Prevent Data Loss With AI-Driven Anomaly Detection
Data is potentially an incredible way to hone your marketing results. Collecting data from website visitors, leads, and return customers can give you insights that have never before been available. Drilling down to the finest detail, you can now examine how a customer moves their mouse to gain insight. Indeed, you can identify which pages convert and which repel. Refine your strategy based on use-case data and a flood of millions of data points analyzed by business AIs. But in that flood of data, the benefit is only gained if you know how to put your data to use with AI-driven anomaly detection.
The Cost of Data Loss
Failing to collect data effectively or put your data to good use creates data-loss. In the data-driven business world, business goals should include turning data towards better process optimization and happier customers. The cost of data loss to a business includes less customer satisfaction, inefficient decision-making, unoptimized performance, increased operational costs, and reduced trust in the company data itself; to name only a few.
The data you lose could contain essential insights to serve your customers and resolve problems, often before they become problems. Part of the use of anomaly-detection is that you receive alerts in real-time. When your data even starts to vary from the norm, examine the situation to determine if the change is good or bad. Then, formulate the ideal response to either solve the problem or capitalize on the anomalous benefit. But you can only take this action if you know what your data is telling you. Without insight, problems are caused and opportunities are lost.
If you have more data than ability to use in marketing, the good news is that there are cutting-edge tools designed to put analysis and machine-learning to use finding the insights you need. One of the best tools at your command is anomaly detection; the ability to identify when one or more marketing data points fall outside your standard operating norms. Even in highly specific circumstances.
Anomaly Detection and Data Loss
Anomaly detection is, statistical analysis that has taken on a life of its own. You probably already have an analytics tool that tells you your highs, lows, averages, and issues helpful warnings like items low in stock. You may even have marketing analysis data that shows you user paths through the website and tells you how many conversions each landing page inspired. But do you have software that can tell you when something is out of place?
Anomaly detection is the gap in your analysis and, therefore, a plug for your data loss. AI-driven and empowered by machine learning, anomaly detection can tell you when something has gone wrong under broad or very refined circumstances. In marketing, anomaly detection essentially notices when data points are out of place and can learn to tell you what that means.
Marketing Anomaly Detection Examples
- In marketing, anomaly detection could tell you when an unusual number of leads were abandoning carts at the address-entry stage. This can save sales by pointing to a temporary error in the interface that has been turning customers away.
- Anomaly detection tells you when something has gone right, when a particular UI element gets more clicks than others, or when a particular promo bundle tempts buyers.
- It can tell you if there is an unintentional marketing loophole. Like accepting multiple discount codes, or the same discount code stacking multiple times.
- Detecting anomalies tells you if conversion seems to fail in response to a single broken cross-selling link.
Using Anomaly Detection Tools for Data Loss Prevention
An AI-driven anomaly detection tool is a marketer’s best friend. Better than any analytics dashboard, preventing data loss is all about training the software to interpret your data. Using machine learning, your tools first learns what ‘normal’ is for your business. This can be a narrow-focus only on website activity and customers or a much broader focus including your servers and employee activity as well.
Identifying Data Points Outside the Norm
Once ‘normal’ is defined, anomaly detection gives you a heads-up any time something falls outside of normal. The more the software learns to understand, the more sophisticated these alerts can become. Fine-tune it to let you know about slight variations in one area, like A/B testing lead conversion. Then, have alerts for profound anomalies for other things like inventory fluctuation.
The great thing is that you don’t have to know what you’re looking for ahead of time. Anomaly detection is designed to let you know any time something ‘statistically interesting’ occurs. Where other analytics tools only examine what you tell them to examine, anomaly detection can give you a heads-up about changes even if you do not yet know how to interpret them. Then provide other changes in data that happened nearby for context.
You can learn all sorts of things, from how the weather influences buyers to alerts about broken web store links in real-time.
Resolving Your Data Dilemmas
If your marketing department has experienced data loss (and who hasn’t?) then anomaly detection software can close the gap. When you are already collecting all the data you need, why let insights slip through the cracks? Machine-learning anomaly detection gives you insights in real-time.
Anomaly detection is like a security camera for your data, letting you know when something significant changes that you’ll want to know about. Every business that uses anomaly detection will glean different results and insights because each business and its customer base is unique. Those insights are valuable and just waiting to be discovered, acted upon, and the benefits gained. Never let data slip through the cracks again. Consider anomaly detection software as your solution to data loss prevention.
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