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  • 100% rental in record time through intelligent advertising

    Do you want to get in touch with us, learn more about Emerse Labs or programmatic marketing? Contact us through the form here or Johan Bertilsson by phone +46 739 337 732. Background UniverCity is a residential developer focusing on rental properties in Sweden's strongest growth region, Stockholm-Uppsala. The purpose of UniverCity's marketing was to attract interest applications for their newly built rental properties in Upplands Väsby. Therefore, through simple means and creativity, they aimed to find the right tenants and create awareness around their project in Upplands Väsby. Challenge UniverCity wanted to receive quality interest applications from individuals who could move in immediately. After all, the apartments were ready for occupancy. Who are these people, where do we find them, and how do we capture their attention? People living nearby and considering separation or divorce are likely interested in quick move-ins. Individuals living in other parts of Sweden who have obtained jobs in Stockholm were also a potential target audience. The task was to find the right message tailored to the right target group, which the hired renting team at Fastiella could then manage. Being visible on social media is a given, but here we also wanted to make an extra effort to step outside the "pond" and create and strengthen interest among the target group in a different way. UniverCity was open to testing new creative ideas to see what works best. Given our previous very positive experience with automated material tests, known as A/B/N tests, through programmatic marketing, we decided to add this to the strategy. Social Media + Programmatic Advertising + Chat GPT = TRUE Social Media - The focus on UniverCity's social media was to drive traffic to, which is the external page where more information about the apartments can be found, and where one can fill in their contact details. Chat GPT - We didn't know in advance which message would yield the best results. Therefore, we wanted to test different messages to determine what works best, i.e., generate traffic and conversions. We used Chat GPT to generate variations of texts. We chose 10 suggestions to test in EMERSE LABS, a platform for testing different variations of ads, known as A/B/N tests. There, we could quickly see exactly which variation yielded which result. After that, it was easy to optimize towards the best messages. Programmatic advertising - For the programmatic advertising, we used a method known as contextual targeting to reach the target audience. This strategy ensures that ads appear in an editorial environment containing "keywords" that we have specified and that are relevant to the ad. In this case, we specified words such as divorce, separation, moving out, moving in, cohabitation law, among others. In addition to contextual advertising, we also used relevant site lists like Boli, Hemnet, and Blocket Bostad. Results During the advertising period (April – June), UniverCity received a steady stream of applicants with a very high match rate on the criteria set for being approved as a tenant. A total of 106 new lease agreements were signed, and 100% of the project is now rented out. "Through the advertising and the smart solutions, we reached our goal. It has been a creative and educational collaboration. Moreover, we have gained inspiration for how we can work with upcoming projects to get them rented out more quickly. The fact that we had fun and laughed a lot along the way is a plus that has increased our job satisfaction!" says Christina Sundman, CEO of UniverCity. "It has been very gratifying to have a flow of good prospects that we could work with continuously," adds Eva Andersson Ericson, CEO of Fastiella. "This has facilitated our work and contributed to us being able to fill the property in record time with happy and expectant tenants." Eva Andersson Ericson, CEO at Fastiella Summary Achieving a good reach and creating awareness are often associated with expensive purchases via TV or radio. Programmatic advertising is also a powerful reach medium but at a significantly lower price. However, programmatic advertising is a complex and unfamiliar territory for many, and adding an A/B/N testing platform to optimize the ad content can seem overwhelming. Therefore, it's crucial to work with a partner who does more than just set up ads and let them run their course. Knowledge, optimization, and detailed, in-depth work are required to get value for the investment. On the other hand, social media is an obvious choice for many, a channel that is strong further down in the sales funnel, both in driving traffic and conversions. Combining programmatic advertising to create reach with social media for traffic and conversions is a strategy that UniverCity used and found effective. A winning concept, in simple terms. It should be noted that UniverCity's openness to actually daring and wanting to test new methods is a key factor in our ability to deliver the results we did. About UniverCity UniverCity is a residential developer focusing on rental properties in Sweden's strongest growth region, Stockholm-Uppsala. Their philosophy is to center human needs and offer homes that meet the expectations of conscious individuals about living as an important part of their lifestyle. Emphasizing ecological and social sustainability, with plenty of green spaces and opportunities for socializing, they create a living environment where people feel comfortable and thrive. Link to the project in Upplands Väsby, Sweden About Fastiella Fastiella is a privately-owned consultancy firm specializing in property management, particularly focused on the revenue side. Fastiella is determined that the foundation of effective management consists of three parameters: a stable platform, knowledgeable individuals, and well-functioning processes. More information about Fastiella here: About Emerse Emerse has been in the industry since 2007 and was one of the very first to start writing their own code to create a programmatic tool, a DSP. This gives Emerse a deep understanding of algorithms, machine learning, AI, and how to meticulously handle programmatic advertising for the best results. With this knowledge, they manage all digital tools in a senior and unique manner. Emerse is part of the international committee W3C, a global organization that sets standards and guidelines for the web. They are also members of IAB (the global organization for online marketing). If you want to get in touch with us, learn more about Emerse Labs or programmatic marketing, contact us through the form here or Johan Bertilsson by phone +46 739 337 732.

