[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"cms-page:\u002Fabout\u002Four-team\u002Fharry-brace\u002Fpage\u002F4":3},{"name":4,"url":5,"description":6,"avatar_urls":7,"acf":9,"social":193,"head_links":195,"breadcrumbs":181,"posts":199,"pages":176,"head":1464},"Harry Brace","","I'm the Director, Head of Solutions at Impression. I spend my time debugging and implementing tracking using Google Tag Manager, managing data warehousing platforms and building Looker Studio reports!",{"24":8,"48":8,"96":8},"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F10\u002FHarry-Brace2.png?auto=compress&fit=fit&fm=jpg&h=96&q=90&w=96",{"full_bio":10,"job_title":11,"specialist_service_links":12,"photo":49,"page_content_modules":105,"hero":177},"\u003Cp>Director, Head of Solutions. Joined Impression in November 2017.\u003C\u002Fp>\n\u003Cp>I gained 4 years of experience as a web developer before moving to Impression as a digital account manager in 2017. I moved across to the Analytics department in 2019 and I’ve been strengthening and growing our Analytics offering ever since.\u003C\u002Fp>\n\u003Cp>Day to day, I spend my time debugging and implementing tracking using Google Tag Manager, managing data warehousing platforms and building Looker Studio reports!\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Something that I’m proud of:\u003C\u002Fstrong>\u003Cbr \u002F>\nBuilding the analytics department over the last couple of years with the help of Aaron and now Alex H.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Outside of work:\u003C\u002Fstrong>\u003Cbr \u002F>\nFind me socialising, skiing or gaming.\u003C\u002Fp>\n","Director, Head of Solutions",[13,30,40],{"page":14,"link_text":29},{"ID":15,"post_author":16,"post_date":17,"post_date_gmt":17,"post_content":5,"post_title":18,"post_excerpt":5,"post_status":19,"comment_status":20,"ping_status":20,"post_password":5,"post_name":21,"to_ping":5,"pinged":5,"post_modified":22,"post_modified_gmt":22,"post_content_filtered":5,"post_parent":23,"guid":24,"menu_order":23,"post_type":25,"post_mime_type":5,"comment_count":26,"filter":27,"url_path":28},374,"98","2021-01-11 16:25:32","Analytics","publish","closed","analytics","2026-09-28 11:36:16",0,"\u002F?page_id=374","page","0","raw","\u002Fanalytics\u002F","Web 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11:05:27",17552,"\u002F?page_id=17916","\u002Fmedia-solutions\u002Ftag-management\u002F",{"page":41,"link_text":44},{"ID":42,"post_author":16,"post_date":43,"post_date_gmt":43,"post_content":5,"post_title":44,"post_excerpt":5,"post_status":19,"comment_status":20,"ping_status":20,"post_password":5,"post_name":45,"to_ping":5,"pinged":5,"post_modified":46,"post_modified_gmt":46,"post_content_filtered":5,"post_parent":37,"guid":47,"menu_order":23,"post_type":25,"post_mime_type":5,"comment_count":26,"filter":27,"url_path":48},17140,"2022-05-27 14:22:19","Google Marketing Platform","google-marketing-platform","2026-09-25 10:43:13","\u002F?page_id=17140","\u002Fmedia-solutions\u002Fgoogle-marketing-platform\u002F",{"ID":50,"id":50,"title":51,"filename":52,"filesize":53,"url":54,"link":55,"alt":5,"author":56,"description":5,"caption":5,"name":57,"status":58,"uploaded_to":23,"date":59,"modified":59,"menu_order":23,"mime_type":60,"type":61,"subtype":62,"icon":63,"width":64,"height":65,"sizes":66},25135,"Harry-Brace2","Harry-Brace2.png",306919,"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F10\u002FHarry-Brace2.png?auto=compress%2Cformat&q=90","\u002Fharry-brace2\u002F","12","harry-brace2","inherit","2023-10-03 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Brace’s posts",{"data":111,"pages":176},[112,126,136,146,158,167],{"type_key":113,"title":114,"excerpt":115,"to":116,"postedAt":117,"readingTime":118,"image":119,"authors":120,"category":123},"post","Improve conversion accuracy with Enhanced Conversions","\u003Cp>Google’s Enhanced Conversion tracking is a feature by Google designed to recover conversion data where important identifiers such as Google Click IDs are missing. With these recovered conversions, campaigns can be better optimised to target more appropriate audiences. Whilst being listed as a ‘Beta’ feature for some time, it’s still a valuable tool to implement […]\u003C\u002Fp>\n","\u002Fblog\u002Fimprove-conversion-accuracy-with-enhanced-conversions\u002F","2023-12-22T14:46:39",3,"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F12\u002Fabstract-background.jpg?auto=compress%2Cformat&fit=crop&h=640&q=90&w=640",[121],{"name":4,"image":122},"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F10\u002FHarry-Brace2.png?auto=compress&fit=crop&fm=jpg&h=150&q=80&w=150&bg=CFE6F9",{"to":124,"name":125},"\u002Fblog\u002Fcategory\u002Fmeasurement\u002F","Measurement",{"type_key":113,"title":127,"excerpt":128,"to":129,"postedAt":130,"readingTime":131,"image":132,"authors":133,"category":135},"Use Google Consent Mode or lose advertising features","\u003Cp>Non-compliant websites won’t be able to fully leverage Google advertising features post 6th March 2024. If unsure whether your website currently has Consent Mode implemented, submit your website domain to hello@impressiondigital.com and our Solutions team will be in touch to help. In a recent announcement, the European Commission has designated six ‘gatekeeper’ organisations that must […]\u003C\u002Fp>\n","\u002Fblog\u002Fuse-google-consent-mode-or-lose-advertising-features\u002F","2025-03-18T14:54:58",2,"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F12\u002Ftimer.jpg?auto=compress%2Cformat&fit=crop&h=640&q=90&w=640",[134],{"name":4,"image":122},{"to":124,"name":125},{"type_key":113,"title":137,"excerpt":138,"to":139,"postedAt":140,"readingTime":141,"image":142,"authors":143,"category":145},"Enhancing media planning with incrementality testing","\u003Cp>Accurately measuring the effectiveness of a media channel or campaign is a common challenge in digital marketing. We’re always seeking ways to accurately measure impact and assign credit to media channels to ensure we understand what performs best and the impact our channels have. The challenges of measuring media effectiveness  One of the most frequently […]\u003C\u002Fp>\n","\u002Fblog\u002Fincrementality-testing-media-planning\u002F","2025-02-24T16:50:56",8,"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fchristopher-burns-Kj2SaNHG-hg-unsplash.jpg?auto=compress%2Cformat&fit=crop&h=640&q=90&w=640",[144],{"name":4,"image":122},{"to":124,"name":125},{"type_key":113,"title":147,"excerpt":148,"to":149,"postedAt":150,"readingTime":151,"image":152,"authors":153,"category":155},"Measure Marketing Effectiveness with Media Mix Modelling","\u003Cp>Measuring media effectiveness and optimising budget allocation is a challenge for any marketer. As we constantly seek better ways to ensure that every penny spent contributes to the overall success of our campaigns, the traditional approach of relying on heuristics, which involves using rule-of-thumb methods, often falls short in providing actionable insights for long-term success.  […]\u003C\u002Fp>\n","\u002Fblog\u002Fmedia-mix-modelling\u002F","2023-11-20T13:31:14",10,"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fconny-schneider-pREq0ns_p_E-unsplash.jpg?auto=compress%2Cformat&fit=crop&h=640&q=90&w=640",[154],{"name":4,"image":122},{"to":156,"name":157},"\u002Fblog\u002Fcategory\u002Fdigital-marketing\u002F","Digital Marketing",{"type_key":113,"title":159,"excerpt":160,"to":161,"postedAt":162,"readingTime":131,"image":163,"authors":164,"category":166},"How data-driven attribution works in Google Analytics 4","\u003Cp>As we all adapt to using Google Analytics 4, one of the most important changes marketers are facing is the change to data-driven attribution. With Universal Analytics, all conversions were attributed to the last non-direct channel. Whilst this model awarded the conversion to the channel that ultimately led to the conversion, it didn’t show the […]\u003C\u002Fp>\n","\u002Fblog\u002Fhow-data-driven-attribution-works-in-google-analytics-4\u002F","2023-08-10T08:47:07","https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F06\u002Fcrissy-jarvis-gdL-UZfnD3I-unsplash.jpg?auto=compress%2Cformat&fit=crop&h=640&q=90&w=640",[165],{"name":4,"image":122},{"to":124,"name":125},{"type_key":113,"title":168,"excerpt":169,"to":170,"postedAt":171,"readingTime":131,"image":172,"authors":173,"category":175},"Custom