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Traveloka, a leading online travel portal in Southeast Asia, operates in a highly dynamic and competitive space. Any disruptions to the platform, even for a few minutes, could result in significant revenue loss. The company needed a tool that could provide real-time alerts for any disruptions, enabling quick rectification. Additionally, Traveloka required a self-service solution due to the high volume of employees needing access to data. The company was looking for a solution that could avoid creating a bottleneck for information and allow employees to serve themselves.

Christopherson Business Travel, a travel management company, was facing a challenge with its proprietary business travel software, AirPortal®. With millions of transactions flowing through its systems at any given moment, the company wanted a way to aggregate the data in a real-time dashboard. This would provide clients and internal employees better insights into how they are spending their travel budgets. The company needed to bring together data from multiple sources and inputs and was looking to consolidate the business reporting structure.

PBS, a private, nonprofit corporation, was facing a challenge in monitoring the web performance of all its properties. They had a selection of web analytics tools installed, but these proved difficult to maintain and use. PBS wanted to develop a coordinated approach to analysis and reporting that would inform their future strategic decisions. They needed a cohesive system across the entire enterprise, and for this they turned to Google Analytics. In addition to top-level analysis of PBS.org and PBSKids.org, they also hoped to implement a solution that would allow producers of individual programs to see only the data on those pages and microsites that related to their own shows. This challenge proved more difficult than the standard implementation of Google Analytics, since giving a producer access to one show would not only allow them to see all other shows, but would also force them to dig through massive amounts of data in order to find their own.

Posadas, Mexico’s largest hotel chain, was looking to improve its conversion rates by gaining a better understanding of customer behavior during the booking process. The company was using Google Analytics to analyze its website’s efficiency in converting visitors into customers. However, Posadas wanted to segment the traffic flowing through the conversion funnel to make a differentiated analysis for each of its over 100 hotels. The company also wanted to enrich the abandonment analysis by uncovering the opportunity cost of users leaving the booking process before completing a transaction.

Rozetka, Ukraine’s leading online retailer, was looking to increase revenue per user and average order value. The company had a large customer database and a wide variety of products, which provided a significant amount of data that could be used for product recommendations based on users' behavior and transactions. However, Rozetka needed help with product bundling, merchandising, product recommendations, and email campaigns. The company aimed to monetize its customer database through repeat sales and improve its direct marketing efforts.

The San Francisco Museum of Modern Art (SFMOMA) was one of the first museums to launch an institutional website. Their primary goal was to develop rich, dynamic content that engages visitors and keeps them coming back to the website as well as the physical museum. SFMOMA’s website receives nearly four times the number of visits than the physical museum. Providing compelling digital content that visitors want was as critical as hosting popular exhibitions. SFMOMA had been using another web analytics tool, but suspected an issue with accuracy. They were unable to monitor the usage of key investments in the website - such as audio, video, and specialized content. Finally, e-commerce tracking had not been installed properly, and so they were not measuring revenue or product sales from the online store.

Shoes of Prey, an innovative bespoke shoe label and online retail store, was looking to forge online partnerships leading to sales opportunities. As a new start-up, the company relied heavily on positive buzz about their products, so staying up-to-date on what’s being written about Shoes of Prey across websites and blogs was crucial. The company needed a way to monitor their website’s traffic and identify which blogs were sending the most valuable converting traffic to their website. They also faced the challenge of accurately tracking their conversion funnel due to their use of PayPal for payment processing.

Swissôtel Hotels & Resorts, a group of deluxe hotels in 26 cities worldwide, was facing challenges in understanding the performance of its digital marketing spend and monitoring user behaviors to tailor advertising for maximum appeal. The hospitality sector is highly competitive in search marketing, making it crucial for Swissôtel to track where its digital marketing spend is going and whether it's effective. Additionally, the ability to monitor who is spending money with the company is a significant benefit to investing wisely and generating future income. Swissôtel was running Google AdWords campaigns in Australia, the US, and the UK for one of its Singapore properties. The goal of the campaign was to drive sales by getting prospective customers to click on their AdWords ads and then make a purchase on their site.

