[{"data":1,"prerenderedAt":1650},["ShallowReactive",2],{"blog-en-improve-google-ads-strategy-with-profit-data":3,"related-en-improve-google-ads-strategy-with-profit-data":220},{"id":4,"title":5,"author":6,"body":7,"category":202,"description":193,"extension":203,"image":204,"isToc":205,"langAlt":6,"meta":206,"metaDescription":6,"navigation":207,"path":208,"published":207,"publishedAt":209,"readingTimeMinutes":210,"readingTimeText":211,"relatedArticles":212,"seo":216,"stem":217,"teaser":218,"updatedAtCustom":6,"__hash__":219},"blog_en\u002Fen\u002Fblog\u002Fimprove-google-ads-strategy-with-profit-data.md","Improve Google Ads strategy with Profit data",null,{"type":8,"value":9,"toc":192},"minimark",[10,15,24,28,31,49,56,60,63,70,74,81,88,95,99,104,111,134,137,148,158,162,169,175,179,186],[11,12,14],"h2",{"id":13},"google-ads-bidding","Google Ads bidding",[16,17,18,19,23],"p",{},"Simply put, Google Ads advertising serves one purpose only: invest sources to get conversions. However, in practices, the “science” behind it is not that simple. You are bidding over your competitors thousands of times every second. Every time the ad space is available (a person search something on Google or opens a page), Google carries out an auction and decides which particular ad will be shown to that particular person. Some cookies (users) are more worthy for you than others. ",[20,21,22],"strong",{},"Automatic smart bidding algorithm learns from your data using AI",", which cookies (users) are likely to convert, and it uses the information for decisions of automatic bidding.",[11,25,27],{"id":26},"you-need-data-but-what-data","You need data. But what data?",[16,29,30],{},"Google Ads automated smart bidding AI needs conversion data to learn and optimize its strategy to function properly. However, sending orders to Google Ads has two dimensions.",[32,33,34,42],"ol",{},[35,36,37,38,41],"li",{},"The first is to record ",[20,39,40],{},"the order"," as such that it has been actually made by a user.",[35,43,44,45,48],{},"But the second dimension is ",[20,46,47],{},"the value of the order",".",[16,50,51,52,55],{},"The simplest and at the same time the most widespread solution is to send data on orders with their turnover. Turnover is publicly known information displayed on your website, so it is easily available and at the same time you do not have to be afraid to send it anywhere. However, if you have ever encountered product pricing at least marginally, then you must know that turnover is actually the worst value on which to optimize a marketing algorithm. It is more ",[20,53,54],{},"optimal to build the algorithm on the profit or at least on margin",", as that is the value you get your earnings from, at the end of the day. The order with the highest turnover is often not the one with the highest profit. However, obtaining the profitability of orders is not an easy task and requires a non-trivial infrastructure and implementation of processes in the company.",[57,58,59],"note",{},"\nThis article does not explains calculating the profitability of orders, but it is a necessary condition before you can send profit to Google Ads.\n",[16,61,62],{},"By default, order turnovers are sent directly from the website frontend, which unknowingly solves one of the other important tasks for you. Because the order is sent from the frontend, Google can link the order with a specific user or with a specific click on the advertisement via cookies, which it needs to optimize its algorithm.",[16,64,65,66,69],{},"The problem is that profitability is not an information you would like to expose publicly or directly to your competition. And whatever is sent from the frontend of the site is completely available for anyone to see. Our solution sends only a part of the information from the website frontend and connects them with the profit in backend processes, thus ",[20,67,68],{},"the profit on individual order is passed on in a secure, non-public way",". Also, the order’s profit changes over time and thus it is not even possible to send the final profit from the frontend once the order is completed.",[11,71,73],{"id":72},"before-you-start","Before you start",[16,75,76,77,80],{},"There is only one, but very challenging, condition before you send profit to Google Ads: ",[20,78,79],{},"You must have the calculated profit (or margin) on each individual order."," If may seem like a simple task at first, but trust us, it is not. From the experience of working with many clients, profit calculation can sometimes take longer than the solution implementation itself.",[16,82,83,84,87],{},"However, the profit must be calculated ",[20,85,86],{},"correctly, reliably and on time",". All three of these aspects are key to managing Google Ads profitability. There will always be something missing from the profit calculation. It is not possible to have real-time profit calculation, nonetheless, the more accurate and faster you can calculate it, the better your Google Ads targeting will work.",[16,89,90,91,94],{},"For clients with ",[20,92,93],{},"longer customer journey"," like banks, automotive, B2B, traveling and so on, just sending so called real conversion could be a huge step in bidding effectivity. If you are sending conversion into Google Ads, which has less than 80 % probability to be profitable, then it is your case. This is mostly happening in cases when conversion sent into the Google Ads is just a lead, and someone must take another action to pursued the user to really want the product or service. If you start sending data on the leads that actually converted into Google, your bidding effectivity will rise significantly, you will save more money and get more conversions. Everything we describe in the following parts of the article can by applied on these cases as well.",[11,96,98],{"id":97},"how-it-works","How it works",[100,101],"image-with-caption",{"source":102,"caption":103},"\u002Fupload\u002Fmhubcloud-simple.webp","mHub Cloud system data flow",[16,105,106,107,110],{},"For processing and connecting data, you can use our tool called ",[20,108,109],{},"mHub Cloud",". This tool manages backend measurement into several marketing platforms including Google Ads.",[112,113,114,115,118,119,122,123,126,127,130,131],"example",{},"\nmHub Cloud enables backend data processing and connects them to marketing platforms. The main advantage is integrating different data sources, as each platform requires different approach. A part of mHub Cloud is \n",[20,116,117],{},"data preparation","\n including deduplication and other cleaning mechanisms. It also includes consent processing and \n",[20,120,121],{},"sophisticated alerting system","\n. The \n",[20,124,125],{},"data is thus better protected","\n because it is no longer publicly visible and therefore less attackable.