One of conundrums which has been quietly emerging over the last couple of months concerns how to maintain privacy when attempting to improve customer experience, but the power of the edge might save the day.

If telcos want to be able to improve customer experience, data needs to be collected and analysed. This might sound like a very obvious statement to make, but the growing privacy movement across the world, and the potential of new regulatory restraints, might make this more difficult.

This is where the edge could play a more significant role. One of the more prominent discussions from Mobile World Congress in Barcelona this year was the role of the edge, and it does appear this conversation has continued through to Light Reading’s Big 5G Event in Denver.

Some might say artificial intelligence and data analytics are solutions looking for a problem, but in this instance, there is a very real issue to address. Improving customer experience though analytics will only be successful if implemented quickly, some might suggest in real-time, therefore the models used to improve performance should be hosted on the edge. This is an example of where the latency business model can directly impact operations.

It also addresses another few issues, firstly, the cost of sending data back to a central data centre. As it was pointed out today, telcos cannot afford to send all customer data back to be analysed today, it is simply an unreasonable quantity, therefore the more insight which can be actioned on the edge, with only the genuinely important insight being sent back to train models, the more palatable customer experience management becomes.

Secondly, the privacy issue is partly addressed. The more which is actioned on the edge, as close to the customer as possible, the lesser the concerns of the privacy advocates. Yes, data is still being collected, analysed and (potentially) actioned upon, but as soon as the insight is realised the sooner it can be deleted.

There are still sceptics when it comes to the edge, the latency business case, artificial intelligence and data analytics, but slowly more cases are starting to emerge to add credibility.