Helping BT price their services
A dynamic platform for pricing
The balance between price and churn is never an easy one. In a highly competitive market, even the smallest change in rate plans can have a significant impact on a company’s overall revenue.
With a sharp decrease of landline rentals and an increase reliability on bundle packages prices, BT needed to ensure they had full visibility of customer line rental usage as well as a deep understanding of how much they could push price increases without hurting their customer base.
For over 20 years, BT has partnered with CACI for dynamic re-pricing and analysis. Powered by an in memory powerful platform, this analysis has helped BT maintain its market-leading status.
Recently however, due to increased competition, BT needed more than just a generic analytics platform. They needed a holistic approach to predictive modelling.
To do that, BT utilised CACI’s many years of industry experience of implementing large-scale predictive analytics over granular data, enriched by the CACI service team. By using a complex modelling written in Python and R, including neural networks and complex forecasting methods, CACI has been able to provide BT with predicted outcomes based on BT’s full business customer base, rather than having to rely on samples of aggregated data.
Qlik Sense was used to deliver dashboard solutions to the BT teams, giving them a clear, easily digestible, visualisation of complex analytics. In addition, the Qlik Sense on demand App generation now means BT can change inputs into the algorithms and rely on the in memory platform to process the results in a timely manner.
This strategically outsourced approach has allowed BT to control its costs without constraining creativity.
15 months’ worth of BT’s over all daily calls are analysed and re-priced, allowing BT to have full visibility of the impact of price changes on revenue and customers.
The predictive modelling gives BT much more than just the ability of analysing data at a granular level. It gives BT a deep understanding of its customer’s behaviour, allowing the company to balance churn and price with a minimum impact to customer retention.