Cosmos Impex is a successful high-technology CNC Machine Tool manufacturer. It was established in 1987 and has robust manufacturing systems, and advanced technologies.
Their products include HMCs, CNC Turret Lathes, Horizontal/Vertical Machining Centres and CNC Vertical Machining Centres.
They enjoy a strong presence in the Indian market and are one of the leading importers of quality imported machined components and assemblies. Recently, they entered into IT field and also came up with software products.
They are a reputed exporter of machined components and assemblies to the European market. Their team strength goes above 700+. Total turnover ( 2018-19) over USD 45+ Million with over USD 6 Million in exports.
Before using Sangam CRM, they used a customized solution where they use to manage stock and used excel for sales management.
They wanted to have one solution that should take care of lead management to follow up to get their sales deal close.
If multiple people get involved in one sales process, which was managed in excel then it was hard for them to know what conversation they had before with customers.
Their quotation sending process has two main levels, initially sending quotation with the standard pricing and then revised quotation after negotiation process with the customer.
They used to make quotations with different formate in doc files manually. Second, there are suggested products which should come in quotation with relation to the main product; managing all this every time manually was hard for them.
In their quotation sending process, two different teams get involved. Quotation is prepared by the back office team and finally sent by a sales team. Managing this manually through the doc was creating a lot of complexity for them.
To manage the progress of individual data across the different platforms was the major challenge.
As there was no single platform to maintain all records and detail, It was hard to make business analyses from the scattered data.
Before, generating customization reports and analyzing them was impossible as data were recorded on different platforms.