Analytics

The retail landscape is in the midst of a dramatic, data-driven renaissance. New tools help to build new connections — between consumers and retailers, and across supply chains. Data analytics and machine learning further these connections to better understand and predict customer behavior and improve demand forecasting. In this emerging era of smart retail, organizations have access to a range of powerful new capabilities and tools.

One of my favorite Talend customer success stories is the International Consortium of Investigative Journalists (ICIJ). I love this story not only because they transformed investigation journalism with data, won the Pulitzer prize for the Panama papers, and helped the public to recover billions of dollars lost to illegal tax evasion.

Raise your hand if you’ve ever heard that “data-driven companies make more money”. McKinsey started beating that drum half a decade ago. Financial Times wrote extensively about the topic. Google even commissioned a multi-year study from Boston Consulting Group (BCG), which showed that “best-in-class digital marketers benefit from 1.4 times greater cost benefits and up to 2.5 times revenue impact” after implementing analytics to drive their business growth.

Most of the day to day work for knowledge workers is spent helping the business make better decisions, like choosing whether it’s worth expending the effort (or actual money) to achieve the desired business goal. The example I often use when talking about ML is churn prediction (and I’m starting to think I’m overusing it now). It costs money to retain a customer who is thinking of moving, but this is less than the cost of getting new customers.

In February 2017, I was out on a routine training ride when I made a turn on loose gravel. Next thing I knew, I was laying on the pavement. Just like that, I broke my hip and collar bone, and I knew I woudn’t be able to race in the Ironman Lake Placid that year. So, I adjusted from racing to recovery. And, I’m happy to report, I returned to racing in 2019, completing the Ironman Lake Placid that year.

Do you still find yourself visually monitoring dashboards for anomalies? That leaves catching revenue-related issues to chance. It’s become humanly impossible to catch incidents on streaming data. This is why many eCommerce and data-driven companies have adopted automated anomaly detection.

In today’s business world, marketing segmentation is a must have for every organisation. It helps you process and aim different targets in a market into multiple customer or prospect segments to enhance your marketing actions. Through this discipline, you can hold a crucial competitive advantage over your competitors because you can adapt your offer and your communication according to the identified groups of personas you want to address.