Email messages contain valuable auxiliary information in unstructured or semi-structured form. It can be an
If such kind of information is already tracked in CRM you are completely fine. But first you need to get to this state.
If you do it as you go it is a routine but relatively simple task. You can enter new contacts or leads to a CRM system field-by-field, keep track of documents, opportunities, etc. The situation is worse when you just started to implement CRM in your company. You are in front of a huge email archive and information is somewhere inside. Hopefully you have some Excel spreadsheets, but they can be incomplete.
Email signatures are semi-structured. Though there are some common patterns people create a lot of variations for signature formats. Check the examples:
Sheldon Cooper Senior Theoretical Physicist Caltech 1200 E California Blvd, Pasadena, CA 91125, United States (626) 555-9157 - phone (626) 555-4717 - fax Leonard Hofstadter Neuron Ltd. 50 Oak Street, London W1T 1RJ, England Tel: +44 20 5555 5543 | Fax: +44 20 5555 5518 | Mobile: +44 555 5555 5559 Mail: firstname.lastname@example.org | Web: http://www.domain.local/ Howard Wolowitz Vice President, Purchasing, IT Aerospace Parts & Materials 5064 East Kemper Road Cincinnati, Ohio 45241 555.555.1400 Ext. 4415 555.555.4415 (direct) 555.555.4270 (fax) 555.555.1380 (mobile)
To cope with such variety we apply the power of machine learning to signature identification and extraction. We developed GrinMark TextMiner - a sophisticated technology that uses innovative algorithms to extract valuable structured data and relationships from email body.
In it's current state TextMiner recognizes people names, organizations, departments, titles, addresses, emails, urls and phones. GrinMark TextMiner is now a part of Outlook 365 Plugin and shortly will become a part of all other our integration tools.For sales people it means