It is past time for your business to embrace AI-powered business forecasting tools. Data forecasting has become an essential business development and commercial stability planning process. Finance, supply chain, procurement, and operations are the most prevalent industries that employ data prediction, and more are entering the ranks. Using Artificial Intelligence (AI) technology, you may add additional power to the historical data used for forecasting. Many apps now employ AI and Machine Learning technologies to anticipate data. Before delving into the best AI-based business forecasting tools, let’s define, categorize, and use data prediction.
What Exactly Is Business Forecasting?
Using numerous tools and methodologies, business forecasting implies projecting developments in many business sectors, such as sales, costs, and profits. These predictions are useful for developing well-informed strategies. Companies may detect difficulties during any organizational inquiry by forecasting. This process employs several quantitative or qualitative models to analyze the historical data. Companies get predictions from the analysis, which they may use for demand planning, marketing, financial operations, and user experience. There is a discrepancy between forecast data and actual performance. You may increase the accuracy of future predictions by using the deviation.
Business Forecasting Major Types
While there are other types of data forecasting or predictions, we will explore two of the most prevalent types below:
Demand Forecasting
Demand is a vital component of every business. Forecasting resource demand, including raw content, inventory, and workforce, enables organizations to plan properly and satisfy needs far in advance. As a result, companies can meet both internal and external needs.
Growth Forecasting
Forecasting a company’s growth model (sales/revenue) is crucial for planning and strategizing. Organizations may make precise decisions on budget, resource allocation, marketing strategy, and business patterns based on metrics such as inventory location and customer subscription cancellation with data on future growth.
Use Cases For AI In Data Prediction And Business Forecasting
Here are some cases of AI forecasting in the workplace:
Finance
Finance companies may use AI-based forecasting to anticipate fraudulent behaviors and take action against them. For example, they can use AI tools to anticipate property values based on location and historical pricing.
Government
AI forecasting may help government agencies update and digitize their processes, reduce the danger of cyberattacks on national databases, minimize costs, boost personnel productivity and database maintenance, and improve lawmaking responses.
Manufacturing
Manufacturers use AI forecasts to decrease production downtime, increase productivity, and enhance customer happiness. In addition, predictions may be used for process design, maintenance, supply chain optimization, and other purposes.
Healthcare
Healthcare organizations often confront services while integrating new technologies. With AI business predictions, healthcare organizations can easily integrate new technologies and simplify old processes.
Insurance
AI may forecast tasks such as risk management and client happiness for insurance companies. Insurance organizations also use forecasting in fraud detection, efficient marketing, customer growth, underwriting, and personal rate control.
Sales
AI data forecasting educates sales companies about the leads that have the best chance of converting. It helps by supplying information such as the desire to pay and the likelihood of canceling membership.
Telecommunication
Telecom companies use AI tools in business forecasting to create client connections and increase consumer happiness. In addition, data prediction may help you retain loyal consumers and reduce fraud.
Product
AI may be used to determine product pricing and compare competitor data. In addition, it forecasts the chance of accidents during product acquisition and delivery, allowing you to be prepared with insurance.
Operations
Using AI, operations companies may get a credit risk score and insurance premiums for people. In addition, they can identify workers who are likely to quit the organization shortly. Now that you’ve learned about the capabilities of AI-powered business forecasting, it’s time to learn about the tools available to help you. Check out the following list of AI forecasting tools for business prediction:
5+ Best AI Business Forecasting Tools To Try
AI Business Forecasting Tools to try in 2022.
1. Neptune
Neptune is an experiment management tool that allows you to monitor the results of Machine Learning experiments. By leveraging its one dashboard for less context switching, ML researchers and developers may become more productive. For example, companies may share AI forecasting results, logs, or even dashboards with colleagues through a simple link rather than organizing wasteful meetings. In addition, because the dashboard is based on an ML model, you can locate any data from it.
The same platform allows you to compare and troubleshoot your models. You may control the process of model development and experimentation. Companies may learn about the underlying dataset as well as the model parameters. Neptune centralizes all ML metadata, including visualizations and metrics. It integrates with over 30 prominent Machine Learning and IDE libraries. As a result, businesses get the most out of daily apps.
2. H2O AI Cloud
H2O AI Cloud is an excellent solution for businesses looking to create AI models and apps. This all-in-one platform enables quick AI model development in the cloud and on-premise. It has a sophisticated autoML tool that promptly provides accurate and transparent data prediction. Using its predicted results, this platform enables you to generate new business concepts to address crucial business concerns. Business organizations may use it in any context and profit from several modeling approaches for various data types. In addition, you may use autoML to create effective models and perform various additional tasks during your lifetime.
H2O AI Cloud helps a unique blend of open-source and proprietary algorithms, allowing you to identify data drift in real-time. The tool ensures you obtain the best CPU and GPU performance while delivering real-time business forecasting. You may do time series analysis for business forecasting using its ML Interpretability toolbox. The tool employs distributed Machine Learning for petabytes.
