It is believed that in the West, customers practically do not call brands, and all communication occurs exclusively online. But this is not true — it depends on the niche. The American company Ardmor makes and receives more than 2000 calls a week. It is simply impossible to control such numerous conversations without a digital assistant. That’s why the company has connected Ringostat AI-powered conversation intelligence, thus saving working time and using its data for training.
About the company and Ringostat connection
Ardmor has been operating in New York, New Jersey, and Pennsylvania for nine years. Customers turn to it for full-cycle services, such as:
- repair windows and doors;
- install them;
- replace certain types of doors and windows, including storm windows.
One of the advantages of the company is mentioned on the website: “Accurate offer and prices”. However, this cannot be achieved without a detailed discussion of the problem the client is facing. Doing this in correspondence is quite long and inconvenient, so customers often call. Knowing this, Ardmor placed the phone number in many places on the website — even in the form of an online request for a free consultation:
Managers mostly call customers rather than write to them on messengers. After all, the technician needs to arrange a time to visit the customer, and the customer may not respond for a long time on Facebook or WhatsApp.
The business is built on calls, so the company sought a professional solution to handle them. Ardmor also wanted the telephony to integrate with their CRM. Ringostat met all these requirements, so the company connected our virtual PBX and, later, call tracking.
In 2023, Ringostat became the AI-enabled telephony and interested Ardmor in the possibilities of a digital assistant.
How language analytics works
- All calls made or received by managers are recorded in Ringostat reports.
- At the same time, AI analyzes all conversations and adds its own data to each team call.
- Artificial intelligence transcribes the dialog, captures the mood of the interlocutors, advises on the next steps, and so on. We will talk about all this below.
- A special report created by our Customer Care Manager for everyone who uses language analytics allows a quick review of the AI data.
- Managers go to the call card for more detailed information about each call. To do this, they click on the date and time of the call.
Now, let’s examine what AI data can be viewed in a call card and how it is useful for Ardmor.
Transcription of a conversation
Artificial intelligence turns every conversation into text, allowing users to quickly read the conversation instead of listening to the call. According to Ardmor, this is one of most important options for them. This transcription also allows users to find dialogues discussing only certain services, such as window replacement.
If you click on any line, the conversation will start playing from that line. You can also download, delete, and copy the text of the dialog.
A brief summary of the conversation
A brief summary of a conversation usually consists of a few sentences. They contain the most essential information: what the conversation was about and how it ended. You can view this summary in the corresponding block of the call card or directly in the report. To do this, hover over the corresponding column:
The mood of the dialog and interlocutors
Artificial intelligence understands the mood of the client and the manager during the conversation. It also shows the general mood of the dialog. This data is summarized right, so Ardmor can easily filter and analyze potentially problematic conversations. For example, if an employee or customer was:
- indifferent;
- confused;
- experienced negative emotions, etc.
The call card describes the mood in more detail than the report. Therefore, you can always understand why artificial intelligence interpreted it in this way:
The best next steps
Language analytics doesn’t just summarize what happens during a dialog. It can also improve teamwork. The digital assistant analyzes what the employee and customer discussed and records their agreements. It may also notice shortcomings and advise on eliminating them during the next communication.
For example, one of our clients called Ardmor to order glass replacements for her windows. The windows were non-standard, and it was difficult to assess visually how much glass each needed to be replaced and whether it contained a double-glazed unit. The customer offered to send photos so that Ardmor could estimate the scope of the work.
At the end of the conversation, the artificial one advised:
- send a text message — what was discussed in the conversation — in response to which the client had to send a description and a photo;
- make sure the image is received and assess the scale of the work;
- write the approximate cost and next steps for the glass replacement process.
If necessary, such data can help an employee remember agreements with the client without having to listen to the entire conversation to recall them.
Customer feedback on cooperation with Ringostat
For me, it’s much easier not to listen to the calls but to just look at the statistics provided by AI speech analytics. For example, I can pay attention only to the mood of the employee and the client, and I can already understand how the communication went.
We also use AI data to train future sales reps. With a brief conversation summary and other data, we can easily find successful calls to train the team by their example.”
