Case study
How Virgin Media successfully met the End of Contract Notification Regulation
Summary
The Ofcom regulation launched 15 February 2020 outlining that customers must be sent an End of Contract Notification (EoCN) 10-40 days before their contract ends. These should include details of the account such as current contract deal and associated offers. The regulation is designed to raise awareness to the customer that they’re out of contract and their price may change. Virgin Media, a major provider of broadband, TV, phone and mobile services in the UK, had never previously sent out such a notification, nor were their systems ready to do so.
Company size
10,000
Industry
Retail
Services used
Products used
Challenge
Virgin Media requested support from a dedicated CACI Adobe Campaign consultant to assist with the creation and the facilitation of the end-to-end solution. CACI’s Senior Consultant, Fraser Rallison, joined the team to support Virgin Media with its EoCN campaign.
Implementation
Virgin Media faced significant challenges in implementing EoCN. Its existing systems were not equipped to produce these notifications, necessitating the creation of an end-to-end solution from scratch. Not only was this a complex task, but it had to be managed within a very tight timeline, with substantial financial implications if the deadline was missed.
Communication
Additionally, Virgin Media needed to ensure the accuracy and clarity of the notifications to avoid customer misunderstanding. In addition, they needed to identify the most appropriate and accessible way to contact customers, whether via email or special formats like audio or braille.
Solution
The EoCN approach consisted of passing data through several different data systems. The process began by selecting all eligible customers using Virgin Media’s source billing system. This data is then released to be transformed into a more customer friendly format. Once complete, the customer specific offers are appended and the data is delivered into Adobe Campaign.
Within Adobe Campaign, six individual workflows were created to release over 20 different data files. These workflows ensured that the data coming through was correct and accurate with no missing values which could cause confusion to the customer. The data is also checked to ensure all offers are correct and make sense to the consumer.
Once these steps are complete the data is reviewed to identify the most appropriate way to contact customers. This is identified by reviewing their previous email engagement, quality of email address and whether they require a notification in a special format (such as audio or braille).
Once these checks and classifications are complete a bespoke report is built from Adobe and shared with project stakeholders with a request to approve the accounts should they match the project plan. Once sign off is agreed the data passes a final two-stage quality assurance check before then being released to separate email and direct mail agencies.
Results
The level of granularity within the workflows allowed Virgin Media to better understand the offering provided to customers. The flexible and dynamic approach has also lead to a significant amount of customers communicated to since 15 February 2020 when the regulation came into force. With the support of CACI, Virgin Media has kept within the EoCN regulations and avoided substantial fines.
Case study
How CACI supported Tesco to quickly join the dots and suggest seamless approaches to problem solving
Summary
Tesco approached CACI to get support from our data specialists on a new project to connect the dots using CACI data.
Company size
10,000+
Industry
Retail
Services used
Challenge
For some years Tesco analysts have used map data from CACI to help define store delivery catchment areas. They have also used data from CACI to help them understand where the uptake of the company’s home delivery service was likely to be highest.
Digital mapping
Latterly Tesco.com, Britain’s biggest grocery home shopping retail business, has introduced a new, more advanced routing and scheduling system to plan home deliveries by its fleet of over 2,000 vans; and in the light of its established relationship with CACI, the retailer again turned to the company to supply appropriate digital map data for both the UK and Ireland.
Solution
To work on this software, CACI has supplied Tesco with premium vector street-level map data, which includes essential routing information such as one-way streets, banned turns and address ranges. The premium mapping data was also used to provide a visually pleasing map background for display and presentational purposes.
Tesco.com generally delivers to homes from 8am right through to 11pm from Monday to Friday, as well as up to 10pm at weekends, so it is vital for the company to be able to route its vehicles to take account of changing traffic speeds and flows at different times of day and at weekends.
CACI has therefore also supplied Tesco.com with Traffic Patterns, a data set that contains average traffic speed on individual road segments, calculated from past traffic flow measurements and differentiated by time of day and day of the week.
