The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

Will Privacy Fears Undermine The Future Of Machine Learning?

Artificial intelligence (AI) and machine learning technology present an interesting meeting point between our fear of the unknown and our fear of being known (that is, fear of our private information being exposed and known by others.) The erosion of privacy and rise of intelligent machines is actually a common theme in science fiction. But while reality still has a lot of catching up to do before we can call Skynet’s customer support or play cards with Agent Smith, many people have expressed genuine concern over the implications of modern technology – especially regarding their privacy.

When Outsourcing Analytics Offshore Makes Sense

Thanks to its broad applicability, data analytics has rapidly become a critical business function for modern organisations. But with expertise in the field in short supply and high demand, companies with an identified need for data analytics are looking beyond their traditional borders to monetise their information assets. Forrester Research predicts that a third of businesses will “pursue data science through outsourcing and technology”  as organisations become less process-driven and look to their data to find new opportunities for innovation. And with globalisation and technological advancements making outsourcing a realistic and practical option for businesses, this trend is set to gain momentum. With this in mind, let's take a look at why an organisation would even consider outsourcing their analytics capabilities in the first place.

How Machine Learning Is Boosting Sales For One Food Retailer

Machine learning is helping brands narrow the divide between their products and consumers in ways that would appear almost magical only ten years ago. From Amazon's personal product recommendations based on past purchases and browsing habits, to Netflix's uncanny ability to suggest just the right movie title according to your taste in film, data-driven insights are helping companies speak to individual customer preferences, who are demanding more personalisation in their products and engagements. This has moved data analytics from novelty status to an integral part of the marketing strategy, as brands discover new opportunities to communicate their unique selling points.

Customer Value Management Tips From Steve Jobs

In his final keynote speech at the 2011 Apple Worldwide Developer’s Conference, Steve Jobs remarked that, “If the hardware is the brain and the sinew of our products, the software is its soul.” Jobs’ intimate understanding of and vision for his products stands out as one of the key reasons behind Apple’s success. His notoriously protective stance on his company vision and the extent of his involvement in the conception, design and development of his products right up until their anticipated release is legendary. But the man behind Forbes’ most valuable brand of 2015  also knew a little something about value creation and customer value management.

How One Bank Uses Speech Analytics To Improve Customer Loyalty

In order to improve customer loyalty, we need to listen to our customers more. Increasing our share of wallet and maximising customer lifetime value (CLV) will only happen when customers are prepared to choose our brands and products over our competitors. Fortunately, businesses are uncovering clues to improving customer loyalty in new places thanks to data and evolving analytics platforms. This led one bank in Canada to turn to the thousands of conversations between its representatives and its customers for new insights into elevating the customer experience.

Principa CEO Speaks Artificial Intelligence With Brainstorm Magazine

Principa CEO Jaco Rossouw, speaks to ITWeb's Brainstorm Magazine, a publication aimed at the decision makers of the world, about the impact artificial intelligence will have on life as we know it, asking the pertinent question of whether machines can be taught how to reason.

Using Predictive Analytics For Retail Capacity Management

Capacity management describes a company's ability to meet present and future demands for its products and services. This involves a wide set of roles, responsibilities, processes and functions that all depend on their successful execution and interplay between one another. Although the working parts are many, the end goal behind capacity management is a shared one: to beat the competition in delivering the best products and services to the customer.

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