  • Reinforcement Learning for Real Time Bidding

    Master’s thesis carried out at Emerse Sverige AB for the Department of Computer Science, Lund University. Author: Erik Smith Supervisors: Pierre Nugues, Department of Computer Science, Faculty of Engineering, Lund University Elin Anna Topp, Department of Computer Science, Faculty of Engineering, Lund University Carl-Johan Grund, Emerse Sverige AB Rasmus Larsson, Emerse Sverige AB Link: Link to full-text PDF: Reinforcement Learning for Real Time Bidding Today, the most common software-based approach to trading advertising slots is real time bidding: as soon as the user begins to load the web page, an auction for the slot is held in real time, and the highest bidder gets to display their advertisement of choice. But each bidder has a limited budget, and strives to spend it in a manner that maximizes the value of the advertisement slots bought. In this thesis, we formalize this problem by modelling the bidding process as a Markov decision process. To find the optimal auction bid, two different solution methods are proposed: value iteration and actor–critic policy gradients. The effectiveness of the value iteration Markov decision process approach (versus other common baselines methods) is demonstrated on real-world auction data.

  • Optimal Real Time Bidding in Online Advertising

    Master’s thesis carried out at Emerse Sverige AB for the Department of Automatic Control, Lund University. Author: David Rådberg Supervisors: Karl-Erik Årzén, Department of Automatic Control, Lund University. Martina Maggio, Department of Automatic Control, Lund University. Anders Rantzer, Department of Automatic Control, Lund University. Carl-Johan Grund, Emerse Sverige AB Rasmus Larsson, Emerse Sverige AB Link: Full-text PDF: Optimal Real Time Bidding in Online Advertising This thesis explores some of the possibilities of demand side optimization in online advertising, specifically how to evaluate and bid optimally in real time bidding. Theory for many types of optimizations is discussed. The thesis evaluates auctions from a game theory and control theory perspective. It also discusses how big data sets can be used in real time, and how agents can explore unknown stochastic environments. All items are valued through an estimated action probability, and a control system is designed to minimize the cost for these actions. The control system aims to find the lowest possible price per item while spending the entire budget. Periodic market changes and censored data makes this task hard and imposes low pass characteristics on the closed system. Using data to evaluate items is a high dimensional problem with very small probabilities. When data is limited the algorithm is forced to choose between low variance and precision. The choice between exploring and exploiting the unknown environment is crucial for long and short term results. An optimization algorithm was implemented and run in a live environment. The algorithm was able to control the spend optimally, but distributed it suboptimally.

  • Managing Programmatic Advertising Using Machine Learning

    Master’s thesis carried out at Emerse Sverige AB for the Department of Computer Science, Lund University. Authors: Carl Dahl, Pontus Ericsson. Supervisors: Pierre Nugues, Department of Computer Science, Faculty of Engineering, Lund University Jacek Malec, Department of Computer Science, Faculty of Engineering, Lund University Carl-Johan Grund, Emerse Sverige AB Rasmus Larsson, Emerse Sverige AB Link: Link to PDF: Managing Programmatic Advertising Using Machine Learning Articles in this series are theoretical and involves a substantial part of mathematics and computer science. This thesis is an exploratory study into the possibility of using machine learning to manage advertisement campaigns and agents involved in real-time bidding. The norm for the industry of real time bidding is currently having human operators managing campaigns by changing settings to maximize the number of clicks. The goal was to investigate the possibility of automating this process, to at the very least assist the human operators with making better decisions. The first part of the project was to build a model for predicting the clickthrough rate (CTR) of the ad campaigns. The second part was to use the model to suggests optimal settings for bidding agents. The outcome was a model with an accuracy of 92% in predicting whether an ad was to generate any clicks or not, and with an accuracy of 58% to predict the outcome of an agent in the different categories “few clicks”, “some clicks” and “many clicks”.

