OLX Autos’ Maneesh Kaushal decodes the rise of data analytics in the auto industry

There is an ever increasing instrumental role played by data analytics in the automotive industry and the role of data in this industry is significant given the rising importance of data driven decision making. Automotive brands can optimise numerous aspects of their business by gaining useful insights from market research and taking decisions accordingly. One of the advantages of data analytics is enabling efficient supply chain management, optimising logistics, and reducing costs. It also helps in analysing customer data allowing companies to segment their customer base and targeting certain groups with marketing strategies which are personalised.

In conversation with Adgully, Maneesh Kaushal, Global Head of Business & Marketing Analytics, OLX Autos, speaks about how data analytics has become increasingly critical in the automotive industry, how it is helping improve operational efficiency and uncover new monetisation opportunities, and much more.

Could you tell us about the growing importance of data analytics in the automotive industry?

Data analytics has become increasingly critical in the automotive industry, primarily due to the escalating complexity of the market and the growing importance of data-driven decision-making. The emergence of connected vehicles, IoT devices, and digital platforms has provided automotive companies with access to vast amounts of data, unlocking new possibilities for improving their businesses.

Within the automotive industry, two key verticals that face challenges in terms of consumer demand behaviours and meeting customer value expectations are the ‘Buying’ and ‘Selling’ processes. In the new car segment, value and pricing ecosystems are relatively straightforward to decide, but in the used car market, it becomes highly dependent on numerous variables. Collecting data related to these variables incurs certain costs, such as Customer Acquisition Cost (CAC) and the expenses involved in physical inspections.

This is where data modelling comes into play, aiding in extracting meaningful insights from the collected data. By leveraging data modelling, automotive companies can optimise various aspects of their operations:

1. Measuring User Interaction: Data analytics helps track user interactions with the product during the pre-sales phase, providing valuable insights into customer preferences and behaviours.
2. Tentative Quote (Pitching): By analysing data, companies can generate accurate tentative quotes based on market value and customer expectations, leading to more successful pitches.
3. Final Quote (Go-to-Market/ Inspection): The data-driven approach helps automotive companies offer the ‘right/ expected’ value in line with the market value of the vehicle, ensuring customer satisfaction.
4. Supply Chain Management: Data analytics enables efficient supply chain management, optimising logistics, and reducing costs.
5. Inventory Optimisation: By forecasting demand and supply, automotive companies can better manage their inventory, minimizing overstocking or shortages.
6. Predictive Maintenance: Data analytics helps predict maintenance requirements in vehicles, leading to proactive servicing, reduced downtime, and enhanced customer experience.
7. Customer Segmentation & Targeting: Analysing customer data allows companies to segment their customer base and target specific groups with personalised marketing strategies.

By employing data analytics, automotive companies can make well-informed decisions, improve operational efficiency, enhance product development, and uncover new monetisation opportunities. Data-driven insights empower these companies to stay competitive in a rapidly evolving market, adapt to changing customer needs, and create more value for their customers.

Overall, data analytics is a powerful tool that empowers the automotive industry to thrive in the face of complexity and uncertainty, leading to better customer experiences and sustained business growth.

What is the role of data in the automotive industry?

The role of data in the automotive industry is multifaceted and spans various aspects of the business, revolutionising how companies operate and interact with customers. Here are some key areas where data plays a crucial role:

Vehicle Design and Development: Data is used to improve vehicle design by analysing performance, safety, and fuel efficiency metrics. Advanced simulations and real-world testing generate data that helps engineers refine designs and create safer, more efficient, and innovative vehicles.

Manufacturing and Quality Control: Data is employed in manufacturing processes to ensure quality control, reduce defects, and optimise production efficiency. Sensors and IoT devices on the assembly line collect data to monitor and fine-tune manufacturing processes.

Supply Chain Management: Data-driven insights enable automotive companies to optimise their supply chains by predicting demand, tracking inventory levels, and improving logistics. This leads to reduced costs and improved production planning.

Sales and Marketing: Data is instrumental in understanding customer preferences and behaviour. It helps automotive companies target specific customer segments, personalise marketing campaigns, and make data-driven decisions to enhance sales and customer satisfaction.

