To\u00a0round off\u00a0our latest article\u00a0series\u00a0on the challenges of data quality and the risks associated with unreliable data, here is a summary of the 28 quality criteria essential to improve marketing performance, campaign success and strategic decision-making.\u00a0<\/p>\n
1 \u2013\u00a0<\/strong>C<\/strong>ertified measure<\/strong>ment<\/strong>\u00a0<\/strong>\u00a0<\/h2>\nChoose a digital analytics partner whose measurement is\u00a0certified<\/a> by\u00a0independent multimedia measurement organisations such as ACPM (France), OJD Spain, T\u00dcV Saarland (Germany), ABC (United Kingdom), KIA-INDEX (Sweden) and ENED (Greece).\u00a0<\/p>\n2 \u2013 Identified (and excluded) robot traffic<\/strong>\u00a0<\/h2>\nYour analytics supplier can identify these robots using an official\u00a0IAB<\/a>\u00a0exclusion list that is regularly updated.\u00a0\u00a0<\/p>\n3 \u2013 An independent analysis tool<\/strong>\u00a0<\/h2>\nAn\u00a0analytics solution<\/a>\u00a0provider should not be both judge and\u00a0jury. There must be no reason or motivation to overestimate or manipulate the reported data, nor any conflict of interest in\u00a0your\u00a0activity.\u00a0<\/p>\n4 \u2013 A transparent algorithm on its calculations<\/strong>\u00a0<\/h2>\nYour digital analytics supplier must be able to explain to you, in complete transparency, how the indicator calculations are carried out.\u00a0In other words, to help you understand what is included in the algorithm. Beware of black boxes that do not offer any possibility of human interaction when calculating your data.\u00a0<\/p>\n
5 \u2013 Data control procedures\u00a0<\/strong>\u00a0<\/h2>\nAs an integral part of your good data governance, regular procedures (automatic tests for example) allow you to check the presence of all tags.\u00a0<\/p>\n
6 \u2013 Complete\u00a0<\/strong>tagging<\/strong>\u00a0audits<\/strong>\u00a0<\/h2>\nThey must be carried out in particular in the event of a very important modification redesign of your site and\/or applications.\u00a0<\/p>\n
7 \u2013 No sampled data<\/strong>\u00a0<\/h2>\nThey can highlight general trends, but the smaller their size, the less representative they are of reality.\u00a0Sampling<\/a>\u00a0can be risky, especially on financial data.\u00a0\u00a0<\/p>\n8 \u2013 Service contracts (SLAs)<\/strong>\u00a0<\/h2>\nYour Web Analytics provider is contractually committed to guaranteeing you a data collection rate close to 100%.<\/p>\n
9 \u2013 A\u00a0<\/strong>first domain<\/em><\/strong>\u00a0measure<\/strong>ment<\/strong>\u00a0<\/h2>\nYou recover as much of the traffic blocked by\u00a0ad blockers<\/a>\u00a0or\u00a0ITP<\/a>\u00a0systems as possible via a collection solution on your own domain name.
Important note:<\/strong> the CDDC method available from AT Internet is fully compliant with the GDPR and is not exempt from the collection of required consent for all websites.\u00a0<\/p>\n10 \u2013 Accessible and well formatted data\u00a0<\/strong>\u00a0<\/h2>\nTest how your data is retrieved and presented.\u00a0Is it\u00a0being\u00a0collected\u00a0as planned? Are the values displayed correctly on your interface?\u00a0<\/p>\n
11 \u2013 Fair and verified values<\/strong>\u00a0<\/h2>\nCheck<\/a>\u00a0that no technical (collection) elements could have altered the\u00a0accuracy\u00a0of the figures in your analysis.\u00a0<\/p>\n12 \u2013 Tools for customi<\/strong>s<\/strong>ing\u00a0<\/strong>tagging<\/strong>\u00a0<\/strong>\u00a0<\/h2>\nBy defining customised data processing rules, you are able to correct errors due to\u00a0tagging\u00a0problems, enrich collected data and exclude unwanted traffic, all without any intervention from technical teams.\u00a0<\/p>\n
13 \u2013 Automated quality control<\/strong>\u00a0<\/h2>\nConsider using\u00a0tools<\/a> that\u00a0will allow your analyst to update the data independently, without relying on technical teams to modify the code.\u00a0<\/p>\n14 \u2013 Real time data\u00a0<\/strong>\u00a0<\/h2>\nVerify that your digital analytics solution can provide you with real-time KPIs, i.e. that the data availability does not exceed 5 minutes on your analyses and dashboards.\u00a0<\/p>\n
15 \u2013 A reusable data<\/strong>\u00a0<\/h2>\nEnsure that your analytics data is reusable for customer re-engagement, push notifications, re-targeting and e-mail campaigns.\u00a0\u00a0<\/p>\n
16 \u2013 An exportable data\u00a0<\/strong>\u00a0<\/h2>\nYou must be able to extract millions of events every hour to feed your IS or data lake (or other Data Science project) with highly granular and up-to-date analytical data.\u00a0<\/p>\n
17 \u2013 Data that can be understood immediately<\/strong>\u00a0<\/h2>\nUse the customer support experts at your analytics supplier (if any) to decrypt your data quickly.\u00a0\u00a0<\/p>\n
