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The Key to Successful Churn Renewals Analytics: Actionable Insights, Building Trust, and Optimizing Model Accuracy
Advanced analytics can help predict customer churn and inform proactive outreach. But models must provide actionable insights and build trust to drive value.
How effective diagnostics generate value for business and pave the way for successful data initiatives
The analytics diagnostic is an essential tool for understanding how an organisation can use data to drive strategy, accelerate ways of working, or simply to make money. Over short sprints, QuantSpark identifies and ranks these opportunities according to feasibility and ROI, creating a supporting roadmap to develop high priority items.
The economics of churn reduction: Why analytics for SaaS is so vital for valuation
QuantSpark has worked with PE-backed SaaS businesses since 2016 in providing an end-to-end service offering data engineering, dashboarding, predictive analytics, bespoke tool development, and due diligence support.
Private Equity.
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%.
A PE-backed prosthetics company wanted more accurate forecasts to improve the performance of their supply chain. They business wanted to leverage historic performance trends to improve forecasting accuracy of future sales on automated basis.
A PE-backed industrials manufacturer wanted to create a process for predicting churn by anticipating risk at the customer level and help its sales team pre-empt likely customer churn.
A PE-backed SaaS business needed a robust analysis of revenue and churn in order to support its Vendor Due Diligence process.
A PE-backed accounting and HR SaaS provider wanted to reduce customer churn and drive value from its existing customer base.
For a leading UK supermarket QuantSpark developed a best-in-class macro space recommendations platform.
Retail and Consumer.
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.
A UK high-street retailer wanted to drive incremental growth in email revenues and increase customer retention.
A fast-growing cloud software business had developed an in-house KPI dashboard to monitor sales performance and customer success, however the process to manage and update the dashboard was manual and time-consuming.
For a leading UK supermarket we developed a model to help estimate the location of vegan population and then recommend ranging adjustments at the store-specific level.
For a leading UK supermarket QuantSpark developed a best-in-class macro space recommendations platform.
SaaS / Recurring Revenue.
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.
A PE-backed SaaS business needed a robust analysis of revenue and churn in order to support its Vendor Due Diligence process.
A PE-backed accounting and HR SaaS provider wanted to reduce customer churn and drive value from its existing customer base.
For a leading UK supermarket QuantSpark developed a best-in-class macro space recommendations platform.