“Anodot allows us to capture incidents an hour or two before they create a customer experience impact. This also helps take complexities away from our operations people”

Anodot Chief Data Scientist Ira Cohen covers the five alert settings you should adjust to get more relevant and actionable alerts for your business metrics.

The State of KPI Dashboards for Business Intelligence When they were first introduced, business intelligence (BI) KPI dashboards were intended to help provide continuous visibility into an enterprise’s performance, and thus optimize the analysis process of BI. Continuous visibility, however, is not the same as real-time intelligence. This has become increasingly and painfully clear to businesses over the years. In our latest series of articles we’ve shown how dashboards have failed to deliver on their hype for many reasons: Real actionable insights come from intelligently correlating many (often subtle) individual clues, which KPI dashboards are unable to do because they are designed to give a general overall picture. In their goal to simplify the complex, business intelligence KPI dashboards are unable to present the granular data required to quickly get to the root cause of a KPI’s behavior, thus requiring analysis to occur in a separate tool. So much for the “single pane of glass”. KPI dashboards are tools for visualizing the behavior of a metric, not for monitoring them. Since they require human eyeballs continuously glued to the screen, KPI dashboards are unable to automate the real-time discovery of the clues which can help you earn more revenue or decrease losses. That’s just the tip of the iceberg. KPI Dashboards for Business Intelligence: Delays, Costs, and More Costs Traditional BI products which usually feature these dashboards are complicated platforms that require a heavy investment of time and money to implement, resulting in a long time to value. When you buy one of these tools, you’re not getting a turnkey solution, but rather a down payment on a large IT project which frequently blows past deadlines and budgets. Even if you’re lucky and actually get one of these solutions up and running, the costs – and delays – keep coming. That’s because those KPI dashboards for business intelligence don’t continuously feed on a stream of real-time data, but on reports and tables generated by IT. This increases business latency and kills real-time decision-making. Without real-time data, profit-damaging business incidents come and go days before you’re even aware of them. Do you want to avoid the lag due to waiting for the reports? Be ready to pay more for additional custom integration. These integrations add a whole new layer of labor costs, further pushing out the already long time to value. The additional expenses include the time of your CDO, CTO, data scientists with enough experience to do this integration completely, and often additional programmers, data analysts, and decision-makers. Your only alternative to these hefty one-time integration costs is often a continuous subscription with a middle man like Zapier for the connectors you need. Even for the business events those dashboards are able to catch, only skilled analysis can deliver an explanation for why a particular KPI changed the way it did. Not everyone who relies on the BI dashboard is a skilled data scientists capable of performing that sleuthing. Truth be told, those KPI dashboards require sleuthing even before they’re created. This is because every dashboard first needs to be designed, and that design begins with knowing what questions you want to be answered. This is of course completely useless when you are looking for unknown unknowns. Since, by design, business intelligence KPI dashboards visualize only a small subset of a company’s important metrics, some KPIs will inevitably be left out if they don’t match all the criteria you currently think are important. Since the dashboard, and the analysts using them, can’t see every metric, picking the wrong KPIs is a very real risk. No choice of chart types, colors or text options will be able to highlight signals in data you’re not collecting. Correcting for this early mistake in the dashboard design is time-consuming and costly since any new KPIs need new data to be gathered, new reports run, a chart type chosen, etc. With all of these built-in delays and latencies inherent in KPI dashboards, is it any surprise that the BI adoption rate among employees was only 30% in Gartner’s 2017 survey? Unsurprisingly, a solution that is unable to deliver high-velocity business intelligence is also unable to drive rapid adoption. AI Analytics Drives Past Business Intelligence KPI Dashboards  If KPI dashboards for business intelligence have so many problems, why are companies still using them? Slick visualizations hypnotize users to the point where they miss the big picture. When staring at data they become blinded by information and miss the obvious. These tools give the illusion of transparency into business performance, but that transparency, if it comes at all, provides no value if it is not provided at the speed of your business in a way that makes the data insights truly actionable. AI analytics, however, can deliver actionable insights in real time. With built-in data science, this new breed of solutions uses powerful machine learning algorithms to accurately and automatically detect anomalies in every time series metric—not just a few KPIs. AI analytics also automatically correlates and combines related anomalies, giving your analysts all the clues they need to respond to business incidents like third-party API breakage, a pricing glitch, or a surge in product orders. These are the types of rapid-fire events every modern company needs to manage and those which do so successfully have long left cumbersome KPI dashboards behind.

