Apr 24, 2023 1209 reads

Universal Analytics Attribution Models

Attribution models are essential tools in digital marketing for understanding the impact of marketing activities, optimizing budgets, developing strategies, gaining customer insights, measuring performance, evaluating different channels’ contributions, and making data-driven decisions.By choosing the right attribution model, you can make your marketing efforts more efficient and effective, thereby increasing the success of your marketing strategy.To select the appropriate attribution model, you need to understand the models available in Universal Analytics and Google Analytics 4.What Is Attribution Modeling?Attribution modeling is a method used in digital marketing and advertising to assess the contribution of various marketing channels during a customer’s conversion journey. It determines which channels were most effective before a user completes a purchase or conversion.In digital marketing, multiple channels—organic search, paid search, social media, email marketing, referral traffic, content marketing, and interactive ads—often contribute in sequence to a single conversion. Attribution models evaluate these complex interactions to reveal each channel’s weight in driving that conversion.In short, attribution models provide valuable insights for budget allocation, strategy optimization, channel performance analysis, conversion path tracking, and understanding customer behavior.Why Are Attribution Models Important in Digital Marketing?When used correctly, attribution models offer marketers critical analytical insights into the effectiveness and return on investment of their campaigns. This empowers them to understand performance, optimize budgets, refine strategies, gain customer insights, measure ROI, evaluate channels, and make informed decisions.Common Attribution ModelsGoogle Analytics provides several built-in attribution models: Last Interaction (Last Click) Last Non-Direct Click Last Google Ads Click First Interaction (First Click) Linear Time Decay Position-Based Last Interaction (Last Click)The Last Interaction model attributes 100% of the conversion value to the final click or interaction before conversion, ignoring all earlier interactions. It assumes the last touchpoint is the most important, but it can overlook the influence of previous channels in the customer journey.Last Non-Direct ClickThis model gives full credit to the last click or interaction that was not “direct” traffic, and it ignores any direct visits. It’s useful for understanding the impact of non-direct channels, but like Last Interaction, it disregards earlier touches.Last Google Ads ClickThe Last Google Ads Click model assigns all conversion credit to the last Google Ads click. It’s ideal for measuring paid search performance but ignores contributions from other channels.First Interaction (First Click)First Interaction attributes all conversion value to the very first click or interaction in the customer journey. It highlights awareness channels but overlooks any later touches that may have influenced the final conversion.LinearThe Linear model distributes credit equally across every touchpoint in the conversion path. It provides a balanced view but may mask the true impact of especially crucial interactions.Time DecayTime Decay gives more credit to interactions closer in time to the conversion. Early touches get less weight, emphasizing the last steps in the journey.Position-BasedThe Position-Based model assigns 40% of the credit to both the first and last interactions, and the remaining 20% is evenly split among the middle interactions. This highlights both awareness and conversion touchpoints but gives less weight to in-between channels.Which Attribution Model Does Universal Analytics Use by Default?By default, Universal Analytics uses the Last Interaction (Last Click) attribution model. That means every conversion is attributed to the last channel the user clicked before converting, and all other channels are ignored.In our next article, we’ll examine Google Analytics 4 and its attribution model options.

Apr 16, 2023 6108 reads

What is Google Tag Manager? How to set up GTM?

