The implementation of Artificial Intelligence in business management software isn’t new. However, up until now the implementation of AI in business applications wasn’t that much of productive. Microsoft infuses Artificial Intelligence with Dynamics 365 for sales app to mainstream the business management capabilities.
Implementing AI to business suits requires not only huge development process but also enormous amount of machine power. Microsoft keeps upgrading every single chips on their Azure platform since Artificial Intelligence was introduced in Dynamics 365. The best thing is, these built-in AI functionality is available out-of-box and does not require further coding.
Here is a quick checklist of the available built-in AI features in Dynamics 365 that keeps improving the business management of your organization:
- Lead Scoring: Using Artificial Intelligence, Dynamics 365 can core and grade all leads automatically based on the predefined behavior of your lead scoring model. The system is extremely easy to use so you can configure and assign lead scoring models to match precise business needs of your organization.
- Demand Forecasting: Demand foretelling is used to predict freelance demand from sales orders and dependent demand at any decoupling purpose for client orders. It’s an intrinsic feature for Dynamics 365 for Operations, to assist makers and different massive producers produce foretelling processes. It’ll generate an applied mathematics baseline forecast from historical knowledge. The system mechanically removes outliers and creates measurements of forecast accuracy.
- Relationship Insights: In Dynamics 365, Artificial Intelligence continuously analyze consumer interaction like activities, communications, meetings, and other activities to improve customer relationship health score. It does these tasks to evaluate your activities and suggests the best path forward to achieve the business goal.
- Product Recommendation: Product Recommendation is a task of the built-in AI suit –Cortana. It uses consumer’s data to predict recommended products.
- Predictive Sales & Inventory Forecast: This is a functionality of Dynamics 365 for Financials uses. The Sales and Inventory Forecast extension predicts potential sales using historical information and offers a transparent summary of expected stock-outs. Inventory forecast also helps produce renewal requests to your vendors and saves you time.
- Intent Analysis: Using machine learning and deep learning methods, Microsoft Dynamics 365 analyze the uploaded post from the consumer and detects their intention. Post are then scored against the algorithm and predicts the most possible intentions of what they want. This help improving your customer relationship and productivity.
- Sentiment Analysis: Sentiment Analysis sees through the perception of a post and sentiment value using the sentiment algorithm in the original language. The sentiment value results in a positive, negative, neutral or unknown sentiment for a post.