  • How does programmatic advertising work - The Details

    The Detailed Mechanics of Programmatic Advertising Programmatic advertising has emerged as a game-changer, reshaping how brands connect with audiences. But what exactly is it, and how does it function? For the curious reader, this article delves deep into the mechanics of programmatic advertising. Definition of Programmatic Advertising Programmatic advertising automates the decision-making process of buying and placing ads by targeting specific audiences and demographics. In essence, it's the algorithm-driven purchase and sale of advertising space in real-time. It eliminates the traditional manual methods, introducing precision, efficiency, and scale to the advertising process. The Intricate Process of Programmatic Advertising Programmatic advertising is propelled by technology platforms, the most integral being the Demand Side Platform (DSP) and the Supply Side Platform (SSP). Here's a breakdown of these platforms and their roles: Demand Side Platform (DSP): A system that advertisers use to automate the purchasing of digital media across various inventories. Through the DSP, advertisers can set their targeting preferences, budget, bid for ad impressions, and monitor campaign performance. Supply Side Platform (SSP): This platform allows digital media owners (publishers) to manage, price, and sell their ad space. An SSP assesses the value of incoming impressions, invites bids from potential buyers (via DSPs), and chooses the highest bid. The real magic unfolds when a user visits a web page. Here's a step-by-step process of what happens: User Visits a Website: The moment a user accesses a webpage with an ad space, the publisher sends a "bid request" to the SSP. This request contains information about the user, including their browsing history, location, and more. Auction Process: The SSP evaluates this data and sends the bid request to the ad exchange. The ad exchange then invites advertisers to bid for that ad impression. Advertisers Place Bids: Advertisers, through their DSPs, evaluate the user's data and decide if this user is valuable to them. If they're deemed valuable, the DSP places a bid on behalf of the advertiser. Selecting the Winner: The highest bidder wins the auction. The ad exchange then notifies the SSP, which in turn tells the publisher's platform to display the winning ad. Ad Delivery: The user's browser fetches the ad and displays it. This entire process, from the user visiting the site to the display of the ad, takes mere milliseconds. A Detailed Breakdown of an RTB Auction Many companies building technology for programmatic advertising follow the OpenRTB specification. Here's an overview of a typical RTB auction. 1. User Accesses a Web Page When a user navigates to a webpage that has spaces allocated for programmatic ads (like banner ads or video ads), this action triggers the start of an RTB auction. 2. Bid Request Initiated The publisher's ad server, often through a Supply-Side Platform (SSP), sends out a bid request to an ad exchange. This bid request contains a bundle of information about the user without revealing their personal identity. This can include: User Data: Browser type, device (mobile/desktop/tablet), operating system, IP address (often anonymized), and possibly historical data about the user's past browsing behaviors. Page Context: URL of the site, content category, page keywords, and other relevant metadata. Ad Details: Ad sizes/types available, ad formats, and placement positions. 3. Advertisers Evaluate the Bid Request Once the ad exchange receives the bid request, it broadcasts this request to multiple potential advertisers (or their representatives, which are Demand-Side Platforms or DSPs). These DSPs evaluate the bid request based on: Targeting Criteria: Advertisers have predefined criteria (like targeting users from a certain location or using a specific device) they look for. If the user's profile matches this criteria, they proceed with the bidding. Retargeting Lists: If the user had previously interacted with the advertiser's content (like visiting their website without making a purchase), they might be on a retargeting list, making them more valuable to the advertiser. Bid Algorithms: Advanced algorithms determine the bid amount based on the perceived value of the impression to the advertiser. 4. Bidding Interested advertisers submit their bids through the DSPs. This bid includes the amount they're willing to pay for the impression and the specific ad creative they want to display if they win the auction. 5. Selecting the Winning Bid The ad exchange reviews all the submitted bids and identifies the highest bidder. Some auctions may use a second-price auction model, where the winner pays $0.01 more than the second-highest bid, ensuring they pay the fair market value. Some auctions use a first-price auction where you pay what you bid if you win. 6. Ad Delivery Once the winning bid is determined, the ad exchange instructs the publisher's site (or the SSP) to display the winning advertiser's ad to the user. 7. User Sees the Ad The user's browser fetches the winning ad creative and displays it within the ad space on the webpage. The user can then interact with the ad, and the advertiser can record any relevant metrics, like clicks or conversions. 8. Post-Auction Analysis Advertisers often analyze the results of their bids to refine their strategies. They might look at metrics like click-through rates, conversions, or viewability to determine the success of their bids. The Fuel: Data in Programmatic Advertising Programmatic advertising's prowess lies in data. Various sources, from websites, apps, social networks, to even offline sources, feed data into programmatic platforms. This rich data allows for: Audience Segmentation: Advertisers can identify micro-segments within broader categories. Instead of targeting "males aged 25-30", they can target "males aged 25-30 who are vegan, enjoy hiking, and recently searched for eco-friendly products." Retargeting: Users who have interacted with a brand but didn't convert can be retargeted. This increases the chances of conversion as the user is already familiar with the brand. Types of Programmatic Purchases Real-Time Bidding (RTB): This involves buying and selling ads in real-time auctions, much like stock trading. Advertisers bid for impressions based on the value of the user, and the highest bid wins. Programmatic Direct: This is a more traditional approach where advertisers directly purchase guaranteed ad impressions from publishers. The price and volume are pre-determined. Private Marketplaces (PMPs): These are exclusive RTB auctions where premium publishers invite select advertisers to bid on their inventory. It offers more control and transparency to both parties. PMPs can also be bought through using a DSP. Advantages of Programmatic Advertising Efficiency: Automation streamlines the ad buying process, eliminating the need for manual negotiations. Precision: Advanced algorithms and rich data allow for hyper-targeted ad placements. Flexibility: Advertisers can adjust campaigns in real-time based on performance data. Scale: Access to a vast array of publishers means advertisers can expand their reach easily. Challenges in Programmatic Advertising Transparency: "Black box" operations of some platforms mean advertisers don't always know where their ads appear. Ad Fraud: Automated systems can sometimes display ads to bots, leading to wasted ad spend. Privacy Concerns: With data as the driving force, there's an ongoing debate about user privacy and data misuse. Conclusion Programmatic advertising has transformed the digital advertising sphere with its efficiency, scalability, and precision. By leveraging technology and data, it has allowed brands to engage with their target audience like never before. However, as with any technological advancement, it's essential to navigate the ecosystem with knowledge and awareness, ensuring that user trust and privacy are upheld, even as advertisers work to craft compelling, personalized ad experiences. If you want to get started with programmatic advertising, you can either setup an account now in the Emerse DSP using this link. Or contact us to learn more and schedule a meeting.

