newData is a data science consulting agency located in the Nashville Metropolitan Area. Our objective is to use machine learning and statistics to assist businesses achieve their goals. We offer predictive analytics marketing, operational and scientific AI solutions tailored to the specific needs of our clients, as well as a range of AI solutions in partnership with top universities and niche AI businesses.
Segmentation divides data into smaller, more homogeneous groups based on common characteristics and behaviors. Examples of
Digital analytics is a critical component of modern business that involves measuring and analyzing data from digital channels. The goal is to understand how people are interacting with digital assets, such as websites and mobile apps, and to use this information to improve digital experiences and drive business outcomes. Digital analytics tools can range from simple website analytics platforms to advanced tools that incorporate machine learning algorithms, and they can provide insights into a wide range of metrics, such as website traffic, user behavior, and conversion rates.
The insights generated from digital analytics can inform key business decisions, such as website design and content, user experience, digital marketing strategies, and product development. By using digital analytics, organizations can gain a deeper understanding of their customers and their digital interactions, which can help them make data-driven decisions to improve their overall digital performance and drive business success.
Data mining is the process of discovering patterns, relationships, and insights in large datasets. It is used to extract meaningful information from data and to make informed decisions. The techniques used in data mining can vary depending on the type of data being analyzed, but common methods include association rule learning, clustering, and decision tree analysis. Data mining can be applied in a variety of industries, such as finance, healthcare, marketing, and retail, and it can help organizations make more informed decisions, such as improving business processes, predicting customer behavior, or detecting fraud.
Data mining requires large datasets, powerful computational resources, and expertise in statistical and machine learning methods. The results of data mining can provide valuable insights, but it is important to consider the ethical implications of data mining, such as privacy and data security. Overall, data mining is a powerful tool for organizations looking to make data-driven decisions and to gain a deeper understanding of their customers and their business operations.
Anomaly detection is a process of identifying unusual patterns or behaviors in data that deviate from the normal or expected patterns. It helps organizations identify data points that are rare, unusual or difficult to explain, providing insights into potential problems and opportunities. Anomaly detection can be applied in various industries such as finance, healthcare, marketing, and retail, helping organizations detect fraud, identify problems in business processes, and improve customer experiences.
The techniques used in anomaly detection vary and may include statistical methods, machine learning algorithms, and data visualization. The choice of technique depends on the nature of the data and the goals of the analysis. It is crucial to validate the results using subject matter expertise and domain knowledge to ensure that the results are meaningful and actionable. Anomaly detection is a valuable tool for organizations to better understand their data and to identify potential issues and opportunities in their operations.
A recommender system, also known as a recommendation system, is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item. Recommender systems are utilized in a variety of applications, including movies, music, news, books, research articles, search queries, social tags, and products in general. These systems can operate using a single input, like music, or multiple inputs within and across platforms like news, books and music.
Recommender systems use a variety of algorithms to provide personalized recommendations to users based on their past behavior, preferences, and interests.
Predictive analytics helps companies understand the to forecast customer behavior. Statistical techniques or machine learning algorithms are used to create sophisticated models that uncover trends and patterns. They can also be used to create sophisticated models that uncover trends and patterns...
Both business and scientific communities have learned to successfully use machine learning and statistics to provide predictive analysis, yet machine learning has increasingly become the preferred analyzation method. Before looking at why, it’s important to understand the difference between between...
Just when you thought you had machine learning (ML) figured out, you find a new type waiting to be discovered. If you’re a marketer or data scientist, staying up-to-date on the different types of machine learning and how they can be used to improve your campaigns and analytics is important...
newData's predictive analytics framework provides a simple and effective way to align company goals with data science.
Companies that utilize newData's predictive analytics framework have discovered a powerful way to easily and quickly integrate their goals with the use of data science methods. This not only saves time, but also helps ensure that outcomes are achieved according to predetermined criteria. The integration of data science techniques into the overall goal-driven ecosystem allows for more accurate decision-making and higher ROIs over the long term. Automation of processes such as customer segmentation, risk management and predictive maintenance further streamlines operations while boosting efficiency.
newData created synthetic data that Funnel Metrics used to mimic a sales organization of different sizes, structures and complexities. We used this data to power Funnelocity® our Salesforce performance management app. newData also developed a custom machine learning model for us that predicts which salespeople are most likely to reach their potential. By using newData’s modelling approach, Funnelocity® provides continuous insights to analyze and identify the metrics, KPI’s & skills that have the greatest impact on sales achievement. Thus, enabling sales managers to focus on improving their sales team's performance, instead of spending valuable time analyzing data.