Ringostat expands customization for AI-powered conversation intelligence

Ringostat has elevated its AI-powered conversation intelligence for sales teams and call centers. The solution, already a game-changer in performance analysis, now offers fully customizable speech analytics. Businesses can set tailored evaluation criteria for different languages, expertise levels, and roles — all without needing developers. This update streamlines operations and enhances efficiency, making performance oversight more precise and time-efficient.

What Ringostat’s AI-powered conversation intelligence offered before the update  

1. Automatic analysis of every call.
2. Dialogues are transcribed in the original language or translated into English as needed.
3. Concise summaries of conversations.
4. The mood of the dialogue and each of the interlocutors is recorded. This way, you can quickly notice conflicts or situations where the deal may fail due to negativity.
5. Artificial intelligence makes recommendations on the best next steps after the call. This way, the operator and management know what to do to close the deal.

The AI-powered conversation intelligence now boasts these capabilities, but following a global update, it has evolved significantly. It now offers enhanced functionalities and bespoke customization for any operational process.

The transformations in AI-powered conversation intelligence following the recent update

1. It is now possible to create individual profiles. Previously, all conversations could be evaluated based on only one principle. However, teamwork should not always be analyzed in the same way. You can set up multiple profiles for evaluation using different metrics within the same project. 
2. There are many more parameters for analysis. Artificial intelligence will take into account the context of the conversation, whether the manager used mandatory phrases or forbidden words, and much more. 
3. Everything is highly customizable. Depending on the situation, who is communicating with the customer, and what topic is being discussed, you can choose which metrics AI will use for evaluation. You don’t need to hire developers, draw up technical specifications, and wait for implementation. 

Let’s take a closer look at each of these points.

Ability to create separate profiles

When might you need different profiles for analysis? Here are some common examples.

1. The company operates in different countries. In such case conversations in different languages, such as German or Japanese, may require original or translation transcription to ensure all stakeholders, like a German manager, can fully grasp the dialogue’s content.
2. The team includes both experienced employees and newcomers. For teams comprising seasoned professionals and newcomers, new operators may need to be assessed using more comprehensive metrics due to their initial learning curve and higher likelihood of errors.
3. You have a sales department and a support department. Sales and support departments often have different priorities. Sales teams may need evaluation on adherence to scripts and product presentation, while support teams require criteria focused on customer resolution and service quality.

Profiles for analysis, tailored to various parameters, are now available in the Settings — AI Analytics section. These profiles can be created and adjusted either manually or with the assistance of our dedicated technical support team. Additionally, profiles may be activated or deactivated at any time using the convenient toggle feature provided.

Each profile can also be individually customized as follows:

• transcription in the original language — the AI will automatically detect and transcribe the dialogue in its original language;
• translation into English — alternatively, the AI can translate the conversation into English for comprehensive understanding.

If you are the owner of an existing project, please contact our technical support to get the opportunity to create profiles.

Expanded analytical parameters

The AI language analytics now accommodates a broader range of factors during evaluation, including:

• stop words — that is, expressions that are prohibited in your company;
• parasitic words;
• foul language;
• mandatory phrases that a manager should use during a conversation;
• assessing the quality of the dialog;
• the topic of the conversation;
• keywords;
• critical points of the dialog;
• operator errors;
• which was good during the conversation;
• whether to pay attention to the dialog;
• a structured summary of the call.

You can also add your parameters for analysis.

Flexible Customisation Options

The system offers unparalleled customization to meet your specific requirements. Should mood analysis be unnecessary, you may simply deactivate this feature. Adjustments to dialogue quality assessment can be swiftly tailored to align with the distinct nuances of your processes, all accomplished within five minutes. This facilitates a focus on essential data devoid of extra information.

Furthermore, you can now customize the scope of call analysis by selecting from predefined filters to specify which calls are examined under a given AI profile. The applicable rules are automatically implemented by choosing a filter from the drop-down menu, further refining and streamlining the analytical process.

You may also configure which sales managers’ calls are analyzed by a specific profile by selecting Employee — Equals — [Name]. The same method applies to setting up call analysis for entire departments — specify the department’s name.

Moreover, customizing the Context for Analytics and Context for Transcription fields can enhance the AI’s efficacy. For example, within the Context of Analytics, you can outline the typical structure of conversations and define key terms. This refinement allows the AI to assess service quality more accurately.

For instance: “As the head of the ABC Online English Language School sales department, I expect conversations between staff and prospective students or their parents. The school offers English lessons for preschoolers, schoolchildren, and business professionals, including individual and group sessions. Prospective clients are interested in enrolling their children or themselves in our programmes”.

Important: the context must be provided in the desired language to ensure accurate results.

As illustrated below, the metrics previously outlined can be customized by activating the toggle. You may then establish specific conditions for various parameters by adding the metric and defining the requisite conditions.

For instance, in the “Opening” stage, you might specify that “the sales representative should greet the customer, state their name, and mention the company.” The AI will then analyze the call according to these instructions. If the representative meets all the criteria, the AI will report, “The employee greeted the customer, stated their name, and mentioned the company.” Conversely, if any element is lacking, the analysis will reflect this.

Furthermore, you control the cost of analytics per minute of conversation. The system lets you view the pricing immediately based on the selected parameters. Configure the required metrics and choose from the following AI options in the drop-down menu:

• Claude Sonnet
• Claude Opus
• Claude Haiku
• Chat GPT-4 Turbo
• Chat-4o

Ringostat will then provide the cost for analyzing each minute of conversation, ensuring transparent and efficient management of your analytics budget.

How to utilize the new analytics update

To begin, ensure that Ringostat’s AI-powered conversation intelligence is connected correctly. Navigate to General Settings — AI Analytics and follow the outlined steps to configure the update. Results from the AI analysis will be visible as follows:

• for an individual call — in the call log; 
• for all calls — after setting up the appropriate type.

Should you require assistance or wish to customize specific settings, please contact our technical support team. We also welcome your feedback on the update through our support or Customer Success departments.