\n",[128,129],"br",{},"\n\n\nThanks to mHub cloud you \n",[20,132,133],{},"gain more control over your data which you can enrich and increase the performance of your campaigns.",[16,135,136],{},"In theory, the process is simple, as shown on the picture above. We'll take data from two sources, combine them, and send them to Google Ads. In practice, it is a matter of integrating several very different data sources and non-trivial data cleaning. The process includes deduplication, attribution and additional cleanup mechanisms that prepare the data for proper processing by Google Ads.",[16,138,139,140,143,144,147],{},"The fundamental issue of the whole technique is that the ",[20,141,142],{},"profit changes and is actually more and more accurate in time",". For example, because you already know that the order has been paid for and collected, it can no longer be returned or claimed, etc. All these events affect the resulting profit. On the contrary, from an accounting point of view, until the order has been paid, the profit is 0. Which, in case of a cash payment, the actual profit will be delayed for a few days. That's too late for Google Ads. For this reason, ",[20,145,146],{},"we recommend calculating the profit on the order immediately after completing the order."," Otherwise, Google Ads receives a large number of zero values ​​that keeps the bidding algorithm grounded. Another extreme situation is when the algorithm is encouraged to bid unnecessarily, as some orders will not be paid in the end.",[16,149,150,151,154,155,157],{},"The solution to this conflict is ",[20,152,153],{},"prediction, which greatly improves the effectivity of the bidding algorithm",". The calculation of profit prediction using AI takes place inside the ",[20,156,109],{},". The prediction is used especially when the order has not yet been paid, or when 14 days have not elapsed since the order was picked up (due to possible returns). In the moment that the order is canceled, returned, etc., the predicted value is replaced by the real profit value directly from your system.",[11,159,161],{"id":160},"error-alerts","Error Alerts",[16,163,164,165,168],{},"The cherry on top is a ",[20,166,167],{},"consistent assurance that everything is going smoothly",". mHub Cloud has an already integrated sophisticated alerting, which monitors data at various levels. If there is an error or even a data failure at any level, we will know immediately, and we can react in a reasonable time and fix the problem.",[16,170,171,172,48],{},"A short-term outage is not critical for the entire system. If the system fails for one or two days, then it doesn’t have to be critical. The bidding algorithm in Google Ads will continue to work and a few days outage will only slightly affect it, still keeping within the campaign plans. However, a multi-day outage could be critical, effecting the bidding severely, as the algorithm will begin to affect each day more and more. Therefore, having a ",[20,173,174],{},"system of warnings that scans the data for correct retrieval makes a difference",[11,176,178],{"id":177},"conclusion","Conclusion",[16,180,181,182,185],{},"Sending profit to your Google Ads instead of turnover can make a significant change in terms of optimizing your marketing budget, hence increasing performance of marketing campaign, simply by not wasting resources on nonprofitable products, or draining your budget due to false orders. The easiest, secure and better in a long-term way as well, is ",[20,183,184],{},"integrating the information on the backend and sending clean and enriched data to Google Ads",". mHub Cloud is a quick and easy solution that may help you overcome more obstacles. The anonymization, predictions and alerting system opens new opportunities how you can use the data you already have and achieve better outcomes.",[187,188,191],"action",{"link":189,"button":190},"\u002Fen\u002Fget-in-touch\u002F","Contact Us","\n Contact us if you are ready to change the way you are bidding now.\n",{"title":193,"searchDepth":194,"depth":194,"links":195},"",2,[196,197,198,199,200,201],{"id":13,"depth":194,"text":14},{"id":26,"depth":194,"text":27},{"id":72,"depth":194,"text":73},{"id":97,"depth":194,"text":98},{"id":160,"depth":194,"text":161},{"id":177,"depth":194,"text":178},"Products","md","\u002Fupload\u002Fbidding-illustration.webp",false,{},true,"\u002Fen\u002Fblog\u002Fimprove-google-ads-strategy-with-profit-data","2021-06-16T09:07:00+00:00",7.735,"8 min read",[213,214,215],"content\u002Fen\u002Fblog\u002Fconversion-rate-explained.md","content\u002Fen\u002Fblog\u002Fhow-to-optimize-utm-for-uniform-campaign-typology.md","content\u002Fen\u002Fblog\u002Fare-the-results-of-your-a-b-testing-accurate.md",{"title":5,"description":193},"en\u002Fblog\u002Fimprove-google-ads-strategy-with-profit-data","Are you using smart bidding in Google Ads? Are you sending into the Google Ads conversions with turnover? Or even worse, are you sending conversions into the Google Ads that are not real conversions, like for example not paid order or just a lead from a web form? If you answered yes, then you are at right place and reading this article will be worthy for you.","MlUOR-3CnXPZV9Q5TqOJyMNvzLFmmH7F3HSvmV1mM-c",[221,351,664],{"id":222,"title":223,"author":6,"body":224,"category":6,"description":228,"extension":203,"image":338,"isToc":205,"langAlt":6,"meta":339,"metaDescription":6,"navigation":207,"path":340,"published":207,"publishedAt":341,"readingTimeMinutes":342,"readingTimeText":343,"relatedArticles":344,"seo":347,"stem":348,"teaser":349,"updatedAtCustom":6,"__hash__":350},"blog_en\u002Fen\u002Fblog\u002Fare-the-results-of-your-a-b-testing-accurate.md","Are the results of your A\u002FB testing accurate?",{"type":8,"value":225,"toc":333},[226,229,233,244,250,253,256,267,273,280,285,289,292,307,318,325,327,330],[16,227,228],{},"A\u002FB test is an important tool for optimizing marketing expenses. It provides information about the benefits of a solution without the interference of other factors. Moreover, it can lower the risk of exposure to the whole audience before you are sure that is the right choice for you. Especially if you want to compare two competing solutions, for example, two agencies offering you a different promotional solution, and you like both of them. It can be difficult to choose one only by looking at it. What had worked in the past may not be as profitable now. With A\u002FB testing methodology you can evaluate if the more expensive proposition is really worth the premium you are paying for it. Or try a more daring idea to see the outcomes of the possibly high risk.",[11,230,232],{"id":231},"data-issues","Data issues",[16,234,235,236,239,240,243],{},"However, to perform an A\u002FB test ",[20,237,238],{},"you need to rely on the data"," needed for the analysis. To avoid systematic differences in the groups, random assignment of users to groups is generally preferred if the type of data allows it. Although, even with the random assignment, not all issues are solved yet. In particular, it is essential to check if the real shares of users in compared groups are not significantly different from their expected shares that are used in the evaluation. For the A\u002FB test, there is no problem having groups that are not equally distributed, given that the smaller group has a reasonable amount of traffic in it. However, if you expect the groups to be divided into halves, assigning systematically one of the solutions to 55 % of traffic will ",[20,241,242],{},"distort the results of the A\u002FB test dramatically",". This is even more relevant for A\u002FB tests with more than two groups for comparison as the individual shares can vary more relative to their size.",[112,245,246,249],{},[20,247,248],{},"Example:","\n if users are divided into three groups at 20:40:40 distribution and the data have high variation, it can happen that the smallest group which on average has 20 % of the traffic will oscillate between 12 % and 28 % in daily shares. This causes the results to be difficult to interpret due to changing relative position and large standard deviation of the effect.