April 2026·5 min read

Competitive pricing intelligence

A leading Indian automaker’s pricing team faced a critical bottleneck: announcing new prices took over a month due to complex spreadsheet workflows, 40+ pricing variables, and no way to run dynamic simulations across states and configurations. Infoveave implemented a

competitive pricing intelligence platform with What-If Analysis, Goal Seeking, and automated dealer reporting — cutting simulation time from months to minutes, enabling differentiated pricing across jurisdictions, and delivering precise reports to 200+ dealers automatically.

At a glance:

Industry: Automotive
Platform focus: Data Insights
Proof type: Quantified outcomes on a governed unified data layer

Minutes

Pricing simulations that previously took over a month

200+

Dealers receiving automated precise pricing reports

40+

Pricing variables managed within a single analytical model

In this story:

Client Overview
The Challenge
The Solution
Results

Client Overview

Product pricing is a critical function for the automotive industry. With fierce competition and customers’ options, pricing intelligence is the key to profits. A minor change in the price can have a major impact on the bottom line. To respond to the changing market, regulations & competitor prices, the pricing team needed an immediate technology-driven approach. An agile method for responding to these price changes would be beneficial. This should also keep a close tab on margins and other business parameters. A cost-plus approach is used to arrive at the on-road price. Parameters like dealer margins, federal and state taxes & cess, transportation charges, insurance, discounts, and others add to the complexity of the problem. The analysis becomes further cumbersome when it involves many variables. They include location, fuel type, vehicle color, vehicle type, and road taxes based on jurisdiction.

The Challenge

The key concern of the business was that it could not respond to the changing market needs at speed. Adding a new tax component or changing competitor prices consumed a lot of work hours. This led to the Pricing team taking at least a month for the announcement of new prices.

The usage of spreadsheets to calculate the price made the process slow. The increasing number of variant combinations made it even more unmanageable. Running various scenarios for different combinations of price points was not easy. With changing variables in runtime to see the impact on price added to the complexity. This forced the client to peg the price to one jurisdiction, thus eliminating the differentiated pricing support to its customers. With increasing data and scenarios, spreadsheets failed to support. This led to a lot of re-work, inconsistencies, and delays. This was a sign of inefficiency and unproductivity of the pricing team. The team wanted a solution that could help them perform analysis, send reports and insights to dealers right away, and announce the pricing amendments on their website, share with media, all in one go. Data automation aided by decision intelligence supported the team’s requirements on competitive pricing intelligence.

The Solution

Ability to respond to the market quickly in publishing new prices.
Supporting complex algorithms with various parameters like vehicle configurations & location.
Running multiple pricing simulations on the fly.
Saving data for past comparison, analysis, and benchmarking the prices.
Effective and timely communication to dealers.

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The Solution

By employing Infoveave, the client was able to measure the factors impacting pricing. Infoveave also provided an end-to-end solution to the problem at hand and much more. Infoveave’s module allowed connecting to sources of data. This helped to fetch all the information on prices, models, and dealers. This also includes competitor data to compare against their prices. The What-If Analysis module configured the pricing algorithms within. This includes over 40+ variables that determine the price.

The user can run the scenarios within the What-If Analysis & Goal Seeking. Scenarios had different combinations of State, Model, Dealer, Vehicle Type, Fuel Type, and Color. Infoveave also does a single-step goal seeking. By which the user can set an optimal goal price and work backward to arrive at the component prices.

Once completed, the price that best fits the need gets stored back into the data source. This forms the new baseline for prices and all the simulations that follow. The Address Book feature of the Reporting module ensures on-time delivery of reports. This report that reaches all 200+ dealers is precise and with no information overlap.

Results

Improved time to market: Simulations for new launches were much faster. Infoveave ran simulations in minutes rather than days.
Deeper insights: Provided on how often prices changed, the correlations to sales associated with price change, and the timing of the change.
Increased coverage: Earlier, one state was the central point to determine pricing. With Infoveave, differentiated pricing across all jurisdictions became possible.
Improved market intelligence: Peer group benchmarking and price assessment against segments and states enabled competitive pricing analysis across geographies.

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About the Authors

Infoveave Product Team is a member of the Infoveave Product and Solutions Team — specialists in Unified data platforms, agentic BI, and enterprise analytics. Infoveave (by Noesys Software) helps organizations unify data, automate business processes, and act faster with AI-powered insights.

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