18 \u2013 Increased data<\/strong>\u00a0<\/h2>\nUse the\u00a0Machine Learning<\/a>\u00a0features of your analytics solution to anticipate or predict possible urgent and critical events.\u00a0<\/p>\n19 \u2013 Governance in place\u00a0<\/strong>\u00a0<\/h2>\nThe collection, processing and use of data is part of a governance strategy initiated by the company management and driven by a CDO or data expert.\u00a0<\/p>\n
20 \u2013 Comparable indicators\u00a0<\/strong>\u00a0<\/h2>\nDetermine which analytical solution serves as a reference for the entire company. Then, more precisely define and calculate the indicators to be used as benchmarks in the different services.\u00a0<\/p>\n
21 \u2013 Common analysis tools<\/strong>\u00a0<\/h2>\nUse\u00a0dashboards<\/a>\u00a0and analytical reports that can be adapted to all types of data users in the company: everyone can base their analyses and decisions on data collected, calculated and processed in a consistent way.\u00a0<\/p>\n22 \u2013 A cross-device vision\u00a0<\/strong>\u00a0<\/h2>\nAlways keep an overview when\u00a0analysing your performance<\/a>. Avoid approaches that are too platform or device specific, as they may miss important insights.\u00a0<\/p>\n23 \u2013 Exact data\u00a0<\/strong>\u00a0<\/h2>\nThe law requires that the data be\u00a0accurate<\/em>\u00a0to be compliant. You must take reasonable steps to avoid processing incorrect data (imagine, for example, the consequences of data errors in a medical record).\u00a0<\/p>\n24 \u2013 A collection of lawful consent<\/strong>\u00a0<\/h2>\nIt is also a condition of compliance. Some Analytics solutions such as AT Internet benefit from an exemption from data collection, which makes measurement easier and more reliable.\u00a0<\/p>\n
25 \u2013 A limited\u00a0<\/strong>cookie\u00a0<\/strong>lifetime<\/strong>\u00a0<\/h2>\nIf the Internet user has given his or her consent, your Web Analytics solution must offer functionalities to ensure that the lifetime of cookies is respected.\u00a0<\/p>\n
26 \u2013 Complete and transparent information<\/strong>\u00a0<\/h2>\nIt is a duty to the Internet user. These principles concern the processing of data and in particular: duration and place of storage and type of data collected.\u00a0<\/p>\n
27 \u2013 A clear and precise definition of personal data<\/strong>\u00a0<\/h2>\nThis is one of the obligations of the\u00a0GDPR<\/a>\u00a0(section 14). At AT Internet, all types of analytical data are considered as personal data.\u00a0<\/p>\n28 \u2013 Data accessibility<\/strong>\u00a0<\/h2>\nYou and your subcontractor must have the capacity to respond to the rights of the persons concerned. AT Internet is organised on this point.\u00a0\u00a0<\/p>\n
AT Internet offers\u00a0a wide range of tools for quality control<\/a> of\u00a0analytical data. Fewer errors are therefore likely to alter your data and influence your decisions.\u00a0<\/p>\nIf you are interested in the subject of data quality, download our latest guide:<\/p>\n![\"Data](\"https:\/\/blog.atinternet.com\/wp-content\/uploads\/2019\/09\/In-post-banner-Data-Quality-EN.jpg\")
<\/a><\/figure>\n
2 \u2013 Identified (and excluded) robot traffic<\/strong>\u00a0<\/h2>\nYour analytics supplier can identify these robots using an official\u00a0IAB<\/a>\u00a0exclusion list that is regularly updated.\u00a0\u00a0<\/p>\n3 \u2013 An independent analysis tool<\/strong>\u00a0<\/h2>\nAn\u00a0analytics solution<\/a>\u00a0provider should not be both judge and\u00a0jury. There must be no reason or motivation to overestimate or manipulate the reported data, nor any conflict of interest in\u00a0your\u00a0activity.\u00a0<\/p>\n4 \u2013 A transparent algorithm on its calculations<\/strong>\u00a0<\/h2>\nYour digital analytics supplier must be able to explain to you, in complete transparency, how the indicator calculations are carried out.\u00a0In other words, to help you understand what is included in the algorithm. Beware of black boxes that do not offer any possibility of human interaction when calculating your data.\u00a0<\/p>\n
5 \u2013 Data control procedures\u00a0<\/strong>\u00a0<\/h2>\nAs an integral part of your good data governance, regular procedures (automatic tests for example) allow you to check the presence of all tags.\u00a0<\/p>\n
6 \u2013 Complete\u00a0<\/strong>tagging<\/strong>\u00a0audits<\/strong>\u00a0<\/h2>\nThey must be carried out in particular in the event of a very important modification redesign of your site and\/or applications.\u00a0<\/p>\n
7 \u2013 No sampled data<\/strong>\u00a0<\/h2>\nThey can highlight general trends, but the smaller their size, the less representative they are of reality.\u00a0Sampling<\/a>\u00a0can be risky, especially on financial data.\u00a0\u00a0<\/p>\n8 \u2013 Service contracts (SLAs)<\/strong>\u00a0<\/h2>\nYour Web Analytics provider is contractually committed to guaranteeing you a data collection rate close to 100%.<\/p>\n
9 \u2013 A\u00a0<\/strong>first domain<\/em><\/strong>\u00a0measure<\/strong>ment<\/strong>\u00a0<\/h2>\nYou recover as much of the traffic blocked by\u00a0ad blockers<\/a>\u00a0or\u00a0ITP<\/a>\u00a0systems as possible via a collection solution on your own domain name.