  • Programmatic Recruitment Advertising

    Programmatic Recruitment Advertising: A Modern Approach to Hiring In the age of digital transformation, nearly every industry is witnessing the integration of technology for optimization, efficiency, and innovation. The recruitment sector is no exception. Programmatic recruitment advertising has emerged as a game-changer, utilizing technology to automate the process of buying, placing, and optimizing job ads. Let's delve deeper into understanding this approach and how organizations can harness its potential. What is Programmatic Recruitment Advertising? At its core, programmatic recruitment advertising is about automating the distribution of job advertisements across various platforms. By using data analytics, algorithms, and real-time bidding, it ensures job ads reach the most suitable candidates at optimal times and places, maximizing visibility and engagement while minimizing costs. The Process Job Ad Creation: Before launching a campaign, recruiters must craft compelling job descriptions. With the right content, tailored to the target audience, the subsequent steps in the programmatic approach become even more effective. Defining the Audience: With data analytics, recruiters can set detailed parameters on who should see the ad—be it based on skills, location, browsing habits, or any other metrics. This ensures the ad is shown only to those who are the best fit. Real-time Bidding (RTB): Unlike traditional methods where job ads are bought for a set price on specific platforms, RTB allows for real-time auctions. The advertisement is dynamically bid on using a Demand Side Platform such as the Emerse DSP, ensuring it's placed where it will gain the most traction among potential candidates. Optimized Ad Distribution: The ad is then strategically displayed across various platforms—be it job boards, social media, or niche websites—depending on where the target audience is most active. Continuous Analysis and Adjustment: One of the biggest advantages of programmatic advertising is its dynamic nature. As the campaign runs, algorithms monitor its performance. Based on real-time data, adjustments are made—whether it's changing the platforms, tweaking the audience parameters, or adjusting the bid—to ensure maximum efficacy. Advantages of Programmatic Recruitment Advertising Cost-Effective: By targeting ads more accurately and relying on RTB, organizations can reduce wasteful spending. You're not paying for ads that reach the wrong audience. Wider Reach: With the ability to distribute across multiple platforms simultaneously, programmatic recruitment offers a wider reach. Moreover, it can tap into passive candidates—those not actively looking but might be interested if the right opportunity presents itself. Efficiency: Automated processes mean reduced manual intervention. The time taken from creating a job ad to it being viewed by potential candidates is drastically shortened. Data-Driven Decisions: Relying on data analytics means decisions aren't based on hunches. Recruiters get a clear picture of what's working and what's not, allowing for more informed strategies. Challenges and Considerations However, like any other method, programmatic recruitment isn't without challenges. There's a learning curve involved. Organizations need expertise, whether in-house or outsourced, to understand the intricacies. Moreover, while automation aids efficiency, the human touch in recruitment shouldn't be entirely discounted. Lastly, data privacy concerns, especially with increasing regulations, need to be meticulously managed. Conclusion Programmatic recruitment advertising is reshaping the hiring landscape. By blending automation with data analytics, it promises a smarter, more efficient, and cost-effective way to connect employers with potential employees. As the digital landscape evolves, it's an avenue organizations cannot afford to overlook if they wish to stay competitive in their hiring strategies. If you are interested in learning more about using programmatic advertising for recruitment, don't hesitate to contact us. If you want to create an account in the Emerse DSP and start running programmatic ads today, you can do so today using this link.

