Analytics Tools And Software
Expert-defined terms from the Certificate in Customer Service Analytics course at London School of International Business. Free to read, free to share, paired with a professional course.
A/B Testing – a method of comparing two versions of a customer‑service in… #
Related terms: control group, variant. Example: testing two email scripts for post‑call surveys. Practical application: improves response rates and satisfaction scores. Challenges: ensuring statistical significance and avoiding sample bias.
ABM (Account‑Based Marketing) – a strategy that aligns sales and marketin… #
Related terms: target account, personalization. Example: tailoring support dashboards for key enterprise clients. Practical application: deepens relationships and highlights service‑impact metrics. Challenges: data integration across silos and measuring ROI.
Adobe Analytics – a comprehensive web‑analytics platform that tracks user… #
Related terms: report suite, eVar. Example: monitoring live chat usage and conversion funnels. Practical application: identifies drop‑off points in self‑service portals. Challenges: steep learning curve and licensing costs.
Alteryx – a self‑service data‑preparation and analytics tool that enables… #
Related terms: workflow, predictive toolset. Example: blending call‑center logs with CRM data to calculate churn risk. Practical application: speeds up data blending for non‑technical analysts. Challenges: managing large data volumes and version control.
Amazon QuickSight – a cloud‑based business‑intelligence service that crea… #
Related terms: SPICE engine, ML Insights. Example: visualizing ticket‑resolution times across regions. Practical application: provides fast dashboards without on‑prem infrastructure. Challenges: limited custom visual types and data‑source connectivity.
Apache Spark – an open‑source distributed computing engine for big‑data p… #
Related terms: RDD, DataFrame. Example: real‑time sentiment analysis of social‑media mentions about support. Practical application: handles massive streaming logs from omnichannel platforms. Challenges: requires specialized skills and cluster management.
API Integration – the process of connecting different software systems th… #
Related terms: REST, webhook. Example: pulling ticket data from a help‑desk system into a BI tool. Practical application: ensures data consistency across analytics pipelines. Challenges: versioning, security, and latency.
Artificial Intelligence (AI) – the simulation of human intelligence proce… #
Related terms: machine learning, natural language processing. Example: AI‑driven chatbots that categorize inbound requests. Practical application: reduces manual tagging effort and improves routing. Challenges: bias, transparency, and model drift.
Attribution Modeling – a technique that assigns credit to various touchpo… #
Related terms: first‑click, linear. Example: allocating satisfaction score impact between phone, email, and chat. Practical application: informs budget allocation for support channels. Challenges: data fragmentation and multi‑touch complexity.
Automated Insights – software that automatically generates narrative expl… #
Related terms: natural language generation, reporting bot. Example: a tool that writes daily summaries of queue‑length trends. Practical application: saves analyst time and democratizes insights. Challenges: accuracy of language and contextual relevance.
Azure Machine Learning – a cloud service that enables building, training,… #
Related terms: ML Studio, pipeline. Example: predicting first‑call resolution likelihood from historical tickets. Practical application: integrates with Microsoft Dynamics for real‑time scoring. Challenges: cost management and model governance.
B2C Analytics – analytics focused on business‑to‑consumer interactions, e… #
Related terms: consumer behavior, segmentation. Example: tracking self‑service portal usage by retail shoppers. Practical application: uncovers pain points in consumer‑facing channels. Challenges: high volume of low‑value interactions and privacy considerations.
Bar Chart – a simple visual that compares categorical values using rectan… #
Related terms: vertical axis, horizontal axis. Example: displaying average handle time per support team. Practical application: quickly highlights outliers. Challenges: over‑crowding with many categories reduces readability.
Behavioral Segmentation – grouping customers based on actions such as pur… #
Related terms: RFM analysis, usage patterns. Example: creating a “high‑touch” segment for customers with frequent escalations. Practical application: tailors proactive outreach. Challenges: dynamic segment updates and data latency.
Big Data – extremely large data sets that require specialized processing… #
Related terms: volume, velocity, variety. Example: storing terabytes of call‑recording metadata for analytics. Practical application: enables deep pattern discovery. Challenges: storage costs, governance, and ensuring data quality.