Technologia, a leading business training firm in Montreal, had been successful with paid search marketing for years. However, they wanted to understand the influence of cost-per-click advertising on conversions, not just at the moment of sale, but in the days and weeks beforehand. They knew that potential customers did detailed research and made multiple visits to their website before buying. The challenge was to understand what influenced these customers along the way. They suspected that organic search and paid advertising were having just as much to do with sales as the strength of the Technologia brand.

TechSmith, a software company based in Okemos, Michigan, develops a variety of applications designed to narrow communication gaps through images, videos, online hosting, and remote usability testing. Online advertising is a key lead source for them, and they have used Google’s advertising tools over the years. TechSmith understood the importance of display advertising and its broad reach allowed them to find new customers who were previously unfamiliar with their products. However, they felt they were underestimating the impact of display using a Last Interaction Attribution model. TechSmith wanted a way to quantify Display’s effectiveness throughout the conversion funnel.

TiVo Inc., a global leader in the advanced television entertainment market, wanted to supplement its existing log-based tracking solution with an analytics tool better suited to its needs and budget. The existing solution required heavy customizations and significant development knowledge, and also kept data somewhat sheltered from teams that needed to see it most. TiVo’s app for smartphones and tablets allows customers to browse and schedule recordings and download or stream live or recorded shows to their mobile device, anywhere, for on-the-go viewing. The company wanted to measure user behavior inside the mobile app, see app usage patterns by category, and understand what content is consumed and how.

TopTarif.de, a leading German price comparison portal, was facing the challenge of identifying users who are highly likely to convert and appeal to them with advertisements. The company had been advertising with Google AdWords for several years using text ads, banners, and YouTube videos. However, they wanted to increase the probability of a conversion and reach interested users more effectively. They aimed to differentiate remarketing lists and adjust bids based on various factors such as the date of the last site visit, traffic origin, depth in the sales funnel, and the probability of conversion for a keyword.

TV App Agency, a pioneer in the development of applications for connected TVs, was facing a critical need to record data on clicks and downloads on apps for connected TV. The emerging platform was facing questions about monetization, and the agency needed to understand what consumers wanted from the apps. They wanted to gain data-led insights into future development. However, there were no existing statistics on what happens after a client downloads these apps. The agency spoke to a host of vendors offering analytics capabilities based on numerous APIs, but found that many were complex and difficult to implement.

Twiddy & Company, a family-owned vacation rental company, was facing a challenge in keeping visitors on their page for as long as possible. They wanted to communicate to their guests that they were competing with other visitors for the rental homes. If visitors waited too long to book, they might not get their first-choice rental. The company was also facing a challenge with their business model. The transparency of supply through the website put all the leverage into the guests’ hands. The closer they got to the time of occupancy, the more the guests could negotiate. This was leading to Twiddy’s owners sacrificing revenue by not always filling rentals.

Established in 1989, WBC is the UK's largest supplier of hamper, dell and drinks packaging to independent retailers. The company's website is its main business generation tool, promoting their range of 850 products. WBC was keen to understand how web traffic interacted with the site, and where potential improvements could be made. The company wanted to redesign their e-commerce site and increase the number of sales it generates. However, they faced challenges in understanding visitor interaction with the site and ensuring accurate Google Analytics implementation for solid data analysis.

Westwing, a leading international ecommerce company for home and living products, was facing a challenge in understanding cross-device usage patterns and purchasing paths of its customers. As members increasingly seek inspiration and buy products across multiple devices and platforms – including desktop, smartphone and tablet – purchasing paths grow in complexity. Westwing recognized the need to develop a clear understanding of cross-device usage habits in order to create effective marketing plans. The company began using Google Analytics when the business launched and upgraded to Google Analytics Premium in collaboration with Google Analytics Premium reseller Trakken in 2012, which enabled them to improve accuracy with unsampled data and increase speed with the freshest data possible.