  • Programmatic Advertising Examples

    Five outstanding examples of programmatic advertising campaigns Programmatic advertising has redefined the landscape of digital marketing, offering unprecedented opportunities for precision targeting. While programmatic encompasses a wide range of formats, banner ads remain one of the most widely used. The combination of programmatic buying with visually engaging banners can lead to powerful campaigns. Let's explore five memorable programmatic advertising example banner campaigns: Coca-Cola's "Share a Coke" Campaign: Coca-Cola's iconic "Share a Coke" campaign took personalization to a new level. Originally a traditional marketing campaign, Coca-Cola used programmatic buying to push personalized banner ads to users. Based on user data, these banners would display names or personalized messages encouraging users to find and purchase a Coke bottle with that name. The dynamic nature of these programmatic banners significantly increased user engagement, making it a digital counterpart to its real-world success. Cadbury's "Match & Win" Campaign: Cadbury leveraged programmatic banners to promote its "Match & Win" competition. Users would see banners with a unique code prompting them to buy a Cadbury product, enter the code online, and win prizes. What made the campaign special was its dynamic targeting. Using data, the banners were displayed to users more likely to participate, such as past competition entrants or those who had shown interest in similar promotions. Nike's Weather Sync Campaign: Nike decided to showcase its weather-appropriate gear using real-time weather data. Through programmatic banners, if a user was experiencing rainy conditions, they'd be shown Nike's latest waterproof running gear. Conversely, on hotter days, Nike would promote its breathable sportswear. The synchronization with real-time conditions made the ads timely, relevant, and highly effective. Lexus' Dynamic Retargeting Banners: Lexus utilized programmatic technology to retarget users who had shown interest in specific car models on their website. Depending on which model the user had shown interest in, they would see a customized banner ad showcasing that particular model, its features, and any ongoing promotions or discounts. This precise targeting made users feel that the ad was tailored for them, increasing the chances of them returning to the website and progressing further down the sales funnel. Burberry's Personalized Fragrance Ads: To promote its range of fragrances, Burberry used programmatic banners to target users based on their browsing behavior and previous purchases. If a user had previously shown interest in men's products, they'd see a banner promoting Burberry's latest men's fragrance. Similarly, those browsing female-centric products would see banners for women's fragrances. By ensuring that the ads were closely aligned with user interests, Burberry increased the resonance of its messaging. In conclusion, these programmatic advertising examples show how data, creativity, and technology can come together to deliver impactful messaging. As programmatic advertising continues to evolve, we can expect even more innovative and personalized campaigns that resonate deeply with audiences. Start running programmatic advertising in the Emerse DSP today by signing up for an account. No minimum deposit and you can launch your first campaigns quickly.