Business Intelligence (BI) – technologies and practices for collecting, i… #
Related terms: dashboard, reporting. Example: a BI portal that shows SLA compliance across regions. Practical application: supports strategic decision‑making. Challenges: aligning metrics with business goals and avoiding information overload.
Call Center Analytics – analysis of telephony interactions to improve per… #
Related terms: queue metrics, IVR. Example: measuring average speed of answer during peak hours. Practical application: informs staffing and script adjustments. Challenges: integrating voice data with CRM and handling silent periods.
Chatbot Analytics – measurement of conversational bot interactions to ass… #
Related terms: intent recognition, fallback rate. Example: tracking resolution rate of automated chat sessions. Practical application: identifies knowledge‑base gaps. Challenges: sentiment detection accuracy and handling complex queries.
Clickstream Analysis – the study of the sequence of clicks a user makes o… #
Related terms: session, path analysis. Example: analyzing navigation from help‑center articles to ticket submission. Practical application: optimizes content placement. Challenges: cookie restrictions and data privacy.
Customer Effort Score (CES) – a metric that gauges how much effort a cust… #
Related terms: post‑contact survey, effort reduction. Example: asking “How easy was it to get your problem solved?” after a chat. Practical application: predicts churn risk. Challenges: survey fatigue and cultural bias.
Customer Journey Mapping – visual representation of the end‑to‑end experi… #
Related terms: touchpoint, pain point. Example: mapping steps from initial inquiry to ticket closure. Practical application: reveals gaps where analytics can be inserted. Challenges: keeping the map current as channels evolve.
Customer Lifetime Value (CLV) – the projected net profit attributed to th… #
Related terms: revenue per user, churn probability. Example: calculating CLV for high‑value enterprise accounts based on support spend. Practical application: prioritizes resource allocation. Challenges: accurate churn forecasting and data integration.
Data Lake – a centralized repository that stores raw data in its native f… #
Related terms: schema‑on‑read, object storage. Example: ingesting call recordings, chat logs, and CRM records into a lake. Practical application: provides flexible source for varied analytics. Challenges: governance, security, and preventing “data swamp”.
Data Mining – the process of discovering patterns and relationships in la… #
Related terms: association rules, clustering. Example: uncovering frequent co‑occurring issues in ticket descriptions. Practical application: informs knowledge‑base updates. Challenges: over‑fitting and ensuring actionable insights.
Data Visualization – the graphical representation of data to facilitate u… #
Related terms: chart types, dashboard. Example: heat‑map of call volume by hour of day. Practical application: enables rapid pattern recognition. Challenges: choosing appropriate visuals and avoiding misinterpretation.
Dashboards – interactive visual interfaces that aggregate key metrics for… #
Related terms: KPIs, drill‑down. Example: a real‑time SLA dashboard for supervisors. Practical application: supports operational decisions at a glance. Challenges: data latency and maintaining relevance.
Descriptive Analytics – analysis that summarizes historical data to answe… #
”. Related terms: reporting, trend analysis. Example: monthly report of ticket volume by category. Practical application: establishes baseline performance. Challenges: limited predictive power and potential for outdated insights.
Predictive Analytics – techniques that use statistical models to forecast… #
Related terms: regression, classification. Example: predicting likelihood of escalation based on initial call sentiment. Practical application: enables proactive interventions. Challenges: model accuracy, data drift, and interpretability.
Prescriptive Analytics – advanced analysis that recommends actions based… #
Related terms: optimization, decision engine. Example: suggesting optimal staffing levels to meet forecasted demand. Practical application: automates resource planning. Challenges: complexity of scenario modeling and integration with execution systems.
Event Tracking – the capture of specific user actions within a digital en… #
Related terms: custom dimension, tag. Example: logging when a customer clicks “Live Chat” on the support portal. Practical application: measures feature adoption. Challenges: correct implementation and tag management.
Excel Power Query – a data‑transformation add‑in for Microsoft Excel that… #
Related terms: M language, data mashup. Example: merging CSV exports from a ticketing system with survey results. Practical application: empowers analysts without coding. Challenges: performance limits with very large data sets.