channel groupings introduced to Google Analytics 4","\u003Cp>Google has announced that you are able to create your own custom channel groupings in Google Analytics 4, giving you more control over how you can interpret your data. Previously available in Universal Analytics, this feature now brought over to GA4 allows you to configure your traffic groupings to your own preferences, letting you collect […]\u003C\u002Fp>\n","\u002Fblog\u002Fcustom-channel-groupings-google-analytics-4\u002F","2023-05-04T10:42:55","https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F05\u002Fkier-in-sight-Bqx_QDE-Kzk-unsplash.jpg?auto=compress%2Cformat&fit=crop&h=640&q=90&w=640",[174],{"name":4,"image":122},{"to":124,"name":125},"6",{"type":178,"style":179,"title":180,"heading":4,"intro":10,"services":12,"breadcrumbs":181,"photo":67,"social":193},"author","dark","Meet the Team",[182,185,188,191],{"path":183,"name":184},"\u002F","Home",{"path":186,"name":187},"\u002Fabout\u002F","About Us",{"path":189,"name":190},"\u002Fabout\u002Four-team\u002F","Meet the team",{"path":192,"name":4},null,{"twitter":5,"linkedin":194},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fharrison-brace-137b8482\u002F",[196],{"rel":197,"href":198},"canonical","https:\u002F\u002Fwww.impressiondigital.com\u002Fabout\u002Four-team\u002Fharry-brace\u002F",[200,515,704,896,1090,1279],{"id":201,"date":202,"date_gmt":202,"guid":203,"modified":117,"modified_gmt":117,"slug":205,"status":19,"type":113,"link":116,"title":206,"content":207,"excerpt":210,"author":211,"featured_media":212,"comment_status":20,"ping_status":20,"sticky":209,"template":5,"format":213,"meta":214,"categories":215,"collections":217,"coauthors":218,"class_list":220,"acf":228,"head_links":229,"breadcrumbs":230,"url_path":116,"search_description":237,"featured_image_urls":238,"authors":273,"type_nicename":286,"reading_minutes":118,"category":287,"yoast_title":289,"yoast_meta":290,"yoast_json_ld":343,"_links":466},26587,"2023-12-22T14:33:34",{"rendered":204},"\u002F?p=26587","improve-conversion-accuracy-with-enhanced-conversions",{"rendered":114},{"rendered":208,"protected":209},"\n\u003Cp>Google’s Enhanced Conversion tracking is a feature by Google designed to recover conversion data where important identifiers such as Google Click IDs are missing. With these recovered conversions, campaigns can be better optimised to target more appropriate audiences. Whilst being listed as a ‘Beta’ feature for some time, it’s still a valuable tool to implement in a privacy centric industry.\u003C\u002Fp>\n\n\n\n\u003Cp>Given the increasing challenges of tracking and targeting consumers across devices due to stricter privacy regulations, marketers may see diminishing ad performance over time as fewer conversions are reported. Google’s response to this issue is the introduction of enhanced conversion tracking, aligning with the efforts of other platforms in addressing the evolving landscape of user privacy.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"so-what-exactly-is-google-enhanced-conversion-tracking\">\u003Cstrong>So, what exactly is Google Enhanced Conversion Tracking?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>With many different privacy acts and the death of 3rd-party cookies, tracking has become increasingly difficult to maintain across devices. In an effort to offset these challenges, new approaches to tracking have been created that use first-party data to deduce which ads are carrying customers across different devices. Different platforms are utilising this, beginning with Meta and its “Advanced Matching”, and then Google unveiled its “Enhanced Conversion Tracking”.\u003C\u002Fp>\n\n\n\n\u003Cp>Google’s Enhanced Conversion, in a nutshell, is essentially a feature that enhances the precision of your conversions. First-party data such as email, phone number and address of the user is securely encrypted and then sent to Google within the conversion payload. This encrypted data is then matched against registered Google users accounts in an attempt at finding a match where the same user has interacted with an ad. If a match is detected and the user has indeed interacted with one of your ads, a conversion can be counted against the related campaign.\u003C\u002Fp>\n\n\n\n\u003Cp>The method by which Google securely encrypts the data is through a hashing algorithm: SHA-256. Nobody but Google will have access to the customer’s data, as stated by Google’s privacy policy. It is however important (and required by law) that customers are made aware that their data is being used in this manner, such as in a privacy policy.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"how-is-it-implemented\">\u003Cstrong>How is it implemented?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>The easiest way to set up consent mode is through Google Tag Manager. Specifically for this purpose, there is a new built-in variable called ‘User-provided data’. This variable can be set to automatically attempt to collect the appropriate data by analysing each page and trying to detect values which match email addresses, telephone numbers etc. Whilst this can work, we always recommend manually specifying each variable as this will result in more accurate results.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1506\" height=\"1322\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F12\u002FScreenshot-2023-12-22-at-14.01.46.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-26588\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>With any event you’re tracking on your website, we always recommend using a data layer which contains all the key information about the conversion. This makes it easy to populate your conversion tags with the right data. Alternatively you can extract the inputted values using other means such as custom Javascript variables.\u003C\u002Fp>\n\n\n\n\u003Cp>Once you have your new variable set up, the next step is to configure your tags. For this example we’ll be setting up Enhanced Conversions for a Google Ads conversion tag, specifically a purchase event. In setting this up you’d enter the appropriate ID and Label provided in Google Ads and add a revenue and Transaction ID variable in the appropriate fields. To then enable Enhanced Conversions, you tick ‘Include user-provided data from your website’ and select the new variable you’ve set up.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image is-style-default wp-duotone-unset-1\">\n\u003Cfigure class=\"aligncenter size-medium_large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1462\" height=\"1362\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F12\u002FScreenshot-2023-12-22-at-14.07.20.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-26589\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>After saving and publishing your new tags, you also need to ensure that Enhanced Conversions is enabled within your Google Ads account. These settings can be found in the main settings area within your ad account and within individual conversion actions. Make sure you select ‘Google Tag Manager’ as the implementation method when enabling these settings.\u003C\u002Fp>\n\n\n\n\u003Cp>For support in implementing Enhanced Conversions and similar tracking technology, our Solutions team at Impression have hands on experience and can help you prepare you website for a privacy focused future.\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003C\u002Fli>\n\u003C\u002Ful>\n",false,{"rendered":115,"protected":209},29,26590,"standard",{"_yoast_wpseo_focuskw":5,"_yoast_wpseo_title":5,"_yoast_wpseo_metadesc":5,"inline_featured_image":209,"footnotes":5},[216],41,[],[219],120,[221,113,222,223,224,225,226,227],"post-26587","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-measurement",[],[],[231,232,235,236],{"path":183,"name":184},{"path":233,"name":234},"\u002Fblog\u002F","Blog",{"path":124,"name":125},{"path":192,"name":114},"Google’s Enhanced Conversion tracking is a feature by Google designed to recover conversion data where important identifiers such as Google Click IDs are missing. With these recovered conversions, campaigns can be better optimised to target more appropriate audiences. Whilst being listed as a ‘Beta’ feature for some time, it’s still a valuable tool to implement 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If unsure whether your website currently has Consent Mode implemented, submit your website domain to \u003Ca rel=\"noreferrer noopener\" href=\"mailto:hello@impressiondigital.com\">hello@impressiondigital.com\u003C\u002Fa> and our Solutions team will be in touch to help.