Background
This article will take you from a basic understanding of your CRM as a relationship management tool to an understanding of its power to help refine money-making strategies like client acquisition and engagement.
The Typical CRM Use Cases
CRM users are motivated to use their respective systems for various benefits.
Think about when you were on the phone with a client who called to follow up on a previously spoken-about service issue.
You quickly referred to the CRM for notes to refresh your memory of the details of the issue and show them you were well-informed and focused on fixing their problem.
Or when you were actively trying to reconnect with a prospect you hadn’t spoken with in over a year, and you wanted to start the conversation with a subject that would be relevant to them.
The CRM was there to help you by providing demographic information that allowed you to choose a helpful conversation topic.
For instance, a financial planner may open a reconnection conversation with a soon-to-be retiree about changes to the pension payment rate rather than modifications to first-home buyer grants.
Or you could be more focused on the Operational Customer Relationship Management (OCRM) capabilities of CRMs.
OCRM is a specific approach that leverages CRM tools to focus on streamlining and automating customer interaction tasks.
Examples of OCRM features may include offering prompt responses (e.g. automated email responders), personalised interactions (e.g. recipient name is pre-entered on communication), and customised recommendations based on customer data (e.g. CRM suggests a particular client is notified of a product that complements a prior purchase).
These features drive enhanced satisfaction, loyalty, and business expansion.
The Advanced Use Case: Mining CRM Data
Data mining is necessary for those eager to explore their CRM system’s full potential.
Data mining uses various CRM datasets, such as sales or customer data, to find trends or perform statistical analysis to uncover valuable insights.
The process of gaining insights from CRM data (known as data transformation) doesn’t need to be complex; it follows this simple process:
1) Define & Collect: Determine the questions you want answers to & gather relevant data.
2) Clean: Tidy your data; this may include removing duplicate information and creating rules for addressing missing pieces of information.
3) Analyse: Apply charts, statistics or a combination of both to help answer your initial question.
Data Transformation Outcome Example: Customer Segmentation
After the data transformation process, customer segmentation can be achieved.
Proper customer segmentation is crucial for optimising your products, services and marketing to meet customer needs.
Segmentation can be completed in many ways; some common examples include demographics, behaviour, and preferences.
Understanding each customer’s needs enhances marketing strategies, increases engagement, and drives business growth.
A beneficial behaviour-based segmentation process is placing your customers into a hierarchy based on their value to the business. Categorisations follow the following format:
- Champions (frequent high spenders)
- Loyalists (reliable repeat buyers)
- Newcomers (encourage them back!)
- At-Risk (win them back!)
- Lost (learn why & improve retention)
This particular segmentation process can be achieved by conducting an RFM (recency, frequency, monetary) analysis.
This technique focuses on assigning customers a score based on how recently they made a purchase, how frequently they have made purchases, and the total monetary value of purchases in a given period.
By understanding a customer’s status in a value-based hierarchy (like above), the right tactics can be employed to optimise how they are addressed in marketing communication, for instance.
The Alternatives to Using CRM Data
Businesses may explore options such as conducting customer feedback surveys and reviewing market research reports to complement CRM data mining and deepen their understanding of their industry.
However, these options have their challenges.
Primarily, customer feedback surveys have the issue of respondees simply providing answers that need to reflect their true thoughts, and industry reports are relatively expensive to obtain.
For context, a generic report created by a market research organisation, IBISWorld, titled “Insurance Brokerage in Australia”, costs AUD 1,095. Click here for more information.
Challenges and Considerations
Empowering employees with skills and knowledge, offering continuous support, and fostering a culture of ongoing learning are critical for getting your employees on board with CRM data mining activities.
A way in which employee momentum can be harnessed is by establishing why CRM data mining is of value rather than simply being a task that has no immediate impact on the direction of the business.
Conclusion
Most CRMs are utilised only on a surface level as a centralised data hub that streamlines and automates various processes.
It may be daunting to dig below the surface of your CRM in search of data that will lead to valuable insights. This is particularly true if you are unfamiliar with your CRM interface, but it’s worthwhile.
The alternative is to continue to operate based on unprocessed information that, if left unexplored, may result in you missing crucial insights to help orient your business strategy.
Where to Start?
To get you started in data mining your CRM, you need to establish what questions you want the answers to. For instance, you may want to know the answer to questions like:
• What client age range provides my business with the most significant share of income?
• Is there a particular service most commonly selected in the past 12 months?
It is essential to prioritise questions based on pressing business matters. For instance, an insurance brokerage may forecast an upcoming month where they cannot meet their financial commitments.
A question they may want the answer to is, Which insurance policy has the shortest conversion cycle? Finding this answer would allow them to focus on securing clients related to this policy for a fast income source.
Start exploring your CRM data, and you will begin to unlock hidden gold.
If you want to learn more about how your CRM can be data mined to advance your financial services business or if you have questions regarding this topic, click here to message us.