\n",[16,251,252],{},"In practice, even with the use of random assignment, the data are rarely distributed by the exact share. When there is no problem in the data, the average over a long period of time should converge to the expected share. However, the real daily shares vary naturally around their averages depending on the volatility of the data.",[16,254,255],{},"Consequently, this unfolds two aspects of the issue of correct group distribution:",[16,257,258,259,262,263,266],{},"1. Check if there is no problem in the data causing the ",[20,260,261],{},"average shares"," to ",[20,264,265],{},"differ from the expected shares"," (e.g. due to implementation of the random assignment or due to sample in Google Analytics)",[16,268,269],{},[270,271],"img",{"alt":193,"src":272},"\u002Fupload\u002Fexample1_wrongdistribution.webp",[16,274,275,276,279],{},"2. If you want to evaluate the A\u002FB test on a daily basis, the results can be influenced by the ",[20,277,278],{},"fluctuation of data"," around their average shares.",[16,281,282],{},[270,283],{"alt":193,"src":284},"\u002Fupload\u002Fexample2_largevariation.webp",[11,286,288],{"id":287},"how-to-approach-the-issue-with-the-wrong-distribution","How to approach the issue with the wrong distribution?",[16,290,291],{},"Over the years of practice, when we experienced similar problems in a few of our clients, we found two possible ways to approach this matter that works for most cases. Depending on the particular case and the testing frequency, you can check the difference between the real ratio and the expected one or you can choose to calculate daily shares.",[16,293,294,295,298,299,302,303,306],{},"Firstly, you perform a test whether the real representation of the groups is ",[20,296,297],{},"not statistically different"," from the expected distribution and in case of no difference, ",[20,300,301],{},"evaluate"," the test ",[20,304,305],{},"based on the expected distribution",". This is mostly relevant for a one-time A\u002FB test or an A\u002FB test that is evaluated over an aggregated time period (for example weekly or monthly based on the size of the data).",[16,308,309,310,313,314,317],{},"Alternatively, you can approach the problem in a more systematic way. We use this approach in our analyses, especially in repeatedly evaluated daily A\u002FB tests. In addition to other data necessary for the A\u002FB test evaluation, we also ",[20,311,312],{},"collect daily data about new users"," that visited the client’s website. For these new users, we obtain data on their assignment to the test groups. Based on this data ",[20,315,316],{},"we calculate daily share"," for each test group as the ratio between the daily count of new users in the given group and the total count of all new users. This calculated daily share is then used instead of the expected shares of the test groups.",[16,319,320,321,324],{},"The systematic approach ensures that even on the basis of daily evaluation, the results are ",[20,322,323],{},"not affected by the differences of current share to the expected share"," for the given group. Furthermore, it ensures that no error in assignment to groups affects the results. This leads to more reliable and potentially stable outcomes that help you to select the better performing solution quicker and avoid miss-interpretation based on the wrong representation of the solutions among users.",[11,326,178],{"id":177},[16,328,329],{},"To conclude, A\u002FB testing should be a part of a decision process. It doesn’t matter if you are trying to choose between and agency or a different color. Especially, when the decision is strategic and can impact the business significantly, the verification of the results is crucial.",[187,331,332],{"link":189,"button":190},"\nOur methodology has successfully revealed and corrected the data issue and supported the accuracy of the evaluation for multiple clients. Contact us for more information. We can ensure the accuracy of your A\u002FB testing too.\n",{"title":193,"searchDepth":194,"depth":194,"links":334},[335,336,337],{"id":231,"depth":194,"text":232},{"id":287,"depth":194,"text":288},{"id":177,"depth":194,"text":178},"\u002Fupload\u002Fab-testing-article-cover.webp",{},"\u002Fen\u002Fblog\u002Fare-the-results-of-your-a-b-testing-accurate","2020-07-29T12:00:00.000+00:00",5.015,"6 min read",[345,346],"content\u002Fen\u002Fblog\u002Fincrease-conversions-with-category-page-product-ranking.md","content\u002Fen\u002Fblog\u002Fgetting-the-most-out-of-permission-marketing.md",{"title":223,"description":228},"en\u002Fblog\u002Fare-the-results-of-your-a-b-testing-accurate","You are testing two versions of your content or two marketing agencies and their performance. Generally, testing is vital to make better business decisions. Therefore, you expect the results to tell you what you need to know. However, what if the tested data is not correctly distributed into the groups? How can you rely on the results? Is it possible to detect it?","UUf0hx43SuKaK9Jv_PRJERitDPCLh4NXYLTSuAjog6I",{"id":352,"title":353,"author":6,"body":354,"category":650,"description":358,"extension":203,"image":651,"isToc":205,"langAlt":6,"meta":652,"metaDescription":6,"navigation":207,"path":653,"published":207,"publishedAt":654,"readingTimeMinutes":655,"readingTimeText":656,"relatedArticles":657,"seo":660,"stem":661,"teaser":662,"updatedAtCustom":6,"__hash__":663},"blog_en\u002Fen\u002Fblog\u002Fconversion-rate-explained.md","Conversion Rate Explained",{"type":8,"value":355,"toc":644},[356,359,362,373,377,380,383,386,389,392,396,399,402,411,414,417,420,426,429,432,436,439,442,445,448,453,456,461,464,469,481,484,489,492,495,507,511,514,519,522,526,540,544,552,556,564,568,576,580,588,592,607,610,613,616,621,630,637],[16,357,358],{},"In reality, you probably wouldn't want your site to be on one of those lists. However, there is a way to make the conversion rate really matter as a metric that can help you improve your site.",[16,360,361],{},"There are three things to review:",[32,363,364,367,370],{},[35,365,366],{},"What is the conversion rate?",[35,368,369],{},"Why isn't it the answer to all of the world's problems?",[35,371,372],{},"What can you do to make a conversion rate more meaningful?",[11,374,376],{"id":375},"what-is-conversion-rate","What is Conversion Rate?",[16,378,379],{},"The conversion rate is the percentage of visits to your site that result in a conversion. For most site owners, a conversion can be a sale or a lead of some kind, typically related to the number of visits or sessions:",[57,381,382],{},"\nConversion Rate = Number of Sales \u002F Number of Visits\n",[16,384,385],{},"If your store is visited 100 times and 5 of those visits end in a sale, you have a 5% conversion rate.",[16,387,388],{},"The reason people care about that, and the big idea behind conversion optimization, is that if you can figure out how to increase your conversion percentage, you will increase sales for the same traffic costs.",[16,390,391],{},"But that isn’t exactly the case.",[11,393,395],{"id":394},"why-conversion-rate-isnt-the-answer-to-all-your-problems","Why Conversion Rate Isn't the Answer to All Your Problems",[16,397,398],{},"A higher conversion rate doesn't always mean higher performance.",[16,400,401],{},"The simplest way to explain this is with an example. Here are the stats for two days of activity on one e-commerce site:",[403,404,405,408],"ul",{},[35,406,407],{},"Day 1: 4% conversion rate. (5000 visits, 200 sales)",[35,409,410],{},"Day 2: 10% conversion rate. (1000 visits, 100 sales)",[16,412,413],{},"On the second day, the conversion was more than double the rate from day 1. Yet, it's easy to see day one was a much better day for the business (assuming all outgoing costs were the same).",[16,415,416],{},"When focusing on a conversion number, we are pretending that every visit to our site is a potential sale. Although, not all visits to your site have the potential to convert. While that might be true for a particular PPC landing page, it is very rarely true for an entire site.",[16,418,419],{},"Visitors may be checking the status of their orders, looking for your phone number, job hunting, grabbing a link to share with a friend, or any number of other activities. Focusing purely on improving the overall conversion rate from any given visit ignores scores of other possibilities.",[16,421,422,423],{},"It’s