Google Analytics – a widely used web‑analytics service that tracks site t… #
Related terms: property, goal. Example: measuring bounce rate from the support FAQ page. Practical application: identifies content gaps. Challenges: data sampling at high volumes and privacy regulations.
Heatmap – a visual that uses color intensity to represent data density or… #
Related terms: click intensity, session replay. Example: showing where users hover most on a troubleshooting guide. Practical application: informs UI redesign. Challenges: anonymization and ensuring statistical significance.
KPI (Key Performance Indicator) – a measurable value that demonstrates ho… #
Related terms: metric, target. Example: first‑contact resolution rate. Practical application: aligns teams around shared goals. Challenges: selecting meaningful KPIs and avoiding metric overload.
Machine Learning (ML) – a subset of AI that enables systems to learn from… #
Related terms: supervised learning, feature engineering. Example: clustering tickets by similarity to suggest relevant articles. Practical application: automates knowledge‑base maintenance. Challenges: data quality, model transparency, and ongoing training.
Natural Language Processing (NLP) – a field of AI that focuses on the int… #
Related terms: entity extraction, sentiment analysis. Example: extracting intent from email support requests. Practical application: routes tickets automatically. Challenges: language nuances, slang, and multilingual support.
Net Promoter Score (NPS) – a metric that measures customer loyalty based… #
Related terms: promoter, detractor. Example: surveying customers after a support interaction. Practical application: links service quality to brand advocacy. Challenges: low response rates and cultural bias.
Operational Analytics – analysis focused on day‑to‑day business processes… #
Related terms: process mining, real‑time monitoring. Example: monitoring average handle time during a product launch. Practical application: enables rapid operational adjustments. Challenges: data latency and aligning analytics with operational workflows.
Predictive Modeling – the creation of statistical models that estimate fu… #
Related terms: logistic regression, random forest. Example: building a model to forecast ticket surge after a software update. Practical application: informs capacity planning. Challenges: over‑fitting and data drift.
Real‑time Analytics – the processing of data as it arrives to provide imm… #
Related terms: stream processing, low latency. Example: dashboards that update queue length every minute. Practical application: supports dynamic staffing decisions. Challenges: infrastructure cost and handling data spikes.
Sentiment Analysis – the use of NLP techniques to determine the emotional… #
Related terms: polarity, subjectivity. Example: scoring customer comments on post‑call surveys. Practical application: surfaces emerging dissatisfaction trends. Challenges: sarcasm detection and language diversity.
Service Level Agreement (SLA) Monitoring – tracking compliance with agree… #
Related terms: response time, resolution time. Example: alerting managers when ticket‑resolution SLA breaches occur. Practical application: maintains contractual obligations. Challenges: data synchronization and defining realistic thresholds.
Tableau – a leading data‑visualization platform that enables interactive… #
Related terms: worksheet, calculated field. Example: visualizing ticket volume trends by product line. Practical application: empowers business users to explore data. Challenges: licensing cost and performance with large extracts.
Text Analytics – the process of extracting meaningful information from un… #
Related terms: topic modeling, keyword extraction. Example: identifying common phrases in escalated tickets. Practical application: informs FAQ updates. Challenges: handling misspellings and multilingual content.
Ticketing System Analytics – analysis of data generated by help‑desk plat… #
Related terms: ticket lifecycle, priority. Example: measuring average time to close low‑priority tickets. Practical application: highlights bottlenecks in support workflow. Challenges: data consistency across multiple systems.
Voice of the Customer (VoC) – a collection of customer feedback mechanism… #
Related terms: survey, feedback loop. Example: integrating post‑call NPS scores with CRM records. Practical application: drives continuous service improvement. Challenges: ensuring representative sampling and actionable insight extraction.
Web Analytics – the measurement, collection, analysis, and reporting of w… #
Related terms: session, bounce rate. Example: tracking visits to the self‑service knowledge base. Practical application: improves content relevance. Challenges: cross‑device tracking and privacy compliance.
Workflow Automation – the use of software to streamline repetitive tasks… #
Related terms: RPA, trigger. Example: automatically creating a follow‑up ticket when a chat ends with negative sentiment. Practical application: reduces manual effort and speeds response. Challenges: maintaining flexibility and avoiding over‑automation.