Important note:<\/strong> the CDDC method available from AT Internet is fully compliant with the GDPR and is not exempt from the collection of required consent for all websites.\u00a0<\/p>\n10 \u2013 Accessible and well formatted data\u00a0<\/strong>\u00a0<\/h2>\nTest how your data is retrieved and presented.\u00a0Is it\u00a0being\u00a0collected\u00a0as planned? Are the values displayed correctly on your interface?\u00a0<\/p>\n
11 \u2013 Fair and verified values<\/strong>\u00a0<\/h2>\nCheck<\/a>\u00a0that no technical (collection) elements could have altered the\u00a0accuracy\u00a0of the figures in your analysis.\u00a0<\/p>\n12 \u2013 Tools for customi<\/strong>s<\/strong>ing\u00a0<\/strong>tagging<\/strong>\u00a0<\/strong>\u00a0<\/h2>\nBy defining customised data processing rules, you are able to correct errors due to\u00a0tagging\u00a0problems, enrich collected data and exclude unwanted traffic, all without any intervention from technical teams.\u00a0<\/p>\n
13 \u2013 Automated quality control<\/strong>\u00a0<\/h2>\nConsider using\u00a0tools<\/a> that\u00a0will allow your analyst to update the data independently, without relying on technical teams to modify the code.\u00a0<\/p>\n14 \u2013 Real time data\u00a0<\/strong>\u00a0<\/h2>\nVerify that your digital analytics solution can provide you with real-time KPIs, i.e. that the data availability does not exceed 5 minutes on your analyses and dashboards.\u00a0<\/p>\n
15 \u2013 A reusable data<\/strong>\u00a0<\/h2>\nEnsure that your analytics data is reusable for customer re-engagement, push notifications, re-targeting and e-mail campaigns.\u00a0\u00a0<\/p>\n
16 \u2013 An exportable data\u00a0<\/strong>\u00a0<\/h2>\nYou must be able to extract millions of events every hour to feed your IS or data lake (or other Data Science project) with highly granular and up-to-date analytical data.\u00a0<\/p>\n
17 \u2013 Data that can be understood immediately<\/strong>\u00a0<\/h2>\nUse the customer support experts at your analytics supplier (if any) to decrypt your data quickly.\u00a0\u00a0<\/p>\n
18 \u2013 Increased data<\/strong>\u00a0<\/h2>\nUse the\u00a0Machine Learning<\/a>\u00a0features of your analytics solution to anticipate or predict possible urgent and critical events.\u00a0<\/p>\n19 \u2013 Governance in place\u00a0<\/strong>\u00a0<\/h2>\nThe collection, processing and use of data is part of a governance strategy initiated by the company management and driven by a CDO or data expert.\u00a0<\/p>\n
20 \u2013 Comparable indicators\u00a0<\/strong>\u00a0<\/h2>\nDetermine which analytical solution serves as a reference for the entire company. Then, more precisely define and calculate the indicators to be used as benchmarks in the different services.\u00a0<\/p>\n
21 \u2013 Common analysis tools<\/strong>\u00a0<\/h2>\nUse\u00a0dashboards<\/a>\u00a0and analytical reports that can be adapted to all types of data users in the company: everyone can base their analyses and decisions on data collected, calculated and processed in a consistent way.\u00a0<\/p>\n22 \u2013 A cross-device vision\u00a0<\/strong>\u00a0<\/h2>\nAlways keep an overview when\u00a0analysing your performance<\/a>. Avoid approaches that are too platform or device specific, as they may miss important insights.\u00a0<\/p>\n23 \u2013 Exact data\u00a0<\/strong>\u00a0<\/h2>\nThe law requires that the data be\u00a0accurate<\/em>\u00a0to be compliant. You must take reasonable steps to avoid processing incorrect data (imagine, for example, the consequences of data errors in a medical record).\u00a0<\/p>\n24 \u2013 A collection of lawful consent<\/strong>\u00a0<\/h2>\nIt is also a condition of compliance. Some Analytics solutions such as AT Internet benefit from an exemption from data collection, which makes measurement easier and more reliable.\u00a0<\/p>\n
25 \u2013 A limited\u00a0<\/strong>cookie\u00a0<\/strong>lifetime<\/strong>\u00a0<\/h2>\nIf the Internet user has given his or her consent, your Web Analytics solution must offer functionalities to ensure that the lifetime of cookies is respected.\u00a0<\/p>\n
26 \u2013 Complete and transparent information<\/strong>\u00a0<\/h2>\nIt is a duty to the Internet user. These principles concern the processing of data and in particular: duration and place of storage and type of data collected.\u00a0<\/p>\n
27 \u2013 A clear and precise definition of personal data<\/strong>\u00a0<\/h2>\nThis is one of the obligations of the\u00a0GDPR<\/a>\u00a0(section 14). At AT Internet, all types of analytical data are considered as personal data.\u00a0<\/p>\n28 \u2013 Data accessibility<\/strong>\u00a0<\/h2>\nYou and your subcontractor must have the capacity to respond to the rights of the persons concerned. AT Internet is organised on this point.\u00a0\u00a0<\/p>\n