"When someone asks 'What is Google Tag Manager?', our article aims to answer this more easily by also covering how to add GTM codes in panels like WordPress, Ticimax, and T-Soft, and we hope it will be useful for you.What Is Google Tag Manager (GTM)?Google Tag Manager is an online tool used to add analytics, marketing, and other code snippets to websites. Often abbreviated as "GTM," it makes it easier for digital marketers and web developers to add and manage code on their sites without directly editing the source code.Instead of traditional code edits, Google Tag Manager provides a user-friendly interface for adding code snippets. This approach reduces the need for developer intervention and offers a flexible way to manage quick code changes—making GTM a major advantage in any toolkit.GTM can manage Google Analytics, Google Ads, Meta Pixel, Hotjar, Microsoft Clarity, and many other marketing tags. These tags collect user behavior, conversions, and other analytics data. GTM allows you to easily add, edit, remove, and manage tags, making site management more efficient.It can also handle A/B tests, targeting, personalization, and other marketing efforts, giving site owners and marketers the flexibility and control to optimize their sites effectively.In short, Google Tag Manager is a tool that simplifies and centralizes tag management for analytics and marketing, streamlining website management processes.Why Is Google Tag Manager Important and What Are Its Benefits?GTM offers many benefits to site owners and analysts: Easy Code Management: Simplifies adding and updating code snippets via a user-friendly interface, reducing reliance on developers. Fast Tag Management: Quickly add, edit, remove, or manage analytics and marketing tags such as Google Analytics, Google Ads, Facebook Pixel, Hotjar, speeding up campaign launches and optimizations. Flexibility & Control: Specify which pages, events, or user segments trigger each tag, enabling personalized strategies and optimized user experiences. Rapid Testing & Optimization: Supports A/B testing, targeting, and personalization, allowing marketers to test variations and continuously improve site performance. Data Accuracy & Reliability: Ensures tags fire correctly, reduces configuration errors, and increases data reliability for better decision-making. Quick Updates: Update tags without changing site code, keeping your site current and secure. Team Collaboration: Multiple users can work in the same container, with version history and change tracking to support collaborative workflows. How to Install Google Tag Manager (GTM)?Follow these steps to set up GTM:Step 1: Create a GTM Account Go to https://tagmanager.google.com and sign in. Click “Create New Account.” Enter the account name, country, and time zone. Accept the terms and click “Create.” Log in to your new GTM account. Step 2: Create a Container Within your GTM account, create a container (the workspace for tags, triggers, and variables). Name it and choose the target platform (Web, iOS, Android). Click “Create.” Step 3: Add Container Code to Your Site After creating the container, copy the code provided from “Install Google Tag Manager.” Paste the code immediately above the opening tag on every page of your site. Save changes and publish your site. Step 4: Add Tags, Triggers, and Variables Return to your GTM container. Use the “Tags” tab to add tags, “Triggers” for firing rules, and “Variables” for dynamic values. Click “New,” choose the tag type, configure settings, and publish. Step 5: Publish Your Setup After adding tags, triggers, and variables, save changes and click “Submit” to publish. How to Install GTM in Ticimax?To add GTM code in Ticimax:Step 1: Log in to Ticimax Go to https://panel.ticimax.com/ and log in. Step 2: Site Management In the panel, go to “Site Management” and select your site or create one. Step 3: Settings Click “Settings,” then go to “General Settings” > “Digital Marketing.” Step 4: Add the GTM Code Paste the container code into the “Google Tag Manager (GTM) Code” field. Click “Update.” Step 5: Verify on Your Site Visit any page, view the source (right-click > “View Page Source”), and confirm the GTM code is present. How to Install GTM on WordPress?In your WordPress admin panel: Go to “Appearance” > “Theme Editor.” Select header.php, locate the opening tag, and paste the GTM code immediately after it. Save changes and verify on your site. How to Install GTM in T-Soft?In your T-Soft panel: Log in and navigate to “Settings” > “Main Settings” > “Tracking Codes.” Click “+ New,” paste the GTM code, and save. What Are the Components of GTM?Key GTM components include:TagCode snippets that perform specific functions, such as Google Analytics tracking code, Meta Pixel, or AdWords conversion tracking.TriggerConditions that determine when tags fire, such as page views, form submissions, or button clicks.VariableDynamic values used by tags and triggers, such as page URL, page title, or form field values.How to Preview in GTM?After setting up an event in GTM, always use Preview mode to verify correct implementation.

Apr 16, 2023 3288 reads

What are cookies? What do they do?

