MavenMagnet- Mahindra & Mahindra

Disclaimer: Due to NDA's, I will not be able to share any final insights and areas of application and

will be focusing on process & high-level findings + recommendations.

Automobile Research at MavenMagnet

Consumers do extensive research before making a vehicle purchase. Especially, decision making in automobiles is one of the most active topics on the Internet.

Using deep learning analysis Mavenmagnet tools and the team attempts to get actionable insights through in-depth analysis of consumers, owners and intenders when they are really engaged in discussions about the product online or over support calls.

MavenMagnet Tools

MavenMagnet Digital Mapping™ technique is developed help Businesses to understand their market and their consumers. Instead of keywords it forms a digital map pertaining to the business objectives for which data is being aggregated from digital sources including blogs, forums, news, reviews, video logs, audio files, and social networks.

The vibe associated with the themes is identified by MavenMagnet Vibe Sensor™, a technology developed based on natural language processing and machine learning techniques to associate the right sentiments to the right themes in a conversation using inputs from strategists.

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Project Objectives

• Understand the Dip in Sales for two of Mahindra & Mahindra cars

  • Mahindra XUV 700

  • Mahindra Thar

• Derive consumer-based insights on-scale to improve service quality and innovate on new variants of the car models.

** The pictures are latest variants and not the variants on which the study was done

Research Processes

I Areas of Enquiry

• Understanding the pains and delights of using Mahindra XUV 700's new Adrenox (all-inclusive tech-entertainment system)

• Competitor price benchmarking for both the models

• Thar's brand image and usability index

• Key decision making factors for choosing/not choosing Mahindra over others

II Analysing the Dataset

Step 1: Client given qualitative raw data on customer support calls to be fed into the software along with the company's key terms on car names, features, common remarks.

Step 2: The software will produce a digital map (coverational mining) of all the common themes associated with the car models, above and beyond what the client gives

Step 3: Analyse the thematic grouping done by the software and identify more user-centred nuances of the qualitative data through extensive secondary research.

Step 3.1 The emerging themes are segmented into sub-themes for ease of analysis.

Step 3.2 Keep updating the emerging themes based on the influx of more newer data.

Step 3.3 The analysis is discontinued once the theme analysing hits a saturation point

Step 4: Identify common market trends and user behaviour patterns that is leading to the dip in sales and form insights for the clientele.

Usage of specialized Deep learning software aided in avoiding interviewer based biases and also to derive actionable insights rather than mere assumptions that an experimenter would derive our of manual research.

As a final outcome Mahindra & Mahindra was able to walk out with rich information about customer experience, product management and futuristic marketing strategies.

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Redacted Findings

I Mahindra XUV 700 findings

• Mahindra XUV 700's costliest variant was with the ADRENOX system but it was glitchy and did not give a 'luxury' experience

• Mahindra XUV 700's basic variant did not have controllable rear view mirrors which pushes consumers to pick the upper variant and users did not like that tacky experience

II Mahindra Thar findings

• Brand perception that Mahindra Thar would be used by rogue politicians and local rogue gangs owing to the image portrayed in movies

• Thar is not women friendly as it becomes harder for women wearing sarees to climb in the car and also into the backseat making this a non-family car.
  

What Happened Next?

• The ADRENOX software was refined and got integrated with Amazon alexa for top quality functionalities

• Thar released a newer variant with foldable front seat and easy movement to the back row seats