Week 10: Customer Relations Management & Business Intelligence

What is Your Understanding of CRM?

Customer Relationship Management (CRM) is the management of all aspects of a customer’s relationship with an organisation to increase customer loyalty and retention as well as an organisation’s overall profitability. In other words, CRM allows a business to gain insights into their customers’ shopping and buying behaviours and treat each consumer as a valued individual.

Typically, a CRM system consists of customers contacting the organisation through various means such as call centres, web access, email, faxes and direct sales. The CRM system then tracks every one of these communications and provides access to the information generated across different systems from accounting to marketing. In doing this, CRM provides many benefits to users enabling them to;

• Provide Better Customer Service
• Improve Call Centre Efficiency
• Cross-sell Products More Effectively
• Help Sales Staff Close Deals Faster
• Simplify Marketing and Sales Processes
• Discover New Customers
• Increase Customer Revenues

Compare Operational and Analytical Customer Relationship Management.

Both Operational and Analytical Customer Relationship Management are the 2 main components of any CRM strategy. Despite this, they also have significant differences. While Operational CRM supports traditional types of transactional processing for day-to-day front office operations or systems that deal directly with customers, Analytical CRM does the opposite. Instead, its focus revolves around supporting back-office operations and strategic management, and includes all systems that don’t deal directly with the organisation’s customers. In this way, the primary difference between Operational and Analytical CRM can be summarised in the level of customer interaction it involves.

Describe and Differentiate the CRM Technologies used by Marketing Departments and Sales Departments

Although both use Operational CRM, the technologies used by Marketing and Sales departments are significantly different.  As modern business continues to develop, the primary goal of marketing has shifted so that it is now focused on trying to sell one customer as many products as possible. To support this objective, the CRM technologies used within this department allow them to gather and analyse customer information to deploy successful marketing campaigns.

In comparison, the CRM technologies used in the Sales Department are more focused on management. In this way, the two main aims for CRM in a sales department is to;

• Manage and organise customer account information that needs to be tracked
• Get customer information out of the heads of sales representatives and onto paper

With these goals in mind, CRM technologies suited to the Sales Department such as ‘Sales Force Automation’, automatically track the steps of the sales process, allowing management to focus on other things such as increasing customer satisfaction, building customer relationships and improving product sales.

How could a Sales Department use Operational CRM Technologies?

There are 3 main Operational CRM technologies that a sales department could use;

Sales Management systems such as “Sales Force Automation” automate each phase of the sales process. In this way, by using this type of system and its features such as calendars, alarm reminders and document generation, sales representatives can coordinate and manage their accounts. Additionally, this operational CRM technology can also be used by a sales department to analyse the organisation’s sales cycle and calculate how each individual sales representative is performing during the sales process.

Contact Management CRM systems are those technologies which help departments maintain customer contact information and identify prospective customers for future sales. With features such as organisational charts, detailed customer notes, and supplemental sale information, departments can use these technologies to help foster better customer relationships and maximise efficiency within the sales process. An example of a company who has done this is 3M, whose implementation of a contact management CRM system has allowed them to;

• Cut the time taken to familiarise sales professionals with new territories by 33%
• Increase management’s visibility of the sales process
• Decrease the time taken to qualify leads and assign sales opportunities by 40%

In comparison, Opportunity Management CRM systems focus on gaining new customers rather than retaining old ones. In this way, a sales department can use these CRM technologies to target sales opportunities by finding new customers of companies for future sales and gaining their loyalty by;

• Getting their attention
• Valuing their time
• Over-Delivering
• Frequently Contacting
• Generating a trustworthy mailing list
• Following Up

Describe Business Intelligence and its Value to Businesses

Business Intelligence (BI) is the applications and technologies that are used to gather, provide access to and analyse data and information to support decision-making efforts. In this way, BI is very valuable to businesses because similar to countries in war, an organisation in a competitive industry can only succeed if they have full knowledge of their own strengths and weaknesses as well as those of their opponents. Similarly, a certain school of thought draws parallels between the challenges faced within business and those of war as describes in Sun Tzu’s famous work, ‘The Art of War’. These central components of competitive business strategy that BI helps a business achieve are;

• The collection of information
• Discerning the patterns and meaning within this information
• Responding to the resultant information

Explain the Problem Associated with Business Intelligence. Describe the Solution to this Business Problem

The main problem associated with BI revolves around the decision-making capabilities of the managers and employees of an organisation. In every business, employees must make hundreds of decisions each day, and while these decisions can sometimes be based on fact, they are most often based on experience, accumulated knowledge and rule of thumb. This can often pose problems in that these skills can take years to develop, and even if an employee does acquire them they can still make errors in judgement.

For this reason, the solution to this problem lies in equipping organisational staff with BI systems and tools so that they can make effective decisions and shorten latency times. When used effectively, these systems can not only improve the quality of business decisions, but also help employees and management create an agile and intelligent enterprise where data is;

• Reliable
• Consistent
• Understandable
• Easily Manipulated

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. In order to perform this process, data mining tools are used which utilise a variety of algorithmic techniques to find patterns and relationships in large volumes of information and infer rules from them that can predict future behaviour and assist decision-making. In this way, data mining has several possible capabilities and outcomes. Two of these outcomes are Cluster Analysis and Statistical Analysis.

Cluster Analysis divides information sets into mutually exclusive groups that are as close together as possible to one another and the different groups are as far apart as possible. In this way, Cluster Analysis is extremely effective to segment customer information for CRM systems and help organisations identify customers with similar demographics, lifestyle behaviours and buying patterns.

Statistical Analysis performs such functions as information correlations, distributions, calculations and variance analysis. In this way, this outcome of data mining supplies knowledge workers with a large range of powerful statistics and capabilities, allowing them to build statistical models, examine the model’s assumptions and validity, and compare and contrast the various models to determine the best one for the particular business issue.