In previous entries we explained the importance of QoE (Quality of Experience), how it is measured and the benefits of measuring it.
With QoE Optimization not only can we measure Quality of Experience, but we can also optimize it. We can integrate the solution with internal systems to execute automatic actions, extract useful information and deliver insights to enhance QoE perceived by our customers, and reduce churn.
How We Measure QoE?
QoE optimization solution measures quality of experience from the user’s’ point of view. To do this we install agents in the user’s device. These agents measure different technical parameters within the use of the services. We retrieve and store the data and using analytical techniques we obtain each clients’ MOS measurement in the use of each service.
Taking Advantage Of The Information
With the amount of data collected by the agents, in addition to calculating each customers’ MOS in the use of each service, we can also use analytical techniques and combine them with other information from the operator to obtain multiple reports, predefined or tailored, according to the needs of each operator.
Some examples could be temporary QoE evolutions for each customer or groups of customers, geographical groupings, customer profiling based on the use of each service….
But we can also create alarms based on any of the data ( whether a particular customer reduces the value of QoE, alarms in specific geographical areas….)
Integrating The Solution
To draw the maximum benefits out of the QoE measurement, we integrate the solution with the operators’ systems to carry out actions with the insights obtained. This is how we ensure the increase in the levels of QoE, reduce costs, improve marketing campaigns and so on.
The QoE optimization solution forms part of Augura, the analytics platform for Telcos by Optare Solutions, a consultancy that has, since 2002, been working on the integration of Telco operator systems around the world.
Examples Of Benefits Obtained With QoE Optimization Solution
Here are some examples of the use of QoE information:
Example 1: Detecting Technical Problems That Can Be Solved
Thanks to real time monitorization of QoE we can create several use cases. We are able to detect technical problems, which affect a customer, and can be solved using provision/activation systems. The integration allows us to automate these tasks reducing the costs of the operation while improving the customer’s experience, hence solving the problem before the customer contacts the operator.
In some cases it is not possible to solve problems automatically, or they shouldn’t be solved, pending on the specific business requirements. In these cases the solution may need to be carried out manually and tickets must be created in the Problem Handling System or in the CRM.
Example 2: Detecting Investment Needs And Priorities
The QoE optimization solution allows the use of analytical techniques to detect common problems for groups of customers ( geographic groups, groups defined through use of services such as gamers and so on) or problems in the use of certain services like gaming, streaming etc. The solution would undergo investment in CAPEX to solve the bad experiences in QoE
QoE optimization allows for the detection of these problems before they even occur through visualization of the historical data and its evolution. Visualization can be done directly with a web tool using custom or standard made control panels.
Example 3: Complaint Management
On detecting customers dissatisfied with the use of the services, it is vital that the Operator acts proactively, both in the solution of the problems and the communication with the customer.
QoE combined with CRM and the MKT automation systems allows to create specific campaigns for customers with problems in QoE; eliminate them from sales campaigns, creation of loyalty campaigns…… This transforms into better global customer experience and lowers churn rates.
Example 4: Knowledge Of Our Customers
By measuring QoE for all customers, we will obtain a measure of the well-being of our customers. The temporary evolution of the QoE measure will give us valuable information to predict the future of our customers and to act preventively.
Adding this data to predictive analytics systems will help improve the accuracy of the predictive models. Knowing the experience perceived in the use of services will greatly increase the accuracy of the churn prediction model. For example, Adding the QoE measurement and the data that we also obtain from QoE optimization allows us to know which services are used by each customer and the experience they have with them. With this information we are able to improve marketing campaigns by offering the most relevant services to individual users.
These are just some examples of what can be achieved with QoE optimization, but there are many more solutions to common problems for the company in its relationship with its customers, as a result of the QoE measurement .
Download the QoE optimization solution PDF to learn more on how to measure and optimize QoE for your customers.
