Assisted Predictive Modeling Enables Business Users to Predict Results with Easy-to-Use Tools!
Gartner predicted that, ‘75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance.’
With all of this business data, how can your organization a) help your team gather and use data to make fact-based decisions, and b) use that data to predict which products and services your customers will need in the future, how your customer buying behavior is shifting, how your competition will respond to the market, when and how to sell your products, which marketing campaigns will work in the future, and how and when to recruit new resources and open new locations.
‘Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background.’
A misstep in any of these areas can create risk, damage your business reputation, or put you years behind your competition. That’s why your business needs predictive analytics. And, not just any predictive analytics! If you want to democratize data among your team members and provide easy-to-use tools to encourage user adoption and enable data-driven decisions, you must choose wisely.
Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze. These tools allow the organization to apply predictive analytics to any use case using forecasting, regression, clustering and other methods to analyze an infinite number of use cases including customer churn, and planning for and target customers for acquisition, identify cross-sales opportunities, optimize pricing and promotional targets and analyze and predict customer preferences and buying behaviors.
Prescriptive analytics for regression models combines predictive modeling and optimization techniques to produce actionable recommendations for decision-making. While descriptive and predictive analytics use past events to predict future outcomes, prescriptive analytics goes beyond this process to recommend optimal actions that will help the business to achieve specific goals. By merging prediction with prescription, the enterprise can proactively identify challenges and opportunities, and drive more effective and strategic outcomes.
These are just some of the tools your business should consider to build a solid foundation for predicting outcomes using historical and forward-looking data analytical techniques.
Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background. Your users can access:
- Time Series Forecasting
- Regression Techniques
- Classification
- Association
- Correlation
- Clustering
- Hypothesis Testing
- Descriptive Statistics
‘Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze.’
With the right predictive analytics solution, your business can also support data scientists, IT and business analysts with tools that allow for R script integration, so these users can perform complex statistical and predictive analysis and reporting to support strategic organizational needs.
Smarten Assisted Predictive Modeling will support your team with tools that are intuitive and easy to use and will encourage user adoption. Leverage the essential components of Augmented Analytics and improve decision-making and outcomes.
Original Post : Leverage Predictive Analytics for Every Business User!
