Lantek Customer Analytics
Because knowledge is power. And sales.More info + Get a DEMO
Advanced client knowledge to anticipate and plan production orders.
Our algorithms recover the clients’ historical data in our Lantek Quotes and Lantek Sales CRM software, or in the clients’ external CRM software, and we analyze it for patterns and periodicities. These are automatically incorporated into production planning, reserving times and resources, as well as anticipating quoting tasks for the smart management of discounts, costs and prices for clients.
Companies that work with Lantek Integra Quotes and/or with Lantek Integra Sales, and in combination with our MES, have important information that Lantek Customer Analytics makes use of: the capacity to analyze the behaviors of each client: purchase frequency, quantities, average production time for each manufacturing order, average manufacturing cost, average offset for each type of manufacturing order, average margins, etc. This is a source of high-quality data that when filtered, analyzed and processed, will allow you to anticipate orders and reserve resources, improve planning, quote quickly and objectively, and finally, increase profitability for each client with recursive knowledge. You can quote more competitively without the risk of affecting your margins, and you can plan raw material purchasing and working hours more efficiently.
Having access to the clients’ data, purchase frequency and profitability, and combining this with the manufacturing data obtained from each production order, for cutting operations as well as non-cutting processes, captured by our CAD/CAM software, as it can be installed on any machine regardless of the manufacturer or cutting technology, facilitates smart quoting: quick, objective and profitable. By knowing the offset history per client, manufacturing times, possible discounts and payment methods, you can obtain an objective and profitable quote before your competition does.
Smart Quoting is a quoting service based on client knowledge linked with accumulated historical data and recursive learning from past production. It will provide you with: