The Customer Intelligence Cycle in CRM
Successful CCEs adhere to customer intelligence Lifecycle. This is a closed-loop business process that has four steps. We will be discussing this four-step in order to throw more light on what customer intelligence Lifecycle is
#1 Capturing as part of the customer intelligence cycle
The capture phase extracts the customer interaction data from operational systems and then integrate and store the data for easy retrieval. What we are saying here is that, under the capture stage, the system extracts information from front-line applications and store the information where it can be used by back offices to make decisions concerning the customers.
#2 Analysis phase as part of the customer intelligence cycle
During the analysis phase, business analysis creates a report of customer behaviour, define customer segments, and create predictive models that determine what recommendations or effects to make to customers. Under analysis, a Business Analyst works on information that has been gathered at the capture stage; this will give the organization an insight into customers purchase behaviours and how the customer wishes to be served. This will now allow the organization to segment their customers and come up with goods and services that will meet up with their needs.
At the planning phase, the organization uses the knowledge gained from analyzing customer information to create rules that will help the organization to optimize customer interactions. These rules enable the business to deliver the right offer to the right customer, through the right channel at the right time.
The interact phase involves executing these rules in various touch point systems, such as web and call centres. Here, the action is taken to optimize customer interaction across all channels. They then capture the result, and repeat the cycle, refining their plans based on experiences that they have had with their customers over the years.
A critical component of customer-centric strategies
The objective of any customer-centric strategy is to have a 360 view of customers. In order for an organization to achieve this, there is a need for them to consider three vital components that produce value and speed today’s customer-centric business strategies required.
#1 Data as part of the customer intelligence cycle
Data includes all information required about the customer to extend solutions across contact channels or product lines within the enterprise. There are a lot of data that are required in order to give customers total experience. But one thing is certain; the right data should be delivered to the right channel in order to get the right result.
The organization should properly organize customers’ data in a way that it will be useful. They must be able to update their data without hindrance.
Timing is also very important, the organization needs to attend to customers’ issues as they come in, this would help the organization to drive real-time analytics and affect customer treatments applied in real-time at the point of interaction. The organization also needs to adopt real-time analytics so that they can be well informed when two customers share the same information. Two customers might have the same thing in common. A customer may present self as an ordinary person, whereas he is a VIP, real times analytics and quality across all channels within minutes/. Take, for example, a bank customer that checked his account using ATM and withdraw his money in one of the branches.
The defines what the enterprise does with the information after it had been captured in the CRM data warehouse.
These are two basic rule for achieving a 360 view of customers. The rules come in two forms.
#1 Personalization Rule
This is the rule that shapes customer interaction. They provide the organization with the ability to personalize their interaction with their individual customers. Personalization rule guide what kind of information is passed to the customer and how it is being passed across to them.
#2 Data Transformation Rule
Data transformation rule governs non-customer facing activity. They are rules that govern the merging of customer data from source systems of third parties. They help in turning customers’ information into a pool of resources that the organization can use in meeting the customer at the point of their needs.
Note: That both rules are effective when they address the broadest possible set of scenario.
This is the translation of the enterprise’s customer strategy into rules meant to deliver that strategy. Context is said to be the missing link in many CRM implementations, yet it has the most impact of all the three rules. There are two facets of context that are essentially important.
First is that the rule should provide a holistic understanding of all the potential customer interactions within an organization, the events that make up those interactions and how the outcome of each interaction affects subsequent interactions or the overall customer relationship.
The organization also needs to determine the purpose of each rule. The objective of this is to ensure manifestation of context, which governs which of these rules, should take precedence at any given time.
At the end of this chapter, we have been able to know that:
- Successful CCEs adhere to Customer Intelligence Cycle.
- We have four steps under Customer Intelligence Cycle which are: Capture Analysis, plan and Interact.
- Under the critical component of Customer-Centric Strategies, we have Data, Context and Rule.
- Under the rule, we have Personalization rule and Data transformation rule.
- You have just received a message from MTN that is asking you to load N100 and stand a chance to win N12million. Based on your knowledge as a CRM expert, do you think this is the best way to reward loyal customers?
- It has been observed that due to the advent of the social media and internet, location is no longer a barrier as far as business operation is concerned what are some of the ways by which businesses can take advantage of the internet for their business growth.
Now your take on this argument.
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