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Customer intelligence (CI) as part of business intelligence is the process of gathering and analyzing 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 – basic key facts about the customer, such as their geographic location.
This data is then supplemented [2] with transaction data – reports of customer activity. This can be commercial information (for example purchase history from sales and order processing), interactions from 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 – 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 – used to monitor the popularity and usage of corporate web sites, 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 – 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 which 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 other organization administers its interactions with customers, typically using data analysis to study large amounts of information.
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.
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.
Salesforce management systems are information systems used in customer relationship management (CRM) marketing and management that help automate some sales and sales force management functions. They are often combined with a marketing information system, in which case they are often called CRM systems.
Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.
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.
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 in order 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.
Transpromotional ("transpromo") is a compound expression formed from the words "transaction" and "promotional". By adding relevant messages, companies can piggyback promotion or even advertising onto existing transaction-related documents, such as statements, invoices, or bills. Transpromotional documents combine CRM and data mining technology with variable data printing and location intelligence.
EPESI BIM is a web based, cloud-native CRM/ERP application to store, organize, access and share business records. Manage your data precisely, flexibly and easily, simplifying internal communication and making work-flow more efficient. Epesi has been designed as a Kickstarter project and provides "no code" and "low code" environment for developers. Epesi is an open-source, PHP/Ajax framework for rapid development of web-based, database-driven single page applications. The framework includes the Epesi CRM multi-user application. It requires PHP 7.x and MySQL or PostgreSQL database server on the server-side and can be accessed using any modern browser. Epesi framework and Epesi CRM application are released under MIT license.
Customer experience, sometimes abbreviated to CX, is the totality of cognitive, affective, sensory, and behavioral consumer responses during all stages of the consumption process including pre-purchase, consumption, and post-purchase stages. Nihat Tavşan and Can Erdem bring an extensive elucidation to the customer experience, encompassing the dimensions of consciousness, subjectivity, and interactional nature and define customer experience as the sum of subjective ideas regarding a product or service that occur at a conscious or subconscious level due to direct or indirect interaction of a customer with brand-related stimuli. Pine and Gilmore described the experience economy as the next level after commodities, goods, and services with memorable events as the final business product. Four realms of experience include esthetic, escapist, entertainment, and educational components. Tavşan and Erdem divided the customer experience into four categories based on the levels of cognitive and physical involvement of customers. These four categories are euphoric experiences, captive experiences, mellowing experiences, and conductive experiences.
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 contact-centric databases that provide a fully integrated approach to tracking all information and communication activities linked to contacts. Simple ones for personal use are included in most smartphones. The main reference standard for contact data and metadata, semantic and interchange, is the vCard.
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.
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.
Marketing automation refers to software platforms and technologies designed for marketing departments and organizations to more effectively market on multiple channels online and automate repetitive tasks.
Data-driven marketing is a process used by marketers to gain insights and identify trends about consumers and how they behave — what they buy, the effectiveness of ads, and how they browse. Modern solutions rely on big data strategies and collect information about consumer interactions and engagements to generate predictions about future behaviors. This kind of analysis involves understanding the data that is already present, the data that can be acquired, and how to organize, analyze, and apply that data to better marketing efforts. The intended goal is generally to enhance and personalize the customer experience. The market research allows for a comprehensive study of preferences.