Best use of FastStats® 2015 Award Finalist
Using FastStats® to put customer insight at the heart of direct marketing activity and engage with customers via timely and relevant content
Ageas Retail Ltd, through its direct to consumer brands, RIAS and Castle Cover, provide Motor, Home, Travel and Life Insurance products to nearly 1m policyholders through Telephony, Website and Price Comparison Websites. Ageas Insurance Ltd also provide insurance to partnership clients.
Ageas’ new Marketing leadership team had a very clear objective – put customer insight at the heart of direct marketing activity and engage with customers with timely and relevant content.
This simple objective required a complete transformation of the database marketing team, processes, technology and data to move from a very labour-intensive disjointed situation to an opportunity to strive for efficiencies and deliver greater effectiveness in campaigning. The original team, plus the managed services element, was too costly to justify and therefore savings had to be made in both FTE and costs that could drive a more acceptable cost per acquisition.
FastStats delivered our first segmented view of our customers and introduced new levels of personalisation into our campaigns, achieving significant uplift in response.
The business case for the transformation project identified significant business, customer and staff benefits. This could be realised by:
- consolidating the data into a single customer and marketing database;
- introducing the appropriate technology to automate campaign delivery;
- integration of customer insight into campaign selections;
- introducing personalisation and multi-channel campaigns to deliver between 6-12% uplift in direct-marketing response rates;
- cost avoidance benefits by repurposing the internal marketing SQL servers to support other IT projects.
Ageas Retail did not have the capacity or capability to deliver this transformation in-house due to a strategic IT change programme and marketing resources focused on delivering BAU activity. The project was therefore outsourced to Communisis Data Intelligence to develop, host and maintain the Customer and Marketing Database which allowed Ageas Retail, supported by Communisis, to deliver analysis and campaigning internally.
This project was focused on the creation of a single customer view marketing database (SCV) built from Ageas Retail customer data; Ageas Retail prospect data; Ageas Retail suppression data; Communisis Alliance prospect data; and third party suppression data. This provided the foundations from which the business case deliverables could be built. The SCV database was also required to be built to fulfil future aspirations, capable of taking in other Ageas Retail owned brands, new data sources and more timely refreshes, without major rework of data ETL process. Ageas Retail wanted the capability for their analysts to be able to focus on analysing data themselves, rather than spending time managing data processing or relying on external suppliers to conduct analysis.
The first phase of the project was to create an SCV for Ageas Retail’s warm data and match this to the Communisis Alliance prospect database, enriching customer data by populating missing fields with prospect data, where available. The next step created a process to amend and append delta records on a weekly basis and with the capability to extend to daily refreshes.
As part of the weekly data build, 11 feeds from 46 data sources containing in on average 1.13 million records are integrated into one SCV and presented back to Ageas Retail users through 500 system variables.
Another requirement from Ageas Retail was the ability for the user to create their own variables without the need for IT or Administrator resources. FastStats functionality has enabled users to create many virtual variables, as derivations or data imports, which can be utilised in analysis and campaign activity.
For the first time, customer and policy data sources have been brought together and made available to the end users via a FastStats front-end (Discoverer, PeopleStage & Excelsior) enabling analysis and campaign outputs based on modelled segments of customer, prospect and inactive data.
By bringing together the data for both Ageas Retail direct brands (RIAS and Castle Cover), it has been possible to enrich each individual brand’s data with detail from the other brand, improving the number of contactable details including email addresses, as well as increasing the volume of, and confidence in, customer renewal dates. As a result, the volume of contactable customers for campaigning has increased by 20%, with increased confidence in renewal dates leading to uplifts in response rate and less wastage.
FastStats Discoverer was able to facilitate the first view of the overlap between customers, brands and product holdings, both for live and warm data, identifying and understanding the extent of any brand cannibalisation and identifying opportunities for cross-brand customer engagement. This has allowed campaigns to be created that specifically target the other brand’s customers as well as de-dupe against prospect data, saving on data purchase costs. This Venn diagram shows customers across both brand and product relationships.
Having a view of the customer and household product holding led to the first customer-insight macro-segmentation, easily identifying those eligible for our main campaign journeys: Get (acquisition), Grow (cross sell and upsell), Keep (retention); and introducing tailored messaging depending on the customer relationship, its strength and where the customers are in the life stage of their policy.
Previously, creation of a new model would take months and deploying the model against the RIAS customer base took a further 20 days each month. The introduction of the FastStats System allowed a suite of models to be developed and deployed for campaigning in hours, through the Profiling and Modelling Module functionality in Discoverer.
These models have revealed clear distinctions within the customer base facilitating improved targeting and the opportunity to use the differentiating variables in campaign design to deliver greater personalisation.