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Minute Media is a leading technology and digital content company. The company's proprietary video and multimedia publishing platform, Voltax, powers the creation, distribution, consumption and monetization of third party publishers and advertisers as well as our own sports and culture content brands, including The Players’ Tribune, FanSided, 90min, DBLTAP, Mental Floss and The Big Lead. The Challenge   As Minute Media’s business scaled, it became increasingly difficult to keep tabs on incidents that impacted user experience, revenue, and costs. The company needed a solution that could help: • Identify underlying issues in the platform to prevent penalties with Google and other supply-side platforms • Understand issues with the integrity of data aggregated from a wide variety of sources • Improve the ad profit margins, especially during consistently changing patterns such as the pandemic • Prevent revenue loss by quickly notifying of fraudulent bot clicks on video ads The Solution   Minute Media’s AdOps, BI and SEO, and sales and marketing teams have integrated Anodot into their data aggregation and analysis. They’re leveraging the platform to proactively protect revenue, investigate data integrity and platform issues, and improve ad performance. Read Case Study Here  Anodot Reveals Granular Issues Impacting Ad Performance   The company has numerous use cases for Anodot’s autonomous anomaly detection capabilities. One of the big ones is reclaiming revenue from Google Ad Manager. At the end of each month, Google has a process where they deduct revenue from all publishers according to their own internal algorithm. “It’s not always apparent to us how that works, but they will hint about the performance of what we’re running," says Farangiz Fayz, Data Analyst at Minute Media. "The deduction can be a big hit on the overall revenue that we generate. We take that as a lead to investigate further so we can optimize our ad performance to reduce these monthly deductions.” One example issue that Google can deduct revenue for is invalid traffic (IVT), such as fraudulent clicks generated by a bot, which can bleed revenue from a campaign. “Anodot can tell us exactly which unit the bad traffic is coming from and which partner was bidding on it,” says Fayz. “We can look into the bid level data in the API [application programming interface] and then we can further question Google on these penalties.”   Anodot Helps Protect Minute Media’s Bottom Line   One of the most important uses for Anodot is to help Minute Media maintain compliance with Google Ad Manager’s strict operating rules. “Most of our revenue is derived from video, and that’s why we have so many Anodot alerts built around the video player’s performance,” says Tomer Cohen,VP of BI and SEO. For example, if there’s a problematic behavior with the player on one of our partners – say a high click-through rate – this can lead to a penalty with Google and reflect on all the sites that are monetizing on their account. If one partner site has a problem, all of their partners suffer a penalty because they are all under one Google account To address this, their team created Anodot alerts on things like click-through rates and other behaviors that Google monitors closely. Cohen says that when Google issues a penalty, all the partner sites will be out of Google’s ad serving for at least a couple of days, which can lead to revenue losses in the hundreds of thousands or even millions of dollars.  

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Find out why global companies like Payoneer, Credit Karma and SplitIt are using Anodot to detect and resolve operational incidents before they impact revenue and customers. The digital transformation and decentralization of the fintech segment has resulted in increasing complexities in payment transactions, more third party applications and a higher volume and velocity of payments data that need to be monitored in real-time. To make sure every payment transaction is completed as expected, payment operations teams must be able to find and fix payment issues as they’re happening anywhere along the end-to-end transaction path. Whether you’re a merchant, acquirer, or payments processor, it’s crucial to have complete visibility into your payments environment. Anodot’s powerful and easy-to-use anomaly detection and triage technologies help fintechs stay on top of their operations, deliver flawless customer experience, and optimize approval rates and fees. Anodot’s AI-driven platform learns the expected behavior across all permutations of digital banking — including payment approvals, merchant activity, partner APIs, deposits and withdrawals, login attempts, and more — and alerts teams in real-time to any incident, delivering the full context of what is happening, where and why.