\u003C\u002Fp>\n\n\n\n\u003Cp>In a recent announcement, the European Commission has designated six ‘gatekeeper’ organisations that must comply with the \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fblog\u002Fconsent-management-digital-advertising-and-the-digital-markets-act\u002F\">Digital Markets Act\u003C\u002Fa> by March 6th 2024 or be handed severe fines. Alphabet (Google), Amazon, Apple, ByteDance, Meta, and Microsoft must now all ensure that they are only handling consented data that is compliant with the Transparency Consent Framework 2.0 (TFC) standard. \u003C\u002Fp>\n\n\n\n\u003Cp>Google’s implementation of TCF is called “\u003Cstrong>Consent Mode\u003C\u002Fstrong>” and this is a Google product, but all major advertising platforms must comply in their own way and must meet the same levels of user privacy when honouring consent choices. Without a valid TCF-compliant implementation, Ad companies will be required to delete or not store your tracking data, and repeatedly sending this data could lead to advertising account suspension.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"what-steps-do-you-need-to-take\">What steps do you need to take? \u003C\u002Fh2>\n\n\n\n\u003Cp>First, you need to ensure you have a functioning cookie consent notice as \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fblog\u002Fgoogle-consent-mode\u002F\">Consent Mode\u003C\u002Fa> is designed to work alongside the cookie consent notice and not instead of one. Popular \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fblog\u002Fconsent-management-platforms-privacy-compliance\u002F\">Consent Management Platforms\u003C\u002Fa> (CMPs) such as CookieBot, CookiePro and OneTrust all have built-in support for Consent Mode which will make the implementation easier. If you have a custom cookie consent notice, this can still be implemented with Consent Mode but may require some additional integration work.\u003C\u002Fp>\n\n\n\n\u003Cp>Often we see that web tagging is not always configured correctly to honour users’ preferences as provided by the cookie banners, usually due to how these are configured in \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fmedia-solutions\u002Ftag-management\u002F\">tag managers\u003C\u002Fa>, such as Google Tag Manager.\u003C\u002Fp>\n\n\n\n\u003Cp>Once you’ve confirmed a working and compliant consent notice, you can begin integrating Consent Mode. The process of setting this up will depend on the CMP you use and how your tags are deployed but most popular CMPs provide detailed documentation. For other publishers such as \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fpaid-media\u002Fppc\u002Fmicrosoft-ads\u002F\">Microsoft Ads\u003C\u002Fa>, we also recommend changing your tags so they are also \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fhelp.ads.microsoft.com\u002F#apex\u002Fads\u002Fen\u002F60186\u002F2\">compliant with the TCF V2 framework\u003C\u002Fa>. Each publisher will be different but most will require a new flag or variable to be set, based on the user’s consent options. \u003C\u002Fp>\n\n\n\n\u003Cp>This will be a changing landscape between now and March as advertisers enable new consent features, and after that too as additional gatekeepers are inevitably named, so a proactive approach to managing your tag management is always advised. If you’d like support implementing Consent Mode, our \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fmedia-solutions\u002F\">Media Solutions\u003C\u002Fa> team at Impression have hands-on experience with various CMPs and integrating Consent Mode. \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fget-in-touch\u002F\">Get in touch\u003C\u002Fa>.\u003C\u002Fp>\n",{"rendered":128,"protected":209},26304,{"_yoast_wpseo_focuskw":5,"_yoast_wpseo_title":527,"_yoast_wpseo_metadesc":528,"inline_featured_image":209,"footnotes":5},"Use Google Consent Mode or lose advertising features says EU Commission | Impression","The European Commission has designated six ‘gatekeeper’ organisations that must comply with the Digital Markets Act by March 7th 2024. Learn 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measuring the effectiveness of a media channel or campaign is a common challenge in digital marketing. We’re always seeking ways to accurately measure impact and assign credit to media channels to ensure we understand what performs best and the impact our channels have.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"table-of-contents\">\u003Cul>\u003Cli class=\"heading-h2\">\u003Ca href=\"#the-challenges-of-measuring-media-effectiveness\">The challenges of measuring media effectiveness?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h2\">\u003Ca href=\"#what-is-incrementality-testing\">What is incrementality testing?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h2\">\u003Ca href=\"#why-would-you-conduct-incrementality-testing\">Why would you conduct incrementality testing?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#quantifies-direct-media-effectiveness\">Quantifies direct media effectiveness\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#calibrates-your-media-mix-model\">Calibrates your media mix model\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#validates-marketing-strategies\">Validates marketing strategies\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#provides-easily-interpretable-results\">Provides easily interpretable results\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#example-of-incrementality-testing-results\">Example of incrementality testing results\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h2\">\u003Ca href=\"#advantages-of-incrementality-testing\">Advantages of incrementality testing\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#casual-impact\">Casual Impact\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#avoids-potential-bias-due-to-group-differences\">Avoids potential bias due to group differences\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#data-driven-media-planning\">Data-driven media planning\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#uses-advanced-up-to-date-software\">Uses advanced, up-to-date software\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#iterative-improvement-in-the-modelling-process\">Iterative improvement in the modelling process\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#iterative-improvement-in-the-media-planning-process\">Iterative improvement in the media planning process\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h2\">\u003Ca href=\"#limitations-of-incrementality-testing\">Limitations of incrementality testing\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#data-collection\">Data collection\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"heading-h3\">\u003Ca href=\"#selection-of-control-groups\">Selection of control groups\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Ful>\u003C\u002Fdiv>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"the-challenges-of-measuring-media-effectiveness\">The challenges of measuring media effectiveness \u003C\u002Fh2>\n\n\n\n\u003Cp>One of the most frequently used methods to do this in online advertising is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fbusiness.adobe.com\u002Fblog\u002Fbasics\u002Fmulti-touch-attribution\">multi-touch attribution modelling\u003C\u002Fa>. Multi-touch attribution uses “touch-points” throughout the customer journey to model and assign credit to various media channels. Multi-touch attribution models can only assign and model credit based on the data collected. \u003C\u002Fp>\n\n\n\n\u003Cp>With the decaying lifetime of third-party cookies and the ever-increasing use of multiple devices and mobile in-app browsers, measuring the customer journey becomes increasingly difficult. Incrementality testing, on the other hand, goes above and beyond attribution models, helping you understand the causal impact of specific marketing efforts and avoiding misattribution of success.