Dear Customers,
We hope you're well!
Loss and customer churn are inevitable in any business, even for historically successful ones. While it's never pleasant to see customers leave, it's crucial for businesses to identify the triggers behind these losses and address their root causes.
Root cause analysis is a process management technique whereby a business analyzes the root cause of a problem or constraint it's facing to address negative triggers. It involves identifying and defining the problem, gathering data and evidence, identifying possible causes, and testing each cause against the evidence to obtain the ultimate root cause. Many businesses manually examine causes one by one, often collecting reasons from users for each problem that arises. But this examination process takes a lot of time and unfortunately isn't often backed by data.
This brings us to Zoho CRM's root cause analysis (RCA) feature in VoC.
VoC categorizes customer feedback based on various traits. For RCA, VoC identifies negative outcomes in your business, such as customers that have churned out and deals that you've lost. As a reactive investigation, RCA backtracks the events and responses of those lost deals and churned customers to identify the reasons and causes that led to them. Based on their keywords and behaviors after, VoC categorizes potential root causes as follows:
- Lack of innovation
- Product glitches
- Response delays
- Poor service
- Product pricing issues
- Missed deadlines
- Lack of follow-ups
- Mismatched requirements
- Others
How you can use RCAs
Regardless of what you're investigating, RCA can play a role in it. Using VoC events or responses, you can build new custom charts and group them based on these categorized root causes.
Let's look at a few scenarios to see how you can use RCA to build custom charts.
Analyzing declining revenue for Q1
A decline in revenue is a serious issue for any business, and suggests there have been consecutive losses in terms of deals. To understand the trend and trajectory of this issue, you can build a cohort chart with RCA values.
Analyzing failed lead conversions
Attracting and converting a lead is itself a complex process, and most businesses allocate portions of their expenses to marketing their products in order to convert their leads. Despite these efforts, if the acquired leads are lost, the business will incur two types of losses: no return on the marketing costs, and a loss of potential business with those leads. Thus, businesses can use a simple chart to analyze the factors that are causing the leads to walk away.
Based on the results, let's say the most significant cause relates to follow-ups and poor service. The business can then do the following:
- Use the cause to find those records that are lost due to follow-ups and extend a reconciliation proposal. Click here to learn about cross-module filtering of VoC parameters.
- Investigate further to determine the cause of the lack of follow-ups or poor service and correct course.
- Educate users and sales reps in areas that need improvement and prevent future errors.
Under development
In line with the inclusion of RCA while building custom charts in VoC, we're developing an exclusive dashboard for RCA investigations. Using charts like sankey and cohort, the system itself identifies the problem area, computes the findings, and provides you with a turnkey dashboard that you can readily use. We expect this to be ready soon.
While we're at it, we hope you'll include this new RCA computation in your business analyses for a more focused examination of your operations.
That's all about RCA in VoC for now. Each day at Zoho CRM, we're developing VoC to address countless niche requirements that involve customer feedback and behaviors. If you have questions, comments, or feedback around these topics, we'd be happy to hear them. Please drop them in the comments section. Let's connect!
Release plan: This has been opened for all users in all DCs.
Resources: Conduct root-cause analysis in VoC
Thanks and have a good one!
Kind regards,
Saranya Balasubramanian
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