Cookies are small data files collected via users’ browsers on websites. These files are used to track and analyze how users interact with a site. That’s why cookies are so important in the analytics world: they help measure site performance, understand user behavior, and improve the site.Here, we’ve compiled everything you need to know and all the frequently asked questions about cookies.What Are Cookies?Cookies are small text files that a web browser stores on a user’s device.These files allow websites to track users’ preferences and behavior, deliver personalized content and services, ensure proper functionality, enhance security, and identify areas for improvement through performance analysis.For example, a site can store a user’s login credentials in a cookie so that when the user returns, they are automatically signed in. You may know that Google announced in January 2020 that Chrome and its other products would phase out third-party cookies. That date was ultimately pushed to mid-2024 because Privacy Sandbox is still in testing.Privacy Sandbox is Google’s privacy-focused ad initiative for Android that replaces third-party cookies. To predict how a cookieless digital marketing world will look, we first need to understand what cookies are and their types.What Are First-Party Cookies? First-party cookies are small data files set under the site’s own domain when a user visits. They are created via the browser and used on later visits. They measure site performance, manage user sessions, remember preferences, and help improve the site. For example, they can recall a visitor’s language choice or site theme for faster access. Because first-party cookies are limited to a single domain, they help protect privacy and provide a more secure browsing experience. What Are Third-Party Cookies? Third-party cookies are set by a different domain than the one the user is visiting, delivered by an external server and stored in the browser. They are used for advertising and marketing. For example, an ad network uses third-party cookies to determine user interests and serve relevant ads across sites. They can threaten user privacy, so browsers offer blocking options, and regulations like GDPR and CCPA restrict their use. Site owners may limit or disable third-party cookies to protect privacy rights. Why Cookies MatterThird-party cookies play a crucial role in digital advertising. Advertisers rely on them to define target audiences and build accurate consumer profiles during campaign planning. User Experience: Cookies track preferences and behavior to deliver personalized content and services. For example, remembering cart items or language settings enhances the experience. Marketing Strategies: Cookies enable marketers to analyze behavior, segment users, create targeted campaigns, and optimize strategies with personalized offers. Site Performance: Cookies help monitor which pages are most visited, what content is most effective, and which devices are used, guiding performance improvements. Conversion Tracking: Cookies verify conversions—such as purchases or form submissions—and measure campaign effectiveness. The data collected is often used in retargeting and display advertising campaigns, underscoring cookies’ importance. Third-party cookies track user behavior over time by storing data on their device. This enables personalized ads for previously viewed or interacted-with products or services. Especially in display advertising, personalized ads often outperform traditional ones, highlighting cookies’ direct impact on ad performance, analysis, and measurement. Cookie TypesCookies come in various types and serve different purposes. Common ones include: Session Cookies: Temporary cookies created during a session and deleted when the browser closes. Persistent Cookies: Remain on the device for a set period to recognize returning visitors and preserve preferences. Third-Party Cookies: Set by external domains—ad networks, analytics providers, social platforms—to track across multiple sites. Performance Cookies: Used to monitor site speed, detect errors, and track user interactions to enhance user experience. Targeting/Advertising Cookies: Deliver ads tailored to user interests and measure ad performance. Life Without Third-Party CookiesAd platforms that lose third-party data will turn to server-to-server connections or CRM integrations. But these methods can’t fully restore the current data flow or ad efficiency. Many efforts today focus on prolonging third-party cookies rather than innovating CRM-based measurement solutions.Brands will see decreased ROI from new and existing users and higher CPAs. Even if CPA remains stable, engagement metrics (bounce rate, pages per session, etc.) will likely decline. For example, Meta’s targeting algorithms won’t work without third-party cookies.On the web, analytics via Google or Adobe will also suffer data loss, leading to flawed performance metrics and misaligned attribution modeling in ad platforms.Alternative ChannelsAs third-party cookies diminish, alternative data channels grow more important. For example, login and signup data plus site search history can power targeted ads and recommendations.Email addresses can fuel email marketing, and social media profiles can support personalized advertising and suggestions.What Can We Do with Cookies?Think of cookies as a browser-stored data repository. We can capture every user action on the site, store searches and clicks in cookies for defined periods, and use that data as input for analysis. The possibilities are limited only by our imagination. First-party cookies let us create a rich dataset directly from user interactions, giving us true first-party data.Google Analytics & CookiesCookies are the cornerstone of Google Analytics’ data collection. By deploying GTM and Analytics tags, we can track every user action on the site and report on it.

Apr 16, 2023 13116 reads

What is Adjust and what is it used for?