\u003C\u002Fp>\n\n\n\n\u003Cp>Another frequent challenge faced by marketers is the accurate measurement of long-term media effects. \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.thinkwithgoogle.com\u002Fintl\u002Fen-emea\u002Fmarketing-strategies\u002Fdata-and-measurement\u002Fincrementality-testing\u002F\">Incrementality testing\u003C\u002Fa> helps strengthen understanding of both short-term and long-term media effects through conducting these tests using geographical location, in which a media channel is active in the “treatment” location only. The time in which it takes for the impact to become significant is called the delayed effect, sometimes referred to as the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FAdvertising_adstock\">Adstock effect\u003C\u002Fa>. Alternatively, deactivating a media channel in the treatment location only and observing the time taken to see a significant decaying impact can provide useful insights into the carryover effects, sometimes referred to as the saturation, of that particular media channel. These insights are crucial for developing a reliable media plan that contributes to long-term business growth.\u003C\u002Fp>\n\n\n\n\u003Cp>Having a strong understanding of media impact, delayed effects and carryover effects is vital for improving media planning and in turn, increasing overall business performance. \u003C\u002Fp>\n\n\n\n\u003Cp>This is where incrementality testing comes into its element!\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"what-is-incrementality-testing\">What is incrementality testing?\u003C\u002Fh2>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"779\" height=\"381\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fincrementality-testing.jpg?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-26018\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>From a media perspective, incrementality testing is a statistical method used to measure and estimate the direct impact, cumulative impact, and short\u002Flong-term effects of a campaign or particular media channel. \u003C\u002Fp>\n\n\n\n\u003Cp>Incrementality testing aims to establish a causal relationship by comparing a “treatment” with a “control” group. The treatment group refers to a group exposed to the marketing experiment and the control group refers to a group that hasn’t been affected. Incrementality testing can be done using various methods depending on the context of the test. Incrementality testing provides ways to quantify media impact using data and through the separation of any efforts directly from the media channel with other external factors.\u003C\u002Fp>\n\n\n\n\u003Cp>As mentioned previously, incremental testing can be conducted using geographical location. We call these types of tests geo-experiments. A geo-experiment aims to measure and assess variations in media impact across areas or regions. While incrementality testing is a broader concept,  geo-experiments represent a specific type of incrementality testing focused on geographic variations. In other words, geo-experiments are an element of incrementality testing, and the principles of incrementality testing can be applied to understand the causal impact of marketing interventions, whether they are geo-specific or not (see an example of where we conducted geo-experiments with our client Topps Tiles \u003Ca rel=\"noreferrer noopener\" href=\"\u002Four-work\u002Ftopps-tiles-integrated\u002F\">here\u003C\u002Fa>).\u003C\u002Fp>\n\n\n\n\u003Cp>Here at Impression, we perform incrementality testing using a \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FSynthetic_control_method\">synthetic control group\u003C\u002Fa>. A synthetic control group serves as an artificial comparison for the treatment group. The synthetic data is generated by a weighted sum of the geo-segments around it to account for any slight regional differences. This approach to incrementality testing also helps to account for confounding variables and external factors, providing a more accurate estimation of the media impact.\u003C\u002Fp>\n\n\n\n\u003Cp>We utilise the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.britannica.com\u002Fscience\u002FBayesian-analysis\">Bayesian framework\u003C\u002Fa> to derive a synthetic control group. This allows us to measure and account for any uncertainty we may have on the resulting impact and in the \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fdigital-marketing\u002Fstrategy\u002Fmedia-planning\u002F\">media planning\u003C\u002Fa> process. For example, say the incrementality test estimates that turning on a particular media channel causes a cumulative increase in revenue of £1000, Bayesian models enable us to attach an interval of greatest probability to this point estimate, hence allowing for a greater understanding throughout the media planning process. \u003C\u002Fp>\n\n\n\n\u003Cp>Formally, Bayesian models use a combination of prior knowledge and the data to produce what’s called the posterior distribution. It is this posterior distribution that contains the point estimates and the corresponding uncertainties. To derive a synthetic control group, we elicit non-informative priors, and hence let the data do the talking!\u003C\u002Fp>\n\n\n\n\u003Cp>To perform incrementality tests this way, approximately 2-3 years of clean, well-formatted historical time series data is required. Within this data, there must be the treatment group, time of treatment, and numerous control groups concerning similar campaigns or locations, which we wish to use to approximate a synthetic control group. \u003C\u002Fp>\n\n\n\n\u003Cp>Provided we have this data, a weighted sum of the similar control groups is taken to derive the synthetic one to be used for testing. It is these weights that are modelled under a Bayesian framework, and hence uncertainties associated with the synthetic control are produced to inform the media planning process. As a result, the differences between the observed treatment, and the synthetic controls are recorded to produce the causal media impact and their associated uncertainties. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"why-would-you-conduct-incrementality-testing\">Why would you conduct incrementality testing?\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"quantifies-direct-media-effectiveness\">Quantifies direct media effectiveness\u003C\u002Fh3>\n\n\n\n\u003Cp>The difference between the synthetic control and the treatment observations gives the estimated media impact and any uncertainty. This impact can be used to provide useful insights into the media planning process and for comparison with other media channels. Incrementality testing helps determine which advertising channels contribute most effectively to business performance.\u003Cbr>\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"calibrates-your-media-mix-model\">Calibrates your media mix model\u003C\u002Fh3>\n\n\n\n\u003Cp>Media impact estimates can be used to fine-tune your media mix model to give a better representation of your media mix, and hence to inform your budget allocation forecasts.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fmedia-mix-modelling-graphic.jpg?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25577\" width=\"595\" height=\"329\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"validates-marketing-strategies\">Validates marketing strategies\u003C\u002Fh3>\n\n\n\n\u003Cp>Incrementality testing allows us to validate how well a current marketing strategy works and whether it needs updating. For instance, if a new media channel is found to have a significant impact through incrementality testing, then a budget should be allocated for this channel in the next marketing strategy.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"provides-easily-interpretable-results\">Provides easily interpretable results\u003C\u002Fh3>\n\n\n\n\u003Cp>Cumulative impact translates directly into the dependent variable, meaning that if you’re measuring revenue, the cumulative impact tells you how much revenue you’ve gained\u002Flost for a given time point plus any uncertainty you may have.