AT Internet offers\u00a0a wide range of tools for quality control<\/a> of\u00a0analytical data. Fewer errors are therefore likely to alter your data and influence your decisions.\u00a0<\/p>\nIf you are interested in the subject of data quality, download our latest guide:<\/p>\n<\/a><\/figure>\n
3 \u2013 An independent analysis tool<\/strong>\u00a0<\/h2>\nAn\u00a0analytics solution<\/a>\u00a0provider should not be both judge and\u00a0jury. There must be no reason or motivation to overestimate or manipulate the reported data, nor any conflict of interest in\u00a0your\u00a0activity.\u00a0<\/p>\n4 \u2013 A transparent algorithm on its calculations<\/strong>\u00a0<\/h2>\nYour digital analytics supplier must be able to explain to you, in complete transparency, how the indicator calculations are carried out.\u00a0In other words, to help you understand what is included in the algorithm. Beware of black boxes that do not offer any possibility of human interaction when calculating your data.\u00a0<\/p>\n
5 \u2013 Data control procedures\u00a0<\/strong>\u00a0<\/h2>\nAs an integral part of your good data governance, regular procedures (automatic tests for example) allow you to check the presence of all tags.\u00a0<\/p>\n
6 \u2013 Complete\u00a0<\/strong>tagging<\/strong>\u00a0audits<\/strong>\u00a0<\/h2>\nThey must be carried out in particular in the event of a very important modification redesign of your site and\/or applications.\u00a0<\/p>\n
7 \u2013 No sampled data<\/strong>\u00a0<\/h2>\nThey can highlight general trends, but the smaller their size, the less representative they are of reality.\u00a0Sampling<\/a>\u00a0can be risky, especially on financial data.\u00a0\u00a0<\/p>\n8 \u2013 Service contracts (SLAs)<\/strong>\u00a0<\/h2>\nYour Web Analytics provider is contractually committed to guaranteeing you a data collection rate close to 100%.<\/p>\n
9 \u2013 A\u00a0<\/strong>first domain<\/em><\/strong>\u00a0measure<\/strong>ment<\/strong>\u00a0<\/h2>\nYou recover as much of the traffic blocked by\u00a0ad blockers<\/a>\u00a0or\u00a0ITP<\/a>\u00a0systems as possible via a collection solution on your own domain name.
Important note:<\/strong> the CDDC method available from AT Internet is fully compliant with the GDPR and is not exempt from the collection of required consent for all websites.\u00a0<\/p>\n10 \u2013 Accessible and well formatted data\u00a0<\/strong>\u00a0<\/h2>\nTest how your data is retrieved and presented.\u00a0Is it\u00a0being\u00a0collected\u00a0as planned? Are the values displayed correctly on your interface?\u00a0<\/p>\n
11 \u2013 Fair and verified values<\/strong>\u00a0<\/h2>\nCheck<\/a>\u00a0that no technical (collection) elements could have altered the\u00a0accuracy\u00a0of the figures in your analysis.\u00a0<\/p>\n12 \u2013 Tools for customi<\/strong>s<\/strong>ing\u00a0<\/strong>tagging<\/strong>\u00a0<\/strong>\u00a0<\/h2>\nBy defining customised data processing rules, you are able to correct errors due to\u00a0tagging\u00a0problems, enrich collected data and exclude unwanted traffic, all without any intervention from technical teams.\u00a0<\/p>\n
13 \u2013 Automated quality control<\/strong>\u00a0<\/h2>\nConsider using\u00a0tools<\/a> that\u00a0will allow your analyst to update the data independently, without relying on technical teams to modify the code.\u00a0<\/p>\n14 \u2013 Real time data\u00a0<\/strong>\u00a0<\/h2>\nVerify that your digital analytics solution can provide you with real-time KPIs, i.e. that the data availability does not exceed 5 minutes on your analyses and dashboards.\u00a0<\/p>\n
15 \u2013 A reusable data<\/strong>\u00a0<\/h2>\nEnsure that your analytics data is reusable for customer re-engagement, push notifications, re-targeting and e-mail campaigns.\u00a0\u00a0<\/p>\n
16 \u2013 An exportable data\u00a0<\/strong>\u00a0<\/h2>\nYou must be able to extract millions of events every hour to feed your IS or data lake (or other Data Science project) with highly granular and up-to-date analytical data.\u00a0<\/p>\n
17 \u2013 Data that can be understood immediately<\/strong>\u00a0<\/h2>\nUse the customer support experts at your analytics supplier (if any) to decrypt your data quickly.\u00a0\u00a0<\/p>\n
18 \u2013 Increased data<\/strong>\u00a0<\/h2>\nUse the\u00a0Machine Learning<\/a>\u00a0features of your analytics solution to anticipate or predict possible urgent and critical events.\u00a0<\/p>\n19 \u2013 Governance in place\u00a0<\/strong>\u00a0<\/h2>\nThe collection, processing and use of data is part of a governance strategy initiated by the company management and driven by a CDO or data expert.\u00a0<\/p>\n
20 \u2013 Comparable indicators\u00a0<\/strong>\u00a0<\/h2>\nDetermine which analytical solution serves as a reference for the entire company. Then, more precisely define and calculate the indicators to be used as benchmarks in the different services.\u00a0<\/p>\n
