The brief
Drishti is a competitive intelligence and market analysis platform built for a used-car dealership in the United States.
The dealership operated in a highly competitive market and needed a way to continuously understand what competing dealers were doing with their inventory.
The requirement went beyond simply collecting competitor listings. The system needed to monitor competing inventory at regular intervals, compare those vehicles against cars on the dealership’s own lot, analyse the surrounding market, and turn the results into actionable recommendations.
The central question was:
Given what the competitive market looks like right now, what should we do with each vehicle on our lot?
From web data to business intelligence
Drishti continuously gathers publicly available competitor inventory and converts changing website information into structured market data.
Competitor websites are monitored at regular intervals, with the system collecting relevant information about available vehicles.
The collected data is then processed and compared against the dealership’s own inventory.
This creates a continuously refreshed view of the market rather than a static snapshot.
The pipeline follows:
Monitor → Collect → Normalise → Match → Compare → Analyse → Recommend
Continuous competitive monitoring
Real-world competitor websites are not static data sources.
Listings can be added, removed, repriced, updated, or completely sold between two observations. Websites can also use dynamic rendering and changing page structures.
Drishti was therefore designed as an ongoing data-collection pipeline rather than a one-time scraper.
Browser automation and specialised scraping infrastructure were used to reliably navigate competitor websites, collect relevant information, and feed the results into downstream analysis.
Vehicle-level market intelligence
The system compares dealership inventory against comparable competitor vehicles at a detailed level.
Rather than matching only on make and model, Drishti can evaluate multiple attributes of each vehicle, including pricing, mileage, specifications, descriptions, and other listing-level details.
This allows the system to understand how an individual vehicle is positioned relative to similar inventory in the market.
The resulting analysis can surface questions such as:
- Is this vehicle competitively priced?
- How many comparable vehicles are currently available?
- How does its mileage compare with competing inventory?
- Are competitors providing information that is missing from our listing?
- Is the vehicle positioned competitively?
- Has the surrounding market changed since the last analysis?
From analysis to recommendations
Collecting data is only useful if it can influence decisions.
Drishti transforms market observations into actionable recommendations for vehicles on the dealership’s lot.
If a vehicle is positioned strongly against comparable inventory, the system can identify that condition for pricing review.
If competing listings contain useful information that is missing from a dealership listing, the system can highlight the missing details.
If a vehicle appears poorly positioned against its competitors, the system can surface the situation for attention.
The system therefore moves from:
What is happening in the market?
to:
What should we do about it?
Understanding the competitive market
Drishti does not stop at individual vehicles.
The system also builds profiles of competing dealerships based on the inventory and market information collected over time.
This creates a broader view of competitor behaviour, including inventory composition, vehicle mix, pricing patterns, and positioning.
Instead of looking at isolated listings, the dealership can understand competitors as organisations operating within the same market.
This provides a 360° competitive perspective spanning both individual vehicles and competing dealers.
A living market model
Because the system repeatedly collects and analyses inventory, it can track how the competitive landscape changes over time.
Vehicles appear and disappear. Prices move. Descriptions change. Inventory composition shifts.
These changes become signals that can be incorporated into the dealership’s understanding of the market.
The result is a living market model rather than a report generated from a single point in time.
Engineering a difficult data problem
The project combined browser automation, web data extraction, anti-bot and reliability considerations, data processing, entity matching, market analysis, automated reasoning, and infrastructure.
The difficult part was not extracting a single vehicle listing.
The difficult part was creating a reliable system that could repeatedly collect large amounts of changing information, determine which vehicles were actually comparable, understand the differences between listings, and transform those observations into useful intelligence.
The complete intelligence pipeline
Drishti connects several layers into one system:
Competitor Websites
↓
Automated Collection
↓
Data Normalisation
↓
Vehicle & Dealer Profiling
↓
Comparable Inventory Matching
↓
Market Analysis
↓
Business Recommendations
This architecture turns raw external data into a decision-support system for dealership operations.
Built for a competitive market
Used-car inventory is highly dynamic, and competitive positioning can change quickly.
A vehicle that looks competitively priced today may become expensive when a similar vehicle enters the market. A vehicle that appears difficult to sell may become highly attractive when comparable inventory disappears.
Drishti was designed to keep that competitive context continuously visible.
The result is an intelligence layer that helps the dealership understand not just what it owns, but how those vehicles compare with everything happening around them.
The idea behind Drishti
Competitive advantage often comes from seeing changes before they become obvious.
Drishti continuously observes the market, builds structured intelligence from competitor behaviour, and connects that information to the dealership’s own inventory.
See the market. Understand the competition. Act with context.
Project highlights
- Continuous competitor inventory monitoring
- Automated web data collection
- Detailed vehicle-level comparison
- Comparable vehicle matching
- Pricing and market-position analysis
- Listing completeness analysis
- Dynamic business recommendations
- Competitor dealership profiling
- 360° competitive intelligence
- Historical market-change awareness
- Browser automation for dynamic websites
- Production-oriented scraping and analysis pipeline