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"example-of-incrementality-testing-results\">Example of incrementality testing results\u003C\u002Fh3>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1470\" height=\"884\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fincrementality-testing-results.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-26021\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>The “pre-intervention Bayesian R2” represents a measure of model fit – in this case, as it is close to zero, the model is a very poor fit! \u003C\u002Fp>\n\n\n\n\u003Cp>The top graph shows both pre and post-treatment periods of revenue over time. The grey lines represent the control groups used to derive the synthetic control, and the red vertical lines represent the treatment\u002Fintervention period.\u003C\u002Fp>\n\n\n\n\u003Cp>The middle graph shows the direct causal impact, that is the treatment observations subtracted from the synthetic control. The blue-shaded area represents the causal impact.\u003C\u002Fp>\n\n\n\n\u003Cp>The bottom graph shows the cumulative causal impact, that is what happens to the dependent variable during the post-intervention period. Here we can see that approximately £6000 in revenue has been lost as a result of the treatment. Additionally, we can see that the treatment effects are immediate due to an instant decline in cumulative impact from the point of treatment.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1470\" height=\"884\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fcumulative-impact.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-26020\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>Based on this graph, we can see that on average, approximately £5841 in revenue has been lost as a result of the treatment. However, there is a 94% probability that the exact amount lost in revenue is at least £5719 and at most £5963. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"advantages-of-incrementality-testing\">Advantages of incrementality testing\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"casual-impact\">Casual Impact\u003C\u002Fh3>\n\n\n\n\u003Cp>Constructing a synthetic control group to mimic the treatment group before the treatment helps to isolate the media impact in the absence of any confounding variables.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"avoids-potential-bias-due-to-group-differences\">Avoids potential bias due to group differences\u003C\u002Fh3>\n\n\n\n\u003Cp>By using a synthetic control, we eliminate any possible errors or biases due to individual differences within the control and treatment. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"data-driven-media-planning\">Data-driven media planning\u003C\u002Fh3>\n\n\n\n\u003Cp>Incrementality testing enables you to quantify the impact generated by a campaign or media channel and use this to inform your \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fdigital-marketing\u002Fstrategy\u002F\">marketing strategy\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"uses-advanced-up-to-date-software\">Uses advanced, up-to-date software\u003C\u002Fh3>\n\n\n\n\u003Cp>Here at Impression, we use the most up-to-date and statistically advanced software packages to aid in the modelling process.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"iterative-improvement-in-the-modelling-process\">Iterative improvement in the modelling process\u003C\u002Fh3>\n\n\n\n\u003Cp>Once an initial synthetic control group has been derived, we can assess which control groups contribute towards its derivation. Through model comparison techniques we can derive an optimal synthetic control group that best captures the treatment group in the absence of the treatment.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"iterative-improvement-in-the-media-planning-process\">Iterative improvement in the media planning process\u003C\u002Fh3>\n\n\n\n\u003Cp>Once one incrementality test has been conducted, we gain insights into which control groups create a good synthetic control group and how long a test should typically run to see a significant impact. These insights can aid in the modelling process of other incrementality tests of the same or similar nature. \u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"limitations-of-incrementality-testing\">Limitations of incrementality testing\u003C\u002Fh2>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"data-collection\">Data collection\u003C\u002Fh3>\n\n\n\n\u003Cp>Typically 2-3 years of data is required to create an accurate synthetic control group. Additionally, the data must be of good quality as incomplete or inconsistent data can limit the accuracy of the results.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"selection-of-control-groups\">Selection of control groups\u003C\u002Fh3>\n\n\n\n\u003Cp>If the control groups used to generate the synthetic control group don’t adequately capture the potential outcomes of the treatment group in the absence of the treatment, the synthetic control may become inaccurate. \u003C\u002Fp>\n\n\n\n\u003Cp>Overall, Incrementality testing is a valuable tool that allows marketers to gather insights into media planning. Through data analysis and the understanding of how different media channels impact KPIs in the absence of any confounding variables, businesses can make informed decisions on marketing strategy.\u003C\u002Fp>\n\n\n\n\u003Cp>If you’re looking to improve media planning and overall business performance, based on data-driven statistical evidence, incrementality testing is crucial. Get in touch with one of our media solutions experts if you have any questions or need assistance with incrementality testing. Alternatively, explore our \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fdigital-marketing\u002Fstrategy\u002Fmedia-planning\u002F\">media planning services\u003C\u002Fa> page to learn more about how we can help. \u003C\u002Fp>\n",{"rendered":138,"protected":209},26025,{"_yoast_wpseo_focuskw":5,"_yoast_wpseo_title":716,"_yoast_wpseo_metadesc":5,"inline_featured_image":209,"footnotes":5},"How can incrementality testing improve media planning? | Impression",[216],[],[219],[721,113,222,223,224,225,226,227],"post-26002",[],[],[725,726,727,728],{"path":183,"name":184},{"path":233,"name":234},{"path":124,"name":125},{"path":192,"name":137},"Accurately measuring the effectiveness of a media channel or campaign is a common challenge in digital marketing. We’re always seeking ways to accurately measure impact and assign credit to media channels to ensure we understand what performs best and the impact our channels have. The challenges of measuring media effectiveness  One of the most frequently 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rel=\"noreferrer noopener\" href=\"\u002Fmedia-solutions\u002Fmedia-effectiveness\u002F\">Measuring media effectiveness\u003C\u002Fa> and optimising budget allocation is a challenge for any marketer. As we constantly seek better ways to ensure that every penny spent contributes to the overall success of our campaigns, the traditional approach of relying on heuristics, which involves using rule-of-thumb methods, often falls short in providing actionable insights for long-term success. \u003C\u002Fp>\n\n\n\n\u003Cp>Additionally, over the last couple of decades, there has been an over-reliance on digital Multi-Touch Attribution (MTA) models. These attribution models track and assign credit to multiple media channels based on “touchpoints” within the customer journey. However, Multi-Touch Attribution relies on its ability to see each step of the customer journey. Although, in recent years, this has become increasingly difficult due to the decaying lifetime of the cookie as a result of the Intelligent Tracking Prevention (ITP) browser feature introduction in 2017. \u003C\u002Fp>\n\n\n\n\u003Cp>To address this challenge, marketers need to use more advanced approaches in producing data-driven insights in order to enhance their decision-making processes. \u003C\u002Fp>\n\n\n\n\u003Cp>Welcome to the world of \u003Cstrong>Media Mix Modelling\u003C\u002Fstrong>, or Marketing Mix Modelling – the secret weapon for optimising marketing strategies.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"what-is-media-mix-modelling\">What is Media Mix Modelling?