Wiggle, the UK’s number one online cycle shop and the country’s fifth most popular online sports shop, was facing challenges in aggregating data from multiple sources and gaining meaningful insights into campaign performance. The company wanted to continually convert website visitors into customers to maintain and increase their competitive advantage. Promotions were a top influencer in obtaining conversions, so Wiggle’s website content manager Naveed Nasir turned to Google Analytics Premium for support in refining measurement for this critical area of online revenue generation. His goals were to measure campaign performance, analyze e-commerce data from the campaigns and optimize the campaigns’ aesthetics – all with maximum efficiency.

Marketo, a leading marketing automation software company, needed a platform that could combine external data with user site behavior, allowing it to increase the relevance of its marketing. The company's main objectives were to reengage potential customers at each stage of the funnel, first educating them on its products and later encouraging them to complete a lead form. To achieve these goals while getting full visibility across all its channels and programs, Marketo turned to Google Analytics. The challenge was to improve customer engagement and generate more conversions by tying data obtained from Marketo’s Real-Time Personalization product to an online remarketing campaign.

Airbnb, a global marketplace for accommodation listings, was facing a challenge in managing its complex tagging system. The company uses a large number of website tags, including a unique tag for each of their multiple AdWords accounts and additional tags for an array of vendors measuring different types of conversions. To accommodate the needs of various vendors, many tags had to be replicated several times. At one point, Airbnb was running 88 different audience lists and 100 different tags. The company needed a tag management system to prevent a bottleneck between the operations and marketing teams. The first solution the company tried was not successful — it required significant technical knowledge to implement tags, needed add-on tools for QA and reporting, and was too expensive.

Jobs2Careers, a rapidly expanding job search engine, was facing challenges with its tag management system. The company was using AdWords campaigns to attract relevant users to its site, specifically targeting 35- to 54-year-old job seekers. However, whenever the company wanted to update campaigns with new creative content, it had to edit tags manually. This process required collaborative support from both the marketing and engineering teams, often leading to bottlenecks in workflow as one team would have to wait for the other to complete its part of the tag update. The company was in need of a better solution for tag management to streamline its efficiency and increase conversions.

The American Cancer Society, a century-old organization dedicated to fighting cancer, was facing a challenge in understanding how users interacted with their various websites and mobile apps. They were aware that their digital platforms were being visited by users with different needs and goals, but it was difficult for their digital marketing team to isolate these customer segments and assist them in achieving their goals. Additionally, the Society wanted to address concerns with the Google Analytics implementation on its sites, monitor how its users changed behavior over time, and remarket to all segments once they were identified. To tackle these challenges, the Society turned to Search Discovery, a digital analytics and marketing company.

Big Bang, one of Slovenia’s largest consumer electronics retailers, decided to put more focus on online sales after a major strategic overview in 2013. Their ambitious goal was to increase online revenue by 250% by the end of 2014. To achieve this, Big Bang’s team needed to better understand the consumer decision journey (CDJ) and then use what they learned to improve their customers’ experiences. They needed to find the most important digital channels and touchpoints on the customer journey and measure, analyze, and optimize every step of its online and offline performance.

Rail Europe, the largest distributor of European rail products in North America, operates several B2C and B2B websites catering to US, Canadian and Latin American markets. With up to 20 domains making up the portfolio, the company was struggling with managing tags across all these sites. The implementation and maintenance of these tags was a complex process due to the significant amount of custom data that needed to be exposed. Web developers were spending valuable time on redundant tagging tasks, diverting resources away from enhancing the functionality of the Rail Europe websites. As vendors and technology partners changed over time, tags that had already been deployed would often linger forgotten on sites, burdening page load times and potentially exposing proprietary performance data to third parties. The online marketing team depended entirely on available IT staff for all tag management needs, leading to delays in new tag implementation and lack of valuable insights.

