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.

Mar 26, 2023 734 reads

Website Design from an Analytics Perspective

A website’s UX compatibility and healthy analytics measurement require the site design and technical infrastructure to be structured according to the following points: The GTM (Google Tag Manager) snippet must load before the dataLayer. This ensures that the data needed for analytics and tracking is collected and recorded correctly. If the GTM snippet loads after the dataLayer, it can lead to missing or inaccurate data. Therefore, loading GTM before the dataLayer is essential. Technically, the page structure should not be a single-page application. Single-page sites often cause problems for Analytics measurement and GTM setups. Single-Page; i.e., one-page websites that present all content on a single page. Users scroll or search within that single page to find the content they need. Why Your Site Shouldn’t Be Single-Page Content Density: If a site has a lot of content, cramming it all onto one page makes searching and scanning harder. Splitting content across multiple pages helps users find what they need more easily. SEO Improvements: A multi-page structure allows unique meta tags, titles, and descriptions per page, making it easier for search engines to crawl and index each page. Load Time: Too much content on one page slows down loading. Multiple pages reduce load time and improve user experience. Management Ease: Managing and updating content is simpler when it’s organized across several pages rather than all on one. Content Focus: Multi-page sites let you optimize each page for a single topic or purpose, making messaging clearer and helping users find relevant content. Of course, every site has different needs, and some cases may suit a single-page design. But generally, multi-page sites organize content better, enhance UX, and are more SEO-friendly. Follow Jakob’s Law in your site design to give users a familiar, efficient experience. Instead of reinventing the wheel, integrate standard interaction patterns and refine your design accordingly. When positioning elements, remember user attention decreases from header to footer. Critical conversion-driving components should be placed where they will get the most visibility. The menu should reflect a clear category hierarchy and serve users efficiently, in line with UX best practices. A site’s category hierarchy organizes content and guides users to find what they need. It shows relationships between topics and improves navigation. For example, an e-commerce store uses nested product categories, while a news site groups articles by topic and subtopic.Category hierarchies also help site search engines surface relevant results within a selected category, making content discovery easier. Add a breadcrumb trail made of subcategories so both users and search engines can understand and navigate the site structure. Breadcrumb is a navigation element that shows a page’s position within the site. It typically appears near the top of the page as a series of links like “Home > Section > Subsection”. Pages should load ideally in under 2.5 seconds. Page speed is critical for Analytics and CRO, so optimize technically for fast performance. Use the brand colors and typography defined in the brand book consistently across all elements. Keep URLs as short and meaningful as possible. Append paths that follow the category hierarchy. On an e-commerce site, structure the funnel so users start their conversion path as quickly as possible, offering a straightforward, fast, practical experience. Optimize images: product image files should be under 100 KB to maintain speed. Banner sizes may vary. Also ensure filenames and alt text match the image and page content for better crawling. Downloadable links (e.g., PDFs) should not open in a new page. Serve them directly so tracking treats them as downloads. Avoid “ghost search” in-site search implementations. They hinder tracking and analysis of search terms. Ghost Search automatically shows results before a user types in the search box. While meant to help discovery, it can surface irrelevant results and hurt performance. It’s better to implement a simple, user-friendly search that returns accurate results without extra resource usage. Minimize click depth: users should reach content in as few clicks as possible (ideally 2–3). Deep hierarchies hurt UX; design to keep navigation shallow. On an e-commerce site, prevent “dead clicks” by prompting users when they miss an action (e.g., “Add to cart” or login). This reduces drop-off and improves conversion rate. Banner images linking to listing pages should include clickable links so users can initiate the conversion journey directly. On product pages, add a related-products slider (“You might also like”) to increase engagement and conversion.

