The top 10 CRM analytics buzzwords

Get the top CRM analytics terms and definitions and learn how analyzing customer interactions can help improve the customer experience and marketing efforts.

CRM analytics can provide businesses with a wealth of information about customer behaviors, sales and marketing

campaigns, website performance and more. We've put together this list of the top terms and definitions you need to know to understand CRM analytics and successfully analyze customer interactions.

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Table of Contents

The top 10 CRM analytics buzzwords

1. CRM analytics
2. Customer relationship analysis
3. OLAP
4. Web analytics
5. Web mining
6. Clickstream analytics
7. Predictive analytics
8. Speech analytics
9. Text analytics
10. Real-time analytics

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The top 10 CRM analytics buzzwords

 CRM analytics encompasses all programming that analyzes and presents customer data, with the goal of better enabling organizations to make business decisions. CRM analytics can provide customer segmentation, profitability analysis, personalization, event monitoring, what-if scenarios and predictive modeling. CRM analytics is said to improve customer relationships and supply chain management in many scenarios, and often results in lowered costs and prices.

 Customer relationship analysis (CRA) is the actual process of collecting and analyzing data about customers in order to better understand their relationship to the organization, improve sales and customer service and reduce costs. CRA is a form of online analytical processing (OLAP) and can employ data mining.

 OLAP, or online analytical processing, is a type of computer processing that allows a user to extract and view data from multiple points of view. A user wanting to analyze CRM data might perform OLAP in order to do a specific, interactive analysis of the data.

  • Find out how OLAP tools are used in knowledge discovery.

 Web analytics is the process of analyzing the behavior of website visitors, and is often used as part of CRM analytics. Web analytics is usually used by companies looking to retain or attract more online visitors and/or increase online spending. Web analytics tools can monitor the geographical regions of visitors, track clickthrough and drilldown behavior, monitor purchases and predict the future purchases of customers.

 Web mining is the integration of information extracted through traditional data mining techniques with information gathered on the Internet. Web mining is used to analyze patterns using three techniques: content mining (used to examine data collected by search engines), structure mining (used to examine data related to a particular website) and usage mining (used to examine data related to a specific user's browser). In CRM, Web mining is often used to help companies better understand customer behavior and evaluate the successfulness of a marketing campaign or a website.

 Clickstream analytics is the process of collecting and analyzing data about which pages website visitors visit, and what order they visit them in. Clickstream analysis is split into two levels: traffic analysis and e-commerce analysis. Traffic analysis collects clickstream data based on the user's experience with the website (how many pages the user sees, how fast they load, etc.). E-commerce analysis uses this clickstream data to determine site effectiveness.

 Predictive analytics focuses on predicting future probabilities and trends. The "predictor" is the variable used to predict future behaviors, and is the main element of a predictive analytics tool. In CRM, predictive analytics is often used to predict customer behavior.

 Speech analytics mines customer calls for data, providing insight into customer behaviors. Often used in the call center, speech analytics can be used to reduce operating expenses, improve customer experience, increase revenue and reduce customer attrition. Speech analytics data can also be used to improve up-sell and cross-sell opportunities and establish targeted marketing campaigns.

 Text analytics obtains and analyzes unstructured, text-based customer data from customer surveys and text-based customer interactions. As Web 2.0 technology and social networking gains in popularity, some experts suggest that text analytics may take on a greater role in helping companies analyze their customer relationships.

 Real-time analytics allows users to analyze available data in real time or near real time. Real-time analytics is often used in CRM analytics, letting users track and manage customer behaviors as they occur. Real-time analytics is most often used between call centers and marketing departments.

 


Buzzword definitions provided by WhatIs.com

 


 

This was first published in February 2009

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