21 \u2013 Common analysis tools<\/strong>\u00a0<\/h2>\nUse\u00a0dashboards<\/a>\u00a0and analytical reports that can be adapted to all types of data users in the company: everyone can base their analyses and decisions on data collected, calculated and processed in a consistent way.\u00a0<\/p>\n22 \u2013 A cross-device vision\u00a0<\/strong>\u00a0<\/h2>\nAlways keep an overview when\u00a0analysing your performance<\/a>. Avoid approaches that are too platform or device specific, as they may miss important insights.\u00a0<\/p>\n23 \u2013 Exact data\u00a0<\/strong>\u00a0<\/h2>\nThe law requires that the data be\u00a0accurate<\/em>\u00a0to be compliant. You must take reasonable steps to avoid processing incorrect data (imagine, for example, the consequences of data errors in a medical record).\u00a0<\/p>\n24 \u2013 A collection of lawful consent<\/strong>\u00a0<\/h2>\nIt is also a condition of compliance. Some Analytics solutions such as AT Internet benefit from an exemption from data collection, which makes measurement easier and more reliable.\u00a0<\/p>\n
25 \u2013 A limited\u00a0<\/strong>cookie\u00a0<\/strong>lifetime<\/strong>\u00a0<\/h2>\nIf the Internet user has given his or her consent, your Web Analytics solution must offer functionalities to ensure that the lifetime of cookies is respected.\u00a0<\/p>\n
26 \u2013 Complete and transparent information<\/strong>\u00a0<\/h2>\nIt is a duty to the Internet user. These principles concern the processing of data and in particular: duration and place of storage and type of data collected.\u00a0<\/p>\n
27 \u2013 A clear and precise definition of personal data<\/strong>\u00a0<\/h2>\nThis is one of the obligations of the\u00a0GDPR<\/a>\u00a0(section 14). At AT Internet, all types of analytical data are considered as personal data.\u00a0<\/p>\n28 \u2013 Data accessibility<\/strong>\u00a0<\/h2>\nYou and your subcontractor must have the capacity to respond to the rights of the persons concerned. AT Internet is organised on this point.\u00a0\u00a0<\/p>\n
AT Internet offers\u00a0a wide range of tools for quality control<\/a> of\u00a0analytical data. Fewer errors are therefore likely to alter your data and influence your decisions.\u00a0<\/p>\nIf you are interested in the subject of data quality, download our latest guide:<\/p>\n<\/a><\/figure>\n
4 \u2013 A transparent algorithm on its calculations<\/strong>\u00a0<\/h2>\nYour digital analytics supplier must be able to explain to you, in complete transparency, how the indicator calculations are carried out.\u00a0In other words, to help you understand what is included in the algorithm. Beware of black boxes that do not offer any possibility of human interaction when calculating your data.\u00a0<\/p>\n
5 \u2013 Data control procedures\u00a0<\/strong>\u00a0<\/h2>\nAs an integral part of your good data governance, regular procedures (automatic tests for example) allow you to check the presence of all tags.\u00a0<\/p>\n
6 \u2013 Complete\u00a0<\/strong>tagging<\/strong>\u00a0audits<\/strong>\u00a0<\/h2>\nThey must be carried out in particular in the event of a very important modification redesign of your site and\/or applications.\u00a0<\/p>\n
7 \u2013 No sampled data<\/strong>\u00a0<\/h2>\nThey can highlight general trends, but the smaller their size, the less representative they are of reality.\u00a0Sampling<\/a>\u00a0can be risky, especially on financial data.\u00a0\u00a0<\/p>\n8 \u2013 Service contracts (SLAs)<\/strong>\u00a0<\/h2>\nYour Web Analytics provider is contractually committed to guaranteeing you a data collection rate close to 100%.<\/p>\n
9 \u2013 A\u00a0<\/strong>first domain<\/em><\/strong>\u00a0measure<\/strong>ment<\/strong>\u00a0<\/h2>\nYou recover as much of the traffic blocked by\u00a0ad blockers<\/a>\u00a0or\u00a0ITP<\/a>\u00a0systems as possible via a collection solution on your own domain name.
Important note:<\/strong> the CDDC method available from AT Internet is fully compliant with the GDPR and is not exempt from the collection of required consent for all websites.\u00a0<\/p>\n10 \u2013 Accessible and well formatted data\u00a0<\/strong>\u00a0<\/h2>\nTest how your data is retrieved and presented.\u00a0Is it\u00a0being\u00a0collected\u00a0as planned? Are the values displayed correctly on your interface?\u00a0<\/p>\n
11 \u2013 Fair and verified values<\/strong>\u00a0<\/h2>\nCheck<\/a>\u00a0that no technical (collection) elements could have altered the\u00a0accuracy\u00a0of the figures in your analysis.\u00a0<\/p>\n12 \u2013 Tools for customi<\/strong>s<\/strong>ing\u00a0<\/strong>tagging<\/strong>\u00a0<\/strong>\u00a0<\/h2>\nBy defining customised data processing rules, you are able to correct errors due to\u00a0tagging\u00a0problems, enrich collected data and exclude unwanted traffic, all without any intervention from technical teams.\u00a0<\/p>\n
13 \u2013 Automated quality control<\/strong>\u00a0<\/h2>\nConsider using\u00a0tools<\/a> that\u00a0will allow your analyst to update the data independently, without relying on technical teams to modify the code.\u00a0<\/p>\n14 \u2013 Real time data\u00a0<\/strong>\u00a0<\/h2>\nVerify that your digital analytics solution can provide you with real-time KPIs, i.e. that the data availability does not exceed 5 minutes on your analyses and dashboards.\u00a0<\/p>\n
