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Opportunity Scoring

Built into SmileCrm is the ability to score the data for a company/contact. This allows you to build up 'Ideal customer/buyer information' based on geographic region, company/buyer classification, and whether the information in the record in complete. Operators can call the highest scoring records first and so maximising your investment in the campaign.


Extended Data Capture

While SmileCRM has an extensive set of standard data (employee group, turnover group, department, seniority to name a few), there will invariably come a time when you need to capture data that is none standard - we call this information 'profiles'. Examples of this might be Gas contract end date, average spend per month or which provider are you with? Each of these can be made mandatory to be entered before the call can be converted to an opportunity. Profiles can be linked to opportunity scoring to enhance the visibility of key records.


Data Search

While you can just use an entire set of data for a campaign, often you will need to select data that is more targeted. SmileCRM allows you to use a sophisticated search facility where you can use standard fields such as county, department or sector to search for records, or get even more sophisticated and use the extended data (profiles) to search for data. If you have your own data, then this can become even more powerful as all the historic information will be accessible in the campaign using the search.


Master Data

While we have extensive options to manage purchased or customer data, there is an increasing move towards telemarketing companies building their own datasets. We allow our customers to build a "master" data set with specialist information being captured in what we call "profiles". The master dataset can be searched using the usual location, turnover/employee numbers or the special firmographic, demographic or psychographic information held in the profiles. This search then forms the basis of the data used in a customer campaign in the same way a purchased dataset would.