(Image Credit: iStockPhoto/AndreyPopov)
When telecom operators review their performance, they often find that roughly ten cities in a country generate about 60% of their revenue. Focusing only on those major cities—where competitors also concentrate—leaves significant untapped revenue in smaller towns and suburban areas. In a fiercely competitive market, that neglected potential can make a large difference to the bottom line.
Traditional revenues are under pressure as subscribers increasingly use over-the-top (OTT) apps to make calls and interact with services, and as new market entrants emerge. As a result, operators must explore ways to defend and grow revenue from inside their existing footprint.
So how can mobile operators expand market share and increase revenue in such a competitive environment?
Micro market segmentation
To maximize revenue, operators should adopt micro market segmentation—analysing performance at a local level using telecom data and guided analytics to determine targeted actions for specific cities, towns, and neighborhoods. National and major-city trends are useful, but they don’t reveal the full picture. Examining granular local patterns uncovers opportunities in under-explored markets that broad analysis misses.
Operators that want to grow and capture more of the market must shift from a country-level mindset to a micro-level focus. This approach helps operators stay competitive and drive revenue growth in four key ways:
1. Identifying high-potential opportunities
Every country contains micro-territories with distinct demographics, behaviors, and commercial potential. Successful operators align their commercial, network, marketing, and distribution strategies to reflect these differences.
What works in one locality will not necessarily perform well in another. Guided analytics reveal not just where problems exist, but why they occur. That enables precise, recommended actions. For instance, if an operator is losing market share in a high-average-revenue-per-user (ARPU) town, analytics can pinpoint the cause—perhaps degraded service from a specific antenna—and direct a repair that stops churn and recovers revenue.
By targeting areas with the largest revenue deviations, operators have seen revenue uplifts of up to 15%. Many operators are aware of underperforming regions but lack the insight to understand the causes and execute the right remedial actions.
2. Faster issue identification and effective management
The necessary data already exists within operators’ systems. With the right analytics application, teams can see where to focus and decide which actions will have the most impact.
For example, if ARPU is lower in a particular city, analytics can determine whether this is due to network quality issues or simply lower data usage. With that insight, an operator may choose to improve network performance to reduce churn rather than running an expensive point-of-sale campaign that won’t address the root cause.
Analytics can also expose retail and distribution problems. Suppose a store in a busy shopping district posts below-average new-subscriber sales. Is demand low, or is store foot traffic limited by poor placement? Anonymised location and mobile-behavior data can reveal customer movement patterns and indicate whether relocating the store within the mall would significantly boost visits and conversions.
3. Scaling local wins to the national level
Detailed territory diagnostics allow operators to measure how localized campaigns and improvements affect commercial and network KPIs across the country. Insights gathered in one town can inform adjustments and best practices that benefit broader regions.
When regional managers use guided analytics, they can prioritise actions based on data rather than reacting to perceived issues. This fact-based approach ensures resources are applied where they will deliver the greatest return.
4. Outmaneuvering competitors
When a new provider threatens market share, it may seem logical to avoid head-to-head battles in the competitor’s strongest areas. A better strategy is to identify precisely where the competitor excels and to deploy tailored marketing, sales, and retention activities to win and retain customers in those locales.
In one example, an operator increased market share by more than 7% in six months simply by adapting its strategy using local mobile data. Guided analytics help operators benchmark point-of-sale performance by region and reveal where targeted changes can outpace competitors.
Anonymised mobile data is a valuable, underused source of future revenue for operators. When fed into an analytics application, this data generates actionable insights that drive significant commercial benefits. Operators must ask the right questions and be willing to study data at the micro level—viewing their markets not as a single, uniform country but as a network of diverse, evolving local communities that require tailored strategies to compete successfully.
Do you have further thoughts on micro market segmentation? Let us know in the comments.