For many years BP has operated with a well-established global segmentation to identify optimal consumer targets and develop strategies, using data collected via an online survey of 1000 customers.
BP NZ wanted to understand if the NZ customer base exhibited the same behaviours illustrated by the global segmentation to ensure they were engaging with Kiwi customers in the most effective and relevant way. Mapping the NZ base to the global segments using transactional information showed that a more in-depth understanding of customer behaviour was needed.
Following this insight, BP NZ commissioned a data-driven behavioural segmentation for targeting, measurement, and strategy. The following information was provided for each customer segment:
The segmentation allowed BP NZ to understand the opportunities and challenges that were relevant to each segment. This informed the way the organisation engaged with AA Smartfuel members (message, channel, tone, frequency) going forward to enhance the relevance of their offers.
The segmentation also created a framework from which BP NZ could deliver campaigns to the AA Smartfuel member base while ensuring resource is focused on the most important activities for each segment and provided a large variable set for each customer, to be used in micro-targeting.
A utility company has a large customer base to whom they send regular marketing communications, but they felt that the messages weren’t delivering to bottom line performance. They wanted to shift to delivering highly personalised messages at the right time for the customer – the problem was, they didn’t have visibility into their data or a tool with which to deliver these messages.
The organisation, which had worked with Datamine before, contracted us to help them answer the following questions:
First, we mapped out the use cases, determining what they wanted to do (e.g. email or multi-channel, event-triggered messages, web or social integration etc.) and understanding how their data can enable it.
Datamine then guided the client to select the best platform for their challenge, then implement and test the initiatives before going live. We provided the team with enough knowledge and training to where they were able to successfully run it themselves and see results from their activities. Now, we operate under a support retainer to help them optimise their use of the platform – we provide guidance and support, as well as technical expertise to help them continually improve and act as an overflow resource for when they are busy.
The client now has greater control over their marketing – they’re able to deliver highly personalised content and experiences to their customers. Engagement rates are up 20% since implementation, and the client can deliver 5x more campaigns, all of which are much more targeted and specific. As part of the optimisation, we’ve increased the customer centricity through personalisation of each message, delivering a 10% improvement in revenue per send and a click-to-open rate improvement up to 25%.
The success of these marketing efforts has allowed the client to build the right team of experts to deliver – the team has been able to more than double in size since implementation. Datamine’s focus is now on support and optimisation in order to help them go from good to great.
BP strive to make decisions that are backed with solid evidence that will enhance their position in the market place and deliver the best results to customers.
BP wanted to gain a view of their position in the market and see the behavioural differences between customers that use the AA Smart Fuel (AASF) card and customers that do not.
The idea behind this was to gain better insight into how customers use AASF as a rewards program to inform future interactions with these customers.
The solution was to profile the NZ service station market to get a view of where BP sits in the market. This analysis compared BP’s customers against the total market in terms of brand loyalty, average spend, share of wallet, market share and demographic factors.
The AASF base was then analysed to give an idea of the differences between AASF customers and other BP customers. In addition to the above variables the analysis looked at regional distributions, transaction numbers and spend by day of week and time of day, recency and frequency of visits and purchasing behaviour.
Analysis of BP’s market position showed a few valuable opportunities to increase BP’s share of wallet. AA Smart Fuel was shown to have a positive influence on customer behaviour and can be further leveraged with product offers and targeted communications. Product purchasing behaviour also revealed some interesting relationships with certain age demographics for BP to evaluate in a marketing context moving forward.