Results
Digital map data assembled, prepared and formatted by CACI is playing a key role in the continuing expansion of Tesco.com.
According to Ben Dito Smith, the Location Strategy and Analysis Manager for Tesco.com : “Efficient, timely delivery is a fundamental feature of our home shopping proposition, so it is essential for us to use the most appropriate software and data available for our delivery planning system.”
Tesco.com delivers to consumers’ homes from larger retail stores and from a small number of specially designed dotcom stores. The home shopping business on its own now turns over more than £2 billion.
Case study
How River Island uses ResolvID to effectively perform identity resolution on customer data
Summary
Founded in the 1940s, River Island is now one of the UK and Ireland’s largest fashion retailers. A British high street icon specialising in trend-led, affordable fashion, it was one of the first high street retailers to launch online in the 1990s. The company operates through more than 300 stores globally, as well as e-commerce platforms, with 40% of revenue made from online sales. As an innovative retailer always at the front of the market, the business knew providing seamless, personalised, omnichannel customer experience was vital, but needed to improve its customer data to deliver on a Single Customer View (SCV).
Company size
5,000 – 10,000
Industry
Retail
Services used
Challenge
When River Island began building a marketing and analytics data technology environment with an SCV in-house – a single record that merges all customer data in one place – it recognised that its current customer data set was not deduplicated. It needed real-time identity resolution that could return a single unique customer identifier to River Island.
Data management
Bringing the entire SCV in-house posed a significant operational challenge to River Island. There were many different data feeds that needed to be terminated and also incoming and outbound data that lacked clarity and needed re-evaluation.
Problems of the past
This challenge was compounded by the fact that the original data feeds were also set up by employees who had since left the business, resulting in a trial by fire with their SCV.
Solution
CACI configured ResolvID, a cloud native solution hosted on Amazon Web Services (AWS) Cloud infrastructure, to supply River Island with data cleansing, standardisation, identity resolution and deduplication. Developed with a microservices architecture, the bespoke platform offers significant advantages through its scaling, resilience and flexibility when rapid changes and improvements are required.
ResolvID comprises horizontally and vertically scalable microservices that perform different functions with a seamless interface to enhance River Island’s accessibility. The solution leverages advanced deterministic name and address matching techniques in conjunction with digital and non-digital identifiers specific to River Island customers and their data. As part of this initiative, CACI took a three-step approach to effectively perform identity resolution on River Island’s customer data.
Results
Leveraging ResolvID has resulted in many tangible benefits for River Island, including the creation of various customer dashboards to monitor more targeted figures and generate better, more timely data that bolsters targeted customer campaigns. There have also been noticeable improvements in workload efficiencies, such as cutting down the time required to action workloads to increase the team’s focus on refining their future strategy of doing more with their data to retain oversight on customer performance.
This real-time capability now enables the confident and immediate actioning of data and customer signups to produce effective campaigns based on genuine buying behaviours and generate accurate results.
Case study
Supercharging Hotter Shoes’ customer experience strategy with Fresco segmentation
Summary
Hotter Shoes is the UK’s biggest footwear manufacturer. It’s a digitally led, omnichannel specialist footwear brand with a clearly defined, large and growing target audience.
Company size
5,000
Industry
Retail
Products used
Challenge
Hotter already had a strong heritage in direct-to-consumer marketing when Stephen Shawcross, Senior Global CRM Manager, joined the company four years ago.
Stephen explains: “Like many retailers, we had an abundance of data but it was fragmented. Our first challenge was to bring all the data we had together. We created a true omnichannel single customer view (SCV) that included online, store and contact centre order data, footprint 3D scanning and augmented reality fitting data, web browsing data and email engagement data.
Bringing all data into one location
Creating a single customer view
Solution
CACI’s Fresco data stood out from the competition to offer the level of dynamic detail that Hotter needed. The CRM team was able to match 98% of consumers that order from Hotter to a CACI segment, at an individual customer level.