also possible that ",[20,424,425],{},"making your site more engaging may reduce your conversion rate.",[16,427,428],{},"Let's say you have an e-shop, with absolutely no content other than products. Your average customer comes to the site once a month and buys once every two months. To try and improve this, you add a blog to the site with really engaging content. Suddenly, your average customer is visiting the site twice a week.",[16,430,431],{},"To maintain your conversion rate, you'd have to persuade your longtime loyal customers to buy once per week, instead of once every two months. In other words, your site has most definitely improved, and it's very likely your headline conversion rate will go down. Conversion rates vary wildly based on the visitor type.",[11,433,435],{"id":434},"conversion-rates-vary-wildly-based-on-the-visitor-type","Conversion rates vary wildly based on the visitor type",[16,437,438],{},"A first-time visitor to your site who has never bought your products, is far, far less likely to make a purchase than an existing, proven-to-be-loyal customer. On the opposite, a very loyal customer and a regular visitor are far less likely to be influenced to make a purchase because of minor conversion tweaks.",[16,440,441],{},"Combining those two groups together is like putting first-time house buyers into a big pot with castle owners and trying to make sense of the strange average housing prices.",[16,443,444],{},"Visitors from different traffic sources also differ wildly. Direct visitors convert well as that user group tends to contain more existing customers. Likewise, brand and non-brand search terms, generic and long-tail terms vary too.",[16,446,447],{},"That’s where users come in.",[16,449,450],{},[270,451],{"alt":193,"src":452},"\u002Fupload\u002Fcolumn-rates-graph.webp",[16,454,455],{},"The thing is, growing your site will often decrease conversion rates.",[457,458,460],"h5",{"id":459},"look-at-another-example","Look at another example:",[16,462,463],{},"Here are 2 alternative tables of numbers for a site bringing in £565k in revenue over the period we're looking at.",[16,465,466],{},[270,467],{"alt":193,"src":468},"\u002Fupload\u002Fconversion-example-1.webp",[16,470,471,472,476,477,480],{},"We can see most channels convert between 1% and 3%, yet visits ",[473,474,475],"em",{},"\"direct\""," to the site & via ",[473,478,479],{},"\"email\""," are far more likely to result in a customer purchase (25% chance and 14% chance).",[16,482,483],{},"Hence, the focus sits considerately on the best converting channels. We send out more emails, and we turn off many of the other channels:",[16,485,486],{},[270,487],{"alt":193,"src":488},"\u002Fupload\u002Fconversion-example-2.webp",[16,490,491],{},"The overall conversion rate has more than doubled. Revenue is the same, and we've probably saved a lot of advertising costs.",[16,493,494],{},"That all looks fantastic at first glance. However, we've turned off most of the growth channels of the site. Look at the second table again and ask:",[403,496,497,502],{},[35,498,499],{},[473,500,501],{},"In a year's time, will we still be able to squeeze out new sales from our same old email list?",[35,503,504],{},[473,505,506],{},"Will we be able to win back the customers our competitors have grabbed from us through their PPC and affiliate campaigns?",[11,508,510],{"id":509},"make-conversion-rates-meaningful-again","Make Conversion Rates Meaningful Again",[16,512,513],{},"Despite all of these ugly limitations (and more), the conversion is still an incredibly powerful tool. Here are some tips to make more sense of conversion and take impactful steps to improve your results.",[515,516,518],"h4",{"id":517},"measure-conversion-rates-contextually-not-literally","Measure conversion rates contextually, not literally",[16,520,521],{},"An increase in conversion rate can be caused by a vast decrease in visitors coupled with a gentler decrease in sales.",[515,523,525],{"id":524},"use-it-as-a-question-prompt-rather-than-an-answer","Use it as a question prompt rather than an answer",[16,527,528,535,536,539],{},[473,529,530,531,534],{},"\"My conversion rate has gone up 3%, ",[20,532,533],{},"why","?\""," Avoid using ",[473,537,538],{},"\"my conversion rate has gone up 3%\""," as a declaration of results.",[515,541,543],{"id":542},"it-works-really-well-for-very-specific-tasks","It works (really well) for very specific tasks",[403,545,546,549],{},[35,547,548],{},"Building individual landing pages around conversion",[35,550,551],{},"Putting together an email with conversion in mind.",[515,553,555],{"id":554},"break-your-conversion-rate-down-by-channel","Break your conversion rate down by channel",[403,557,558,561],{},[35,559,560],{},"Generally, acquisition channels like non-brand pay-per-click will convert at a far lower rate than your site average. Seeking to improve those rates individually will save you (and make you) far more money than treating it as part of a bigger 'overall conversion' number.",[35,562,563],{},"Separate out your channels, figure out which you can impact through conversion optimization, and focus on those instead of your headline conversion rate.",[515,565,567],{"id":566},"break-conversion-rate-down-by-visitor-type","Break conversion rate down by visitor type",[403,569,570,573],{},[35,571,572],{},"Split out \"new visitors\" and \"returning visitors\" (or better yet, \"previous buyers\" and \"never bought before\").",[35,574,575],{},"Remember that superficial site changes are far more likely to affect new visitors than old visitors. Your existing customers are swayed by brand, service, product quality, delivery, etc. Your new visitors are far more swayed by perception.",[515,577,579],{"id":578},"break-it-down-by-task","Break it down by task",[403,581,582,585],{},[35,583,584],{},"If your site has several key tasks (e.g. sales, customer support inquiries, leads, account top-ups) treat those as separate conversion tasks.",[35,586,587],{},"If they are important to you, split those tasks from each other, and track work to increase their rates individually.",[515,589,591],{"id":590},"focus-on-micro-conversions","Focus on micro conversions",[403,593,594,601],{},[35,595,596,597,600],{},"Instead of asking ",[473,598,599],{},"\"how can I increase the conversion rate of my site?\""," and wondering where to look first, break this down into smaller chunks.",[35,602,603,604],{},"Start with your most important pages & journeys, e.g. ",[473,605,606],{},"\"what percentage of searches result in a click to a product page? What can I change about our search results to improve that?