The WiFi Natshell system in the park is active, and operational data are the basis for decision-making. The amount of revenue, number of users, region to region to make money, regional loss, user retention rate, and the high percentage of fees owed are not always good enough to operate without looking at the statements. V7 provides a rich operating statement, but many park operators look only at total income, do not look at disaggregated data, wasting their data analysis capabilities.
Income statement: where the money comes from
The income statement is the most basic, divided according to dimensions. By time: daily, weekly, monthly and annual earnings, the trend is either positive or decreasing. By fee pattern: what is the monthly income, how much is the day ' s income, how much is the flow, what is the meal basket ' s income, and which is the most profitable. By payment mode: how much is paid in micro-credit, how much is paid, how much cash is paid, how much is the monthly balance of the enterprise, and how much is paid by the user. By region: how much is earned in A, how much is earned in B, how much is generated in accommodation areas, and what is the office area ' s income, depending on which region the contribution is large. The V7 system supports multi-dimensional income statements, which managers can freely combine filter conditions and export Excel for further analysis.
User report: Where people come from
User reports focus on user size and structure. Total number of users: cumulatively registered users, current active users (30 days online), current online users. Increase in user numbers: number of new users per day, number of additional users per month, source of new users (sMS registration, front desk opening, proxy opening). User structures: number of monthly users, number of daily subscribers, number of users by traffic, number of free users, number of enterprise users, number of individual users, number of visitors. Retention of users: rate of secondary retention for new users, 3 months, 6 months retention rate, feature analysis of lost users. The core indicators of the user statements are active users and retention rates, the growth in active users means that operations are healthy, and low retention rates indicate that users experience problems or price misalignment.
Flow reports: how's the network working?
The flow statement reflects network usage and capacity planning. Total traffic: total daily up/downflow, peak flows, average traffic. Per capita traffic: average daily traffic per user, comparison of per capita traffic between different user groups. Application distribution: video traffic ratio, page browsing ratio, P2P share, game ratio, other ratios. Regional traffic: comparison of traffic across buildings/regions, identification of high-flow areas and low-flow regions. High-flow times: highest time in one day and highest rate in one week. The value of the flow statements is guidance band width and QoS strategy adjustment: if P2P is 30% more than P2P limit speed is enhanced; If regional flows continue to grow, consideration should be given to expanding the region’s export bandwidth; if the use of export bandwidth exceeds 80% at peak times, planning for expansion is required.
Payment statement: where the money was missing
The outstanding fee statement is the focus of the improvement. Number of households in arrears: total currently owed fees, percentage of those in debt. Amount of outstanding charges: total arrears, amount per capita. Distribution of overdue charges: defaults by region, user group, fee model. Length of overdue payments: number of users in arrears for one day, 1 to 7 days, 7 to 30 days and more than 30 days. Repeated rates after downtime: number of users who have recovered within 3 days, number of users over 7 days and number of users lost. Central to the outstanding fee statement is identification of groups of users and regions with high outstanding charges, targeted improvements: if a regional deficit is high, it may be due or poor network quality; If the month-on-month user default rate is high, it may be low for automatic renewal and if the cost recovery rate is low, it may be a loss due to poor user experience. The V7 system can generate details of the outstanding fee and support screening at long delays to facilitate reminders by operators.
Frequency of use of reports and persons responsible
The statement is not produced, it must be viewed, analysed and followed up. Daily: Income per day, number of online users, system status, detection of anomalies are handled immediately by the carrier. Weekly reports: weekly income trends, user growth, changes in fees due, adjustment of operational strategy to the manager responsible for operations. Monthly report: comprehensive monthly analysis including revenue, users, traffic, arrears, agent performance, setting of next month ' s targets and improvements, which is done by the head of campus operations. Quarterly and annual reports: long-term trends, assessment of investment returns, planning of next phase of construction, under management responsibility. Each level looks at data on different particle sizes, carries real-time and daily reports, operates weekly and monthly newspapers, and management reads quarterly and annual reports.
Data-driven operational decision-making
The ultimate purpose of the statement is to guide decision-making. For example: the income statements show a high percentage of round-the-clock user income but low ARPU values, considering that the introduction of the week-round package raises short-term client unit prices; the user statements show only 40 per cent of the monthly retention rate for new users due to poor quality or price levels and targeted improvements in investigations; the traffic statements show 60 per cent of video traffic and consider working with video platforms to launch a targeted flow package; the debt statements indicate 30 per cent of the cost of a building, which has been identified as having less contribution points and increases on self-service terminal or extension lines. Data-driven decisions are much more robust than perceived decision-making, and V7 reporting functions provide data support for such decisions.
Export and docking of reports
V7 statements support the export of Excel and CSV formats, which facilitate the interface between financial systems and BI tools. Financial transactions require monthly income and refund data, which are exported and imported into the financial system for accounting purposes. Management needs visual panels to import V7 report data into BI tools (e.g. FineReport, Tableau). Large parks also allow real-time access to operational data through API interfaces and integration with their own operating management platforms.
The campus WiFi Authentication & Billing operational data statements, which are four dimensions of income, user, flow and debt, analysed on a daily and monthly basis at different frequencies, were responsible for taking decisions using data-driven decisions. The V7 system provides multidimensional statements and export capabilities, so that operators use them to avoid looking at total revenue. Periodic analysis of the statements, problems identified, targeted improvements, continued optimization of park operations, and simultaneous increases in income and user satisfaction.