Artificial intelligence techniques have effectively automated hardware and software processes through computerized systems and automation technology. They have also helped deduce meaning from massive volumes of domain-generated textual and quantitative data.
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More than ever designers have a wide range of tools and skills. From this perspective, using product analytics might be the most distinguishable one for product designers. In this article, I’ll try to break down how to connect metrics to the design process and apply the findings to design future improvements.
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In the contemporary age, the amount of information produced is greater than ever. As sales promotions ingest enormous amounts of data, the information collected might be scattered or redundant, raising questions about the accuracy of the information they include.
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We all know what it’s like that first time you meet a new product, see if you like it, and really fall in love. Or fall in hate, as the case may be. Well there’s a word for that whole process, and today we’ll be focusing on what is one of the very first stages of the customer journey, on how to optimize the onboarding experience so that you never lose a potential customer before you’ve claimed them in the first place.
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Market basket analysis is a method that searches for connections between items in a commercial environment. Despite its name, market basket analysis extends beyond the typical supermarket setting. Any group of products can be analyzed using the market basket method to find affinities that can be used in some way.
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Customer churn is a problem. It’s all clear now. Customer retention is critical to growth. It’s a good idea to keep your users around for a while.
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Customer churn is one of the most crucial KPIs to track for a dynamic company. While it isn’t the most pleasant metric, it is a figure that may reveal the unpleasant reality about your company’s customer retention.
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Analytics is a pervasive term in just about every field or business. While plenty of businesses and business people cling to “old school” ways of doing things, there’s no question that data analytics is a part of the present and the future.
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Most businesses these days have figured out that data is the way to move their business forward. Technology and analytics have become keywords thrown about in business meetings, often by people who don’t even know what all the terminology they’re using means exactly. But regardless, collecting more data and the proper analysis have become an indelible part of just about any modern business.
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It is well-known that gas and oil companies are slower than other industries to adopt technology and create a solid digital transformation strategy. The ageing of operating systems and the complexity of data were some of the reasons that hindered the potential for digital transformation.
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