\"",[16,608,609],{},"Increasing conversion rates has been one of our main goals and we have successfully helped our clients to improve the performance of their websites.",[16,611,612],{},"Get in touch with us and discover how we can help you increase conversions, retention rates, and performance of your marketing strategy.",[187,614,615],{"link":189,"button":190},"\n Our methodology has successfully revealed and corrected the data issue and supported the accuracy of the evaluation for multiple clients. Contact us for more information. We can ensure the accuracy of your A\u002FB testing too. \n",[16,617,618],{},[20,619,620],{},"Read more about our solutions:",[16,622,623],{},[624,625,629],"a",{"href":626,"rel":627},"https:\u002F\u002Fcrossmasters.com\u002Fen\u002Fproducts\u002Ftv-advertising-effectiveness\u002F",[628],"nofollow","Increase your TV Ad effectiveness",[16,631,632],{},[624,633,636],{"href":634,"rel":635},"https:\u002F\u002Fcrossmasters.com\u002Fen\u002Fwhat-we-do\u002Fmeasurement-and-optimization\u002F",[628],"Digital measurement optimization",[16,638,639],{},[624,640,643],{"href":641,"rel":642},"https:\u002F\u002Fcrossmasters.com\u002Fen\u002Fwhat-we-do\u002Fmarketing-performance-consultancy\u002F",[628],"Building and improving MAdTech Architecture",{"title":193,"searchDepth":194,"depth":194,"links":645},[646,647,648,649],{"id":375,"depth":194,"text":376},{"id":394,"depth":194,"text":395},{"id":434,"depth":194,"text":435},{"id":509,"depth":194,"text":510},"Guides","\u002Fupload\u002Fconversion-rate-article-cover.webp",{},"\u002Fen\u002Fblog\u002Fconversion-rate-explained","2020-06-25T12:00:00.000+00:00",6.83,"7 min read",[658,346,659],"content\u002Fen\u002Fblog\u002Fstarting-with-waaila.md","content\u002Fen\u002Fblog\u002Fcan-tv-become-a-performance-channel.md",{"title":353,"description":358},"en\u002Fblog\u002Fconversion-rate-explained","We've all seen the articles with the headline “Top 10 Converting Websites” that made us ask ourselves, “What can I do to get my site to those stratospheric levels?”","2DjFrwqQlszU9Q5llpu91w1tIy0zCCSwfg2HmxEwmGM",{"id":665,"title":666,"author":6,"body":667,"category":650,"description":193,"extension":203,"image":1633,"isToc":205,"langAlt":6,"meta":1634,"metaDescription":6,"navigation":207,"path":1639,"published":207,"publishedAt":1640,"readingTimeMinutes":1641,"readingTimeText":1642,"relatedArticles":1643,"seo":1645,"stem":1646,"teaser":1647,"updatedAtCustom":1648,"__hash__":1649},"blog_en\u002Fen\u002Fblog\u002Fhow-to-optimize-utm-for-uniform-campaign-typology.md","How to optimize UTM for uniform campaign typology & tagging",{"type":8,"value":668,"toc":1614},[669,673,676,683,686,691,695,698,701,704,718,722,725,747,752,759,768,775,786,797,801,815,818,822,828,842,846,850,857,874,880,883,888,916,921,941,945,952,957,979,984,1021,1025,1042,1046,1053,1057,1060,1091,1095,1115,1119,1125,1145,1149,1160,1165,1183,1189,1200,1204,1207,1227,1230,1233,1259,1263,1270,1282,1294,1298,1308,1315,1322,1325,1369,1374,1469,1473,1476,1483,1487,1490,1495,1498,1504,1514,1518,1530,1541,1544,1592,1600,1602,1608,1611],[11,670,672],{"id":671},"introduction","Introduction",[16,674,675],{},"Over years we spent countless hours optimizing online campaigns to make them truly effective. To be able to do so we required a much richer set of campaign parameters available for analyses. One solution how to pass such information for further processing is the traditional UTM parameters. In cooperation with major performance and media agencies and several PPC specialists, we were looking for data entities that could have an impact on performance. Now, our meta-model covers over 60 different entities with hundreds of dimensions. For basic performance tuning you do not need all of them, the maximum, we think is practical, covers roughly 40 dimensions. As there are only five UTM parameters we had to develop a technique to squeeze more information into what is available (Google Analytics 4 has only three parameters) to satisfy our needs. This guide is our approach to how to address the limitation and how to assure consistency and unification of campaign tagging.",[16,677,678,679,682],{},"There are two options how to address this problem, ",[20,680,681],{},"either you combine more parameters into each UTM parameter, or you generate a unique id"," for each dimension combination and keep its metadata in an external system. The external metadata repository is not a simple solution as it requires complex data integration and is thus not suitable for the majority of online spenders. This guide is developed for those using Google Analytics as their primary web analytics tool and other tools besides Google Ads (this can be natively linked to GA and you do not need UTM).",[16,684,685],{},"Combining more dimensions about the campaign in its name UTM parameter can provide you with insight into how targeting, message type, location, etc. impact your performance. You can use these dimensions to filter or compare results between campaigns. In practice, this means that you can easily compare campaign performance when targeting new versus existing customers. Differences between search and retargeting campaigns or when tagging is unified, so you can easily test and evaluate the performance of your channel mix.",[16,687,688],{},[270,689],{"alt":193,"src":690},"\u002Fupload\u002Fcampaign_tagging_utm.webp",[11,692,694],{"id":693},"how-can-the-typology-of-online-campaigns-help-you","How can the typology of online campaigns help you?",[16,696,697],{},"Tagged campaigns bear special information that can tell you, from where your visitors are coming to your site or which of your campaigns are delivering the best results. With web analytics tools like Google Analytics, you can use information from UTM parameters as dimensions to analyze such detail. If you want to identify how many visitors came to your site from a specific Facebook or Twitter post, you must include these UTM tags in these links as well.",[16,699,700],{},"By tagging individual campaigns, you can distinguish how many people came from specific posts or a specific banner. You can also specify UTM parameters within e-mailing campaigns, cost-per-click (CPC) campaigns, or on your blog. There are many options.",[16,702,703],{},"This article will help you unify the configuration of each campaign URL and parameter so that you can simply:",[403,705,706,712],{},[35,707,708,711],{},[20,709,710],{},"Universally filter data"," in Google Analytics according to various criteria and get maximum insight into the success of individual campaigns and traffic on your site.",[35,713,714,717],{},[20,715,716],{},"Link costs and revenues"," from individual campaigns. So, you will see not only how each campaign performed, but also how much money it brought, i.e. ROI.",[11,719,721],{"id":720},"lets-start-with-the-general-principles","Let's start with the general principles!",[16,723,724],{},"Consider these rules below as our recommendation, they are based on our experience and years of practice. If you stick to this guideline, it will minimize the number of errors while tagging campaigns, help you to be more effective in analyzing a large campaign portfolio, and will yield deeper insight. Simply it will allow you to make better decisions.",[57,726,727,728,734,735,740,741,746],{},"\nThe \"text\" written in { } brackets everywhere in this document indicates that it is a \"text\" that must be replaced with a \"specific expression\" when used in practical terms. For example, \n",[20,729,730],{},[731,732,733],"code",{},"p_ {product category}","\n refers to a campaign that will have its own name for each product category, which you add yourself based on the type of campaign being prepared, e.g. \n",[20,736,737],{},[731,738,739],{},"p_shoes","\n or \n",[20,742,743],{},[731,744,745],{},"p_glasses","\n.\n",[748,749,751],"h3",{"id":750},"use-delimiters-correctly","Use delimiters correctly",[515,753,755,756],{"id":754},"underscore-_","Underscore ",[731,757,758],{},"_",[16,760,761,764,765,48],{},[20,762,763],{},"Do not use spaces!"," If you have already used them, replace them with an underscore. For instance, rename the campaign called \"summer sale\" to",[731,766,767],{},"summer_sale",[515,769,771,772],{"id":770},"tilde","Tilde ",[731,773,774],{},"~",[16,776,777,778,781,782,785],{},"The wavy line is reserved as a ",[20,779,780],{},"component separator,"," from which the given UTM parameter is composed. Therefore, if you want to separate the campaign name from the report name in the UTM parameter, you can do so as follows: ",[731,783,784],{},"brand~scott",". It indicates the \"brand\" campaign and a group (adGroup, report) named \"scott\". Or, if you buy ads via an RTB platform, you can identify the RTB platform type through the source parameter.",[112,787,788,791,793,796],{},[20,789,790],{},"Example",[128,792],{},[731,794,795],{},"ihned.cz~adf","\n, where “ihned.cz” is the website on which the ad is displayed and ”adf” is the name of the platform (Adform).