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3 reasons your company needs real-time anomaly detection

In the business world, time is money. When an anomaly, or unexpected data pattern, occurs, each second can amount to additional loss or missed opportunities.

This is especially true for a fast-moving, data-driven business. When manual thresholds and dashboards prove no match at managing millions of metrics, companies need to adopt an analytics solution that works autonomously and in real-time.

Here’s why.

1. Opportunity

As author William Arthur Ward famously wrote, “Opportunities are like sunrises. If you wait too long, you miss them.” Real-time anomaly detection lets you seize business opportunities that have a limited time window and might otherwise slip under your radar.

For example, an eCommerce company might experience a sudden dramatic spike in sales of a particular product or product line that results in the item quickly going out of stock. But by using real-time anomaly detection to track its social media metrics, such as the number of brand mentions on Facebook and other social platforms, the company could immediately link the uptick in sales to a specific event — let’s say, a celebrity endorsement of their product — and quickly restock their inventory. The company might also consider adjusting pricing or offering bundle deals with products experiencing lower sales volumes to further increase revenues.

It’s no surprise then that major players such as T-Mobile, Netflix, Starbucks, and others have adopted AI and machine learning data analytic methods to better understand consumer behaviour and determine demand.

Receiving accurate data in the moment allows you to link anomalies to business incidents quickly to give you a competitive edge. By identifying the strategies that lead to positive business outcomes — whether a social media post, positive product review, or PPC campaign — you can capitalize on opportunities as they arise and repeat this success.

2. Loss Prevention

Generally, the faster a problem is found, the less costly it is to fix it. A number of companies have made headlines for the massive losses suffered from pricing and other technical glitches.

In 2018, Amazon took a major hit due to a price glitch, losing $1.2 million in one minute alone, with the company’s total losses on Prime Day estimated as high as $99 million.

And a pricing error made on shoe retailer Zappos’ website may have been beneficial for consumers, but resulted in $1.6 million in lost revenues.

On a number of occasions over the years, retail giant Walmart has experienced technical errors which have led to items being sold at a fraction of the price. For example, one glitch caused $600 computers and other electronics to be listed at $8.85. And on another occasion, $2,000 televisions were mistakenly priced at $99. Worse, customers were displeased when Walmart refused to honor these prices, claiming that the terms of use allowed it to cancel sales caused by pricing errors.

Real-time anomaly detection analyzes data as it comes in, so any detected anomalies can be addressed immediately. Potential threats that would otherwise proliferate undetected are weeded out before they can escalate. This helps you avoid equipment downtime and the subsequent impact on customer experience.

3. Reputation Management

Bad news travels fast. Business incidents that adversely affect your customers can directly harm company revenue and brand reputation. On average, poor customer service cost companies $62 billion in revenues lost to competitors, according to a 2016 survey.

Bad customer service can tarnish any company’s reputation. Telecommunications conglomerate Comcast was named “America’s most hated company” in 2017 and was labelled the 15th most hated company in 2018. The telecom enterprise further enraged customers in November 2017 due to an hour-and-a-half-long internet outage, which affected millions of customers across the United States. The glitch was reportedly caused by a configuration error.

Discovering anomalies immediately is critical for your brand’s reputation, as it allows you to respond to incidents impacting your customers in real-time. By taking a proactive approach, you’re much less likely to risk negative reviews on user review sites, social media, or through word of mouth, which could otherwise dissuade potential customers.

LivePerson, a leading, AI-powered messaging provider for more than 18,000 businesses, including HSBC, IBM, and L’Oréal, needed a way to guarantee 100 per cent uptime and a superior customer experience. Tracking close to two million metrics every 30 seconds, LivePerson found their existing analytics overwhelmed by the task. They decided to adopt real-time anomaly detection and soon found they were able to identify anomalies adversely affecting their users and those users’ customers immediately.

Real-time anomaly detection enables you to discover and address problems in house. It can save you having to find out about issues from dissatisfied customers — after the damage has already been done, and can certainly help you avoid the kind of service worthy of a “most hated company” listing.

Conclusion

Real-time anomaly detection offers significant advantages to data-driven businesses as they scale. The more accurate your data science, the more actionable your insights — a capability widely recognized as key to maximizing revenues and preventing loss.

Written by Ryan Basserabie

 

Source of the article: https://www.digitaldoughnut.com/

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