  • Programmatic Buying Platforms

    In the digital age, advertisements have evolved beyond mere static images and texts on web pages. They’ve transformed into a dynamic, personalized experience, directly tailored to individual user preferences. The force behind this revolution? Programmatic buying platforms. But what are they, and why are they so crucial in the contemporary advertising ecosystem? What Are Programmatic Buying Platforms? Programmatic buying platforms, at their core, automate the purchase, placement, and optimization of digital advertising, as opposed to the traditional method of human negotiations. They leverage data insights and technology to acquire specific audience segments at optimal price points in real-time. In essence, it’s the "stock exchange" of the digital advertising world. These platforms fall under two main categories: Demand-Side Platforms (DSPs): DSPs such as the Emerse DSP allow advertisers and agencies to buy digital ad inventory across multiple sources, from websites to apps. They optimize based on specific targeting criteria such as demographics, geography, interests, and browsing behavior. Supply-Side Platforms (SSPs): SSPs are utilized by online publishers to sell their ad space to advertisers. They ensure the publishers get the highest possible prices for their ads through real-time bidding processes. How Do They Work? Imagine a user visiting a website. The moment this site loads, it sends a signal to an ad exchange that this particular user is available for an ad impression. The ad exchange assesses the ad impression's data (URL, demographic information, interests) and matches it with an advertiser's criteria. If it's a match, an auction between competing advertisers begins, and the highest bidder gets their ad displayed to the user. All of this happens in milliseconds, ensuring the user experience remains smooth and uninterrupted. Benefits of Programmatic Buying Platforms: Efficiency: Automation means quicker transactions and optimized pricing. Advertisers can reach their desired audience more effectively, and publishers can sell their inventory faster. Precision: By using data-driven insights, advertisers can target ads to specific user segments, ensuring the content is relevant and more likely to lead to user engagement. Real-time Analysis: Programmatic platforms offer real-time data analytics. Advertisers can see how their ads are performing and make immediate adjustments if necessary. Scale: Programmatic buying platforms connect advertisers to a vast network of publishers. This means more opportunities to display ads to the right audience, across various platforms and devices. Challenges and Concerns: While programmatic platforms have revolutionized digital advertising, they are not without challenges. The complexity of the ecosystem can lead to issues like: Transparency: With so many intermediaries involved, it can sometimes be unclear where an advertiser's money is going and how much of it is spent on actual ad placements versus platform fees. Ad Fraud: Automated systems can sometimes be exploited by malicious actors to generate false clicks or impressions, costing advertisers money with no real engagement. Privacy Concerns: Collecting user data for targeted advertising has raised privacy concerns. New regulations like the General Data Protection Regulation (GDPR) in Europe have been instituted to protect user data. Platforms such as the Emerse DSP are members of the IAB TCF Framework which works to ensure the privacy choices of consumers are handled correctly in digital marketing. Conclusion: Programmatic buying platforms have fundamentally altered the digital advertising landscape. They've made ad placements more efficient, targeted, and data-driven. As with all technological advances, they come with challenges. But with continuous innovation and appropriate regulations, they promise a future where advertisements are not just seen as interruptions, but as relevant, timely content that provides value to both the advertiser and the end user. Setup an account in the Emerse DSP today to get started with your programmatic buying or contact our team to schedule a demo and talk more.

  • How does Header Bidding work?

    Header bidding is an advanced programmatic advertising technique that allows publishers to offer their ad inventory to multiple demand partners (advertisers) simultaneously before making ad requests to their ad server, such as Google's DoubleClick for Publishers (DFP). This process increases competition for ad space, leading to higher revenue for publishers and more efficient ad placements for advertisers. Here's a step-by-step explanation of how header bidding works: Setup: The publisher installs a header bidding wrapper, which is a piece of JavaScript code, on their website or app. This wrapper is responsible for managing the header bidding process and communicates with different demand partners or ad exchanges. Ad inventory: The publisher defines the ad inventory (ad units and ad placements) they want to offer for header bidding. Bid request: When a user visits the publisher's website or app, the header bidding wrapper sends bid requests to multiple demand partners, along with information about the ad inventory and user (such as device type, location, and browsing behavior). Bid response: Demand partners review the bid requests and decide if they want to bid on the ad inventory. If they do, they return a bid response, which includes the bid price and the creative (the actual ad content). Auction: The header bidding wrapper collects all bid responses and conducts an auction to determine the highest bidder for each ad unit. Ad server request: After the auction, the header bidding wrapper sends the winning bids to the publisher's ad server. The ad server compares the winning bids from the header bidding process with other demand sources, like direct deals and ad networks, to determine the final winning bid for each ad unit. Ad rendering: The ad server returns the creative for the final winning bid to the publisher's website or app. The ad is then displayed to the user. By allowing multiple demand partners to compete for ad inventory, header bidding helps publishers maximize their ad revenue and ensures advertisers have access to premium ad placements, often resulting in more relevant and engaging ads for users.

