Digital Marketing

Database Solutions

Database Solutions

Quality data leads to a successful lead generation strategies. “Quality & Quantity” of prospect data impacts performance of your campaigns. To begin with mostly the collected data is inaccurate or bogus. In such scenario often campaigns fail. Our experts study the campaign first, we check the collected data to ensure its accurate, no duplicates, redundant details, missing information and then cross check each and every record using email/phone/social media. We append, clean the current information for all the contacts and create sales ready leads. Depending upon your ideal business prospects definition, we build strong contacts lists and keep adding new contacts to your pipeline on regular basis. Foxtin plays the role of a trusted data partner for our clients at each stage of the data life cycle, ensuring that it is accurate, relevant and timely data is available to Sales and Marketing teams on a real-time basis.

Database Clean Up:

data quality solutions allow organizations to cleanse, correct and enhance any type of customer or prospect data - and create an accurate view of your organization, your customers and your business environment High-quality data is critical for success. Good data is the basis for solid business decisions. Having an accurate view of your organization, your customers and your business environment allows you to optimize profitability, mitigate risks and reduce costly operational inefficiencies.

To create high-quality data that is always available, Foxtin provides industry-leading data quality features and functionality, allowing you to create data services that standardize, corrects and integrates data. Foxtin data solutions enable you to analyze, improve and control enterprise data and successfully address data quality issues, including the ability to: Profile data to discover errors, inconsistencies, redundancies and incomplete information. Correct, standardize and verify information across the enterprise from a single platform. Match, merge or link data from a variety of disparate sources. Enrich data using information from internal and external data sources. Check and control data integrity over time with real-time data monitoring, dashboards and scorecards.