Team members:
Tan Zhe Kang, Data Analytics Lead, with:
- Angelina Goodyer
- Kalpak Joshi
- Maggie Ai
- Joy Zhu
- Ken Ng
Country: Malaysia
Organization: Sonepar
Sonepar is an independent family-owned company with global market leadership in B-to-B distribution of electrical products, solutions and related services. Through a dense network of 80 brands spanning 40 countries, the Group has an ambitious transformation agenda to become the first global B-to-B electrical distributor to provide a fully digitalized and synchronized omnichannel experience to all customers. Drawing on the skill and passion of its 44,000 associates, Sonepar had sales of €32.4 billion in 2022. Sonepar makes its customers’ lives easier, over the counter, visiting customers, by phone or online, – however we’re needed.
Awards Categories:
- Best Acceleration Use Case
- Best Approach for Building Trust in AI
- Best ROI Story
Business Challenge:
Sonepar is a global leader in the B2B electrical distribution sector. Across Asia Pacific we have a large and complex network that caters to a broad array of customers in different markets. This means that we generate a lot of data, from customer transactions to logistical information.
Like many large organisations, we are interested in more rapidly harnessing this data to gain insights into our customers and improve our business. However, our scale, complexity, and varied operating businesses across the region have made it challenging to do this.
B2B retail is a relationship business. Our frontline associates develop deep and meaningful relationships with our customers. However, their ability to draw on the collective experience across our diverse businesses is limited.
We believed that we could use our rich customer data to segment and identify insights for our sales teams. This would allow us to make smarter decisions about which customers are most valuable, those about to leave us, and how to increase margin by offering the right products, services, or support at the right time.
This capability is vital for ensuring sustained growth and a consistent understanding of our customer base in the ever-evolving landscape of the electrical product distribution industry.
However, we need a platform that will allow us to leverage our business users' experience while reducing reliance on scarce technical resources. We believe that this platform would allow us to overcome the challenges we face and achieve our business goals.
Business Solution:
Our APAC Data team holds wide-ranging expertise gained from years of experience in various business and technical roles. We conducted an assessment to determine the viability of building a Customer Lifecycle Model, given the increasing demand for customer insights.
Using a combination of commercial business knowledge and the Dataiku platform / Python programming skills, the team realised the potential impacts and enhancements that the model could introduce.
Within Dataiku we conducted data cleansing and pre-processing - a crucial step given our data set’s scale and diversity. Post the data preparation stage, we conducted exploratory data analysis to identify patterns and relationships. We used a customised RFM model along with business rules to help us categorize our customers based on their purchasing behaviour.
In the first quarter of 2023 the preliminary results presented for validation to business teams with good reception. The strategic and leadership teams have been successfully using the insights and enhanced customer understanding to inform and prioritise strategic initiatives, enhance and uplift campaign design and execution and validate and enhance the understanding of our customers thought the businesses. This phase of the project effectively showcased the collective skills and experience augmented by the successful application of the right technology.
The project is moving into the next phase, deploying the model deeper into business processes, where we will look to build out more integrated applications, help us personalize our offerings to increase profitability through the right product offer, gain deeper insights into customer behaviours, and devise targeted strategies to optimize customer retention and growth.
Thus, Dataiku not only offered a solution to our challenges but also unlocked new potential for growth and improvement. It has elevated the data literacy around analytics use cases as it proved the ability to make data-backed decisions which stands as a testament to Dataiku's transformative potential when navigating the vast landscape of big data.
Day-to-day Change:
The initiative has provided Sales and Marketing with valuable insights to identify different customer segments such as lapsing, growing, maintaining, and reducing. By implementing this approach, we can gain deeper insights into customer behaviours and devise targeted strategies to optimize customer retention and growth.
The model insights are published to the Sales Customer Relationship Management dashboard for use on the road by Sales teams for real time data driven support to understand customer purchasing behaviour.
The impact to business has been to more efficiently develop targeted strategies to address profitability opportunities and make informed decisions to drive sustainable growth.
Also, it has helped to break down technical barriers, empowering people across different roles to access, interpret, and utilize data. Long term this fosters a culture of data literacy promoting proactive engagement and informed decision-making at all levels.
Business Area Enhanced: Analytics
Use Case Stage: In Production
Value Generated:
Through the application of this model, we have been able to identify over 500 unique, actionable customer insights, each representing a distinct opportunity for growth such as:
- Reduction in lapsing customers and prevent reducing customers from churning by early identification.
- Increase spends with key customers with targeted offers.
- Re-acquire churning customers assisted with real time insight via the dashboard.
- Push for Maintaining customers to Growing customer through targeted promotions.
Additionally:
- Saved time and increased productivity, estimated at 3-4 hours per sales person.
- Allow strategic allocation of budget for actions above.
Value Brought by Dataiku:
A key advantage that Dataiku offers is the acceleration of our data processes. By providing tools that streamline the handling of data, Dataiku has improved our ability to derive actionable insights swiftly. For our sales representatives, this means they can generate comprehensive lists of target customers more rapidly and accurately, saving valuable time and effort. As a result, we have seen an uptick in efficiency, allowing us to respond to market trends and customer needs promptly and effectively.
Additionally, the resources provided by Dataiku, such as the Dataiku Academy, Community and Local and Regional APAC Partners have been invaluable. These resources offer our team members the opportunity to upskill, staying abreast of evolving trends in data science and analytics. The networking opportunities within the Dataiku community also encourage the sharing of best practices and collaborative problem-solving, fostering a supportive and dynamic learning environment.
Value Type:
- Increase revenue
- Save time
- Increase trust
