Collecting, analysing and reporting on company data takes up a lot of time, resources and manpower (and this is only set to increase as we collect more and more data). Take marketers, for example, they spend on average 3.55 hours a week collecting, organising, and analysing marketing data from different sources. That adds up to 250 hours a year.
This energy spent on understanding data and KPIs is why business intelligence (BI) tools that streamline the process are booming right now. But one little-know tool for to understanding your data inside out is proving to be one of the most effective ways of understanding your data and improving digital performance: Anomaly detection.
What is anomaly detection?
Described by Forbes as ‘one of the most underrated BI tools of 2020’, anomaly detection is a branch of AI that automatically analyses an organisation’s performance and behaviour to uncover data that deviates from the norm and needs further investigation. This kind of data is defined as an anomaly, and anomaly detection systems will alert the user to them in real time when found.
If you want to know more about what anomalies in your business metrics are, we’ve put together a handy guide: ‘What is an anomaly’. But, simply put, anomaly detection a kind of BI tool that detects hidden threats or overlooked digital opportunities in your business metrics.
You might be thinking that anomaly detection sounds technical and intimidating. But, today it isn’t at all. Advances in AI, machine learning, and deep learning algorithms have democratised access to anomaly detection and it’s becoming more widely available. And since, in an MIT Sloan Management Review survey, 83% of companies said they believed AI was a strategic priority for their business today, anomaly detection is actually one of the best and easiest ways for forward-thinking companies to start using AI to make better use of their data.
Let’s look at some of the key benefits of using anomaly detection BI tools.
1. Automated KPI analysis
Perhaps the most significant benefit of anomaly detection is the automation of KPI analysis.
For most businesses, KPI analysis is still a manual task of sorting through all of their digital channel’s data across different dashboards. Depending on how much data the company collects, this can be an incredibly time-consuming task. But, when using an anomaly detection system, AI algorithms are constantly scanning through all your data across all your dashboards and analysing metrics 24/7. This means you’ll no longer have to check BI tools like Google Analytics constantly to know what’s going on in your KPIs. Instead, the anomaly detection will alert users straightaway when it finds anomalies and unusual behaviour – good or bad – in their metrics, so you can use these insights in your strategy without delay.
2. Prevention of security breaches and threats
With hacker attacks now taking place every 39 seconds, online security has never been more critical. And anomaly detection is one of the best ways to prevent security breaches and threats to your business and website.
Often, security threats to your business can fly under the radar for long periods of time. According to IBM, the average time to detect a breach was 206 days in 2019 – just think about how much damage a breach unidentified for that long could do. But, with anomaly detection, security breaches can be detected as soon as they happen, because the AI is constantly scanning your data and will pick up on anything unusual immediately.
To demonstrate just how effective anomaly detection is at preventing security breaches, let’s look at the example of Accenture. Roughly 10% of Accenture’s $25m annual expense line processes were being flagged for potential non-compliance, a huge manual task for their Compliance Team. But when they incorporated anomaly detection into their rule-based system, the results were incredible and led to a significant decrease in false positives. Better still, since AI keeps on learning, their results keep getting better over time, even as the risk of security breaches goes up across the globe.
3. Discovery of hidden performance opportunities
The word ‘anomaly’ might bring to mind only bad connotations, but anomaly detection can unearth hidden digital performance opportunities that were otherwise unknown, too. Currently, digital teams can spend spend hours and hours each week searching through data for ways to improve digital performance. If anomaly detection is applied, this kind of repetitive work can be eliminated, freeing up time to plan and execute more performance-driving strategies. Not to mention the fact that, with AI conducting thorough analysis, many things that were hidden in your data will be uncovered.
For example, anomaly detection may help you find SEO opportunities by alerting you to keywords that you aren’t targeting, but are generating organic traffic to you website. This could have taken you months to pick up on using a reporting tool like Google Analytics, yet with anomaly detection you can swiftly use this information to optimise your campaigns and website for these keywords.
4. Stretch budgets, resources and talent further
In the past, anomaly detection was only available for business Goliath’s, such as Accenture, that were able to dedicate budget, resources and data science talent to ambitious projects. But, as the technology has blossomed over the last few years, companies without resources on this scale have been able to make use of the technology, too. With anomaly detection BI tools, insights that previously would have only been available to you if you had a team of analysts at your disposal are now available to much smaller teams.
This means that teams using anomaly detection BI tools are able to stretch budget, resources and talent further than ever before. Instead of wasting time analysing KPIs to find anomalies and performance opportunities, or putting out the many fires created by missed anomalies, teams can instead focus on innovation and creativity – what humans are great at. This leaves AI to the number crunching it excels at.
5. Faster results
As we’ve already touched on, finding anomalies in data manually can be extremely time-consuming. But, not only do anomalies take a long time to find, anomalies can also take a long time to actually surface using traditional reporting techniques. And, often, they’ve already done significant damage by the time they’re found.
For example, one of our clients, a German gifts retailer, found that, one month, revenue was much lower than normal. They searched through their metrics but couldn’t find the cause – until they started using our anomaly detection platform. Once integrated, the AI immediately detected the problem: The payments page was taking over 10 seconds to load and people were abandoning their carts as a result. If this had been left, undetected in their metrics, they could have potentially lost €120k a month without understanding why. Instead, they addressed the problem immediately. This meant they saved hundreds of thousands in lost revenue and achieved a 13% increase to revenue the following month.
How to use anomaly detection for your business
Anomaly detection is going to become one of the most impressive and exciting developments in both the business world and AI over the next decade. It’s set to add significant business value to many companies. But how can you get started?
Well, you can get started today with a free trial of our anomaly detection platform. At Millimetric, we’ve seen the value that anomaly detection can bring companies first hand, which is why we’ve created our own anomaly detection BI tool to help companies stay on top of their data, without the need for a team of analysts number crunching day in day out.
With our anomaly detection tool, enjoy:
- Google Analytics, Google Ads, Facebook integration without any code
- Analysis of all your historical data – so you can see performance over time
- Time series and comparative anomaly detection
- 24/7 AI analysis
- No code required integration, so it’s easy to use for beginners
- Email alerts