With the amount of data telcos process increasing almost exponentially, using that data effectively is going to be key to telco profitability in the years to come
Business leaders in the telecom industry are acutely aware of the value of customer data in today’s world. As the adoption of location-aware mobile devices has increased, telcos have moved from simply being a channel for information delivery to being a key source of data that can be used to improve customer service levels, increase the effectiveness of marketing campaigns, and address potential problems even before they happen. With that keen awareness of the value of data, it’s not surprising that telcos are turning to data enrichment as a means of enhancing their own capacity for extracting tangible business value from their data.
There are a vast number of use cases in the telecom industry, with more becoming apparent every day. Here are a few ways in which data enrichment and location-based data are helping telcos drive greater value.
1. Building the optimal network
Geospatial intelligence provides unique opportunities to better understand where customers and potential customers are located and where there may be opportunities to improve network coverage to better serve those audiences. That process begins with a hyper-local understanding of the market and property level insights.
By enriching data with accurate information about populations and mobility, telcos add a human dimension to the map of the physical world. You can understand which areas have a larger daytime population vs. evenings or weekends and how that effects market requirements. That data lets you see where your customers live, work, and play.
By overlaying all of that with a company’s existing infrastructure and competitor’s capabilities in a geospatial context, telecom leaders can more easily identify whitespace, discovering untapped market opportunities. New investments can be located to produce the best possible results.
2. Knowing your customers
In the telco industry, knowing your customer can be something of a challenge because each user may subscribe to more than one service and/or may have more than one device. When you add multiple service options, professional roles, and additional family members to that equation, things can get complicated very quickly.
Consider the case of a small business owner who has several employees, each requiring a mobile device, as well as a small office with Internet connectivity. In addition, she has a family with four children, two of whom are in college. At the very least, that amounts to two customers: one for the business and one for personal use at home. If the business is paying for its employees’ cell phone service on a reimbursement basis, that amounts to a few more “customers” with a direct relationship to the business owner (but no connection that you are necessarily aware of). If some of the children have their own distinct mobile phone accounts, do you have any way of knowing that they’re connected to her as well? They may share a common address, but in a large multiple-unit dwelling, that doesn’t necessarily mean anything.
While it may be a tall order to unravel all of that complexity, enriched data can at least help you to begin developing a better understanding of the relationships that are in play. For starters, data enrichment can help you to connect the business owner to the household resident. It could also help you to understand some of the relationships with employees, children, and spouse or significant other.
There are a number of ways that this kind of information can be used to create business value. By proactively identifying potential buying triggers, for example, a telecom provider can reach consumers with the right offer at the right time. If a family has children approaching their teenage years, for example, they may be in the market for a family cell phone plan. People who have recently relocated to a new home, likewise, might be responsive to offers for bundled telecom services.
3. Optimising efficiency
Another case for data enrichment centres around the efficiency and effectiveness of telecom resources, including call centre personnel and field service technicians. By incorporating location intelligence tools with network analysis, incident management, and field service dispatching, telecom companies can deploy resources around a holistic model that prioritises and directs activities to optimise efficiency.
While data analytics have been on the ascent for several decades now, the capabilities of AI, machine learning, and predictive analytics still remain largely untapped. Business leaders in the telecom industry understand the value proposition better than most; after all, much of the data that is driving retail site selection, location-based marketing, and advanced customer profiling is driven by data collected and monetised by the telecom industry. Smart industry leaders are recognising that data enrichment is a two-way street – that telecoms have as much to gain from consuming enriched data as they do from monetising it.
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