\n",[748,798,800],{"id":799},"use-lowercase-letters-without-accents","Use lowercase letters without accents",[16,802,803,804,807,808,811,812,48],{},"Google Analytics distinguishes between uppercase and lowercase letters. The campaign name ",[731,805,806],{},"summer sale"," is not the same as the ",[731,809,810],{},"Summer_sale",". Google Analytics evaluates such tags as two different campaigns. Therefore, we recommend ",[20,813,814],{},"using lowercase for campaign names",[16,816,817],{},"While it is possible to insert accented characters into UTM parameters, we do not recommend you to do so. In fact, when copying, importing, etc., the sign may be lost or misinterpreted if the encoding is set incorrectly.",[748,819,821],{"id":820},"unify-the-names-of-the-campaigns-and-values-sent-in-utm-parameters","Unify the names of the campaigns and values sent in UTM parameters",[16,823,824,825],{},"UTM parameters serve as the keys to connect Google Analytics and marketing or advertising platforms (Sklik, AdWords, etc.). If the platform can't export the configured UTM parameters (and this is often the case), or if the UTM parameters don't match the campaign name, then we can't link data from these platforms. Therefore, you ought to assign the same names to campaigns, adGroups, and other parameters that you also use in  UTM parameters. ",[20,826,827],{},"The same campaign should be named the same on different platforms.",[112,829,830,832,834,835,838,839,746],{},[20,831,790],{},[128,833],{},"\n\n\nIf the campaign management system (like Sklik) allows you to use auto-tagging via UTM parameters, then you can, for example, create \n",[731,836,837],{},"utm_campaign","\n as \n",[731,840,841],{},"{campaign}~{adgroup}",[11,843,845],{"id":844},"utm-parameters","UTM parameters",[748,847,849],{"id":848},"source-utm_source","Source (utm_source)",[16,851,852,853,856],{},"In the \"source\" parameter, we always insert the name of the website where the ad is displayed or the name of the company (platform) through which the ad space is served. In the \"source\" parameter, the word \"direct\" etc. can also appear as a reserved word in Google Analytics, so these reserved values should not be used in UTM parameters. Google Analytics automatically recognizes different sources of visits and if the source is not explicitly defined, it must be set. For example, when a visitor comes from an organic source, the source is assigned to the company that manages that search engine. In order to analyze the impact of a specific company on the traffic\u002Fprofit on your website, ",[20,854,855],{},"we recommend using the company name instead of the platform name"," when buying visits from multiple platforms (e.g. AdWords or Sklik), for example:",[403,858,859,865,871],{},[35,860,861,864],{},[20,862,863],{},"Google"," - the label for Google SERP (Search Engine Result Page), AdWords or merchant",[35,866,867,870],{},[20,868,869],{},"Seznam"," -the label for Seznam.cz, Zboží.cz or Sklik.cz",[35,872,873],{},"other",[16,875,876,877,48],{},"Often it is good to hide the source from which the customers came. The source is therefore identified by a code stored in an external table or added to the transformation filters in Google Analytics. Such a code is indicated by the prefix ",[731,878,879],{},"xd_",[16,881,882],{},"In case you use one or more platforms for ad distribution, it is necessary to distinguish through which tool the ad was purchased. In order to compare the performance of the platforms, the ad placement is created in the \"source\" as a combination of the platform name and the publisher's site name. The platform code should be then part of the \"source\" or alternatively inserted in the \"medium\".",[16,884,885],{},[20,886,887],{},"Platforms:",[403,889,890,893,896,899,902,905,908,911,914],{},[35,891,892],{},"adf (adform)",[35,894,895],{},"adb (adobe)",[35,897,898],{},"dtx (dataXu)",[35,900,901],{},"xnt (Xa.NET)",[35,903,904],{},"svp (silverpop)",[35,906,907],{},"unc (unica)",[35,909,910],{},"mch (Mail Chimp)",[35,912,913],{},"bee (PPC Bee)",[35,915,873],{},[16,917,918],{},[20,919,920],{},"Examples of use",[403,922,923,926,929,932,935,938],{},[35,924,925],{},"utm_source = google",[35,927,928],{},"utm_source = list",[35,930,931],{},"utm_source = heureka.cz",[35,933,934],{},"utm_source = xd_145eer47",[35,936,937],{},"utm_source = list~adf",[35,939,940],{},"utm_source = internal~svp (internal emails sent via Silverpop, if internal is too general and the purpose is, for example, to promote between internal websites, it can be replaced by the domain or company name from which the email addresses were obtained)",[748,942,944],{"id":943},"medium-utm_medium","Medium (utm_medium)",[16,946,947,948,951],{},"\"Medium\" refers to the medium or ",[20,949,950],{},"technology through which the visitor was brought to the site",". It also indicates the type of payment model used to pay for advertising. For example, when auto-tagging is turned on in AdWords, Google uses the CPC label but does not display any information about what medium was used. This information is passed between AdWords and Google Analytics internally. Some platforms use different codes for the same thing - CPM and CPT, for example. We, therefore, recommend that you standardize this terminology and use consistent codes. It is generally preferred to use the name of the medium for \"medium\" rather than the payment model type. This is because the medium has a higher information value for subsequent evaluation. For systems where there is no internal data aggregation, it will provide a wider range of information in return.",[16,953,954],{},[20,955,956],{},"Payment models",[403,958,959,962,965,968,971,974,977],{},[35,960,961],{},"CPC (cost per click)",[35,963,964],{},"CPM (cost per thousand)",[35,966,967],{},"CPT (cost per thousand)",[35,969,970],{},"CPV (cost per view)",[35,972,973],{},"CPA (cost per acquisition)",[35,975,976],{},"CPP (cost per point, price per affected population)",[35,978,873],{},[16,980,981],{},[20,982,983],{},"Medium",[403,985,986,989,992,995,998,1001,1004,1007,1010,1013,1016,1019],{},[35,987,988],{},"product",[35,990,991],{},"email",[35,993,994],{},"affiliate",[35,996,997],{},"display \u002F banner",[35,999,1000],{},"discount",[35,1002,1003],{},"social",[35,1005,1006],{},"offline",[35,1008,1009],{},"paid",[35,1011,1012],{},"post",[35,1014,1015],{},"job post (job advertisement)",[35,1017,1018],{},"fix (paid at a fixed price regardless of the number of impressions or clicks)",[35,1020,873],{},[16,1022,1023],{},[20,1024,920],{},[403,1026,1027,1030,1033,1036,1039],{},[35,1028,1029],{},"utm_medium = cpc",[35,1031,1032],{},"utm_medium = cpa",[35,1034,1035],{},"utm_medium = email",[35,1037,1038],{},"utm_medium = social",[35,1040,1041],{},"utm_medium = banner",[748,1043,1045],{"id":1044},"campaign-utm_campaign","Campaign (utm_campaign)",[16,1047,1048,1049,1052],{},"\"Campaign\" is a complex attribute that should contain ",[20,1050,1051],{},"information about how, to whom, when, where, and for what purpose the ad was displayed",". For example, the objective of a campaign may be to promote brand, product, or service. It is important that the name of the campaign in the marketing platform is the same as the name in the UTM parameter. We recommend creating the campaign name as a composite attribute that contains metadata about the campaign itself, which will allow it to be compared with similar campaigns. For example, a campaign displayed in a SERP has a different performance than a campaign displayed as a banner on a web page.",[515,1054,1056],{"id":1055},"display-type","Display type",[16,1058,1059],{},"Campaigns are classified by type and