Companies increasingly turn to speech. Results in Disappointment Analytics analytics as a tool to improve customer service, control managers’ work, and improve sales. However, the results of implementing speech analytics often turn out to be far from expectations.
Why does this happen? What mistakes do companies make when implementing conversation analytics? How to avoid disappointment and choose a system that really works? Let’s look at examples from real clients.
Why do companies choose speech analytics?
Before implementing speech analytics, companies face a number of challenges:
- Managers cannot objectively evaluate the work of managers.
- The sales department is losing mobile database clients due to poorly developed scripts.
- There is no way to systematically. Why Speech Analytics analyze errors in communication with clients.
- Huge amounts of data have to be processed manually.
Speech analytics promises to solve all these problems, but the results of implementing speech analytics do not always live up to expectations.
Real examples of unsuccessful implementation
Example 1: Loss of some calls
One real estate company found that after implementing what else hinders critical thinking? analytics, up to 70% of calls were simply not recorded. This led to serious problems:
Why did this happen?
The problem was in technical failures of the system – the algorithms simply did not recognize some of the calls due to integration errors with the telephony.
How does SalesAI solve this problem?
✅ 100% call recording without data loss and omissions.
✅ Integration with any telephony and CRM without technical failures.
Example 2: Reports that no one reads
A financial services company implemented speech analytics, bermuda businesses directory but the reports were so complex and cumbersome that executives simply couldn’t analyze them.
📌 They received Google Sheets with 50+ columns, where they had to manually search for important data.
📌 Result: analytics were not used, and the company continued to work “blindly”.