A PE-backed price comparison service wanted to optimise their outbound sales funnel with the aim of increasing monthly sales by improving conversion rate. Using machine learning we improved their conversion by 20%.

How QuantSpark Talent supported the in-house recruitment team of a leading UK retailer, combining our insight into the analytics sector with our expertise in sourcing talent to find the right senior data analyst.

How QuantSpark Talent supported the in-house recruitment team of a leading UK retailer, combining our insight into the analytics sector with our expertise in sourcing talent to find the right senior data analyst.

Predictive analytics can make a big difference to a company’s revenue by delivering cost savings through efficiency and from the benefits of applying a more strategic approach. This case study shares the findings of a recent diagnostics project we undertook for a large national supermarket chain that asked us to look at its discounted stock reporting for an initial proof-of-concept model.

Our client needed an objective assessment of their data engineering stack in order to mitigate risks created by staff turnover, improve institutional knowledge, embed best practice into the rebuild of the data architecture, scope future phases of data engineering work.

A high-street clothing retailer wanted an analytical toolset to allocate digital marketing spend across multiple channels to maximise their return on investment on advertising spend. Our tool reduced CPA by 10% whilst growing profitable acquisition.

Effective churn management is million dollar lever to driving growth and maintaining margin.

As with most SaaS businesses, our client had built up an extensive amount of data about their products and customers but crucially lacked a consolidated view of the key functions of the business, namely marketing, sales, and product usage. This view is an essential building block to sophisticated business management in the digital world – understanding the behaviour of a business’s customers today in order to predict what they might do tomorrow.

A private equity owned B2B SaaS company which had pursued a buy-and-build strategy. Having completed several recent acquisitions, the client could now boast both strong organic as well as acquisition growth. However the constituent business units still used different source systems and business logic across key datasets.