\u003C\u002Fh2>\n\n\n\n\u003Cp>Media mix modelling is a powerful statistical tool used by marketers and \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fmedia-solutions\u002Fdata-science\u002F\">media scientists\u003C\u002Fa> to analyse, optimise and forecast advertising strategies. \u003C\u002Fp>\n\n\n\n\u003Cp>Media mix modelling helps you to determine how different media channels contribute towards achieving the desired marketing goals and uses this to provide an optimal budget distribution. It works by analysing historical data on various media channels and their impact on KPIs. It utilises collected data on media spend, KPIs such as conversions and other context variables such as events, trends or seasonality.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"what-can-media-mix-modelling-do-for-you\">What can Media mix modelling do for you?\u003C\u002Fh2>\n\n\n\n\u003Cp>Media mix modelling allows you to fully understand how effective each media channel is and to what extent each channel contributes towards meeting KPIs such as revenue, enquiries or other outcomes. \u003C\u002Fp>\n\n\n\n\u003Cp>This is done by taking into account not only the effects of each media channel but also how any context variables such as sales events, seasonality or holidays impact KPIs. This provides clarity on which variables are actually impacting KPIs and allows us to quantify their impact. For instance, is a peak or trough in revenue caused by a change in media investment or something else? Media mix modelling incorporates these context variables to allow for a better explanation of anomalies captured within the data set.\u003C\u002Fp>\n\n\n\n\u003Cp>We utilise the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.britannica.com\u002Fscience\u002FBayesian-analysis\">Bayesian framework\u003C\u002Fa> to perform media mix modelling. This allows for any prior knowledge or beliefs that may have to be included in the modelling process for a better quality of model refinement. For instance, if a particular media channel is known (through testing) to have short-term effects that quickly decay over time then it will be beneficial to include this knowledge in the model before incorporating the data. \u003C\u002Fp>\n\n\n\n\u003Cp>Besides strengthening the model through the use of prior knowledge or “priors”, Bayesian models provide a way to account for any uncertainty within the decision-making process. For instance, say the media mix model provides predictions for a particular channel, attached to these predictions will be corresponding probabilities and in most cases, the prediction of the greatest probability will be used.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"640\" height=\"480\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fbayesian-plot.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25571\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>Generally, Bayesian models use a combination of prior knowledge and the data to produce what’s called the posterior distribution. It is this posterior distribution that contains the results and the corresponding uncertainties you require.\u003C\u002Fp>\n\n\n\n\u003Cp>Once a media mix model has been fitted with all the relevant variables and  priors included, you can then also use the media mix model to run simulations on budget allocation among channels, and forecast with different budget scenarios. Media mix modelling allows you to determine the nature of how each media channel affects KPIs, the saturation effects of each media channel and the relative adstock effects. \u003C\u002Fp>\n\n\n\n\u003Cp>Advertising adstock, also known as advertising carry-over, refers to the prolonged effect of advertising after exposure and is best described as the residual effects of an advert that stays with people even after they’ve seen it. Media mix modelling uses various sub-models to best mimic the effects of adstock per channel using a combination of prior knowledge and the data.\u003C\u002Fp>\n\n\n\n\u003Cp>Saturation, on the other hand, occurs when a consumer has been exposed to an advert so frequently that it no longer grabs their attention or influences behaviour. When saturation happens, the effects of the advert diminish over time. In the context of media mix modelling, saturation occurs when further spend on a particular channel begins to generate a non-increasing return on ad spend. Similar to adstock effects, media mix modelling uses various sub-models to best mimic the effects of saturation per channel using a combination of prior knowledge and the data.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n\u003Cdiv class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"640\" height=\"480\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fexample-adstock-plot.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25574\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\u003C\u002Fdiv>\n\n\n\n\u003Cdiv class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"640\" height=\"480\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fexample-saturation-plot.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25573\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\u003C\u002Fdiv>\n\u003C\u002Fdiv>\n\n\n\n\u003Cp class=\"has-text-align-center\">\u003Cem>The above images are plots of example adstock and saturation models for four different media channels. The point shown on the saturation plot denotes the saturation point.\u003C\u002Fem>\u003C\u002Fp>\n\n\n\n\u003Cp>Once determined from the model, a new budget allocation is then proposed based on all these factors. Once budget allocation has been performed, the predicted return on ad spend (ROAS) for each channel can be derived. \u003C\u002Fp>\n\n\n\n\u003Cp>Overall, media mix modelling provides statistically significant insights into media investment which ensures you aren’t over\u002Funder spending on certain media channels. In addition to allowing you to understand anomalies in your KPIs, media mix modelling provides insights concerning how best to avoid or exploit these anomalies with regard to media investment.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fmedia-mix-modelling-graphic.jpg?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25577\" width=\"528\" height=\"292\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>Incrementality studies can also be used to inform media mix modelling by providing useful insights into the incremental impact of various marketing channels. These studies provide prior insights into how a particular media channel contributes to KPI’s in comparison to a scenario with no marketing activity. The model then uses a combination of the data and prior knowledge to assess and forecast business performance.\u003C\u002Fp>\n\n\n\n\u003Cp>Additionally, the model enables you to fine-tune to what extent prior knowledge influences results, therefore if there is a lot of prior uncertainty around the nature of a particular media channel you can incorporate this lack of information into the model. Once any prior knowledge\u002Fbeliefs have been integrated into the model, the data is then used to update this knowledge to provide useful insights derived from both a combination of the data and prior knowledge.\u003C\u002Fp>\n\n\n\n\u003Cp>Once a media mix mode is fitted, you can use this model to predict future KPIs based on either the current or the new optimised budget. Over time these predictions can be compared with reality and as a result, your understanding of the data and modelling process can be iteratively improved over time.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"attribution-modelling\">Attribution modelling\u003C\u002Fh3>\n\n\n\n\u003Cp>Attribution refers to a method that identifies which marketing activities contribute to the KPI of concern. For example, say a customer saw an ad on Facebook, clicked on the website, received a follow-up email then decided to purchase a product, where does the credit for the purchase go? Should the credit go directly to the email (the last touch point) or should it be distributed across each channel (data-driven attribution)? Attribution models aim to accurately capture and model the customer journey and provide insights on channel contribution accordingly. \u003C\u002Fp>\n\n\n\n\u003Cp>With many platforms phasing out the cookie, a different approach for assessing channel contribution on aggregate is needed and this is where marketing mix modelling is best suited.