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Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services to satisfy customers.
Campaign and customer analysis help craft the right offers and learn from information gathered from past campaigns. Campaign management oversees all communication with customers across multiple channels, tracks their responses, and reports results. Data warehousing pulls customer information together from different systems and channels.
A customer data platform (CDP) is a collection of software which creates a persistent, unified customer database that is accessible to other systems. Data is pulled from multiple sources, cleaned and combined to create a single customer profile. This structured data is then made available to other marketing systems. [1]
The definition of an operational analytics processing engine (OPAP) [8] can be expressed in the form of the following six propositions: Complex queries: Support for queries like inner & outer joins, aggregations, sorting, relevance, etc. Low data latency: An update to any data record is visible in query results in under than a few seconds.
This includes online campaign data and customer journey data. 3rd party data – data delivered by data providers, which is available on the market for purchase. [6] There are also three main types of data collected by DMPs: Observed data – the digital footprint of internet users, i.e. search history or type of web browser used.
Customer data or consumer data refers to all personal, behavioural, and demographic data that is collected by marketing companies and departments from their customer base. [1] To some extent, data collection from customers intrudes into customer privacy , the exact limits to the type and amount of data collected need to be regulated.
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