How to Deliver Remarkable Business Outcomes with AI-Powered Data Mappingby Adeptia Inc B2B Data Integration
Customers are the heart and soul of businesses. Organizations wanting to grow at a faster pace are in the quest for myriad ways to expand customer reach and deliver delightful experiences. Regular marketing techniques that were once used to serve customers have failed to make an impact now. In order to attract more customers and stay ahead of the curve, you need to market directly to the source, particularly if you provide services to millennials.
Data collection is one popular method that organizations leverage to gain access to information about their audiences. By identifying customer needs as well as requirements, companies can target their audiences – securely and easily. In other words, the data garnered from multiple customers can be used to analyze their demographics and needs – one gets to know what kind of audiences they cater to, what are their requirements and concerns, and more.
When the garnered data is comprehended properly, it’s easier to understand the buyer’s personas, and hence targeting them becomes a cakewalk. One method that enables companies to use data proactively is data mapping. Not only can it help users to extract insights but also make faster business decisions.
All You Need to Know About Data Mapping
Data mapping enable users to unify and transform large volumes of data (gathered from external and internal sources) into a format suitable for driving operational and analytical processes. It does so by matching source data fields with target data fields. It serves as the first step to facilitate data migration, data integration, and other data management tasks.
Data mapping is the fundamental part of data management and it helps users organize multiple types of data and converts it into an easy-to-understand and manageable system. In other words, the data mapping tools bridge differences between two systems or particular data models. Hence, when data is moved from a source, it is accurate and usable at the destination. Though data mapping has served as a common business function for quite some time, with the proliferation of data and sources, the process of data mapping has turned much complex and time-consuming - that needs automated solutions to keep it feasible for large data sets.
Data mapping tools can be used to handle diverse data of customers and partners. For example, data mapping tools can identify different phone numbers (present in multiple formats), identify them for what they are, and store all of the information in the same destination field instead of having them drift around by other names. Hence, one can easily organize data and enable simplified usage. Data mapping tools enable companies to analyze the audience’s behaviour, their commonalities and recognize errors if any. By doing so, companies can use the information to make improved business decisions.
Despite so many benefits, the data mapping will not impact if the tool is not right. Organizations that still rely on EDI mapping take a lot of time to map customer data, delaying the integration process further. The role of artificial intelligence-powered data mapping tool comes into play here.
Companies can leverage artificial intelligence to map different forms of data from one format to another – at speed and precision. Let’s see how.
Artificial Intelligence Improves Data Mapping
Artificial intelligence (AI) enables users to deliver predictions by recognizing errors such as duplicities, missing values, etc that can be further utilized in decision-making and ultimately value generation. In the example mentioned above, AI can be leveraged to identify phone numbers and assign them to a specific category, which, in turn, allows organizations to execute processes with ease and speed. Hence, AI-powered tools can not only map data sources to target fields with higher accuracy but also maintain data integrity.
In addition, it makes the process much faster, from months to minutes. As a result, the mapped data can be integrated and analyzed faster, thus enabling decision-making and better experiences.
Hence, to improve the quality of data mapping, maintain data integrity, and deliver maximum value, AI-powered tools play a central role.
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