Mar 21, 2023 1348 reads

2023 Trends in the Digital World

The digital world continues to grow and evolve with advancing technology. In order to keep up with innovations driven by leading tech companies like Google, Meta, and Apple, brands and websites must follow the latest trends of 2023 and integrate them into their own practices. In this article, we’ll share the key digital trends for 2023 so you can improve your measurement, stay on trend, and remain competitive in digital marketing.What Awaits Us in 2023?In 2023, the data and analytics driving digital marketing will shift toward a more human-centered approach, with artificial intelligence and machine learning playing an increasingly prominent role. As emphasis on data security grows, analytics professionals will take on ever more critical responsibilities. The practical trends we expect in 2023 are: More Human-Centered Digital Marketing: Delivering personalized, human-centric experiences will be essential. Marketers will leverage customer behavior, interests, and purchase data to craft highly targeted campaigns. Rise of AI & ML Applications: Artificial intelligence and machine learning will become more widespread, enabling deeper data analysis, more accurate predictions, and faster decision-making. AI will help marketers create more effective campaigns by understanding individual interests and purchase behavior. Greater Emphasis on Data Security: With rising data breaches and cyberattacks, companies will invest more in protecting customer data. Privacy regulations like GDPR will guide best practices. Advanced Data Visualization: Comprehensive visualization tools (e.g., Tableau, Looker Studio) will become even more important for rapid, insightful decision-making. IoT Marketing: The Internet of Things will drive new customer insights via device-to-device data collection, allowing marketers to tailor products and services more precisely. The technical and theoretical digital trends for 2023 include: Meta – Conversions API (CAPI) Google – Server-Side Tagging Google – BigQuery ChatGPT UX Laws & Neuroscience Techniques Meta – Conversions API (CAPI)Conversions API is designed by Meta to create a direct connection between marketing data and ad optimization, reducing cost-per-action and improving measurement across Meta technologies. To send website events via CAPI, you set up and configure a server on Google Cloud Platform (GCP), then forward GA4 web tag data to that server and onward to Meta via CAPI.With Conversions API: Brands lower their cost-per-action. Campaigns become easier to optimize. User data is sent directly from your server to Facebook’s, bypassing cookies and preserving privacy post-iOS 14. Ad performance measurement becomes more reliable. CAPI data is less prone to errors than pixel-based tracking. Google – Server-Side TaggingServer-Side Tagging moves measurement tags from the client (browser) to a server you control (e.g., on GCP). This approach offers several advantages over client-side tagging: Fewer tags on your site/app, improving frontend performance. Better data protection by processing user data in a customer-managed server environment. Simplifies manual CAPI integrations via GTM. Google – BigQueryBigQuery, launched in 2012 on Google’s Dremel technology, is an enterprise data warehouse for fast SQL analytics at scale. With GA4 becoming mandatory in July 2023, brands need BigQuery to store data long-term, visualize accurately, and perform deep analyses.Why BigQuery? Secure, long-term data storage and advanced brand-specific analyses are crucial in 2023. GA4’s default data retention is only two months (extendable to 14). BigQuery removes time limits entirely. It captures every custom event and parameter in one table without row limits. Columnar storage and a tree architecture enable lightning-fast queries on massive datasets. Combines online/offline data for advanced analytics (CLV, clustering, association analysis, etc.) and supports built-in ML. Supports cross-platform measurement by joining data from various tools and CRM systems via user ID. Deep analytics in BigQuery lets you—for example—exclude offline purchases from online campaign audiences, boosting conversion rates.ChatGPTUndoubtedly the most talked-about AI of 2023 is ChatGPT. This conversational AI, powered by GPT-3.5, generates real-time, human-like responses—even writing code. Its ability to understand and answer virtually any question places it firmly among the year’s top trends.UX Laws & NeuroscienceNeuroscience studies the nervous system. By integrating physiology, anatomy, maths, developmental biology, and psychology, it explains learning, memory, behavior, perception, and consciousness. UX laws and neuroscience techniques apply these principles to web design to create more intuitive, brain-friendly user experiences. Every user interacting with your design follows certain psychological principles. For 2023, brands will use neuroscience to inform UX analyses and optimize site design for human cognition.For more on UX laws and neuroscience, see UX Laws & Neuro Science. If you haven’t implemented these integrations yet in Q1 2023, act quickly—don’t miss the trend.