location:",[403,1061,1062,1068,1074,1079,1085],{},[35,1063,1064,1067],{},[20,1065,1066],{},"s"," (search) - The ad is displayed in response to data provided by a user (SERP on Google or List).",[35,1069,1070,1073],{},[20,1071,1072],{},"d"," (display, visual advertisement) - The advertisement is displayed in the form of a graphic or text element, the display is based on information collected about the user or about the website where the advertisement is displayed.",[35,1075,1076,1078],{},[20,1077,16],{}," (product, product search) - This is a combination of searches where a user enters a keyword and then displays a predominantly graphic element with an advertisement for a product or service.",[35,1080,1081,1084],{},[20,1082,1083],{},"m"," (message) - A form of a paid message sent mainly on social media, such as Facebook's \"promoted page post\" or LinkedIn \"sponsored updates\".",[35,1086,1087,1090],{},[20,1088,1089],{},"v"," (video) - A video ad shown on television programs or on YouTube that allows direct measuring.",[515,1092,1094],{"id":1093},"targeting-type","Targeting type",[403,1096,1097,1103,1109],{},[35,1098,1099,1102],{},[20,1100,1101],{},"r"," (remarketing \u002F retargeting, re-targeting) - re-targeting an already recognized visitor. This is the use of customer behavior information. For example, if a visitor abandons a cart, they are subsequently communicated via a display ad showing the content of their cart.",[35,1104,1105,1108],{},[20,1106,1107],{},"bhv"," - behavioral targeting based on user’s behavior across the internet, their intent, interests, etc.",[35,1110,1111,1114],{},[20,1112,1113],{},"src"," - search targeting based on user’s intent expressed by submitting specific keywords to search console.",[515,1116,1118],{"id":1117},"segment-type","Segment type",[16,1120,1121,1122],{},"It is necessary to distinguish whether the advertisement is intended to ",[20,1123,1124],{},"attract new visitors (acquisitions) or existing customers (retention).",[403,1126,1127,1133,1139],{},[35,1128,1129,1132],{},[20,1130,1131],{},"l"," (lead) - Acquisition advertising aimed to acquire new contacts",[35,1134,1135,1138],{},[20,1136,1137],{},"n"," (new) - Acquisition advertising aimed to acquire new customers",[35,1140,1141,1144],{},[20,1142,1143],{},"c"," (customer) - Retention advertising aimed to maximize customer value",[515,1146,1148],{"id":1147},"advertising-target","Advertising target",[16,1150,1151,1152,1155,1156,1159],{},"Advertising target ",[20,1153,1154],{},"specifies the subject of the advertisement that is being offered"," to the customer or ",[20,1157,1158],{},"indicates the customer's expected actions",". For a general advertisement for the sale of goods that targets by category, the category name will suffice; the higher level of detail can be specified at the report\u002Fadgroup level.",[112,1161,1162,1164],{},[20,1163,790],{},"\n\nIf an advertisement promotes hats, then you can use the word \"hats\" in the name.  It can also be a category, collection, brand, product, other, or a specific product name or a combination of the above.\n",[16,1166,1167,1168,1171,1172,1175,1176,1179,1180,48],{},"Another option is to state the objective of the ad describing the customer behavior you want to achieve. Examples include campaigns aimed at completing an order or repurchasing. In this case, the name of the campaign should contain the phase of the shopping cycle in which the customer is currently located or the goal that he should achieve, respectively. what he should do, such as ",[731,1169,1170],{},"order_completion",", ",[731,1173,1174],{},"order_delivery_type",", etc. Similarly, it can be an action a visitor should take, such as ",[731,1177,1178],{},"register_demo"," or ",[731,1181,1182],{},"download_study",[16,1184,1185,1188],{},[20,1186,1187],{},"You should always follow a terminology hierarchy"," - from left to right and from general to specific. However, the target of the ad can also be a group of search parameters that are included in a campaign.",[1190,1191,1192,1193,1196,1197],"tip",{},"\nIn a campaign to get the right keywords \n",[731,1194,1195],{},"s_broad","\n, campaign titles should always be in a single language. \n",[20,1198,1199],{},"We recommend using English names.",[515,1201,1203],{"id":1202},"brand-advertising","Brand advertising",[16,1205,1206],{},"There are several types of brand campaigns. It is either an advertisement of your own brand, product promotion, or takeover of the competition.",[403,1208,1209,1215,1221],{},[35,1210,1211,1214],{},[20,1212,1213],{},"brand or {brand}"," is an ad promoting your own brand",[35,1216,1217,1220],{},[20,1218,1219],{},"interbrand_ {competing brand name}"," is an advertisement that captures visits to a competing brand",[35,1222,1223,1226],{},[20,1224,1225],{},"intrabrand_ {product}"," is an ad for promoting products through the brand name of the product",[515,1228,1229],{"id":873},"Other",[16,1231,1232],{},"In \"Other\", provide further details of the campaign, such as:",[403,1234,1235,1241,1247,1253],{},[35,1236,1237,1240],{},[20,1238,1239],{},"type of motivator"," - eg \"sale\", \"promo\", \"bonus\",",[35,1242,1243,1246],{},[20,1244,1245],{},"ad launch time"," - such as emails that are sent daily or weekly.",[35,1248,1249,1252],{},[20,1250,1251],{},"campaign location"," - eg \"brno\", \"prague\", then e.g. \"branches\" or \"cz\"",[35,1254,1255,1258],{},[20,1256,1257],{},"targeting"," men or women, etc.",[515,1260,1262],{"id":1261},"reports-adgroup-advertisement","reports | adgroup | advertisement",[16,1264,1265,1266,1269],{},"Different platforms allow you to split campaigns into subgroups, reports, etc. A campaign is then a ",[20,1267,1268],{},"collection of different subsets",", for example, an AdGroup in AdWords. The parameter sent in the UTM should therefore include both the campaign name and the report name.",[112,1271,1272,1274,1276,1277,1279],{},[20,1273,790],{},[128,1275],{},"\n\n\nIf you have a campaign used for text search, it will be made of subgroups and its goal is to promote a brand, then the name of the campaign might look something like this for illustration:\n",[128,1278],{},[731,1280,1281],{},"s_interbrand~{encrypted code of competing company}",[112,1283,1284,1286,1288,1289,1291],{},[20,1285,790],{},[128,1287],{},"\n\n\nA campaign that targets incomplete orders through remarketing could be named like this:\n",[128,1290],{},[731,1292,1293],{},"dr_order_complete",[515,1295,1297],{"id":1296},"date","Date",[16,1299,1300,1301,1304,1305,48],{},"For recurring campaigns, ",[20,1302,1303],{},"we recommend adding the date the campaign was activated to the name of the campaign."," In an email campaign with the name \"Newsletter\", it is difficult to distinguish when specific emails were sent out. So for recurring email campaigns, we advise using the date as an additional parameter. In basic form, it is sufficient to have the code in YYMMDD format, but for better evaluation directly in Google Analytics, it is more efficient to extend the date code. Then you will be able to directly evaluate cyclical segments, for example, to compare the performance of a specific day. For ",[20,1306,1307],{},"campaigns sent weekly, we recommend using a code containing the week number",[112,1309,1310,1312,1314],{},[20,1311,790],{},[128,1313],{},"\n\n\nCampaigns coded code 21w46tu and 21w46we are sent in the 46th week (ISO week is used) on Tuesday, and Wednesday.\n",[112,1316,1317,1319,1321],{},[20,1318,790],{},[128,1320],{},"\n\n\nMonthly campaigns are assigned a code. For example, the 21m09w2tu campaign is a campaign submitted in September, the second week, and on Tuesday.