"Adjust" is the name of a company operating in mobile app marketing analytics and ad efficiency. Adjust provides mobile app developers and marketers with an analytics and tracking tool to monitor user behavior, analyze data, and optimize ad campaigns.Using mobile app analytics and ad optimization, you can: Track data: Monitor mobile app user behavior and provide detailed data on user interactions. This includes in-app events, session durations, conversion rates, and other metrics. Analyze data: Analyze collected data to uncover trends and patterns in user behavior. Use these insights to evaluate app performance, optimize user experience, and improve marketing strategies. Optimize ad campaigns: Leverage user behavior data to improve campaign performance. Analyze and optimize ads to boost conversions, reduce costs, and manage budgets effectively. User segmentation: Adjust segments users based on behavior, preferences, or demographics. Segmentation helps you understand your audience and tailor marketing strategies accordingly. Real-time analytics: Adjust can monitor and analyze data in real time, enabling rapid assessment of user behavior, ad adjustments, and dynamic strategy updates for analysts. Adjust enables analysts to take user behavior–driven actions for mobile app marketing and optimization, improving marketing strategies and user experience.Key Areas to Check First in the Adjust Dashboard Within the relevant brand account, verify all settings under All Settings. In All Settings → Platforms, if tracking both iOS and Android, enable Multi-platform App. Then confirm iOS App ID and Bundle ID, and Android App ID and Scheme. Ensure iOS 14+ Settings is active; if not, coordinate with your Adjust representative. Integrate the app’s event structure into the dashboard and create event tokens. Under Partner Setup, configure integrations with third-party tools and verify tracking across both platforms. For each third-party integration in Partner Setup, add the correct link ID and App ID for iOS and Android. Ensure Event Linking and Partner Parameter Mapping are filled out accurately. Since some events take longer to appear in statistics, performance teams may see discrepancies. View reports via the Automate section. Data Discrepancies Between Adjust and Other PlatformsData inconsistencies between web analytics and other platforms can arise for several reasons: Data sources: Different platforms collect from different sources (e.g., mobile SDK vs. web tags), reflecting varying aspects of user behavior. Data processing: Each tool uses unique algorithms, filters, and processing steps, causing variations in results. Data accuracy: Collection and validation methods differ; third-party sources or user-provided data may introduce uncertainty. Platform settings: User-configured settings—time zones, lookback windows, filters—can lead to mismatches. Data integration: Complex integrations from multiple sources can create inconsistencies based on how each tool merges data. Common discrepancy scenarios include: Downloads vs. Installs User- vs. device-based installs Time zones and geolocation App updates Third-party store installs Event comparisons Downloads & Installs: “Download” is when a user downloads the app from a store, while “Install” is when they open it first. Adjust only tracks installs via its SDK, whereas stores track downloads and installs. Apps downloaded but never opened cause discrepancies, as Adjust won’t register those.User vs. Device Installs: Stores count installs per account; Adjust counts per Advertising ID. A user installing on two devices will count as two installs in Adjust but one in the store.Time Zones & Location: Adjust uses the device’s IP at install time, while stores use the account’s store region. An app installed in Germany on a UK store account shows as Germany in Adjust, UK in the store. Adjust uses UTC; other platforms use local zones (e.g., Google Ads uses PST).App Updates: If the SDK was added after launch, existing users become “new” in Adjust when they update. Stores see those as updates, not new installs, leading to discrepancies.Third-Party Store Installs: Installs from non–App Store/Play Store sources are tracked by Adjust but not by Apple/Google, especially impacting Android metrics.Event Comparisons: Attribution windows differ. Google Ads uses a 30-day default click window; Adjust uses 7 days by default, so data shouldn’t be compared directly. Facebook uses a 28-day click window; Adjust’s 7-day last-click window omits the extra weeks, so avoid direct comparisons. Adjust attributes events indefinitely to the original install source.Bonus:What Is “Adjust Leverage”?“Adjust leverage” refers to the advantages Adjust’s analytics platform offers for ad optimization—better budget allocation, deeper user insights, and improved campaign performance. For more details, see Binance’s article here.