Smarter Travel Media, a portfolio of online travel brands, was facing challenges in managing and organizing remarketing tags. The task of adding new tags to the website was constant and was handled by the development team. The process was ad hoc and required significant resources, taking anywhere from several days to a few weeks to release. The company wanted to improve turnaround times, alleviate the burden on development staff, and manage tags without having to go through a scheduled release. They needed a faster and simpler way of adding tags to their portfolio.

1stdibs.com, a global destination for the best in furniture, fine art, vintage fashion, and jewelry, was looking to revolutionize a classic old-world industry by connecting the world’s finest dealers with discerning buyers online. As business grew, 1stdibs realized that it would need a broader and deeper understanding of e-commerce customers and the marketplace. The company needed a scalable infrastructure to collect, process, store, and visualize data. It also needed to recruit analytics talent and build a culture in which data was at the heart of the business. The company was using Google Analytics to collect and analyze data, but knew they were just scratching the surface. Without a solid attribution strategy, the marketing team didn’t know what it cost to acquire a customer. The team had no way to measure the effectiveness of cross-channel programs.

AIDA Cruises, a market leader in the cruise industry, wanted to understand the online journey of its customers: how customers were acquired, how they behaved, and when they converted. The company aimed to offer guests an unparalleled vacation experience, improve the environment, and create a secure, success-oriented future for all employees. AIDA needed to relaunch thousands of pages, including a full online booking system, and track the results. The company wanted to create an agile and scalable reporting and analysis environment to help all teams access data to enable better decisions.

The year 2020 saw the largest scale adoption of decentralized exchanges (DEXs). Compared to centralized exchanges, DEXs offer more pairs when trading, provide access to a greater diversity of tokens, and enable non-custodial swaps that keep funds safer. However, DEX users often don’t receive the best price when there is insufficient liquidity, or if a particular DEX doesn’t offer the most attractive price. Before MetaMask Swaps, users needed to navigate many DEXs to compare prices and swap tokens. However, using a single DEX or DEX aggregator did not always yield the best price for every trade, as each aggregator performs differently under different circumstances. Additionally, users needed to approve each token on each DEX, incurring expensive gas costs.

The year 2020 saw the largest scale adoption of decentralized exchanges (DEXs). Compared to centralized exchanges, DEXs offer more pairs when trading, provide access to a greater diversity of tokens, and enable non-custodial swaps that keep funds safer. However, DEX users often don’t receive the best price when there is insufficient liquidity, or if a particular DEX doesn’t offer the most attractive price. Before MetaMask Swaps, users needed to navigate many DEXs to compare prices and swap tokens. However, using a single DEX or DEX aggregator did not always yield the best price for every trade, as each aggregator performs differently under different circumstances. Additionally, users needed to approve each token on each DEX, incurring expensive gas costs.

CenterEdge Software, a company that provides a comprehensive platform for managing various aspects of businesses in the entertainment industry, was seeking a new analytics tool. The goal was to find a solution that could extract raw data and present it in a visually appealing and meaningful way to users. The company wanted to empower its customers with a platform that could provide tangible insights and answer specific questions to help streamline business operations and increase profitability. The challenge was heightened by the onset of the COVID-19 pandemic, which imposed new regulations and safety precautions that businesses had to adapt to.

CleverMaps, a map-based analytics platform, was designed to simplify data-driven decisions for non-technical users dealing with location data. However, previous vendors and in-house attempts to build a BI infrastructure did not meet their needs to quickly and efficiently simplify this process, thus inhibiting CleverMaps’ ability to scale. The team learned that more data is not the key for better decisions. Rather, the key for better decision-making is the correct representation, interpretation, and context of the analytic insights. To address this, the company committed to providing better data storytelling capabilities for customers to combine location intelligence insights with BI visualizations.