Past Projects

We’ve tackled all kinds of analysis, from basic reporting to advanced predictive modeling.

Typically, our work falls into one of two categories: Predictive/Insight Analysis or Reporting Analysis.

A few examples of projects we’ve worked on include:

Predictive/Insight Analyses

Customer Churn Model

We developed a customer churn model for a well known online gifting company.

Replacing their previous model, this new model adopted more tailored definitions of Active, At Risk, Lapsed and Lost in order to allow the business to better tailor their communications and timings for customer retention and reactivation.

Net Promoter Score
&
Mystery Shopper
Modelling

We partnered with a casual dining brand to enhance their customer service journey to increase customer satisfaction and repeat visits.

Leveraging NPS and mystery shopper data, we built a predictive model that identified and quantified the key traits and moments within the dine-in experience that most influenced high customer satisfaction (promoter scores).

CRM
Incremental Uplift Modelling

We modelled the incremental uplift of a client’s CRM activities to quantify the true contribution of CRM to the client’s sales revenue and customer growth targets.

In addition, the model allowed the client to perform A/B experimentation and deep dive analyses of their campaigns and customer journeys which in turn has helped them to refine comms best practices.

Customer Cluster Analysis

We performed cluster analysis on a client's customer base to try and identify previously untapped segments.

The analysis identified two new niche segments for which the client has dedicated resource and effort to target and grow.

Restaurant Cluster Analysis

Instead of performing cluster analysis on the client's customer base, we focused on their restaurant estate.

To optimise the launch and success measurement of a new operations trial, we built restaurant clusters based on key success measures.

This enabled the client to choose more suitable test and control groups for a more accurate assessment of the trial's success.

Time Series Forecasting
(Impact of Covid 19)

Like many businesses, this client was significantly impacted by the Covid-19 pandemic in 2020.

We developed a forecast to estimate what their sales might have looked like had the pandemic not occurred.

This projection helped the client understand the extent of the disruption and informed their recovery planning.

Reporting Analyses

RFM Model

We built an RFM model for a big high street name, with particular focus on the recency and spend of their customers.

The process involved initial customer exploratory analysis and customer profiling in order to define the RFM segments. After the build, we worked with the client's Data Engineering team to productionise the model within the data warehouse.

Report Streamlining and Automation

Upon introducing a new CRM software stack to their business, we were brought in by a luxury fashion brand to build a new suite of CRM reports as well as redesign their existing reports. The key objective was to reduce, if not eliminate, the need of manual intervention and improve delivery time and report accuracy via automation and report streamlining.

We successfully moved the customer away from Microsoft Excel based reporting to Tableau, thereby reducing the time to produce and disseminate their regular reports from 4 days to 2 hours. We also trained the business to run, update and diagnose the reports.

Data Capture Initiative

Another big name in luxury fashion, as part of their business strategy, wanted to adopt a data centric culture throughout their retail stores. We were commissioned to perform a full data quality audit of their customer and transactional database to identify what data was currently being collected, what gaps existed and potential areas of improvement in data quality.

From our findings and recommendations, we were then tasked with the 'data capture initiative'. The initiative, via a process of monitoring, reporting, education and incentivisation, was aimed at encouraging EMEA stores to increase and improve the quality of customer data captured at EPOS.

Our main responsibilities were the build of the logic to identify poor quality captured data, a scoring system for data capture performance and and automating the reporting process.

The initiative has proved successful within EMEA and has also been pushed out to the US and Asia regions.