Showroom to Service Bay: How Rubiscape Redefines Automotive Intelligence

Showroom to Service Bay: How Rubiscape Redefines Automotive Intelligence

In today’s data-driven world, the automotive industry is experiencing rapid transformation. With evolving customer preferences, rising competition, and the growing importance of after-sales services, the need for deeper, data-backed decision-making has never been greater. This is where Rubiscape steps in to drive innovation and growth across every layer of the automotive sector.

 

Why BI Matters in Automotive

Whether you're a manufacturer, dealer, or service provider, you're constantly gathering massive volumes of data from vehicle sales and service records to customer feedback and inventory levels. Traditional methods can’t keep up with the pace of analysis required. Rubiscape helps transform this raw data into meaningful, visual insights that empower smart business decisions.

 

Unlocking Insights with Rubiscape’s GEN AI

What makes this even more powerful is Rubiscape’s GEN AI. With just a few clicks, I was able to generate actionable insights and automated narratives directly from the dashboard. GEN AI helped interpret trends, pinpoint anomalies, and suggest strategic improvements, saving time and delivering deeper business intelligence without manual effort.

 

Curious about what the data revealed? 

Here’s what Rubiscape GEN AI uncovered from the dashboard:

 

Executive Summary

Key Performance Indicators (KPIs):

  • Total Vehicles Sold: 10,000 – This is a strong indicator of overall sales performance. Further analysis is needed to determine if this is growth or decline compared to previous periods.
  • Average Discount per Vehicle: ₹38.57K – This suggests a significant discount is being offered on average. Investigate the reasons behind these discounts (e.g., competitive pressure, clearing inventory). Analyze the impact on profitability.
  • Service Revenue: ₹10.41 Crores – This represents the revenue generated from service operations. Compare this to previous periods and benchmark against industry averages.
  • Vehicles Under Warranty: 50.01% – A high percentage, possibly indicating a strong warranty program or a large number of recently sold vehicles. However, high warranty claims could negatively impact profitability. Analyze warranty claim co
    sts.
  • Financed Sales: 49.97% – Almost half the sales are financed. This shows reliance on financing options. Assess the risk associated with financing and explore alternative sales strategies.

Sales Channel Analysis:

  • Dealer: Shows the largest sales channel contribution. It's important to continue investing and improving this channel.
  • Corporate Sales: The second largest. Explore opportunities for growth in this segment.
  • Online Booking: The smallest contribution. Investigate why online bookings are lagging and implement improvement strategies.

Vehicle Fuel Type:

  • Relatively even distribution across Petrol, Diesel, Hybrid, and EV. This indicates a diverse product offering catering to various customer preferences. Further analysis is needed to understand the profitability of each fuel type and market demand trends.

Sales by Month and Service Type:

  • This chart displays seasonal variations in sales and service demand. It would be valuable to analyze the reasons behind peak and low periods. The data needs further analysis to determine if this reflects a genuine business trend or a random variation.

Sales by Risk Score and State:

  • This heatmap shows sales performance across different states and risk scores. States with higher risk scores might require targeted marketing or stricter credit policies. This visualization requires further drill-down analysis to discover actionable insights at the state level. A deeper dive to understand the cause of high or low risk in each state is crucial.

Overall Insights and Recommendations:

  • Profitability Analysis: While the dashboard shows strong sales volumes, a deep dive into profitability is crucial. Analyze the impact of high average discounts on the bottom line.
  • Warranty Management: The high percentage of vehicles under warranty requires monitoring of warranty claims and their associated costs.
  • Sales Channel Optimization: Continue focusing on the high-performing dealer channel while investing in strategies to boost online booking sales.
  • Targeted Marketing: Utilize the sales by risk score and state data to implement more targeted marketing and sales strategies.
  • Seasonality: Develop strategies to address the seasonal variation in sales and service demands.
  • Data Granularity: The dashboard provides high-level views; more granular data (e.g., individual dealer performance, customer demographics, etc.) would allow for more in-depth analysis.

In conclusion, the Executive Summary provides a good overview of key performance indicators. However, a deeper analysis of the underlying data is necessary to uncover more actionable insights and drive strategic decision-making. Consider adding key metrics such as customer acquisition cost, customer lifetime value, and return on investment (ROI) for a more comprehensive view of business performance.

Sales Analysis 


Here are some insights from the provided sales analysis dashboard:

Overall Sales Performance:

  • Total Sales: A total of 10,000 vehicles were sold (4,997 financed + 5,003 non-financed). This indicates a relatively even split between financed and non-financed sales.
  • Average On-Road Price: The average on-road price is ₹8.69 Lakhs. This is a key metric for understanding the average value of vehicles sold.
  • Monthly Sales Trend: Monthly sales show some seasonality, with peaks in July and December, and a trough in April. This suggests potential factors influencing sales throughout the year (e.g., promotional periods, seasonal demand). Further investigation is needed to understand the reasons behind this trend.

Vehicle Performance:

  • Popular Models: Tata Tiago and Tata Nexon are among the top-selling models, indicating strong customer preference for these vehicles. The Bajaj Pulsar also performs well.
  • Transmission Preference: There's a slight preference for manual transmissions over automatic transmissions across most models. This might indicate price sensitivity or preference for manual driving. The disparity is not significant though.
  • Fuel Type: The sales data across fuel types (petrol, hybrid, EV, diesel) shows slight variations but no overwhelming preference for one type of fuel over others.

Sales Channels:

  • Dealer Performance: There's variation in sales performance across different dealerships. Smith Ltd is the top-performing dealer. Investigating best practices from high-performing dealers might benefit other dealerships.
  • High Discount Vehicles: Specific vehicle variants (Bajaj Pulsar Top, Tata Harrier Mid, etc.) are offered with significant discounts, suggesting potential inventory management challenges or strategies to clear stock.

Financial Aspects:

  • Financing: The nearly equal split between financed and non-financed sales suggests a healthy balance in customer payment options. Further analysis could reveal customer segments who prefer either financing or cash purchases.

In summary, the dashboard provides a good overview of sales performance. However, deeper dives into specific aspects, as outlined above, are necessary to extract actionable insights and improve sales strategies.





Click here to explore the dashboard – you can interact with it, apply filters and see what insights emerge.

GEN AI didn’t just visualize the data it told a story.
[Note: Data analysis for the study is performed on synthetic data]

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