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Customer intelligence (CI) as part of business intelligence is the process of gathering information regarding customers, and their details and activities, to build deeper and more effective customer relationships and improve decision-making by vendors. [1] [ verification needed ]
Customer intelligence is a key component of effective customer relationship management (CRM), and when effectively implemented it is a rich source of insight into the behaviour and experience of a company's customer base.
As an example, some customers walk into a store and walk out without buying anything. Information about these customers/prospects (or their visits) may not exist in a traditional CRM system, as no sales are entered on the store cash register. Although no commercial transaction took place, knowing why customers leave the store (perhaps by asking them, or a store employee, to complete a survey) and using this data to make inferences about customer behaviour, is an example of CI.
Customer intelligence begins with reference data which contain basic key facts about the customer, such as their geographic location.
This data is then supplemented [2] with transaction data to achieve reports of customer activity. This can be commercial information (for example purchase history from sales and order processing), and interactions with service contacts over the phone and via email.
A further subjective dimension can be added, in the form of customer satisfaction surveys or agent data.
Finally, a company can use competitor insight and mystery shopping to get a better view of how their service benchmarks in the market.
By mining this data, and placing it in context with wider information about competitors, conditions in the industry, and general trends, information can be obtained about customers' existing and future needs, how they reach decisions, and predictions made about their future behavior. [3] [4] [ verification needed ]
Speech analytics can be used to monitor telephone conversations taking place between companies and customers, using phonetic analysis or speech to text to find keywords and phrases, classify call types and identify trends. [5] [ verification needed ]
Click tracking can be used to monitor the popularity and usage of corporate websites, this data can provide clues to product interest and buying intention. For example, a company may infer a customer is interested in purchasing a particular service if they are spending time browsing specific product pages. [6] [ verification needed ]
Customer relationship management are software solutions used for to manage customer relationships which can store data on the quantity, type and category of customer and prospect contacts.
Frontline data capture may (or may not) form part of a CRM software solution, but which is used by front line agents to record more subjective data regarding customer contacts, such as the root cause of the customer picking up the phone (e.g. they received their bill) or their emotional state.
Customer satisfaction and market research surveys, often mined via text analytics, which can additionally be applied, for customer intelligence purposes, to contact center notes, e-mail, and other textual sources.
Customer intelligence provides a detailed understanding of the experience customers have in interacting with a company, and allows predictions to be made regarding reasons behind customer behaviors.
This knowledge can then be applied to support more effective and strategic decision making – for example, understanding why customers call makes it easier to predict (and plan to reduce) call volumes in a contact centre.
Customer relationship management (CRM) is a process in which a business or another organization administers its interactions with customers, typically using data analysis to study large amounts of information.
Business intelligence (BI) consists of strategies, methodologies, and technologies used by enterprises for data analysis and management of business information. Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.
A management information system (MIS) is an information system used for decision-making, and for the coordination, control, analysis, and visualization of information in an organization. The study of the management information systems involves people, processes and technology in an organizational context. In other words, it serves, as the functions of controlling, planning, decision making in the management level setting.
Personalized marketing, also known as one-to-one marketing or individual marketing, is a marketing strategy by which companies leverage data analysis and digital technology to deliver individualized messages and product offerings to current or prospective customers. Advancements in data collection methods, analytics, digital electronics, and digital economics, have enabled marketers to deploy more effective real-time and prolonged customer experience personalization tactics.
Database marketing is a form of direct marketing that uses databases of customers or potential customers to generate personalized communications in order to promote a product or service for marketing purposes. The method of communication can be any addressable medium, as in direct marketing.
Data management comprises all disciplines related to handling data as a valuable resource, it is the practice of managing an organization's data so it can be analyzed for decision making.
The eCRM or electronic customer relationship management coined by Oscar Gomes encompasses all standard CRM functions with the use of the net environment i.e., intranet, extranet and internet. Electronic CRM concerns all forms of managing relationships with customers through the use of information technology (IT).