  • What is Prebid?

    Prebid is an open-source set of solutions designed to streamline and optimize the process of header bidding in digital advertising. Header bidding is an advanced programmatic advertising technique that allows publishers to offer their ad inventory to multiple ad exchanges simultaneously before making a call to their ad server. This competition among ad exchanges typically results in higher CPMs (cost per thousand impressions) and increased ad revenue for publishers. Prebid offers a suite of tools, including a JavaScript library for implementing client-side header bidding, server-side header bidding solutions, and additional tools for analytics and reporting. Prebid.js is the most widely used component of Prebid, as it allows publishers to easily integrate multiple demand partners (e.g., ad exchanges and networks) into their websites or apps. The main benefits of using Prebid include: Increased ad revenue: By fostering competition among multiple demand sources, Prebid helps publishers maximize their ad revenue. Improved transparency: Prebid provides publishers with greater insight into how their ad inventory is being valued and sold across different demand partners. Enhanced control: Publishers can customize and optimize their header bidding setup according to their specific needs. Faster page load times: Prebid is designed to minimize the impact of header bidding on page load times, ensuring a better user experience. Strong community support: As an open-source project, Prebid benefits from a large community of developers, users, and contributors who work together to improve and maintain the platform.

  • First-price auctions and second-price auctions in Real Time Bidding

    There are two primary types of auctions in Real Time Bidding (RTB) and programmatic advertising. First-price auctions and Second-price auctions. First-price auctions and second-price auctions are two distinct types of auctions that differ in how the final price paid by the highest bidder is determined. Here's a brief overview of each: First-price auction: In a first-price auction, bidders submit sealed bids, and the highest bidder wins the auction. The winner then pays the exact amount of their bid. Since bidders are unaware of what others are bidding, they must strategize and balance their desire to win the auction against the risk of overpaying for the item. This might lead to bidders submitting lower bids than their true valuation to avoid overpaying, a strategy known as bid shading. Second-price auction: In a second-price auction, also known as a Vickrey auction, bidders also submit sealed bids, and the highest bidder wins the auction. However, the winner pays the amount of the second-highest bid rather than their own bid. This auction format encourages bidders to submit bids that reflect their true valuation of the item, as they only pay the price of the next highest bid if they win. This mechanism is designed to reduce the winner's curse, which occurs when the winner overpays for an item in a first-price auction. In summary, the main difference between first-price and second-price auctions is the way the final price is determined. In a first-price auction, the winner pays their own bid, while in a second-price auction, the winner pays the second-highest bid. This difference in pricing mechanisms affects bidders' strategies and the overall efficiency of the auctions.

  • How to calculate the number of variants in an A/B Test

    To calculate the number of variants in an A/B test, for example when running A/B-testing using Emerse Labs in programmatic campaigns, you first need to understand the components being tested and the variations of each component. An A/B test typically involves two or more versions of a specific element being compared to determine which one performs better. Here's a simple method to calculate the number of variants in an A/B test: Identify the components being tested: List all the elements you want to test in your experiment, such as headlines, images, call-to-action (CTA) buttons, or layouts. Determine the number of variations for each component: For each element you are testing, count the number of variations you want to include in the test. Make sure to count the original version as one of the variations. Multiply the number of variations of each component: To calculate the total number of variants, simply multiply the number of variations for each component. For example, if you're testing three different headlines and two different CTA button colors, the total number of variants would be: Total Variants = Variations of Headlines * Variations of CTA Button Colors Total Variants = 3 * 2 Total Variants = 6 In this case, you would have six different variants in your A/B test. Please note that the method above assumes a full-factorial design, where all possible combinations of variations are tested. In some cases, you may choose to test only specific combinations or use a fractional factorial design to reduce the number of variants, especially when testing multiple components simultaneously. To learn more about how Emerse can offer A/B-testing as a service, please contact us.

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