Mar 30, 2023 5551 reads

Importance of Customer Segmentation

In today's market, where the products are diverse, it should be said that our people are also diverse. Just as we separate and classify products according to their categories and other features, classifying customers according to their features has become a method that we use quite a lot in today's marketing sector. We call this process customer segmentation, in which we classify customers according to their demographic, geographic, psychographic, and behavioral characteristics and determine their marketing strategies specifically for these classes. So why do we need customer segmentation? What benefits does it give us? What are the segmentation types and which segmentation type should be used for which analysis? Let's answer many questions such as understanding the importance of using segmentation together.What is Customer Segmentation?Customer segmentation is the practice of dividing a customer dataset into groups of similar individuals by age, gender, interests, and spending habits. Companies also try to understand what each segment finds most valuable to use their marketing materials more accurately according to that segment and develop marketing strategies accordingly.Every company has billions or trillions of data. However, when the data is transformed into meaningful information with the help of statistical analysis, it is possible to take action. Recognizing the customer and knowing their needs of a business is a very important factor for more effective marketing. For this reason, data science plays a very important role in analyzing billions and even trillions of customer data and drawing meaningful results. Customer segmentation is also a method used to understand who buys and will buy the services or products of the business from these billions of flowing data.  Types of User Segmentation Geographic customer segmentation: Geography consumer segmentation separates audiences according to where they are located (country, state, city, or town). This segmentation technique is beneficial for local SEO and market expansion. Demographic customer segmentation: Grouping audiences based on attributes like age, gender, marital status, education level, and income is known as demographic customer segmentation. Given those variances in these parameters are potent predictors of purchasing patterns, this is one of the most useful segmentation kinds. Psychographic customer segmentation: Psychographic consumer segmentation focuses on traits like personality, attitude, hobbies, and values rather than more fundamental characteristics like age or gender. The psychological characteristics that influence users' purchasing behaviors are thoroughly examined in psychographic segmentation. Behavioral customer segmentation: When segmenting customers based on their behaviors, factors including product usage, inclinations, and shopping preferences (such as in-store or online) are taken into account. Benefits of User SegmentationBy creating different customer segments, the ideal product for these segments can be easily selected and the distribution channels suitable for the business can be easily determined. Having a successful customer segmentation strategy allows the business to develop a deeper understanding of customers and develop marketing strategies for them.Based on characteristics such as age, location, purchasing habits, and interests, it becomes easier to direct efforts to the most profitable customers, thus determining direct marketing strategies to attract the right audience.How to Implement User SegmentationOne of the most difficult aspects of customer segmentation is choosing which data from a large set will constitute the most useful segments. Therefore, a strategic roadmap is needed for successful customer segmentation. Determination of the market:This procedure will assist you in learning how to differentiate yourself from the competition and whether your items have the necessary qualities to satisfy consumer demand. Selection of segmentation type:Choose the segmentation strategy that best serves the objectives of your firm. You must gather consumer data, segment stakeholders, and align on criteria to validate prospective segments to do this. Understanding customers' needs and preferences:Asking the correct questions can help you thoroughly understand the interests, likes, and wants of your consumers so you can successfully cater to them. Identifying the ideal customer segment for your business: To ensure that your customer segmentation efforts are successful, you need to think of a simple group that includes the majority of your customers and allows you to identify their needs and confirm your acceptance of your products. Checking the efficiency of the segmentation: This step involves testing your established market segmentation strategies with the right customers to identify items that need to be adjusted. Define target segments: Select the groups with the highest priority that are likely to bring maximum profit to the company. Developing the product positioning strategy:Positioning is the marketing process that allows to define the competitive advantageous position of the company in the market. It helps to discover direct and indirect competitors. It allows a consumer to find answers to the following questions; - Who is this product for? - Which customer's needs can the product meet? - How does your company's product differ from competitors' products? - Why is it profitable for a consumer to buy your product? - When should a customer use your product? Creating a marketing plan for each target segment: For each section, create a step-by-step strategy that will enable you to complete your company duties. The strategy must be realistic and account for probable difficulties. Real-Life Implementations of the TechniqueTargeting people based on factors like marital status, length of relationships, family size, and child age ranges is another excellent approach to segmenting your audience. Our purchasing habits depend on where we are in life. Parents buy things for their kids. Baby boomers who are caring for their aging parents make several purchases. You can retarget customers with related or complementary products based on past purchasing information. Launch successful cross-selling and upselling campaigns to engage customers using this data. For instance, if you sell phone accessories, you could target different segments of your audience with offers based on the types of phones they use. If your product isn't used differently depending on the type of device, look at your data to see if there are any trends in how people shop using various devices.Moreover, you can use it to target potential clients who share your interests in the luxury lifestyle and have demonstrated a propensity for making large-ticket purchases in the last 30, 60, or 90 days. These settings and target segments can be set depending on the platform you're using.ResultYou must accurately characterize your clients' demands and worries to address those needs and eventually win their contentment. The influence it may have on all aspects of your business, including sales, marketing, product development, customer service, etc., is significant if you manage the best customer segmentation strategy now in use. Your company will have a clearer understanding of the market and a better focus on the customer, enabling it to expand more predictably and effectively. References https://www.euromsgexpress.com/musteri-veri-segmentasyonu-nedir/?psafe_param=1&gclid=CjwKCAiAu5agBhBzEiwAdiR5tPFa3xg05HuyEqbckfrr1EcVp9sWw5MPNhxGUZ0EIcm5enHaczaYJRoCKZMQAvD_BwE https://porsline.com/blog/tr/musteri-segmentasyonu-neden-ve-nasil-yapmaliyiz/ https://business.adobe.com/blog/basics/real-world-examples-of-customer-segmentation https://www.tani.com.tr/blog/musteri-analitiginin-sihirli-kavrami-musteri-segmentasyonu https://www.ticimax.com/blog/musteri-segmentasyonu-ile-hedef-kitlenizi-nasil-tanirsiniz https://netuce.com/musteri-segmentasyonu-nedir-nasil-yapilir/ https://sendpulse.com/tr/knowledge-base/email-service/general/how-segment-customers https://www.mayple.com/blog/customer-segmentation-examples#:~:text=If%20you%20sell%20phone%20accessories,trends%20based%20on%20different%20devices. https://openviewpartners.com/blog/customer-segmentation/