Speech analytics is the process of analyzing recorded calls to gather customer information to improve communication and future interaction. The process is primarily used by customer contact centers to extract information buried in client interactions with an enterprise. Although speech analytics includes elements of automatic speech recognition, it is known for analyzing the topic being discussed, which is weighed against the emotional character of the speech and the amount and locations of speech versus non-speech during the interaction. Speech analytics in contact centers can be used to mine recorded customer interactions to surface the intelligence essential for building effective cost containment and customer service strategies. The technology can pinpoint cost drivers, trend analysis, identify strengths and weaknesses with processes and products, and help understand how the marketplace perceives offerings.
Enterprise feedback management (EFM) is a system of processes and software that enables organizations to centrally manage deployment of surveys while dispersing authoring and analysis throughout an organization. EFM systems typically provide different roles and permission levels for different types of users, such as novice survey authors, professional survey authors, survey reporters and translators. EFM can help an organization establish a dialogue with employees, partners, and customers regarding key issues and concerns and potentially make customer-specific real time interventions. EFM consists of data collection, analysis and reporting.
Customer attrition, also known as customer churn, customer turnover, or customer defection, is the loss of clients or customers.
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. With that in mind, the productive system is considered from its beginning at the production level, to the end of the cycle at the consumer. Customer analytics plays an important role in the prediction of customer behavior.
Customer experience, sometimes abbreviated to CX, is the totality of cognitive, affective, sensory, and behavioral customer responses during all stages of the consumption process including pre-purchase, consumption, and post-purchase stages.
Lead scoring is a methodology used to rank prospects against a scale that represents the perceived value each lead represents to the organization. The resulting score is used to determine which leads a receiving function will engage, in order of priority.
A contact manager is a software program that enables users to easily store and find contact information, such as names, addresses and telephone numbers. They are databases that provide an integrated approach to tracking information and communication activities linked to contacts. Simple ones for personal use are included in most smartphones. Sophisticated contact managers provide calendar sharing features and allow colleagues to access the same database.
Attensity provides social analytics and engagement applications for social customer relationship management. Attensity's text analytics software applications extract facts, relationships and sentiment from unstructured data, which comprise approximately 85% of the information companies store electronically.
Customer value maximization (CVM) is a real-time service model that, proponents say, goes beyond basic customer relationship management (CRM) capabilities, identifying and capturing maximum potential from prospective and existing customers. Customer value maximization is about:
The fields of marketing and artificial intelligence converge in systems which assist in areas such as market forecasting, and automation of processes and decision making, along with increased efficiency of tasks which would usually be performed by humans. The science behind these systems can be explained through neural networks and expert systems, computer programs that process input and provide valuable output for marketers.
Allegiance, Inc is a voice of customer (VoC) and enterprise feedback management (EFM) technology platform that let organizations collect and analyze consumer data in real time. The company was recognized for providing large companies and government agencies with a range of big data mining tools, and it was listed as one of the GSA’s approved vendors. Allegiance’s clients include VMware, Citi, AeroMexico, Nalco, Ameriprise, Adobe and Dell, and it was ranked as one of Inc. magazine’s fastest-growing companies.
Workforce optimization (WFO) is a business strategy that integrates business performance considerations with workforce management. The strategy involves automating processes, data visibility, compliance on legislation and solving business problems related to staffing. It is used by call centers to improve workforce management and agent performance.
A data management platform (DMP) is a software platform used for collecting and managing data. DMPs allow businesses to identify audience segments, which can be used to target specific users and contexts in online advertising campaigns. They may use big data and artificial intelligence algorithms to process and analyze large data sets about users from various sources. Advantages of using DMPs include data organization, increased insight on audiences and markets, and more effective advertisement budgeting. On the other hand, DMPs often have to deal with privacy concerns due to the integration of third-party software with private data. This technology is continuously being developed by global entities such as Nielsen and Oracle.
