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Discover important details about Nanonets' sales order automation capabilities.
Sales order automation is a streamlined process that leverages technology to efficiently manage and process sales orders within a business. It involves automating the entire lifecycle of sales orders, from order creation to fulfillment and invoicing. This automation replaces manual data entry and paper-based processes with digital solutions, reducing errors, saving time, and improving overall order accuracy.
The benefits of sales order automation are substantial. Firstly, it enhances operational efficiency by eliminating the need for employees to manually input order information, allowing them to focus on more value-added tasks. Additionally, it accelerates order processing, reducing lead times and improving customer satisfaction through faster order fulfillment.
Error reduction is another key advantage. Automation significantly reduces the risk of human errors in order entry, which can lead to costly mistakes and customer dissatisfaction. Moreover, automation improves order tracking and visibility, providing businesses with real-time insights into order statuses, inventory levels, and customer preferences.
Furthermore, sales order automation promotes better collaboration among departments, as relevant teams can access and share order information seamlessly. Overall, this technology-driven approach optimizes sales operations, enhances customer experiences, and empowers businesses to remain competitive.
Nanonets uses advanced AI-powered workflows to power its sales order automation capabilities. Nanonets reads incoming orders across sources (emails, attachments, website forms, cloud storage), captures relevant order details and creates entries/records in the seller’s ERP, CRM or system of record.
Nanonets' AI leverages machine learning techniques to read and understand incoming orders so only relevant data is pulled from them. It can capture data from emails, attached documents, scanned PDFs, images etc. Nanonets AI captures order details accurately as and when they are received and if all's well directly pushes them into the system of record.
Nanonets also identifies customer order data that is inconsistent with the seller’s ERP and handles order exceptions. It can also set up business rules and logic to customise sales processes and approval workflows.
Once it passes all the required checks, Nanonets triggers a new sales order creation in the ERP or system of record, which is then sent to the customer. The order then proceeds to different stages: fulfilment, delivery, invoicing and accounting.
Nanonets AI highlights and picks out inconsistencies between incoming customer orders and existing data in the ERP or system of record - e.g. part numbers that don't match, incomplete customer details or a new customer address etc.
The AI can handle such exceptions by doing a lookup (or fuzzy match) to find the closest matching data or flagging the entry/record if no reliable match can be found! A sales or customer service rep can then add the missing information or take corrective measures.
The Nanonets AI can also set up intelligent business rules and approval workflows - e.g. automatically sending orders above a certain threshold value for manager review, verifying inventory and latest pricing details before creating a sales order etc.
Yes, such custom rules and logic can be set up on Nanonets using its advanced AI workflows. Existing customers can be mapped to specific customer service or sales reps and all incoming orders can be assigned accordingly.
Incoming orders can be triaged and classified in all sorts of way.
Yes, absolutely. Nanonets reduces order processing times drastically. Additionally its workflow automation can also improve inventory management, accounts receivable processes, and returns processing workflows.
Nanonets is primarily deployed on the cloud or accessed via API. It is also offered as an on-premise version on a case-by-case basis.
Nanonets has a transparent pricing policy, unlike most sales order automation software.
There are primarily 3 aspects that determine final pricing - the volume of incoming data/documents, the number of AI models required for accurate data capture, and finally the effort needed to integrate with your system of record.