Superpower – for operators
Insights – for managers
Revenue growth – for business
Insights – for managers
Revenue growth – for business
Increasing CC metrics by introducing a prompter with personal adaptive recommendations based on expert and data approaches
Nov.
Oct.
Sep.
With & Without us
The New Way of Getting
Conversations Right
Conversations Right
Answering questions, solving problems, Satisfaction and Retention
Support
Level of automation,
user-friendliness
of interfaces and Speed / Quality
user-friendliness
of interfaces and Speed / Quality
Operations
Compliance according the law, Security controls and Risk mitigation
Objection handling, Customer openers, Conversions and Revenue
Sales
Compliance
How It Works
Dynamic changed and personalized cue
Guidance Checklist for each call
Tracking the pronunciation of recommendations
Guidance Checklist for each call
Tracking the pronunciation of recommendations
Guidance Checklist Online
Knowledge base for fast answering
Data-based effective objections handling
Dynamic timely hints
Data-based effective objections handling
Dynamic timely hints
Questions & Objections
Evaluation of the script following
Scoring cards with various criteria for operators
Trusted insights based on successful dialogues
Scoring cards with various criteria for operators
Trusted insights based on successful dialogues
Quality Assurance
Educational tips based on the dialogue result
Debriefing with the managing manager
Process gamification
Debriefing with the managing manager
Process gamification
Education & Perfomance
Together with a partner consulting agency,
changes are provided in the script for the growth of metrics
changes are provided in the script for the growth of metrics
Expert Scripts Adaptation
Real metrics for each call
Analysis of the dependence between conversion
metrics and cue presence
metrics and cue presence
Reports for operators, products, metrics, calls
Reports & Analytics
Growth your Metrics
E-commerce, Marketplaces
Accompanying products and services
Corporate sales
Credit and insurance products
Banking, Insurance, Collection
Debt collection
Real Estate
Visits to residential complex sales offices
Built-in ASR, company-wide, online recognition
Online ASR
01
Key Technologies Inside
02
02
NLP
NLP
Replica Classification, NER, and the Dialog Engine
Replica Classification, NER, and the Dialog Engine
Sentiment
Sentiment
Evaluation of the emotional color and reaction of the client
Evaluation of the emotional color and reaction of the client
03
03
Profiling
Profiling
Defining a customer typology for a high-level personalization
Defining a customer typology for a high-level personalization
04
04
☎️ Telephony
integration with cloud telephony and online speech recognition
📩 Text channels
omnichannel text integration with click-to-answer hints
💬 Chatbots
adaptation of chatbot scenarios for built-in system scripts
… other infrastructure
flexible approach to product functionality and microservice architecture allow integration with a wide range of existing solutions
integration with cloud telephony and online speech recognition
📩 Text channels
omnichannel text integration with click-to-answer hints
💬 Chatbots
adaptation of chatbot scenarios for built-in system scripts
… other infrastructure
flexible approach to product functionality and microservice architecture allow integration with a wide range of existing solutions
🖥️ Manager Interface
Reports with analytics and quality control in a separate web service:
– Frontend Web App
– Integration with PowerBI and analogues
– Upload to Google Sheets and analogues
📱 Operator Interface
Checklists and dynamic hints:
– Frontend Web App
– Integration into the current interface
– Separate Mobile App
🏗️ Deployment
– In the cloud with CC-Prompter branding
– In the cloud with company branding
- Within the company
Reports with analytics and quality control in a separate web service:
– Frontend Web App
– Integration with PowerBI and analogues
– Upload to Google Sheets and analogues
📱 Operator Interface
Checklists and dynamic hints:
– Frontend Web App
– Integration into the current interface
– Separate Mobile App
🏗️ Deployment
– In the cloud with CC-Prompter branding
– In the cloud with company branding
- Within the company
And also!
Metrics changes
Operators on-boarding cycle
Request processing speed
Best Practices
Call Analysis
With AI-Prompter
Features
With & Without us
Currently
Standard inefficient processes
Plateau or decreasing
Several weeks for peak efficiency
Looking through all manual guides
Depends on operators qualification
Selective, with implausible conclusions
Advanced system
Boosting for each period
After several hours of system usage
At the time of question
Scaling to the work of each operator
100% cover, with transparent insights
Cases
Context: The bank needs to accelerate the training of sales managers due to their high turnover.
I would like to shorten the learning process through individual recommendations online, the use of which will keep the performance of new operators at the current level.
Solution: The operator's prompter upgrades the training system for sales managers, provides online recommendations for following the script, answering questions and working out objections.
I would like to shorten the learning process through individual recommendations online, the use of which will keep the performance of new operators at the current level.
Solution: The operator's prompter upgrades the training system for sales managers, provides online recommendations for following the script, answering questions and working out objections.
Call Center for Credit Cards Sales
Cases
Context: A large taxi aggregator needed to automate the processing of applications and filling in trip data when ordering a taxi by phone.
Solution: AI Prompter modules made it possible to automatically extract the addresses of departures and arrivals of passengers, and other necessary data for ordering a taxi. As a result, this helped relieve call center managers from the tasks of generating tickets.
Solution: AI Prompter modules made it possible to automatically extract the addresses of departures and arrivals of passengers, and other necessary data for ordering a taxi. As a result, this helped relieve call center managers from the tasks of generating tickets.
Call center for order processing
Cases
Context: A network of dealerships needed to solve the problem of controlling the quality
of communication with car sales customers and increasing the yield on a test drive
Solution: With the help of the AI Prompter, the company automated the quality control
of the work of sales managers in dealerships, and increased the conversion rate for a test drive by 20%.
of communication with car sales customers and increasing the yield on a test drive
Solution: With the help of the AI Prompter, the company automated the quality control
of the work of sales managers in dealerships, and increased the conversion rate for a test drive by 20%.
Call center for one of the dealerships
Cases
Context: The bank needs to accelerate the training of sales managers due to their high turnover.
I would like to shorten the learning process through individual recommendations online, the use of which will keep the performance of new operators at the current level.
Solution: The operator's prompter upgrades the training system for sales managers, provides online recommendations for following the script, answering questions and working out objections.
I would like to shorten the learning process through individual recommendations online, the use of which will keep the performance of new operators at the current level.
Solution: The operator's prompter upgrades the training system for sales managers, provides online recommendations for following the script, answering questions and working out objections.
Call Center for Credit Cards Sales
Cases
Context: A large taxi aggregator needed to automate the processing of applications and filling in trip data when ordering a taxi by phone.
Solution: AI Prompter modules made it possible to automatically extract the addresses of departures and arrivals of passengers, and other necessary data for ordering a taxi. As a result, this helped relieve call center managers from the tasks of generating tickets.
Solution: AI Prompter modules made it possible to automatically extract the addresses of departures and arrivals of passengers, and other necessary data for ordering a taxi. As a result, this helped relieve call center managers from the tasks of generating tickets.
Call center for order processing
Cases
Context: A network of dealerships needed to solve the problem of controlling the quality
of communication with car sales customers and increasing the yield on a test drive
Solution: With the help of the AI Prompter, the company automated the quality control
of the work of sales managers in dealerships, and increased the conversion rate for a test drive by 20%.
of communication with car sales customers and increasing the yield on a test drive
Solution: With the help of the AI Prompter, the company automated the quality control
of the work of sales managers in dealerships, and increased the conversion rate for a test drive by 20%.
Call center for one of the dealerships
Let`s schedule a Demo!
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info@mil-team.com