CACI’s consultant provided “amazing” support for Stephen and the team, with initial training and advice about data mapping and regular check-ins to make sure they have everything they need.
Stephen says, “The big appeal of Fresco was being able to map to an individual customer. A lot of profiling customer systems offer flat pen portraits but aren’t necessarily actionable. CACI matches a customer to a segment and means you can do something with it in real time. We immediately stepped up the level of personalisation beyond buying and browsing behaviour to supercharge our Customer Experience Strategy.”
Results
The combination of buying behaviour, digital engagement, foot-scan data and CACI demographics means Hotter Shoes’ marketing is hyper-relevant and offers true personalisation at scale.
Stephen explains:
“At the highest level, we personalise based on CACI segment, recency, frequency, monetary value (RFM) commercial segmentation and channel preference across all customer touchpoints.”
Hotter is able to create relevant, personalised website homepage images, messages and email content as well as Google pay per click ads, social media posts and direct mail. The profiling is specific and sophisticated – there are currently 27 different direct mail variants. We can prospect with social media marketing, finding and targeting lookalike audiences.
Hotter is also exploiting the Fresco data to support acquisition among new customer groups. Beyond their traditional market of customers aged 55+, the firm is looking to attract the next generation. Fresco segmentation is helping the team identify the most likely personas and to design messages, campaigns and products that will appeal to them.
Case study
Using machine learning techniques to increase revenue, conversions and engagement for DFS
Summary
DFS, the UK’s largest sofa retailer and manufacturer, aims to lead furniture retailing in the digital age. Most famous for sofas, DFS also partners with leading lifestyle brands, such as Dwell, French Connection and Joules, to provide a wider range of furniture products.
CACI has worked with DFS for over 20 years and hosts its customer database, providing insight from CACI’s proprietary datasets to support customer understanding and location strategy. Outputs include segmentation, machine learning models, communications strategy, store catchments and digital targeting algorithms.
Company size
1,000 – 5,000
Industry
Retail
Products used
Challenge
DFS sells to a market where customers traditionally make infrequent, high value purchases. As Mike Aspinall, Data Activation Manager at DFS, explains: “The main thing we sell is sofas, with a repeat purchase average of seven years. This can be challenging for CRM, which is all about nurturing ongoing relationships“.
Our challenge was to deliver a CRM strategy that would enable us to maintain relevant engagement in a targeted way. We wanted to understand the opportunity to encourage repeat purchase through a data lens — which customers might be open to further purchases, when they might be likely to make them, and what kind of products they might want.
Maintain relevant targeted engagement
Understand the opportunity of encouraging repeat purchases
Solution
Mike asked CACI to work with their “rich customer database“, containing a large sample of DFS’ previous purchase data.
CACI analysed two years’ data to find people who had bought two items from DFS consecutively within that period, looking at their purchase patterns and pathways.
CACI mapped out the attributes of people who had made the two qualifying purchases using Ocean demographic and lifestyle data blended with DFS behavioural data. The analysis looked at the identified customers’ over and under-indexing attributes, comparing them to people who bought the first item but not the second.
CACI trained a machine learning algorithm, which is updated daily, incorporating the latest transaction and customer information. It is applied to the data in DFS’ customer experience platform (CEP), appending data points to customer profiles.
Results
Mike tells us, “We had fairly low expectations of the first email in a multi-month journey. But against the control group, we saw an 866% uplift in revenue from the email campaign alone, within 14 days. That’s a four-times conversion increase, measured against a control group of people in the same segment who didn’t receive the communication.”
This project was a perfect fit for CACI as an expert data science partner. With our DFS mission to lead furniture retailing in the digital age, machine learning is crucial to engaging our customers with truly relevant, timely communications. We have been working with CACI for decades – their team understands our business and data extremely well and we have a strong relationship.
