Dictionary Archive - Page 7 of 15

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Big Data refers to the large amounts of structured and unstructured data that are generated every day from various sources such as social media, sensors, and online transactions. These datasets are too complex to be processed by traditional data processing applications, and therefore require advanced analytics tools and technologies to extract insights and derive value from them.

In eCommerce, Big Data can be used to better understand customer behavior and preferences, optimise marketing strategies, improve business management, and enhance the overall customer experience.

Average Time on Site refers to the average amount of time customers spend browsing on a website. It provides valuable insights into the level of customer engagement. The longer the time spent on a site or page, the higher the chance of converting a visitor into a customer. This metric can be used to analyse the effectiveness of website design, content, and user experience.

A higher Average Time on Sitegenerally indicates that visitors are finding the website user-friendly and engaging, while a low average time on site may indicate that visitors can’t find what they are looking for, or are not interested in the content.

Annual Recurring Revenue (ARR) is a financial metric that refers to the amount of revenue a business expects to receive annually from its customers for its subscription-based products or services. It is calculated by multiplying the number of paying customers by the average annual subscription fee.

ARR is an important metric for recurring revenue businesses as it provides a predictable source of revenue, helps in forecasting future revenue, and provides a clear picture of their financial health and growth potential.

Artificial Intelligence (AI) is a field of computer science that focuses on creating intelligent machines that can perform tasks that essentially require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. AI technology has advanced rapidly in recent years, thanks to the increasing availability of data and computing power.

In eCommerce, AI is being used to improve the customer experience by providing personalised recommendations, chatbots, etc. AI-powered tools can also help businesses automate processes, detect fraud, and make data-driven decisions. With its potential to transform the way we live and work, AI is likely to play an increasingly important role in eCommerce and many other industries in the following years.

App Store Optimisation (ASO) is the process of optimizing mobile apps to increase their visibility and downloads in the app stores, such as the Apple App Store and Google Play. The goal of ASO is to rank higher in the search results and top charts, which can drive more organic traffic and downloads.

ASO involves various strategies, such as optimising the app’s title, description, keywords, icon, and reviews. It also involves monitoring and analysing app performance metrics, user feedback, and competitor data to continuously improve the app’s visibility and downloads. ASO is an important aspect of mobile app marketing, as it can significantly impact the app’s success and revenue.

Address Verification System (AVS) is a security service used by online retailers to verify the accuracy of billing addresses provided by customers during the checkout process and ensure that the address matches the address associated with the payment method.

AVS compares the billing address provided by the customer with the address on file with the payment processor to confirm that they match. This helps reduce the risk of fraud and protect the retailer from chargebacks. This system is particularly useful for businesses that sell high-value items or operate in industries with a high risk of fraud, such as electronics or luxury goods.

Engagement data is the collected information on the interactions between a customer and a brand. This data can consist of metrics such as time spent on the site, page views, clicks, and shares on social media.

Engagement data paints a comprehensive picture of the customer journey and provides valuable insights into customer behaviour and preferences. It can also help identify potential issues and pain points, as well as make data-driven decisions to optimise customer experience and improve marketing strategies.