Mar 27, 2023 1428 reads

The 5 Most Common Reporting Errors in GA4

Released in beta in October 2020, GA4 became mandatory for all non-360 accounts as of July 2023. From that point on, accounts with GA4 integration must manage their entire reporting workflow through GA4.Although GA4’s interface is more user-friendly than Universal Analytics, many reporting errors still occur. In this article, we cover the five most common GA4 reporting mistakes and how to fix them. Missing Data Sometimes you’ll see no data at all in GA4. This usually happens because the tracking code is installed incorrectly or blocked in the user’s browser. To fix it: In GA4, go to Property → Data Streams → Web and copy the Measurement ID of your stream. Install that ID either by hard-coding it into your page source or by adding a “GA4 Configuration” tag in GTM. Data Duplication Often this is caused by having the GA4 snippet both hard-coded and deployed via GTM. Use only one method—either install directly in your HTML or via GTM, but not both. Misinterpreting Data – UA vs. GA4 Comparison Universal Analytics (UA) and GA4 use different data models (UA: session/last-click; GA4: event/last-engagement) and serve different use cases. Comparing their reports side by side leads to confusion. Instead: Learn what each metric and dimension means in its own context. Choose the tool that best fits your needs rather than forcing a direct comparison. For more details, see: Differences Between UA and GA4 Attribution Model Differences Last Non-Direct Click: Ignores direct traffic and credits the last non-direct source. Last Click: Includes all sources and credits the very last click. Invalid Data Filters Filters that are too strict or misconfigured can exclude valid data. Check your filters under Admin → Data Settings → Data Filters and ensure you only filter out truly unwanted traffic. Overwhelmed Analysis Interface When you have thousands of events and parameters, GA4’s UI can become unwieldy. For large datasets, enable the GA4–BigQuery link and perform your complex queries in BigQuery for more reliable, scalable analysis.