\n",[16,1323,1324],{},"Codes to indicate the days of the week",[403,1326,1327,1333,1339,1345,1351,1357,1363],{},[35,1328,1329,1332],{},[20,1330,1331],{},"mo"," (Monday)",[35,1334,1335,1338],{},[20,1336,1337],{},"tu"," (Tuesday)",[35,1340,1341,1344],{},[20,1342,1343],{},"we"," (Wednesday)",[35,1346,1347,1350],{},[20,1348,1349],{},"th"," (Thursday)",[35,1352,1353,1356],{},[20,1354,1355],{},"fr"," (Friday)",[35,1358,1359,1362],{},[20,1360,1361],{},"sa"," (Saturday)",[35,1364,1365,1368],{},[20,1366,1367],{},"su"," (Sunday)",[16,1370,1371],{},[20,1372,1373],{},"Values for the campaign name",[1375,1376,1377],"figure",{},[1378,1379,1380,1403],"table",{},[1381,1382,1383],"thead",{},[1384,1385,1386,1392,1397],"tr",{},[1349,1387,1388,1389,1388],{},"  ",[20,1390,1391],{},"Attribute name",[1349,1393,1388,1394,1388],{},[20,1395,1396],{},"Allowed values",[1349,1398,1388,1399,1402],{},[20,1400,1401],{},"Parameter","   ",[1404,1405,1406,1416,1425,1434,1443,1451,1461],"tbody",{},[1384,1407,1408,1411,1414],{},[1409,1410,1056],"td",{},[1409,1412,1413],{},"s,d,p,m,v",[1409,1415,837],{},[1384,1417,1418,1420,1423],{},[1409,1419,1094],{},[1409,1421,1422],{},"r,src,bhv",[1409,1424,837],{},[1384,1426,1427,1429,1432],{},[1409,1428,1118],{},[1409,1430,1431],{},"n,l,c",[1409,1433,837],{},[1384,1435,1436,1438,1441],{},[1409,1437,1148],{},[1409,1439,1440],{},"See above for different values",[1409,1442,837],{},[1384,1444,1445,1447,1449],{},[1409,1446,1229],{},[1409,1448,1440],{},[1409,1450,837],{},[1384,1452,1453,1456,1459],{},[1409,1454,1455],{},"Separator",[1409,1457,1458],{},"\\~",[1409,1460,837],{},[1384,1462,1463,1465,1467],{},[1409,1464,1297],{},[1409,1466,1440],{},[1409,1468,837],{},[748,1470,1472],{"id":1471},"content-utm_content","Content (utm_content)",[16,1474,1475],{},"\"Content\" contains variations of sizes and texts in advertisements, types of banners used, etc. This parameter is useful for testing content.",[1477,1478,1482],"external-link",{"title":1479,"link":1480,"button":1481},"Waaila homepage","https:\u002F\u002Fwaaila.com","Go to Waaila","\nCheck your parameters with Waaila and validate your UTM tagging.\n",[748,1484,1486],{"id":1485},"term-utm_term","Term (utm_term)",[16,1488,1489],{},"\"Term\" contains the keyword that was used for the search. The name of the website where the ad was displayed can be inserted in this parameter as well. You can also add the category of content that the visitor was browsing before clicking on the ad. For some types of campaigns, such as paid search, it is added automatically.",[16,1491,1492],{},[20,1493,1494],{},"Data transformation",[16,1496,1497],{},"A number of businesses use various distribution points or kiosks. A website visit from such a kiosk should therefore be recorded as a special campaign or medium. Such detection is done the best via a special Google Analytics setting.",[16,1499,1500,1501,48],{},"A similar case are paid ads, where for some reason the use of the UTM parameters is not appropriate. For example, it could spoil the site's reputation or arouse suspicion among visitors. So if it is not appropriate to use UTM parameters, then the data transformation is done for example from ",[731,1502,1503],{},"document.referrer",[112,1505,1506,1508,1510,1513],{},[20,1507,790],{},[128,1509],{},[731,1511,1512],{},"_bulbs.heureka.cz_","\n is transformed by inserting “bulbs” into the campaign name and to referrer path a custom variable is inserted.\n",[748,1515,1517],{"id":1516},"id-utm_id","Id (utm_id)",[16,1519,1520,1521,1527,1528,48],{},"Some companies are developing complex campaign tagging logic causing high complexity in values of utm parameters. A lot of information covered in URLs can be confusing for users and it may contain sensitive data about the marketing strategy of the company. Also, a number of utm parameters might not be sufficient and more campaign dimensions are needed for proper analysis. ",[20,1522,1523,1524],{},"The complexity of sending all utm parameters can be avoided by using parameter ",[731,1525,1526],{},"utm_id",". It is an Id assigned to a specific campaign performed. In URL only this Id is sent, all additional parameters are stored separately in a table where you can store both standard and custom campaign dimensions. You can import this mapping table to Google Analytics and assign all the dimensions to specific ",[731,1529,1526],{},[112,1531,1532,1534,1536,1537,1540],{},[20,1533,790],{},[128,1535],{},"\n\n\nYou perform emailing campaign on discounted bulbs with a link to a specific product on your website. When assigning tags, instead of all utm parameters, you add \n",[731,1538,1539],{},"utm_id=123xyz","\n to URL of the link.\n",[16,1542,1543],{},"Then a table with mapping of your campaign dimensions needs to be created in the following structure:",[1375,1545,1546],{},[1378,1547,1548,1549,1548,1571,1548],{}," ",[1381,1550,1548,1551],{},[1384,1552,1553,1556,1559,1562,1565,1568],{},[1349,1554,1555],{},"ga:campaignCode  ",[1349,1557,1558],{},"ga:source  ",[1349,1560,1561],{},"ga:medium  ",[1349,1563,1564],{},"ga:campaign  ",[1349,1566,1567],{},"ga:content  ",[1349,1569,1570],{},"ga:dimension11",[1404,1572,1573],{},[1384,1574,1575,1578,1580,1583,1586,1589],{},[1409,1576,1577],{},"123xyz",[1409,1579,991],{},[1409,1581,1582],{},"newsletter",[1409,1584,1585],{},"m\\~bulb\\~disc",[1409,1587,1588],{},"bulbs",[1409,1590,1591],{},"competitor_name",[16,1593,1594,1595,48],{},"To import the data in Google Analytics, you can either import it as .csv file or use management API. Detailed information about the campaign data import can be found ",[624,1596,1599],{"href":1597,"rel":1598},"https:\u002F\u002Fsupport.google.com\u002Fanalytics\u002Fanswer\u002F4522476?hl=en",[628],"here",[11,1601,178],{"id":177},[16,1603,1604,1605,48],{},"Congratulations, you read the article to the end! We believe that the information has been beneficial to you and helped you orient yourself in the wild waters of the campaign naming typology. The most important thing to remember is: ",[20,1606,1607],{},"stay consistent and aligned with marketing strategy",[16,1609,1610],{},"Thanks to mutual discussion and feedback, we can inspire each other and be one step further. Share with us your observation, knowledge, tips, and original solutions from your experience.",[187,1612,1613],{"link":189,"button":190},"\nIf you do not fully understand something listed here or would like to s discuss specific issues, contact us. We can answer your questions and help you with your campaign tagging.\n",{"title":193,"searchDepth":194,"depth":194,"links":1615},[1616,1617,1618,1624,1632],{"id":671,"depth":194,"text":672},{"id":693,"depth":194,"text":694},{"id":720,"depth":194,"text":721,"children":1619},[1620,1622,1623],{"id":750,"depth":1621,"text":751},3,{"id":799,"depth":1621,"text":800},{"id":820,"depth":1621,"text":821},{"id":844,"depth":194,"text":845,"children":1625},[1626,1627,1628,1629,1630,1631],{"id":848,"depth":1621,"text":849},{"id":943,"depth":1621,"text":944},{"id":1044,"depth":1621,"text":1045},{"id":1471,"depth":1621,"text":1472},{"id":1485,"depth":1621,"text":1486},{"id":1516,"depth":1621,"text":1517},{"id":177,"depth":194,"text":178},"\u002Fupload\u002Futm-parameters-illustration.webp",{"externalLinks":1635},[1636],{"url":1637,"name":1638},"https:\u002F\u002Fcrossmasters.com\u002Fen\u002Fproducts\u002Fmeasurement-hub","Measurement Hub","\u002Fen\u002Fblog\u002Fhow-to-optimize-utm-for-uniform-campaign-typology","2012-10-14T09:38:00.000+00:00",16.5,"17 min read",[345,1644],"content\u002Fen\u002Fblog\u002Fnew-data-api-for-google-analytics-4.md",{"title":666,"description":193},"en\u002Fblog\u002Fhow-to-optimize-utm-for-uniform-campaign-typology","Advance online campaign management with UTM parameters, structure unification, and enrichment for more detailed performance evaluation.","2021-05-23T10:00:00.000+00:00","_IXRpSI1KvvsQqvbLoNJQ96SB05Q8MNokWoDAJkBXgQ",1789131822696]