Right up top, the dashboard has two sections — Summary and Action. For more information, visit www. Viewers can click in for more details. For more information on Stripes Group, please visit www. In this section, with a range of data, the colors orange and red show different levels of intensity.
The Summary section has the most important information about the user in focus. Now moving to their dashboard, its purpose is simply to alert an e-commerce website owner of suspicious activity, and prompt them to take action at the earliest. In a time-sensitive environment as this, having the Actions section right next to the Summary section makes the dashboard actionable and intuitive. When dealing with fraud, the time to response is of critical importance. Viewers can click in for more details. Right up top, the dashboard has two sections — Summary and Action. The use of colors, formatting, and layout all serve to reduce the delay between analysis and action. This investment will help us strengthen our global alliances and introduce our award-winning platform to enterprise organizations that rely on ineffective legacy fraud solutions. Location Information Our records provide postcode level location information for websites in 37 supported countries. The company works in a number of vertical markets including physical and digital e-commerce, travel and hospitality, communities and marketplaces, financial institutions and payment processors, SaaS companies and beyond. What immediately catches the eye is the Sift score in large font, made even more noticeable by the block of solid red color surrounding it. With this dashboard, Sift science gives us a lesson on effective dashboard design. This section prompts the viewer to mark the user as fraud or not based on the information in the previous Summary section. Traffic Ranking Multiple Source Traffic ranking information for over 1. The Sift score is the most crucial piece of information in this dashboard, and choice of formatting does justice to its importance. The next and more colorful column is the closest glimpse we get of the secret sauce Sift Science uses to predict fraudulent activity. The Sift score works well as is, but it could communicate the sore more intuitively and powerfully via an interactive gauge. This is done in a logical, data-driven manner by assigning a number to each prediction. With that we end our review of another impressive dashboard, and are almost at the end of our series on predictive analytics. For example, an area chart showing the progressive growth of the Sift score over time, with each suspicious activity, will serve to visualize the same story in a way that immediately resonates with the viewer. What's in the Full Reports? This is at the heart of how Sift Science works, trying to correlate all available data points to identify suspicious patterns, and assign a data-driven, accurate Sift score. The viewer immediately notices the apt use of colors red and green for the buttons, and can guess what they imply with very little cognitive load. The use of color across the dashboard is exceptional. For each of the data points collected, Sift Science predicts the likelihood that this user is fraudulent. In fact, the graying of details that are not selected allows the viewer to gauge the level of suspicion without even clicking through — the more the number of connecting lines, the more the suspicion.
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The Sift Science Engineering Team
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