3. Obviously AI
Obviously AI is a no-code platform that uses Artificial Intelligence to forecast revenue and business results. Companies may modify their supply chain and develop customized marketing strategies using business forecasting data. If you use Obviously AI, your team will not need to learn to code or spend months constructing AI models. This tool is simple to combine with your preferred data sources, such as Google Drive, Salesforce, Dropbox, Evernote, Hubspot, and CSV files. When you choose the prediction category, AI will provide forecasts using AI technology. Your data is safe thanks to the practically unbreakable AES-256 encryption. What-if scenarios help you make predictions and understand the elements that influence them.
This platform supports two types of AI forecasting. The first is AutoML, which allows you to easily create AI models from historical data for real-time data predictions. The second kind is Time Series, which uses as little data as possible to make time-bound predictions about critical business events to a specified date. Even if your data is incompatible with Machine Learning, you may use the Data Dialog function to modify it and convert it to a Machine Learning-compatible format. After developing the data forecasting model, companies may share it with the general public or the whole team. For real-time business forecasting from your app, the Low-code API is accessible.
4. DataRobot
DataRobot use Augmented Intelligence technology to revolutionize intelligence in a variety of industries. It uses machine learning models that need less coding to deliver real-time predictions. Businesses may enhance data-driven and effective decision-making by using various AI elements of this tool. Integrating AI into your company culture is feasible to get trustworthy data predictions. This platform allows you to create rules, policies, and controls for production models. You may produce, deploy, and manage excellent forecasts for your company using its automated time series. This innovative business forecasting model increases robustness and decreases uncertainty while making large-scale predictions.
5. Pecan
Pecan produces data for operations and sales teams using predictive analytics. As a result, companies may devise solutions to their business difficulties. In addition, companies that use their BI-friendly data may increase sales and revenue while providing a better user experience to their consumers. From resource and production planning to distribution and packaging, from customer acquisition to retention, this platform aids you in developing future-ready strategies based on industry-crucial metrics.
Using Pecan, you won’t need to recruit more data scientists for business forecasting. Instead, your current analysts may use this platform’s automated processes to make AI-powered complex prediction models. This tool helps reduce the cost of data scientist code model development from the start. Pecan uses data well to uncover unexpected possibilities or to face the hurdles of changing circumstances. As a result of precise AI forecasting, you will see a considerable increase in KPIs within two weeks.
6. Futrli
Futrli is intended to help you receive rapid business forecasting on business trends, revenue, sales, tax, operations, and employees. It assists you with reliable predictions of growth planning, future cash flow, and operations strategy. The tool is primarily designed to meet the demands of worldwide accounting firms and accounting businesses. Futrli Predict analyses all of your company’s business transactions to make an accurate forecast. It provides three types of predictions: freestyle forecasts, unit forecasts, and recurring forecasts. In addition, this app’s prediction helper can explain the reasoning behind each prediction.
The tool provides scenarios that indicate what will and will not occur. As a result, you may be ready for the best and worst in your business. This baseline forecast will be prepared every day using the most recent data. Futrli Predict now enables hot-linking Google Sheets templates with Futrli Predict for more complex predictions such as payrolls. You may turn off the tool prediction at any time and add your data. The tool integrates directly with Xero and Quickbooks. Futrli will import data from these apps every 24 hours after integration.
7. Dataiku
Dataiku is here to assist you in making data-driven and AI-powered decisions, whether you belong to a code-driven technical community or a low/no-code business. There is no need to undertake manual data cleaning since this tool can analyze the data more rapidly and effectively to recommend essential changes. It supports 109 types of data transformation, such as aggregating time series, geographic data transformation, aggregation across several sources, etc. You may schedule computations after creating a data pipeline in SQL. Its interactive GUI allows you to quickly get the essential data.
Teams may use Dataiku AutoML to construct high-quality data models using various techniques and parameters. In addition to its 32-core algorithms, Dataiku supports major ML engines such as Python, H2O, Spark, and TensorFlow. You may use the business forecasting platform to examine visual models and comprehend important metrics like statistics, mistakes, and insights. As a result, you will understand the reasoning behind each prediction and tailor your strategy appropriately. Companies may use Dataiku to create and show several types of analysis. These are examples of principal component analysis, univariate analysis, bivariate analysis, correlation analysis, and statistical tests.
8. Qlik Sense
Qlik Sense provides dynamic analytics to businesses, allowing people of any ability or competence level to make educated decisions. It provides you with a best-in-class data analytics experience on a larger scale. With speedier computations, contextual predictions, and an interactive user interface, this business forecasting platform goes beyond generic dashboards and query-based analytics. In addition, Qlik provides AI-powered augmented analytics that people may use to better human-centric analysis. AI-generated insights, natural language interaction, and AutoML predictions can help you make smarter business decisions while focused on your business.
This tool extends the breadth of the data model and gives conveniently accessible interactive forecasts. Its Insight Advisor tool produces sophisticated insights automatically and helps you in the data preparation and analytics creation processes. AutoML develops models and evaluates what-if scenarios to provide forecasts in a code-free process. The data may be published on various cloud platforms, including Qlik Sense.
Wrapping Up:
Every day, the business world becomes more competitive, and every company must exert maximum effort to remain competitive. Business forecasting is a strategy that helps businesses in gaining a competitive edge. AI forecasting elevates the whole process and reduces manual labor. In this post, we explored some of the best AI-powered data prediction tools for forecasting businesses of all sizes that may employ them. In addition, using these solutions may give you a better knowledge of future scenarios derived from relevant historical data.
