The global predictive analytics market is expected to reach $ 21.5 billion by 2025, an increase of 25% year-on-year between 2020 and 2025. Increasing acceptance of AI and ML technologies is part of the driving force behind this market.
Others are as follows;
- Increasing attention to digital transformation
- Increased acceptance of big data
- Increasing need for remote monitoring to support the COVID-19 pandemic
An intelligent combination of data, analytics, and artificial intelligence help businesses improve their forecasts. Artificial intelligence in sales allows us to explore datasets and create predictive models that reveal the factors that influence profits. Machine learning algorithms allow the software to train with data and improve over time. Natural language processing can add context. In addition, AI-powered software can provide relevant data such as weather and traffic to sales forecasts.
AI-powered tools can forecast by market segment, region, product type, find historical data, and provide real-time updates. In addition, machine learning solutions collect information about user behavior, purchases, preferences, and dislikes in a variety of ways. These solutions can use CRM, social networks, and email. The software can also track how often a salesperson contacts a particular customer and guide you through the next steps to close a transaction.
Optimization
There are many ways artificial intelligence applications can help e-commerce businesses accurately forecast and plan future growth. These include related product recommendations, smart supply chains to improve production and logistics, and chatbots to improve customer service. All of these aspects help drive sales, start customer-centric searches, add personalization, and localize the customer experience.
Some of the world’s largest fast-food chains, use AI to optimize their supply chain to balance customer demand with inventory levels. For example, if the restaurant has extra chicken sandwiches but not enough veg burgers, the menu will have more visibility of chicken options to avoid running out.
In addition, dynamically changing menus help companies promote sales more intuitively. For example, the menu may suggest a dip to go with french fries to serve bottled water when a customer orders a healthy salad. This system is based on time of day and weather conditions. AI-powered software allows food chains to monitor supply and outage to their restaurant network and use the data to suggest other items that will bring more profit and customer satisfaction.
Bottom Line
Artificial intelligence technology improves a sales forecast in many ways that affect sales. These are just some of the benefits of smart forecasting.
- Ensure faster planning and decision-making. In particular, AI-enhanced software interprets information faster than humans.
- Add prediction accuracy based on current and historical data
- Helps extract valuable and actionable insights
- Improve processes such as appointments and budgets
- Helps solve out-of-stock and oversupply problems
At the same time, smart software does not replace years of experience in human salesmanship, well-tuned teamwork, and intuition. A combination of software that guides active team members and sales reps and helps avoid mistakes is a smart way to ensure year-over-year growth.
