Multi-tenant based analytics for contact centers

Patent metadata

Field	Value
Publication number	US-10346785-B2
Application number	US-201414451310-A
Country	US
Kind code	B2
Filing date	Aug 4, 2014
Priority date	May 27, 2014
Publication date	Jul 9, 2019
Grant date	Jul 9, 2019

Abstract

Embodiments of the present invention are directed to a system and method for collecting and analyzing data from a plurality of contact center tenants. A processor collects from a plurality of source devices over a data communication network, real-time metrics data for a plurality of contact centers. The real-time metrics data relates to a plurality of contact center factors. The processor stores the collected real-time metrics data in the data store, and generates benchmark data based on the collected real-time metrics data. The processor determines, for a particular contact center of the plurality of contact centers, performance of the contact center relative to the benchmark data. The processor further outputs a recommendation based on the comparison.

First claim

The invention claimed is:

1. A multi-tenant analytics system comprising:
a data store;
a processor coupled to the data store; and
a memory, wherein the memory stores therein instructions that, when executed by the processor, cause the processor to:
generate a plurality of software objects associated with a plurality of contact center factors, each of the plurality of software objects providing a method accessible to a plurality of contact centers for pushing data to the software object;
collect from a plurality of source devices over a data communication network, real-time metrics data pushed by the plurality of contact centers to the software objects, wherein the real-time metrics data pushed to a particular one of the software objects relates to the contact center factor associated with the particular one of the software objects, wherein the real-time metrics data further includes data collected from a plurality of physical or virtual retail stores associated with the plurality of contact centers, wherein the data collected from the plurality of physical or virtual retail stores include at least one of interactions at the plurality of physical or virtual retail stores, customer satisfaction data, sales data, or retail store workforce data;
store the collected real-time metrics data in the data store;
generate benchmark data based on the collected real-time metrics data;
determine, for a particular contact center of the plurality of contact centers, performance of the particular contact center relative to the benchmark data;
automatically analyze the real-time metrics data and generate a prediction in response;
output a recommendation based on the generated prediction, wherein the recommendation is for advancing a key performance indicator (KPI) goal of the particular contact center;
receive a first recording of a voice conversation held in a particular retail store selected from the plurality of physical or virtual retail stores, the conversation being between the customer and a representative of the particular retail store during a first interaction at the particular retail store;
store the first recording in a database in association with a user profile of the customer;
receive second recordings of other conversations from a plurality of other one of the plurality of physical or virtual retail stores;
perform real-time analysis of the first and second recordings;
identify a second interaction between the customer and the particular contact center;
link the first interaction in the particular retail store to the customer and the identified second interaction; and
make a particular recommendation based on the identified second interaction and further based on the analysis of the first and second recordings.

2. The system of claim 1 , wherein the recommendation relates to handling of interactions by the particular contact center.

3. The system of claim 1 , wherein the recommendation relates to products or services to be offered by the particular contact center.

4. The system of claim 1 , wherein the real-time metrics data relates to at least one of interactions or contact center workforce data.

5. The system of claim 1 , wherein the instructions further cause the processor to:
model correlations between the plurality of contact center factors and the key performance indicator; and
predict a change to the key performance indicator in response to simulating a change to one of the plurality of real-time time metrics.

6. The system of claim 5 , wherein the instructions that cause the processor to model the correlations include instructions that cause the processor to generate a prediction tree for the key performance indicator, wherein input to the prediction tree is the plurality of real-time metrics data.

7. The system of claim 1 , wherein the key performance indicator is selected from a group consisting of customer satisfaction, revenue, sales conversion, cost, and customer retention.

8. The system of claim 1 , wherein the instructions further cause the processor to:
identify a desired value for the key performance indicator for the particular contact center;
determine values of the real-time metrics that are predicted to achieve the desired value for the key performance indicator; and
recommend the values to the particular contact center.

9. The system of claim 1 , wherein the instructions further cause the processor to:
receive event data from an external data source; and
correlate the event data to the real-time metrics, wherein the prediction is based on the correlated event data.

10. The system of claim 9 , wherein the event data includes at least one of weather data, traffic data, financial market data, geopolitical events, or social media information.

11. The system of claim 1 , wherein the recommendation relates to products or services to be offered by the particular retail store associated with the particular contact center.

12. The system of claim 1 , wherein the recommendation relates to staff for handling customers by the particular retail store of the plurality of physical or virtual retail stores.

13. The system of claim 1 , wherein the instructions further cause the processor to normalize the benchmark data across different size and types of contact centers.

14. A multi-tenant analytics system comprising:
a data store;
a processor coupled to the data store; and
a memory, wherein the memory stores therein instructions that, when executed by the processor, cause the processor to:
generate a plurality of software objects associated with a plurality of contact center factors, each of the plurality of software objects providing a method accessible to a plurality of contact centers for pushing data to the software object;
collect from a plurality of source devices over a data communication network, real-time metrics data pushed by the plurality of contact centers to the software objects, wherein the real-time metrics data pushed to a particular one of the software objects relates to the contact center factor associated with the particular one of the software objects, wherein the real-time metrics data includes first interaction data collected from interactions between a customer and a website associated with the particular contact center, and second interaction data collected from interactions between the customer and a particular contact center of the plurality of contact centers;
store the collected real-time metrics data in the data store;
generate benchmark data based on the collected real-time metrics data;
determine, for the particular contact center, performance of the particular contact center relative to the benchmark data;
automatically analyze the real-time metrics data and generate a prediction in response;
output a recommendation based on the generated prediction, wherein the recommendation is for advancing a key performance indicator (KPI) goal of the particular contact center;
detect occurrence of a trigger event as the real-time metrics data is collected;
transmit a code to a customer device accessible to the customer in response to detecting the trigger event;
receive a message from a retail store device over a data communications network, wherein the message includes the code associated with at least a portion of the collected real-time metrics data, the retail store device being located in a retail store associated with the particular contact center;
in response to receipt of the code, transmit the portion of the collected real-time metrics data to the retail store device for display thereon;
monitor interaction of the customer at the retail store and generate

Assignees

• Genesys Telecommunications Laboratories Inc

Inventors

• Tamblyn Eric
• Wright Simon
• Konig Yochai
• Connolly Christopher
• Hendren Chad David
• Lejeune Arnaud

Classifications

• G06Q30/0601

  Electronic shopping [e-shopping] · CPC title

• G06Q30/0201

  Market modelling; Market analysis; Collecting market data · CPC title

• G06Q10/0639

  Performance analysis of employees; Performance analysis of enterprise or organisation operations · CPC title

• G06Q10/06393 Primary

  Score-carding, benchmarking or key performance indicator [KPI] analysis · CPC title

• G06Q30/0631

  Recommending goods or services · CPC title