https://elacelerador.es/en/data-and-automation/reduce-the-effort-of-joining-a-platform/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 5 min [Data and automation](https://elacelerador.es/en/data-and-automation/) Analysis ### [Connect campaigns, product and revenue](https://elacelerador.es/en/data-and-automation/connect-campaigns-product-revenue/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 5 min ```json {"@context":"https://schema.org","@graph":[{"@type":["Organization","NewsMediaOrganization"],"@id":"https://elacelerador.es/#publisher","name":"El Acelerador","url":"https://elacelerador.es/","description":"Marketing and growth hacking with examples from Spanish companies.","email":"pr@elacelerador.es","publishingPrinciples":"https://elacelerador.es/en/editorial-policy/","correctionsPolicy":"https://elacelerador.es/en/editorial-policy/","verificationFactCheckingPolicy":"https://elacelerador.es/en/editorial-policy/","masthead":"https://elacelerador.es/en/about/","ownershipFundingInfo":"https://elacelerador.es/en/about/","logo":{"@type":"ImageObject","url":"https://elacelerador.es/icon-512.png?v=20261017-stacked"}},{"@type":"Person","@id":"https://elacelerador.es/author/marian-vasile/#person","name":"Marian Vasile","url":"https://elacelerador.es/en/author/marian-vasile/","description":"Marian Vasile is a MarTech and growth professional. 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