15 \u2013 A reusable data<\/strong>\u00a0<\/h2>\nEnsure that your analytics data is reusable for customer re-engagement, push notifications, re-targeting and e-mail campaigns.\u00a0\u00a0<\/p>\n
16 \u2013 An exportable data\u00a0<\/strong>\u00a0<\/h2>\nYou must be able to extract millions of events every hour to feed your IS or data lake (or other Data Science project) with highly granular and up-to-date analytical data.\u00a0<\/p>\n
17 \u2013 Data that can be understood immediately<\/strong>\u00a0<\/h2>\nUse the customer support experts at your analytics supplier (if any) to decrypt your data quickly.\u00a0\u00a0<\/p>\n
18 \u2013 Increased data<\/strong>\u00a0<\/h2>\nUse the\u00a0Machine Learning<\/a>\u00a0features of your analytics solution to anticipate or predict possible urgent and critical events.\u00a0<\/p>\n19 \u2013 Governance in place\u00a0<\/strong>\u00a0<\/h2>\nThe collection, processing and use of data is part of a governance strategy initiated by the company management and driven by a CDO or data expert.\u00a0<\/p>\n
20 \u2013 Comparable indicators\u00a0<\/strong>\u00a0<\/h2>\nDetermine which analytical solution serves as a reference for the entire company. Then, more precisely define and calculate the indicators to be used as benchmarks in the different services.\u00a0<\/p>\n
21 \u2013 Common analysis tools<\/strong>\u00a0<\/h2>\nUse\u00a0dashboards<\/a>\u00a0and analytical reports that can be adapted to all types of data users in the company: everyone can base their analyses and decisions on data collected, calculated and processed in a consistent way.\u00a0<\/p>\n22 \u2013 A cross-device vision\u00a0<\/strong>\u00a0<\/h2>\nAlways keep an overview when\u00a0analysing your performance<\/a>. Avoid approaches that are too platform or device specific, as they may miss important insights.\u00a0<\/p>\n23 \u2013 Exact data\u00a0<\/strong>\u00a0<\/h2>\nThe law requires that the data be\u00a0accurate<\/em>\u00a0to be compliant. You must take reasonable steps to avoid processing incorrect data (imagine, for example, the consequences of data errors in a medical record).\u00a0<\/p>\n24 \u2013 A collection of lawful consent<\/strong>\u00a0<\/h2>\nIt is also a condition of compliance. Some Analytics solutions such as AT Internet benefit from an exemption from data collection, which makes measurement easier and more reliable.\u00a0<\/p>\n
25 \u2013 A limited\u00a0<\/strong>cookie\u00a0<\/strong>lifetime<\/strong>\u00a0<\/h2>\nIf the Internet user has given his or her consent, your Web Analytics solution must offer functionalities to ensure that the lifetime of cookies is respected.\u00a0<\/p>\n
26 \u2013 Complete and transparent information<\/strong>\u00a0<\/h2>\nIt is a duty to the Internet user. These principles concern the processing of data and in particular: duration and place of storage and type of data collected.\u00a0<\/p>\n
27 \u2013 A clear and precise definition of personal data<\/strong>\u00a0<\/h2>\nThis is one of the obligations of the\u00a0GDPR<\/a>\u00a0(section 14). At AT Internet, all types of analytical data are considered as personal data.\u00a0<\/p>\n28 \u2013 Data accessibility<\/strong>\u00a0<\/h2>\nYou and your subcontractor must have the capacity to respond to the rights of the persons concerned. AT Internet is organised on this point.\u00a0\u00a0<\/p>\n
AT Internet offers\u00a0a wide range of tools for quality control<\/a> of\u00a0analytical data. Fewer errors are therefore likely to alter your data and influence your decisions.\u00a0<\/p>\nIf you are interested in the subject of data quality, download our latest guide:<\/p>\n<\/a><\/figure>\n
As an integral part of your good data governance, regular procedures (automatic tests for example) allow you to check the presence of all tags.\u00a0<\/p>\n
6 \u2013 Complete\u00a0<\/strong>tagging<\/strong>\u00a0audits<\/strong>\u00a0<\/h2>\nThey must be carried out in particular in the event of a very important modification redesign of your site and\/or applications.\u00a0<\/p>\n
7 \u2013 No sampled data<\/strong>\u00a0<\/h2>\nThey can highlight general trends, but the smaller their size, the less representative they are of reality.\u00a0Sampling<\/a>\u00a0can be risky, especially on financial data.\u00a0\u00a0<\/p>\n8 \u2013 Service contracts (SLAs)<\/strong>\u00a0<\/h2>\nYour Web Analytics provider is contractually committed to guaranteeing you a data collection rate close to 100%.<\/p>\n
9 \u2013 A\u00a0<\/strong>first domain<\/em><\/strong>\u00a0measure<\/strong>ment<\/strong>\u00a0<\/h2>\nYou recover as much of the traffic blocked by\u00a0ad blockers<\/a>\u00a0or\u00a0ITP<\/a>\u00a0systems as possible via a collection solution on your own domain name.
