Dear Customers,
We hope you're well!
The influence of AI is sprawling, and among the thousands of AI tools available in the market today, nearly half of them are built by businesses for businesses to augment customer experience. By and large, customer experience and cognitive data are related by the human experience, and VoC in Zoho CRM specializes in bringing them out.
As part of bringing human experiences to the table, Zoho CRM has been constantly adding more capabilities to our VoC portfolio. Here's the latest one for your reference. Today, we're here with another retrospective analysis in VoC: customer drilldown.
Customer drilldown
As the name implies, customer drilldown enables you to delve into the data plotted on a chart, displaying all the records that contribute to each chart value and further enabling you to act on them.
Here's a quick look at the feature:
Chart drilldown
Upon clicking on a plotted value, a sliding pane will appear with a list of records. These are records that contribute to the plotted value.
Actions you can perform on drilled-down records:
Each drilldown is a list view of records at play. It enables you to select some or all the records behind a value and perform quick actions like the following:
- Manage columns and clip text.
- Send macros, emails, create tasks, add or remove tags, and perform other quick actions like setting reminders, performing mass field updates, changing owners, triggering or un-enrolling from cadences, adding to campaigns, updating responses, printing mailing labels, initiating mass mail merges, and deleting or updating the basis for data processing.
Imagine you're running a campaign and would like to identify the sentiments in your customers' responses after rolling out your campaign. In the sentiment cohort, you can map your campaign week with the respective cohort weekly distribution to view the new sentiments and understand the behavioral impact your campaigns have had on your customers, investigate which records are participants in that cohort, and target them with more meaningful measures.
As another example, take keyword analyses, which are words customers use. Larger fonts indicate greater concentrations of customers using the same words, which are indicators of customer preferences. If you inspect frequently occurring keywords, you can assess the weight of those words, and by digging further, you can see all the records that have used certain keywords and understand their intentions at scale.
That's all for this update. We have opened this for customers in all DCs.
Please let us know if you have any questions or feedback. Thanks!
Kind regards,
Saranya Balasubramanian
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