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fbusiness-impact-modelling.jpg?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25580\" width=\"457\" height=\"304\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"advantages-of-media-mix-modelling\">Advantages of Media Mix Modelling\u003C\u002Fh3>\n\n\n\n\u003Cp>\u003Cstrong>It incorporates prior business knowledge\u003C\u002Fstrong> \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Incorporating business insights such as marketing trends, pricing information or competitor activities the modelling process can be tailored towards the unique context of the business in question. This ensures recommendations derived from the media mix model align with the goals and objectives of the organisation.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>Includes offline media contribution\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>The effects of offline media are often tricky to include when assigning credit or contribution to media channels, especially in the case of multi-touch attribution models. Given data regarding offline media spend and performance, media mix modelling can provide data-driven insights into the effects of offline media and include offline media in the new budget allocation.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>Data-driven decision making\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Media mix modelling allows you to quantify the impact generated by various different media channels and uses this to provide data-driven insights into budget allocation and marketing strategies.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>Maximises ROAS\u003C\u002Fstrong> \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Obtains an optimal media mix and forecasts channel contribution to maximise ROAS across the entire media channel portfolio.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>Avoids being misled by other variables\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Any peaks or troughs in the data can be accounted for by including non-media variables in the modelling process.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cstrong>Uses the most up to date software to aid with modelling\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Here at Impression, we use the most up-to-date and statistically advanced software packages to quantify channel contribution, perform budget allocation and optimise ROAS.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"limitation-of-media-mix-modelling\">Limitation of Media Mix Modelling\u003C\u002Fh3>\n\n\n\n\u003Cp>\u003Cstrong>Data limitations\u003C\u002Fstrong>\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Typically 2-3 years of data is required to run an accurate media mix model. This is because the model will struggle to truly capture the effects of seasonality with limited data. Additionally, the data must be of good quality as incomplete or inconsistent data can limit the accuracy of the results.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"how-is-media-mix-modelling-done\">How is Media Mix Modelling done?\u003C\u002Fh2>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"730\" height=\"320\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F11\u002Fdata-collection-and-preparation.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-25583\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>The first step to fitting a Media Mix Modelling is data collection and preparation. Data including variables such as marketing events, spend data, sales data and other external factors including seasonality and holidays is required. This data should be cleansed and organised in a structured manner for model input.\u003C\u002Fp>\n\n\n\n\u003Cp>Secondly the relevant spend and context variables are then transformed in order to take into account the effects of adstock and saturation. The nature of these transformations can be tuned according to any prior beliefs\u002Fknowledge one may have. Although the order of these transformations does matter, in general practice the adstock transformation is applied and then the saturation transformation afterwards. \u003C\u002Fp>\n\n\n\n\u003Cp>Once the data has been transformed a statistical model is then fitted with aim of mimicking KPIs. The modelling process involves advanced statistical and machine learning techniques depending on the context of the analysis. This model is used to estimate the impact generated by various media channels.\u003C\u002Fp>\n\n\n\n\u003Cp>Once an optimal model has been defined, it can be used to assess the impact of different budget strategies. Through estimation of the optimal media mix, an optimal budget allocation can be derived which identifies the most effective way to maximise the ROAS. Any uncertainty associated with such predictions can also be extracted from the model, which provides clarity regarding the validity of the results. The larger variation in current media spend and the further we extrapolate from current media spend the larger any associated errors become.\u003C\u002Fp>\n\n\n\n\u003Cp>Lastly, model refinement over time is very important. This may involve updating the data, modifying prior beliefs or adding new variables to account for new abnormalities in the data. Keeping the data up-to-date and adapting the model over time will only improve the predictive validity of the model.\u003C\u002Fp>\n\n\n\n\u003Cp>Media mix modelling is a valuable tool that allows marketers to optimise their \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fdigital-marketing\u002Fstrategy\u002F\">marketing strategies\u003C\u002Fa>. Through the analysis of data and understanding of how different media channels contribute towards KPIs, businesses can make informed decisions on resource allocation. Media mix modelling helps to maximise channel contribution which leads to better results and a stronger return on investment. \u003C\u002Fp>\n\n\n\n\u003Cp>If you’re looking to improve KPIs and overall business performance, based on data-driven statistical evidence, media mix modelling is the way forward!\u003C\u002Fp>\n\n\n\n\u003Cp>For more insights and guides on measurement and GA4, be sure to take a look at our \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fblog\u002Fcategory\u002Fmeasurement\u002F\">blog\u003C\u002Fa>. If you want to talk about your business aspirations, \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fget-in-touch\u002F\">get in touch!\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"javascript:void(0)\">\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"javascript:void(0)\">\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"javascript:void(0)\">\u003C\u002Fa>\u003C\u002Fp>\n",{"rendered":148,"protected":209},25588,{"_yoast_wpseo_focuskw":5,"_yoast_wpseo_title":908,"_yoast_wpseo_metadesc":909,"inline_featured_image":209,"footnotes":5},"Measure Marketing Effectiveness with Media Mix Modelling | Impression","Media mix modelling is a powerful statistical tool used by marketers and media scientists to analyse, optimise and forecast advertising 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we all adapt to using Google Analytics 4, one of the most important changes marketers are facing is the change to data-driven attribution. With Universal Analytics, all conversions were attributed to the last non-direct channel. \u003C\u002Fp>\n\n\n\n\u003Cp>Whilst this model awarded the conversion to the channel that ultimately led to the conversion, it didn’t show the full multi-channel picture and how other channels contributed. Whilst we had assisted conversion reports and ‘Attribution Projects’ these features never felt complete or were always one of Google’s ‘Beta’ features.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"how-data-driven-attribution-works\">How data-driven attribution works\u003C\u002Fh2>\n\n\n\n\u003Cp>In a nutshell, Data-driven attribution uses machine learning algorithms to analyse historical data and determine the impact of different channels, campaigns, and interactions on conversions.