Important note:<\/strong> the CDDC method available from AT Internet is fully compliant with the GDPR and is not exempt from the collection of required consent for all websites.\u00a0<\/p>\n10 \u2013 Accessible and well formatted data\u00a0<\/strong>\u00a0<\/h2>\nTest how your data is retrieved and presented.\u00a0Is it\u00a0being\u00a0collected\u00a0as planned? Are the values displayed correctly on your interface?\u00a0<\/p>\n
11 \u2013 Fair and verified values<\/strong>\u00a0<\/h2>\nCheck<\/a>\u00a0that no technical (collection) elements could have altered the\u00a0accuracy\u00a0of the figures in your analysis.\u00a0<\/p>\n12 \u2013 Tools for customi<\/strong>s<\/strong>ing\u00a0<\/strong>tagging<\/strong>\u00a0<\/strong>\u00a0<\/h2>\nBy defining customised data processing rules, you are able to correct errors due to\u00a0tagging\u00a0problems, enrich collected data and exclude unwanted traffic, all without any intervention from technical teams.\u00a0<\/p>\n
13 \u2013 Automated quality control<\/strong>\u00a0<\/h2>\nConsider using\u00a0tools<\/a> that\u00a0will allow your analyst to update the data independently, without relying on technical teams to modify the code.\u00a0<\/p>\n14 \u2013 Real time data\u00a0<\/strong>\u00a0<\/h2>\nVerify that your digital analytics solution can provide you with real-time KPIs, i.e. that the data availability does not exceed 5 minutes on your analyses and dashboards.\u00a0<\/p>\n
15 \u2013 A reusable data<\/strong>\u00a0<\/h2>\nEnsure that your analytics data is reusable for customer re-engagement, push notifications, re-targeting and e-mail campaigns.\u00a0\u00a0<\/p>\n
16 \u2013 An exportable data\u00a0<\/strong>\u00a0<\/h2>\nYou must be able to extract millions of events every hour to feed your IS or data lake (or other Data Science project) with highly granular and up-to-date analytical data.\u00a0<\/p>\n
17 \u2013 Data that can be understood immediately<\/strong>\u00a0<\/h2>\nUse the customer support experts at your analytics supplier (if any) to decrypt your data quickly.\u00a0\u00a0<\/p>\n
18 \u2013 Increased data<\/strong>\u00a0<\/h2>\nUse the\u00a0Machine Learning<\/a>\u00a0features of your analytics solution to anticipate or predict possible urgent and critical events.\u00a0<\/p>\n19 \u2013 Governance in place\u00a0<\/strong>\u00a0<\/h2>\nThe collection, processing and use of data is part of a governance strategy initiated by the company management and driven by a CDO or data expert.\u00a0<\/p>\n
20 \u2013 Comparable indicators\u00a0<\/strong>\u00a0<\/h2>\nDetermine which analytical solution serves as a reference for the entire company. Then, more precisely define and calculate the indicators to be used as benchmarks in the different services.\u00a0<\/p>\n
21 \u2013 Common analysis tools<\/strong>\u00a0<\/h2>\nUse\u00a0dashboards<\/a>\u00a0and analytical reports that can be adapted to all types of data users in the company: everyone can base their analyses and decisions on data collected, calculated and processed in a consistent way.\u00a0<\/p>\n22 \u2013 A cross-device vision\u00a0<\/strong>\u00a0<\/h2>\nAlways keep an overview when\u00a0analysing your performance<\/a>. Avoid approaches that are too platform or device specific, as they may miss important insights.\u00a0<\/p>\n23 \u2013 Exact data\u00a0<\/strong>\u00a0<\/h2>\nThe law requires that the data be\u00a0accurate<\/em>\u00a0to be compliant. You must take reasonable steps to avoid processing incorrect data (imagine, for example, the consequences of data errors in a medical record).\u00a0<\/p>\n24 \u2013 A collection of lawful consent<\/strong>\u00a0<\/h2>\nIt is also a condition of compliance. Some Analytics solutions such as AT Internet benefit from an exemption from data collection, which makes measurement easier and more reliable.\u00a0<\/p>\n
25 \u2013 A limited\u00a0<\/strong>cookie\u00a0<\/strong>lifetime<\/strong>\u00a0<\/h2>\nIf the Internet user has given his or her consent, your Web Analytics solution must offer functionalities to ensure that the lifetime of cookies is respected.\u00a0<\/p>\n
26 \u2013 Complete and transparent information<\/strong>\u00a0<\/h2>\nIt is a duty to the Internet user. These principles concern the processing of data and in particular: duration and place of storage and type of data collected.\u00a0<\/p>\n
27 \u2013 A clear and precise definition of personal data<\/strong>\u00a0<\/h2>\nThis is one of the obligations of the\u00a0GDPR<\/a>\u00a0(section 14). At AT Internet, all types of analytical data are considered as personal data.\u00a0<\/p>\n28 \u2013 Data accessibility<\/strong>\u00a0<\/h2>\nYou and your subcontractor must have the capacity to respond to the rights of the persons concerned. AT Internet is organised on this point.\u00a0\u00a0<\/p>\n
AT Internet offers\u00a0a wide range of tools for quality control<\/a> of\u00a0analytical data. Fewer errors are therefore likely to alter your data and influence your decisions.\u00a0<\/p>\nIf you are interested in the subject of data quality, download our latest guide:<\/p>\n<\/a><\/figure>\n