Discoverer has increased Ageas Retail's ability to understand, segment and learn about their customer base and they have been able to transfer this learning into campaign management processes. PeopleStage has allowed them to develop campaigns that recognise the customer’s brand and product relationships, allowing them, for the first time, to de-dupe across the brands and introduce multi-channel campaigns for Direct Mail, Outbound Telephony and eMail.
Ageas Retail currently have 86 campaigns set up in PeopleStage with over 60 published campaigns: 11 weekly campaigns, 3 daily campaigns, 6 monthly campaigns, 2 product led fifteen stage campaigns which facilitate the execution of 3 renewals months running concurrently within a single campaign and numerous ad-hoc campaigns which include a follow up element.
Through training and the understanding of the functionality within PeopleStage, it currently takes less than a day to set up a new campaign utilising the editing functionality, without the need for manual intervention across multiple data sources. The time taken for the campaign files to be processed and output has dramatically decreased using the tool, allowing the analysts and campaign managers more time to develop new insight and tests rather than running the campaigns manually as was historically the case. Without these process efficiencies, the FTE savings in the business case could not have been achieved.
Not only does the automated nature of PeopleStage allow the processing of campaigns to become streamlined, it allows the team time to plan and easily facilitate test and learn. Control cells can be included in the diagram, including creative split control groups and campaign no-mail cells, to help understand the uplifts direct and email marketing is achieving. Through the use of Faststats Ageas Retails has been able to develop enhanced insights into campaign performance across multiple channels. They have been able to transition the reliance on Linear telephony response reporting towards matchback across telephony, web and outbound for a richer view of campaign performance.
PeopleStage also allows the Ageas Retail users to create one diagram which enables an automated staggered campaign through schedules and event triggers. This has been used in a campaign triggered by a customer’s birthday, where messages are staggered – one month, one week, a day before their birthday. This was previously executed manually but now runs as a “lights out” campaign.
Personalisation has been easily enabled through the setting up of the content step on each campaign. One of the campaigns personalises mail content 8 different ways, depending on relationship status and type of household (home campaign) or expected mileage (motor campaign), again this was previously a manual process. PeopleStage has allowed the desired splits to be applied to drive relevant customer engagement within timely campaign activity, delivering uplifts in response rates.
To compliment analytics and drive relevant targeting, FastStats Mapping has been used to present data in a clear, visual method, which is understandable to those outside of the data and campaign teams who may not be as data savvy. For targeting, the GEO module has been able to quickly identify postcodes with 20-miles of our breakdown repair centres, allowing targeted campaigns to be built for customers within those postcodes, whilst avoiding making offers to customers outside of the defined area who do not qualify.
The Customer and Marketing Database, MIDAS, has not been exclusively used by the Knowledge Management Team in Marketing. Through development of the MIDAS Wiki in Excelsior, key database information is distributed to the Marketing Department and other business areas to promote and understand the opportunities within the data. Discoverer and Excelsior has enabled the MIDAS Wiki to present insight internally, raising awareness of key trends and also highlighting the importance of adhering to good data practices to ensure that customer data is captured correctly, updated frequently (where applicable) and also to identify any particular gaps of customer information which, if collected, would bring about greater insight to drive personalisation and relevant campaign activity.
Through the database, FastStats and creation of the MIDAS Wiki, campaign activity is being driven in a new direction to transform marketing activity from a product-centric to a customer-centric approach, leading to increased engagement, response and improved campaign performance and efficiency. FastStats is a critical enabler to this transition, not just in running the present campaigns in an automated fashion but in utilising other key functionality such as campaign strategy constraints, integration of single campaigns into a series of interacting campaigns and the inclusion of real time event/trigger driven interactions which can define an individual’s desired customer journey and treatment strategy.
The project has identified and delivered those benefits and additional benefits, over and above the business case
- consolidating the data into a single customer and marketing database, has currently delivered savings with additional savings identified when new data services come on stream;
- introducing the appropriate technology to automate campaign delivery, has saved costs;
- integration of customer insight into campaign selections, has delivered uplifts in Whole of Life targeted response and improved retention activity;
- introducing personalisation and multi-channel campaigns has delivered campaign uplifts well in excess of those planned, including unbudgeted uplifts in retention activity;
- cost avoidance benefits by repurposing the first of two internal marketing SQL servers to support other IT projects.
Since the project has been implemented, the team are delivering an increased level of campaigning across both channel and brand, including doubling the volumes of emails broadcast at 5% of the pre-change costs. IT impact has been minimised as the feeds to the database are automated and the creation of a single cross brand solution has also delivered maintenance and cost savings.