A Nigeria-based utility billing platform scales its user base and business using data analytics

After preparing a data engineering roadmap, Daffodil went about employing its skills to utilize the large volumes of data extracted from the provider’s electricity units purchase app. Data enrichment tools from the Google Cloud Platform (GCP) including DataStream, BigQuery, and Data Studio were leveraged toward the intended purpose. The Daffodil team satisfied the data enrichment needs in the following areas:

Analytics Process Optimization

The existing analytics processes employed by the provider were high on costs and storage utilization, and the throughput time was unsatisfactory. Daffodil extracted the requisite data from a BigQuery warehouse and using Advanced SQL queries and multiple schemas, the processing was made more efficient. Advanced SQL queries were applied for building efficient Extract, Transform, and Load (ETL) pipelines to enable cutting-edge analytics for the finance team of the provider.

Hourly Replication

Data were processed and analytics were conducted on an hourly basis. To accommodate the hourly data replication, proper partitioning of tables was done, thereby further reducing the associated GCP expenditure. Earlier, on average for each refresh, nearly 4 GB of data had to be processed, which was reduced to a minuscule 129 MB after Daffodil’s optimization efforts.

Automated Reconciliation

The payment figures in the accounting systems were properly matched up with transactions reported by the payment gateway. Every settlement event, processing event, and the post-settlement event was automated to make the overall reconciliation of payments more streamlined and effortless. Exceptions for chargebacks and payment reversals were also handled concisely.

Comprehensive Cohort Analysis

Cohort analysis or the grouping of customers based on demographics, psychographics, and other traits was presented comprehensively through dashboards. With background querying, multiple views were available across dashboards, including those for customers waiting to get value notifications, the average time to resolve payments, failed payment attempts, and other data to offer merchants an incisive understanding of their customers.

Customer Service Reportage

Merchants required proper reports about customer service activities so that they could keep a regular account of all ongoing and pending service calls. As merchants could properly monitor customer service metrics, their end users were highly satisfied. This allowed the purchase app provider to build better relationships with the merchants as well.

Channel Efficiency Metrics

The reporting of electricity meter recharges of the power suppliers’ respective customers was also carried out. This helped merchants keep tabs on customers whose payments may have gotten delayed or whose recharges failed at the payment gateways, ensuring channel efficiency. Statistical modeling helped create dashboards to monitor distribution efficiency.

Granular Reporting Capabilities

By building multiple observability systems, the finance team of the provider could obtain transparency in customer and merchant information in granular graphical views. While only generalized data metrics spanning across days were available earlier, the data analytics work by the Daffodil team ensured that every few seconds of system changes could be viewed.