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"collection-of-user-journey-data\">Collection of user journey data\u003C\u002Fh3>\n\n\n\n\u003Cp>Without data, you don’t have data-driven attribution, GA4 therefore collects data from various touchpoints along the user journey, including different marketing channels such as organic search, paid search, social media, email campaigns etc. It also tracks user interactions within your website or app such as page views, clicks, and most importantly, the conversion actions that you define. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"attribution-modelling-and-weighted-credit-distribution\">Attribution modelling and weighted credit distribution\u003C\u002Fh3>\n\n\n\n\u003Cp>This is where the magic happens! Using advanced machine learning techniques, the attribution model assigns a specific weight to each touchpoint based on its influence. It considers factors like the position of the touchpoint in the user journey, the frequency of touchpoints and their relative importance in driving conversions. Touchpoints that have a high impact on conversions receive a higher credit weight.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F06\u002Fdata-drive-attribution-ga4-blog-1.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-23961\" width=\"433\" height=\"365\"\u002F>\u003Cfigcaption class=\"wp-element-caption\">*Taken from Google’s documentation\u003C\u002Ffigcaption>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"reporting-insights\">Reporting insights\u003C\u002Fh3>\n\n\n\n\u003Cp>GA4 provides visual reports and insights that allow you to analyse the attributed credit for each touch point. You can explore the data-driven attribution reports to understand the role of different channels, campaigns, and interactions in your customers’ journey, helping you make data-backed decisions for your marketing strategies.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full is-resized\">\u003Cimg loading=\"lazy\" decoding=\"async\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F06\u002Fdata-drive-attribution-ga4-blog-2.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-23963\" width=\"660\" height=\"407\"\u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\u003Cp>It’s important to note that data-driven attribution relies on historical data and it requires a sufficient volume of data to provide accurate and reliable insights. The model continuously learns and adapts as new data becomes available allowing it to refine attribution over time.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"other-considerations\">Other considerations\u003C\u002Fh3>\n\n\n\n\u003Cp>Whilst this blog has focused on how the principles of data-driven attribution within GA4 and how it’s applied to your standard conversion reports, the technology is fundamental to various other advanced tracking features within GA4 and beyond. For example, if you are using Google’s ‘consent mode’ in your tagging deployment, GA4 collects observable and unobservable data (Declined cookie users) and applies similar machine-learning techniques and data-driven analysis to recover conversions that would otherwise be lost.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"final-thoughts\">Final thoughts\u003C\u002Fh2>\n\n\n\n\u003Cp>Data-driven attribution is here to stay, and whilst it might be a little confusing to understand at first, you can be confident that it will provide a greater understanding of our marketing efforts as a whole, enabling you to make informed decisions about resource allocation, campaign optimization, and overall marketing strategy.\u003C\u002Fp>\n",{"rendered":160,"protected":209},23965,{"_yoast_wpseo_focuskw":5,"_yoast_wpseo_title":5,"_yoast_wpseo_metadesc":1102,"inline_featured_image":209,"footnotes":5},"Data-driven attribution uses machine learning algorithms to determine the impact of 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has announced that you are able to create your own custom channel groupings in Google Analytics 4, giving you more control over how you can interpret your data.\u003C\u002Fp>\n\n\n\n\u003Cp>Previously available in Universal Analytics, this feature now brought over to GA4 allows you to configure your traffic groupings to your own preferences, letting you collect data however you see fit.\u003C\u002Fp>\n\n\n\n\u003Cp>From the ‘Data Settings’, you can create a custom channel grouping by adding conditions based on the Default channel group, Medium, Source, Source platform, Campaign ID and Campaign name.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1999\" height=\"1060\" src=\"https:\u002F\u002Fimages.impression.co.uk\u002F2023\u002F05\u002Fcustom-channel-grouping-ga4.png?auto=compress%2Cformat&q=90\" alt=\"\" class=\"wp-image-22878\"\u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>This versatile feature allows you to:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Create new channel groups\u003C\u002Fli>\n\n\n\n\u003Cli>Edit groups\u003C\u002Fli>\n\n\n\n\u003Cli>Edit channels in a group\u003C\u002Fli>\n\n\n\n\u003Cli>Add new channels to a group\u003C\u002Fli>\n\n\n\n\u003Cli>Remove channels\u003C\u002Fli>\n\n\n\n\u003Cli>Reorder channels\u003C\u002Fli>\n\n\n\n\u003Cli>Remove groups\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>\u003Cbr>You can filter out irrelevant traffic and have the ability to create incredibly granular reports.  \u003C\u002Fp>\n\n\n\n\u003Cp>Since GA4 was introduced users have had to become accustomed to a \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fblog\u002Fgoogle-analytics-4-updates-and-what-they-mean-for-your-business\u002F\">number of changes\u003C\u002Fa>, one of which being the lack of customisation with regard to channel groupings. The built-in and fixed groups combined with the inability to change definitions encourage more standardised UTM-tagging but have been viewed as restrictive by some. It doesn’t necessarily show what you want and can result in a lot of time spent finding workarounds and manually consolidating your chosen data.\u003C\u002Fp>\n\n\n\n\u003Cp>Google did however provide a flow of constant updates that provided new channels, giving a more granularised view of traffic that is much better than the standard UA channel groupings.\u003C\u002Fp>\n\n\n\n\u003Cp>For this reason, we think users should stick as closely as possible to these new channel groupings, despite the new customisation options allowing people to make sweeping changes or even be tempted to simply rebuild the old (and inferior) UA channels.\u003C\u002Fp>\n\n\n\n\u003Cp>The newly provided channels as stated are more granular, giving us groupings such as Paid Social and Organic Shopping that previously you would have to manually create. This goes hand in hand with the increased number of UTM parameters in GA4, which brings you both more control and specificity over the data you can collect.\u003C\u002Fp>\n\n\n\n\u003Cp>All that said, this new feature does allow us to separate very specific traffic which does help in some cases. Emails, for example. Not all emails being sent out are for marketing purposes, and can now be filtered out and not bundled into the Email channel. Edge cases such as this can build up and affect attribution if overlooked. Any customisation to combat this is welcome, especially one that can be applied retroactively.\u003C\u002Fp>\n\n\n\n\u003Chr class=\"wp-block-separator has-alpha-channel-opacity is-style-wide\"\u002F>\n\n\n\n\u003Cp>If you would like more advice on how you can get the most out of your Google Analytics 4 set-up, be sure to read our analytics \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fblog\u002Fcategory\u002Fmeasurement\u002F\">blogs\u003C\u002Fa>. If you have any questions about how to set up GA4 for your business, be sure to \u003Ca rel=\"noreferrer noopener\" href=\"\u002Fget-in-touch\u002F\">get in touch\u003C\u002Fa>.\u003C\u002Fp>\n",{"rendered":169,"protected":209},22886,{"_yoast_wpseo_focuskw":5,"_yoast_wpseo_title":1290,"_yoast_wpseo_metadesc":1291,"inline_featured_image":209,"footnotes":5},"Custom channel groupings introduced to Google Analytics 4 | Impression","Create your own custom channel groupings in Google Analytics 4 to give you more control over how you can interpret your data. Read 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