- What is your understanding of CRM?
Customer relationship management (CRM) – involves managing
all aspects of a customer’s relationship with an organisation to increase
customer loyalty and retention and an organisation's profitability. CRM helps
companies make the their interactions with customers seem friendlier through
individualisation
- Compare operational and analytical customer relationship management.
Operational CRM - supports traditional transactional processing
for day-to-day front-office operations or systems that deal directly with the
customers. Focuses on organising and simplifying the management of customer
information. It uses a database to provide consistent information about a
company’s interaction with a customer.
Analytical CRM -supports back-office operations and strategic
analysis and includes all systems that do not deal directly with the customers. Analytical CRM uses data
mining to provide strategic data about customers. Data mining uses various
modelling and analysis techniques to find patterns and relationships to make
accurate predictions .
Predictions might include;
} Which
customers to market to
} Up
selling / Cross selling
} Retaining
good customers
- Describe and differentiate the
CRM technologies used by marketing departments and sales departments
Marketing and operational CRM-Marketing departments are able to
transform to this new way of doing business by using CRM technologies that
allow them gather and analyse customer information to deploy successful
marketing campaigns.In fact, a marketing campaigns success is directly
proportional to the organisations ability to gather and analyse the right
information.The three primary operational CRM technologies a marketing
department can implement to increase customer satisfaction are;
-list generator-compile
customer information from a variety of sources and segment the information for
different marketing campaigns.
-Campaign management
systems- guide users through marketing campaign performing such tasks as
campaign definition, planning, scheduling, segmentation and success analysis.
-Cross selling-is
selling additional products or services to a customer. Up-selling is increasing
the value of the sale.
Sales and operational CRM is big business.Salesforce.com is
the worldwide leader in on demand customer relationship management services,
with over 50 000 customers worldwide – including companies covering many
products and services to ‘wow’ customers. The three primary operational CRM
technologies a sales department can implement so increase customer satisfaction
are;
Sales management CRM systems-automate each phase of the
sales process, helping individual sales representatives co-ordinate and
organise all of their accounts.
Contact management CRM systems-maintains customer contact
information and identifies prospective customers for future sales.
Opportunity management CRM systems- target sales
opportunities by finding new customers or companies for future sales.
3.How does CRM help businesses find and retain their most valuable customers?
Analytical CRM data can help businesses find and retain their most valuable customers. Analytical CRM enhances and supports decision making by identifying patterns in customer behaviour that has been collated from various operational CRM systems. Analytic CRM systems aggregate, analysis and disseminate customer information that a organisation can capitalise thereby acquire new customers, improve customer service, and therefore increase customer satisfaction.
Analytical CRM information can assist in:
➢ Giving customers what they want.
➢ Expanding its customer base with new clients.
➢ Finding out what the organisation does best.
➢ Giving the organisation a competitive advantage.
➢ Reactivating inactive customers.
➢ Improving customer service.
4. Describe business intelligence and its value to businesses
Business intelligence (BI) –applications and technologies used to gather, provide access to, and analyze data and information to support decision-making efforts. With the successful implementation of BI systems and organization can expect to receive the following; single point of access to information for all users, bi across organizational departments, up-to-the-minute information for everyone.
Many Businesses are finding that they must identify and meet the fast-changing needs and wants of different customer segments in order to stay competitive in today’s consumer-centric market. BI can tell companies things like;
} Determine who are the best and worst customers thereby gaining insight into where it needs to concentrate more for its future sales
} Identify exceptional sales people
} Determine whether or not campaigns have been successful
} Determine in which activity they are making or losing money.
5. Explain the problem associated with business intelligence. Describe
the solution to this business problem
Companies can have a lot of data, however they are not able
to benefit from levering this information and turning it into useful data for
analytical and strategic decision making.
The issue most organisations are facing today is that it is
next to impossible to understand their own strengths and weaknesses, let alone
their enemies, because the enormous amount of organisational data is
inaccessible to all but the IT department. The problem: data rich, information
poor
6.What are two possible outcomes a company could get from using data
mining?
Data Mining is the process of analysing data to extract
information not offered by the raw data alone. Data mining and also begin at a
summary information level and progress through increasing levels to detail
(drilling down) or the reverse (drilling up). Two possible outcomes a company
could get from using data mining are:
Cluster Analysis - a technique used to divide information
set into mutually exclusive groups such that the members of each group are as
close together as possible to one another and the different groups are as far
apart as possible. Data mining tools that 'understand' human language are
finding unexpected applications in medicine.
Association detection - reveals the degree to which
variables are related and the nature and frequency of these relationships in
the information. One of the most common forms of association detection analysis
is market based analysis, which analyses such items as websites and checkout
scanner information to detect customers' buying behaviour and predict future
behaviour.