Data mapping is the process of matching data fields from one source to corresponding fields in another destination. It helps to organise and transform data so that it can be properly understood and used by different systems. This process is essential when integrating databases, moving data between applications, or converting information into a new format.
Diversity analytics refers to the use of data and analysis to measure and understand the range of differences within a group, such as a workplace or community. This includes tracking metrics related to gender, ethnicity, age, disability, and other characteristics. The goal is to provide clear insights that help organisations create fairer and more inclusive…
Test coverage metrics are measurements that show how much of your software’s code is tested by automated tests. They help teams understand if important parts of the code are being checked for errors. By looking at these metrics, teams can find parts of the code that might need more tests to reduce the risk of…
Call centre analytics involves collecting and examining data from customer interactions, agent performance, and operational processes within a call centre. The goal is to identify trends, measure effectiveness, and improve both customer satisfaction and business efficiency. This can include analysing call volumes, wait times, customer feedback, and the outcomes of calls to help managers make…
Upsell and cross-sell analytics refers to the use of data analysis to identify opportunities to encourage customers to buy more expensive items or additional products. By examining customer behaviour, purchase history, and preferences, businesses can suggest relevant upgrades or complementary products. This approach helps increase revenue while also improving the customer experience by offering items…
Pricing optimisation tools are software solutions that help businesses set the best prices for their products or services. These tools analyse data such as market trends, competitor prices, customer demand, and sales history to recommend price points that maximise profit or sales. By using these tools, companies can quickly adapt prices to changing conditions and…
Customer Lifetime Value Analytics refers to the process of estimating how much money a customer is likely to spend with a business over the entire duration of their relationship. It involves analysing customer purchasing behaviour, retention rates, and revenue patterns to predict future value. This helps businesses understand which customers are most valuable and guides…
Churn risk predictive models are tools that help organisations forecast which customers are likely to stop using their products or services. These models use past customer data, such as purchase history, engagement patterns and demographics, to find patterns linked to customer departures. By identifying high-risk customers early, businesses can take steps to improve customer satisfaction…
Product usage metrics are measurements that track how people interact with a product, such as a website, app or physical device. These metrics can include the number of users, frequency of use, features accessed, and time spent within the product. By analysing these patterns, businesses can understand what users like, what features are popular, and…
Customer Journey Analytics is the process of collecting and analysing data about how customers interact with a business across different channels and touchpoints. It helps businesses understand the steps customers take before making a purchase or using a service. By examining these journeys, companies can identify what works well and where improvements are needed to…