It should come as no surprise that telecoms, by nature, generate vast amounts of data. Because of that fact, it is very easy to assume that AI would be a very powerful tool for telecoms. After all, consuming and crunching data are two of AI’s most attractive qualities. Logic would have it, then, that the telecom industry is champing at the bit to leverage AI to open up new opportunities. The billion-dollar question is… how?
Most telecom companies today are built on legacy foundations–outdated software infrastructures that are siloed off from one another. That means that if AI were applied en masse, you would quickly become mired in a messy, garbage-in, garbage-out scenario. Because of this potential pitfall, the answer lies in a targeted approach to AI.
There is one system of record that telecoms have that contains the most valuable data. Billing. It’s one of, if not the most frequent point of entry and the largest depository of customer data. Consider the ways that customers project data connected to billing:
- An increase in data usage or an upgraded data plan could indicate a growing business
- A switch from an individual plan to a family plan could mean that family members have grown into a new demographic with increased buying power
- An uptick in global roaming plans might signal a budding market expansion opportunity
- A surge in refund or discount requests could be a sign of increased competition
- A rush of billing cancellations could be pointing to a churn problem
What’s more, these broad-based insights can be further refined and segmented by knowing specifics of a single billing interaction:
- When did the customer call?
- What was their issue?
- What plan are they on?
- What device do they use?
- Where are they located?
- What other services do they use?
- How did we respond to their issue?
- What new products or services might they benefit from?
With all of this information coming from the same place (billing) AI can be applied to collect, parse, segment and organize this massive, singular trove of valuable data. We can then use AI again to make very specific queries, leading to informed decisions. We can create new models, find efficiencies, strategize new product and service offerings and, ultimately, grow revenues and decrease costs.
Proceed with Urgency
The biggest threat to this opportunity is if the telecom industry is slow to understand the value of an approach like this. This was true with telecom sleeping on the cloud, and there is potential of it happening again. We see some industries like social media and entertainment adopt precise strategies with AI to great benefit, while entirely new industries have been born by adopting similar approaches–adtech and martech, for example.
Here, there is even more at stake. Telecom has emerged as an essential utility. The more that we can strategically and effectively leverage the new tools and technologies available to us, the better we can continue to build and maintain these services, and the greater impact we can have on the industry, and on society as a whole.