Investing in analytics and data science services empowered a household name multi-brand retail and wholesale client to enhance their segmentation strategies, build a holistic view of customer journeys, and discover new ways to boost consumer experiences and sales.
An established multi-brand client of Katalyze discovered a wealth of sales and product data that wasn’t fully utilised by its teams. Customer segmentation efforts using traditional RFV (Recency, Frequency, Value) methods delivered limited results. As key account opportunities emerged, the client lacked insight into how accounts were transforming into essential customers.
To navigate a difficult economic environment and sustain growth, the client needed a holistic view of their customer base, and the journey each buyer was taking. They wanted a new approach to customer segmentation analysis, both for their brand’s use and at a group level.
With an upgraded approach to segmentation, the client planned to implement more refined selling strategies, expand their portfolio of solutions, and increase customer retention. They needed to ensure their new strategy extended across all of their brands and consolidate brand-level segmentations into group-wide segmentations, all without stopping or re-doing any existing work.
The team at Katalyze joined forces with leading data analysis partners to develop a customer segmentation strategy based on the spending behaviours demonstrated by the client’s customers.
Drawing on various advanced analytical strategies and data science services, Katalyze launched a 6-step process to produce a consistent set of customer behavioural segmentation, consolidate them at the group level, and implement them into business processes.
The multi-phase project included:
• Discovery: The comprehensive analysis of historical, customer, product, and sales data enabled a holistic understanding of the business, its target audience, and its goals.
• Detailed segmentation: In-depth analysis of buyer behaviours and microgroups revealed granular characteristics and factors for further segmentation.
• Segment consolidation: Machine learning methods were used to cluster and consolidate accounts into targetable segments, based on behaviour.
• Drift analysis: Customer journeys were further analysed, alongside potential trends and future changes that may affect purchasing trends.
• Opportunity analysis: Recommendations were issued based on evident touchpoint opportunities and potential strategies to improve profitability.
• Comprehensive integration: The segmentation strategies were then embedded into the business BI reporting suite, with custom reports for national sales, regional sales, marcomms, and senior leadership teams.
With the extensive analytical insights, strategic support, and technical expertise of Katalyze and its partners, the client was able to transform their segmentation strategy.
Mapping out clear views of the lived customer journey, allowed for a deeper understanding of each group segment and the wider target audience. This facilitated a more efficient marketing and sales strategy, increasing revenue and return on investment.
What’s more, the client was able to streamline and improve their account management strategies while taking a proactive approach to future growth. The segmentation strategy ensures they can identify groups at risk of churn, discover the pathways from acquisition to greatness, and even discover new cross-selling opportunities to boost customer lifetime value.