Zero‑Touch Resolution – a support approach where customers resolve issues… #
Related terms: self‑service, knowledge base. Example: an AI‑driven FAQ that answers common queries instantly. Practical application: cuts support costs and improves satisfaction. Challenges: ensuring content accuracy and handling complex cases.
AB Testing Platform – software that facilitates the design, execution, an… #
Related terms: variation, statistical significance. Example: testing two different chatbot welcome messages. Practical application: optimizes conversational flow. Challenges: traffic allocation and experiment duration.
Actionable Insights – findings that can be directly translated into busin… #
Related terms: recommendation, impact. Example: a report indicating that long hold times increase churn risk. Practical application: prompts immediate process changes. Challenges: filtering noise and ensuring stakeholder buy‑in.
Aggregated Data – data that has been compiled from multiple sources and s… #
Related terms: roll‑up, granularity. Example: weekly aggregate of total tickets per product line. Practical application: simplifies high‑level reporting. Challenges: loss of detail and potential misinterpretation.
Analytics Maturity Model – a framework that assesses an organization’s ca… #
Related terms: stage, roadmap. Example: moving from descriptive to predictive analytics in the support function. Practical application: guides investment planning. Challenges: cultural resistance and skill gaps.
Anomaly Detection – techniques that identify data points deviating from e… #
Related terms: outlier, threshold. Example: flagging a sudden spike in ticket volume for a specific product. Practical application: early warning for service disruptions. Challenges: defining normal baselines and avoiding false alarms.
Application Programming Interface (API) – a set of rules that allows soft… #
Related terms: endpoint, authentication. Example: using a REST API to fetch real‑time ticket status into a dashboard. Practical application: enables seamless data flow. Challenges: version control and rate limiting.
Artificial Neural Network (ANN) – a computing system inspired by biologic… #
Related terms: layers, backpropagation. Example: classifying incoming emails into support categories. Practical application: handles non‑linear relationships. Challenges: requires large training data and interpretability is limited.
Attribute Enrichment – the process of adding external data to existing re… #
Related terms: demographics, third‑party data. Example: appending industry information to customer accounts. Practical application: enables more precise segmentation. Challenges: data licensing and matching accuracy.
Automation Hub – a centralized platform that orchestrates multiple roboti… #
Related terms: bot, orchestration. Example: coordinating ticket routing bots across email, chat, and social channels. Practical application: streamlines cross‑channel operations. Challenges: governance and monitoring bot performance.
Batch Processing – the execution of a series of jobs on a set of data at… #
Related terms: ETL, cron job. Example: nightly aggregation of call logs for trend analysis. Practical application: reduces load on production systems. Challenges: data freshness and error handling.
Business Rules Engine (BRE) – a system that executes conditional logic to… #
Related terms: rule set, policy. Example: automatically escalating tickets that exceed SLA thresholds. Practical application: enforces consistent handling. Challenges: rule maintenance and conflict resolution.
Cache Layer – a temporary storage component that speeds up data retrieval #
Related terms: in‑memory, Redis. Example: caching recent ticket metrics for dashboard refreshes. Practical application: improves performance for real‑time reporting. Challenges: cache invalidation and data consistency.
Churn Prediction – modeling that estimates the probability of a customer… #
Related terms: survival analysis, propensity score. Example: using support interaction frequency to predict churn risk. Practical application: enables targeted retention campaigns. Challenges: imbalanced data and model interpretability.
Cluster Analysis – a statistical method that groups objects based on simi… #
Related terms: K‑means, hierarchical clustering. Example: clustering tickets by issue type to discover hidden categories. Practical application: refines taxonomy. Challenges: determining optimal number of clusters and handling noisy data.
Cold‑Start Problem – difficulty in making accurate predictions for new us… #
Related terms: bootstrapping, content‑based filtering. Example: recommending support articles to a first‑time caller. Practical application: improves initial experience. Challenges: lack of historical interaction data.
Compliance Reporting – the generation of reports that demonstrate adheren… #
Related terms: GDPR, PCI DSS. Example: audit logs of data access for support agents. Practical application: mitigates legal risk. Challenges: data retention policies and cross‑jurisdictional rules.
