Case Studies
Here are some examples of how RAIS has helped clients to leverage their customer data to improve performance and productivity.
Here are some examples of how RAIS has helped clients to leverage their customer data to improve performance and productivity.
CHALLENGE
Weekly and monthly reporting back to the business was taking up a lot of time. In fact more time was being taken to gather and report on data than to interpret it and figure out what to stop, start or continue. No specialists existed in the business and there was no budget to hire an expensive consultant or employee.
SOLUTION
Using the RAIS platform and reporting service, we automated the generation of various reports, delivering them through Google Data Studio. This saved between 10 to 20 hours a week, which employees put back into value-generating activities. It also provided new insights enabling our customers to make more informed budgetary and marketing decisions.
CHALLENGE
To optimise the types of offers used to attract new customers through different channels and in order to generate as many new customers as possible at the highest possible lifetime value.
SOLUTION
Using the RAIS predictive Customer Lifetime Value algorithm they understood the value of customers generated by various offers in the last two quarters, how many became full-price customers and what their churn rate was like.
They clearly identified specific channels and offers to change and as a result stopped offer types that generated low lifetime value customers resulting in those channels improving CLV by £43 which meant more could be spent on those channels to acquire new customers.
CHALLENGE
Data sat in different systems. It took a long time to pull it together, understand and use it for targeted CRM, especially within email marketing. They also knew that there were duplicate customer records and wanted a clean, trustworthy system that let them treat customers based on their true value and purchase habits.
SOLUTION
RAIS developed custom integrations with various data sources and pulled together a deduplicated view of customers, including a custom pet ownership segmentation. Metadata was pushed and dynamically updated within the ESP and cohorts were synced with Google Ads and Facebook Ads audiences.
A 13% increase in repeat customers and 4% increase in their frequency led to a 16% year on year increase in revenue from existing customers as a result of a more targeted communications strategy.
CHALLENGE
To get members of the Le Col Cycling Club to engage in the programme, exchanging points for vouchers and using those vouchers to drive more repeat purchases, growing lifetime value as a result.
SOLUTION
We integrated loyalty data into RAIS. We then created logic that defined a number of new data fields that were pushed to the ESP, used for triggering and filtering out customers from automation workflows, as well as personalising voucher code content.
Over a 9 month study period, campaigns generated redemptions across 1024 customers. 72% of the purchasers were brand new and of the remaining, existing purchasers, spend per customer increased by 88% due to an increase in purchase frequency.
CHALLENGE
In the post-Covid era of trading the customer needed to manage the Marketing budget very carefully. They wanted to get a feel for what future performance would look like in various investment scenarios and make decisions on where to increase, decrease or maintain spending levels.
SOLUTION
Using the RAIS business performance forecasting model, they were able to track future performance forecasts, understand the impact of different budgetary scenarios and what activities to invest more and less in.
This enabled them to maintain spending levels while increasing the volume of acquired customers by 14%.
CHALLENGE
This luxury brand knew it had some highly important high value customers but didn’t know how many, their purchase habits nor what kind of customer they were. They wanted to develop a VIP strategy and grow the value from this segment.
SOLUTION
Using RAIS they were able to quickly understand who these VIP customers were, what and how they were buying.
Targeted communications were tested and drove a 67% increase in average order value, as a result of these customers more than doubling their units purchased per order placed.
CHALLENGE
To generate more repeat bookings by rewarding customers with the ability to re-book Cottages that they had stayed in previously, or offer a suitable alternative nearby, if the Cottage they had stayed in was no longer listed as a bookable property.
SOLUTION
RAIS created the logic to identify and prioritise specific cottages when they became available to re-book and tie them to customers who had stayed in them previously. Specific metadata was created and sent to the ESP to trigger and personalise email content e.g. Cottage name, Cottage location.
Campaigns generated repeat bookings across 310 customers over a three month period. Average booking value was 20% higher than the average booking value across all bookings made in the equivalent time period.
CHALLENGE
To understand whether an opportunity existed to cross-sell services and products across the clients' different sales channels and whether investing in CRM had the potential to deliver a significant return.
SOLUTION
In this analytics project RAIS combined data from multiple channels to understand the customer crossover and profile of customers that did and didn’t shop in multiple channels.
The summary of results concluded that a large financial opportunity existed in particular between two channels, which provided the business with a focus for their activity and confidence in investing further.
CHALLENGE
To know what kind of budget to set and how best to understand Customer Lifetime Value for paid marketing investment across different segments within the ticketing marketplace.
SOLUTION
Using the RAIS predictive Customer Lifetime Value algorithm and the ability to identify specific segments of customers based on their customer and ticket types as well as opt-in preferences, we identified where the best places to invest in would be. This would increase the likelihood of acquiring higher lifetime value new customers.