They can highlight general trends, but the smaller their size, the less representative they are of reality.\u00a0Sampling<\/a>\u00a0can be risky, especially on financial data.\u00a0\u00a0<\/p>\n Your Web Analytics provider is contractually committed to guaranteeing you a data collection rate close to 100%.<\/p>\n You recover as much of the traffic blocked by\u00a0ad blockers<\/a>\u00a0or\u00a0ITP<\/a>\u00a0systems as possible via a collection solution on your own domain name. Test how your data is retrieved and presented.\u00a0Is it\u00a0being\u00a0collected\u00a0as planned? Are the values displayed correctly on your interface?\u00a0<\/p>\n Check<\/a>\u00a0that no technical (collection) elements could have altered the\u00a0accuracy\u00a0of the figures in your analysis.\u00a0<\/p>\n By defining customised data processing rules, you are able to correct errors due to\u00a0tagging\u00a0problems, enrich collected data and exclude unwanted traffic, all without any intervention from technical teams.\u00a0<\/p>\n Consider using\u00a0tools<\/a> that\u00a0will allow your analyst to update the data independently, without relying on technical teams to modify the code.\u00a0<\/p>\n Verify that your digital analytics solution can provide you with real-time KPIs, i.e. that the data availability does not exceed 5 minutes on your analyses and dashboards.\u00a0<\/p>\n Ensure that your analytics data is reusable for customer re-engagement, push notifications, re-targeting and e-mail campaigns.\u00a0\u00a0<\/p>\n You must be able to extract millions of events every hour to feed your IS or data lake (or other Data Science project) with highly granular and up-to-date analytical data.\u00a0<\/p>\n Use the customer support experts at your analytics supplier (if any) to decrypt your data quickly.\u00a0\u00a0<\/p>\n Use the\u00a0Machine Learning<\/a>\u00a0features of your analytics solution to anticipate or predict possible urgent and critical events.\u00a0<\/p>\n The collection, processing and use of data is part of a governance strategy initiated by the company management and driven by a CDO or data expert.\u00a0<\/p>\n Determine which analytical solution serves as a reference for the entire company. Then, more precisely define and calculate the indicators to be used as benchmarks in the different services.\u00a0<\/p>\n Use\u00a0dashboards<\/a>\u00a0and analytical reports that can be adapted to all types of data users in the company: everyone can base their analyses and decisions on data collected, calculated and processed in a consistent way.\u00a0<\/p>\n Always keep an overview when\u00a0analysing your performance<\/a>. Avoid approaches that are too platform or device specific, as they may miss important insights.\u00a0<\/p>\n The law requires that the data be\u00a0accurate<\/em>\u00a0to be compliant. You must take reasonable steps to avoid processing incorrect data (imagine, for example, the consequences of data errors in a medical record).\u00a0<\/p>\n It is also a condition of compliance. Some Analytics solutions such as AT Internet benefit from an exemption from data collection, which makes measurement easier and more reliable.\u00a0<\/p>\n If the Internet user has given his or her consent, your Web Analytics solution must offer functionalities to ensure that the lifetime of cookies is respected.\u00a0<\/p>\n It is a duty to the Internet user. These principles concern the processing of data and in particular: duration and place of storage and type of data collected.\u00a0<\/p>\n This is one of the obligations of the\u00a0GDPR<\/a>\u00a0(section 14). At AT Internet, all types of analytical data are considered as personal data.\u00a0<\/p>\n You and your subcontractor must have the capacity to respond to the rights of the persons concerned. AT Internet is organised on this point.\u00a0\u00a0<\/p>\n AT Internet offers\u00a0a wide range of tools for quality control<\/a> of\u00a0analytical data. Fewer errors are therefore likely to alter your data and influence your decisions.\u00a0<\/p>\n If you are interested in the subject of data quality, download our latest guide:<\/p>\n8 \u2013 Service contracts (SLAs)<\/strong>\u00a0<\/h2>\n
9 \u2013 A\u00a0<\/strong>first domain<\/em><\/strong>\u00a0measure<\/strong>ment<\/strong>\u00a0<\/h2>\n
Important note:<\/strong> the CDDC method available from AT Internet is fully compliant with the GDPR and is not exempt from the collection of required consent for all websites.\u00a0<\/p>\n10 \u2013 Accessible and well formatted data\u00a0<\/strong>\u00a0<\/h2>\n
11 \u2013 Fair and verified values<\/strong>\u00a0<\/h2>\n
12 \u2013 Tools for customi<\/strong>s<\/strong>ing\u00a0<\/strong>tagging<\/strong>\u00a0<\/strong>\u00a0<\/h2>\n
13 \u2013 Automated quality control<\/strong>\u00a0<\/h2>\n
14 \u2013 Real time data\u00a0<\/strong>\u00a0<\/h2>\n
15 \u2013 A reusable data<\/strong>\u00a0<\/h2>\n
16 \u2013 An exportable data\u00a0<\/strong>\u00a0<\/h2>\n
17 \u2013 Data that can be understood immediately<\/strong>\u00a0<\/h2>\n
18 \u2013 Increased data<\/strong>\u00a0<\/h2>\n
19 \u2013 Governance in place\u00a0<\/strong>\u00a0<\/h2>\n
20 \u2013 Comparable indicators\u00a0<\/strong>\u00a0<\/h2>\n
21 \u2013 Common analysis tools<\/strong>\u00a0<\/h2>\n
22 \u2013 A cross-device vision\u00a0<\/strong>\u00a0<\/h2>\n
23 \u2013 Exact data\u00a0<\/strong>\u00a0<\/h2>\n
24 \u2013 A collection of lawful consent<\/strong>\u00a0<\/h2>\n
25 \u2013 A limited\u00a0<\/strong>cookie\u00a0<\/strong>lifetime<\/strong>\u00a0<\/h2>\n
26 \u2013 Complete and transparent information<\/strong>\u00a0<\/h2>\n
27 \u2013 A clear and precise definition of personal data<\/strong>\u00a0<\/h2>\n
28 \u2013 Data accessibility<\/strong>\u00a0<\/h2>\n
<\/a><\/figure>\n