After-Sales Service and Predictive Maintenance: Data collected from connected vehicles and IoT devices allows manufacturers and service providers to perform predictive maintenance. By analysing data on vehicle health and performance, they can anticipate potential issues, schedule maintenance proactively, and provide better after-sales service.

Connected Vehicles and Telematics: The rise of connected vehicles generates vast amounts of data related to vehicle performance, driver behaviour, and navigation. This data is utilised to enhance vehicle safety, optimise driving experiences, and offer additional services to customers.

Autonomous Driving: Data is at the core of developing autonomous vehicles. The continuous collection and analysis of real-world driving data are critical in improving autonomous driving algorithms, ensuring safety, and enhancing overall performance.

Customer Experience Enhancement: Data analytics helps automotive companies understand customer feedback, preferences, and pain points. This knowledge allows them to create more user-centric products and services, leading to improved customer experiences.

Research and Development: Automotive companies rely on data to conduct research and development for future innovations and technologies. Data-driven insights provide valuable inputs for decision-making in exploring new product lines or entering emerging markets.

In conclusion, data is a vital asset that permeates every aspect of the automotive industry. Its utilisation enables companies to optimise processes, improve product offerings, enhance customer experiences, and remain competitive in an increasingly data-driven world. As the industry continues to evolve, data will continue to play a central role in shaping the future of automotive advancements.

What are the future trends and opportunities in the automotive space?

Future trends and opportunities in the automotive space include the continued growth of electric vehicles (EVs), autonomous driving technology, and the integration of connectivity and IoT in vehicles. The shift towards EVs presents opportunities for automotive companies to develop innovative products and services, including charging infrastructure, battery technology, and energy management systems. The development of autonomous vehicles opens up new possibilities for mobility services, shared transportation, and increased safety on the roads. The integration of connectivity and IoT allows for enhanced vehicle-to-vehicle communication, improved driver assistance systems, and personalized in-car experiences. The gradual shift towards EVs will also favour the “used car” markets soon, which will surge the car penetration down the semi-urban and rural markets.

What, according to you, is the impact of AI on martech in the coming years?

AI is set to have a significant impact on martech (marketing technology) in the coming years. AI-powered technologies such as machine learning, natural language processing, and predictive analytics will revolutionise how marketers understand customer behaviour, personalise experiences, and optimise marketing campaigns. AI can analyse vast amounts of data to identify patterns, preferences, and trends, enabling marketers to deliver more targeted and personalised messaging. Chatbots and virtual assistants powered by AI can provide immediate and personalised customer support, improving customer experience and engagement. Predictive analytics can help marketers anticipate customer needs and preferences, enabling proactive marketing strategies. Additionally, AI can automate repetitive tasks, optimise ad targeting, and provide real-time insights, allowing marketers to focus on strategic activities.

What is the consumer behavior observed in the automotive industry in recent years, especially after the pandemic?

Consumer behaviour in the automotive industry has undergone significant changes in recent years, especially after the pandemic. One notable shift is the increased demand for online car shopping and contactless transactions. Consumers are relying more on digital platforms and marketplaces to research, compare, and purchase vehicles. Online car buying services have gained popularity, offering convenience, transparency, and a wide selection of options.

Additionally, there is a growing emphasis on sustainability and environmental consciousness, driving the demand for electric vehicles and eco-friendly transportation solutions. Consumers are also placing greater importance on safety features, connectivity, and in-car technology. They expect personalised experiences, quick response times, and seamless integration between online and offline touchpoints. These changing consumer behaviours highlight the need for automotive companies to embrace digitalisation, prioritise customer-centricity, and deliver personalised experiences across all stages of the customer journey.

What are the major challenges facing the automotive industry today in terms of marketing as well and what are the probable solutions?

The automotive industry faces several marketing challenges today. One major challenge is the increasing competition, which requires companies to differentiate themselves and effectively communicate their value proposition. Shifting consumer behaviour towards online channels necessitates a strong digital marketing strategy and personalised customer experiences. Electric vehicle adoption presents the challenge of addressing range anxiety and promoting the benefits of EVs. Regulatory changes demand compliance and adjustments in marketing strategies. Balancing traditional and digital marketing approaches is also crucial. Probable solutions include investing in digital transformation, building strong customer relationships, collaborating with partners, monitoring market trends, and making data-driven decisions to address these challenges effectively.