Correlation Analysis – statistical technique to assess the strength and d… #
Related terms: Pearson, Spearman. Example: examining correlation between call duration and satisfaction score. Practical application: identifies drivers of performance. Challenges: causation vs. correlation and multicollinearity.
Customer Satisfaction (CSAT) – a metric that measures how satisfied custo… #
Related terms: rating scale, post‑contact survey. Example: asking “How satisfied are you with today’s support?” after a chat. Practical application: tracks service quality over time. Challenges: survey timing and response bias.
Data Governance – the overall management of data availability, usability,… #
Related terms: stewardship, policy. Example: establishing data ownership for ticket fields. Practical application: ensures reliable analytics. Challenges: aligning stakeholders and enforcing standards.
Data Warehouse – a centralized repository optimized for query and analysi… #
Related terms: star schema, OLAP. Example: consolidating CRM, ticket, and billing data for reporting. Practical application: provides a single source of truth. Challenges: ETL complexity and latency.
Decision Tree – a predictive model that maps observations about an item t… #
Related terms: leaf node, splitting criterion. Example: predicting whether a ticket will be resolved on first contact. Practical application: interpretable rules for agents. Challenges: over‑fitting and handling categorical variables.
Dimensional Modeling – a design technique for data warehouses that struct… #
Related terms: fact table, dimension table. Example: a fact table of ticket events with dimensions for agent, product, and time. Practical application: simplifies reporting. Challenges: maintaining slowly changing dimensions.
Distributed Tracing – a method for tracking requests as they propagate th… #
Related terms: span, trace ID. Example: following a support request from web front‑end to backend ticketing service. Practical application: identifies latency bottlenecks. Challenges: instrumentation overhead and data volume.
ETL (Extract, Transform, Load) – a process that extracts data from source… #
Related terms: pipeline, staging area. Example: nightly ETL that moves call logs into a data warehouse. Practical application: prepares data for analytics. Challenges: error handling and schedule coordination.
Exploratory Data Analysis (EDA) – an approach to analyzing data sets to s… #
Related terms: box plot, distribution. Example: using histograms to view ticket age distribution. Practical application: uncovers data quality issues. Challenges: time‑consuming and may miss hidden patterns.
Feature Engineering – the process of creating new variables from raw data… #
Related terms: derived feature, encoding. Example: creating “time‑of‑day” and “day‑of‑week” features from timestamps. Practical application: boosts predictive accuracy. Challenges: domain expertise and over‑complexity.
Feedback Loop – a system where output information is used as input to ref… #
Related terms: closed‑loop, continuous improvement. Example: feeding CSAT scores back into agent training programs. Practical application: drives ongoing service enhancements. Challenges: latency and ensuring actionable insight.
Forecasting – the use of historical data to predict future values #
Related terms: time series, seasonality. Example: forecasting ticket volume for the upcoming holiday season. Practical application: informs workforce planning. Challenges: handling irregular spikes and model selection.
Granular Data – data that retains a high level of detail, often at the tr… #
Related terms: micro‑data, detail. Example: each individual chat message logged with timestamps. Practical application: enables deep dive analyses. Challenges: storage cost and processing overhead.
Hybrid Cloud Analytics – a strategy that combines on‑premises and cloud r… #
Related terms: multi‑cloud, data federation. Example: running Spark jobs in a private cluster while leveraging QuickSight for visualization. Practical application: balances security with scalability. Challenges: data synchronization and governance.
Incident Management – the process of handling unplanned interruptions to… #
Related terms: ticket escalation, root cause analysis. Example: tracking the resolution timeline of a system outage affecting support agents. Practical application: improves service reliability. Challenges: cross‑department coordination and documentation.
In‑Memory Computing – technology that stores data in RAM for faster proce… #
Related terms: RAM‑disk, cache. Example: using an in‑memory engine to calculate real‑time SLA breaches. Practical application: reduces query latency. Challenges: volatility and cost.
Incident Trend Analysis – evaluating patterns of incidents over time to d… #
Related terms: heatmap, root cause. Example: identifying a spike in password reset tickets after a UI change. Practical application: informs preventive measures. Challenges: attributing cause in multi‑factor environments.
