1. What is your understanding of CRM?
Customer Relationship Management is the focus of the relationship between the customer and the business. It aims to meet the needs and wants of the customer and in return the business receives customer retention, loyalty and, therefore, guaranteed productivity.
Includes a one-to-one relationship between a customer and a seller.
One simple idea “Treat different customers differently.” Helps keep profitable customers and maximizes lifetime revenue from them.
The following article http://searchcrm.techtarget.com/definition/CRM defines a CRM as:
“CRM is an information industry term for methodologies, software, and usually Internet capabilities that help an enterprise manage customer relationships in an organised way. For example, an enterprise might build a database about its customers that described relationships in sufficient detail so that management, salespeople, people providing service, and perhaps the customer directly could access information, match customer needs with product plans and offerings, remind customers of service requirements, know what other products a customer had purchased, and so forth.”
2. Compare operational and analytical customer relationship management.
Operational CRM
Is involved with traditional transactional processing for day-to-day front of house operations (sales, marketing and service) that deal directly with the customers. Each interaction with a customer is generally added to a customer's history, and staff can retrieve information on customers from the database as necessary. It simplifies and orderly creates databases of customer information.
Analytical CRM
Is involved with back of house operations and strategic analysis which does not deal directly with the customers. Data gathered is analysed to segment customers or to identify cross- and up-selling potential. This system uses data mining to gather strategic information/data on customers. This can assist in making forecasts and predictions e.g. retaining customers.
http://www.fidis.net/typo3temp/tx_rlmpofficelib_a219f6551f.jpg -shows the relationship between the two.
3. Describe and differentiate the CRM technologies used by marketing departments and sales departments.
MARKETING
1. List generator – gathers customer information from an array of sources and uses the information in the relevant sectors. E.g. for website questionnaires, customer lists, website visits. This information provides the organisation with the tools it needs to target its customer base.
2. Campaign management system – guides users through marketing campaigns e.g. in planning and scheduling. These systems can calculate results for return on investment for each marketing campaign.
3. Cross-selling and up-selling
Cross-selling: selling additional products or services.
Up-selling: increasing the value of the sale.
SALES
1. Sales Management- which tracks each stage of the sales process, which assists sales representatives in maintaining all of their customer records (including accounts). E.g calendars for events, alarms for meetings.
2. Contact Management- holds customer contact details (which is beneficial for future sales as you can send emails of upcoming sales). It contains features including; customer notes and telephone number and name display.
3. Opportunity Management- Aims to create sale opportunities by finding and attracting new customers or companies for future sales. These systems determine potential customers and competitors and detail selling information including budgets.
4. How could a sales department use operational CRM technologies?
The department could use the technologies to maintain its customers records on purchases, how frequently they shop, etc. It could use the sales force automation, (SFA) a system that automatically tracks all of the steps in the sales process to ensure that the process runs smoothly, efficiently and effectively.
5. Describe business intelligence and its value to businesses
http://searchdatamanagement.techtarget.com/definition/business-intelligence describes business intelligence (BI) as:
“A broad category of applications and technologies for gathering, storing, analysing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.”
Its valuable to business as the market is forever changing and advancing and BI enables businesses to identify, address and meet the needs of their customers which helps them maintain a competitive edge. It allows business users to receive data for analysis. For example BI provides valuable information in:
- Determining who their customer base is, enabling the business to correctly market their product.
- Identifying exceptional sales people through their high productivity figures and continual cross-selling sales.
- Determining whether or not campaigns have been successful through customer retention figures.
- Determining whether the business is profitable.
It also provides a single point of access to information for all users, it can be used in every step of the value chain and gives up-to-the-minute information for users.
6. Explain the problem associated with business intelligence. Describe the solution to this business problem.
'Data rich, information poor'
Technology is on constantly advancing and, therefore, so is the amount of information and data that is being provided in organisational systems and databases. It can take hours, days or sometimes weeks to gather and retrieve different sources of information needed in organisations when compiling things like business reports. Business Intelligence systems can solve this problem as they can provide all the information needed in databases where relationships can be linked, providing data involving aspects like customer sales and contact details, more freely to the sales reps.
7. What are two possible outcomes a company could get from using data mining?
Association Detection- which will reveal the degree to which variables are related and the nature and frequency of these relationships in the information. E.g. buying behaviour. Organisations can use this to make predictions of further purchases as well as opportunities for cross selling.
Statistical analysis- which performs functions such as information correlations, distributions, calculations, and variance analysis. The organisation can use this tool to make forecasts and predictions made on the basis of time-series information.
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