Integration Platform as a Service (iPaaS) – cloud‑based solutions that en… #
Related terms: connector, workflow. Example: connecting a CRM, ticketing system, and analytics platform via an iPaaS. Practical application: streamlines data flow without custom code. Challenges: latency and vendor lock‑in.
Jira Service Management Analytics – reporting capabilities within Atlassi… #
Related terms: issue type, SLM. Example: dashboards showing average resolution time per request type. Practical application: provides native insights for IT support teams. Challenges: limited advanced analytics and customization.
KPI Dashboard – a visual display focused on key performance indicators #
Related terms: traffic light, trend line. Example: a dashboard showing NPS, CSAT, and first‑contact resolution in real time. Practical application: offers quick health checks for managers. Challenges: selecting the right KPIs and avoiding clutter.
Log Analytics – the examination of log files to derive operational insigh… #
Related terms: ELK stack, syslog. Example: parsing server logs to detect spikes in error codes during a release. Practical application: supports proactive issue detection. Challenges: log volume and unstructured nature.
Machine‑Learning Ops (MLOps) – practices that combine ML system developme… #
Related terms: model registry, pipeline automation. Example: automating the retraining of a churn model after each data refresh. Practical application: maintains model accuracy over time. Challenges: version control and monitoring model drift.
Metadata Management – the administration of data about data, such as defi… #
Related terms: data catalog, semantic layer. Example: documenting the meaning of “ticket priority” across systems. Practical application: improves data discoverability. Challenges: keeping metadata up‑to‑date.
Metric Hierarchy – a structured arrangement of metrics from high‑level ag… #
Related terms: top‑level KPI, drill‑down. Example: overall SLA compliance broken down by region, then by team. Practical application: enables focused analysis at each level. Challenges: maintaining consistency across hierarchies.
Natural Language Understanding (NLU) – a subset of NLP that focuses on ma… #
Related terms: intent detection, entity extraction. Example: interpreting a user's request to “reset my password” in a chat. Practical application: improves routing accuracy. Challenges: ambiguous phrasing and domain‑specific vocabulary.
Neural Machine Translation (NMT) – deep‑learning models that translate te… #
Related terms: encoder‑decoder, attention mechanism. Example: translating support tickets from Spanish to English for analysis. Practical application: enables multilingual analytics. Challenges: quality for low‑resource languages and computational cost.
Operational Dashboard – a real‑time visual tool that monitors day‑to‑day… #
Related terms: live view, alerting. Example: a dashboard showing live queue depth and agent availability. Practical application: supports immediate operational decisions. Challenges: data freshness and alert fatigue.
Outlier Detection – identifying data points that differ significantly fro… #
Related terms: z‑score, robust statistics. Example: spotting a ticket that took 48 hours to resolve versus the typical 4‑hour range. Practical application: targets process improvements. Challenges: defining thresholds and handling legitimate extremes.
Predictive Maintenance – using analytics to anticipate equipment failures… #
Related terms: condition monitoring, failure mode. Example: forecasting when a call‑routing server may fail based on error logs. Practical application: schedules proactive repairs to avoid service disruption. Challenges: data collection and model reliability.
Process Mining – extracting process models from event logs to visualize a… #
Related terms: event log, conformance checking. Example: mapping the real sequence of steps a ticket follows from creation to closure. Practical application: reveals inefficiencies and deviations. Challenges: log completeness and privacy concerns.
Quality of Service (QoS) – a set of performance metrics that measure serv… #
Related terms: bandwidth, service level. Example: monitoring network QoS to ensure voice calls remain clear. Practical application: maintains a high‑quality support experience. Challenges: measuring across heterogeneous networks.
Real‑time Data Stream – continuous flow of data that can be processed ins… #
Related terms: Kafka, streaming API. Example: ingesting chat messages as they are typed for live sentiment analysis. Practical application: enables immediate response to emerging issues. Challenges: handling bursts and ensuring fault tolerance.
Reference Data – static data used to categorize or classify other data, s… #
Related terms: lookup table, code list. Example: using a reference table to map product SKUs to product families. Practical application: ensures consistent reporting. Challenges: keeping reference data synchronized across systems.
Regression Analysis – statistical method for estimating relationships amo… #
Related terms: linear regression, coefficients.