Choosing the right pricing software: ‘Take an integral approach’
In today’s hyper-competitive market, pricing has become one of the most powerful levers for differentiation, growth, and profitability. In their pricing endeavours, leading organisations increasingly rely on advanced pricing software to turn their pricing data into strategic advantage.
Yet, with a crowded landscape of solutions and fast-evolving technologies, selecting the right pricing tool is far from straightforward. In this article, experts from Horváth outline the latest developments in pricing software and present a four-step approach to making the right choice.
Pricing excellence with smart technology
Technology is essential for pricing excellence because it enables companies to analyse vast amounts of data quickly, uncovering insights that manual methods would miss. Advanced pricing tools allow dynamic, real-time adjustments that respond to market changes, customer behaviour, and competitor moves. By embedding automation into decision-making, technology ensures consistency, accuracy, and scalability in pricing strategies.
Modern platforms, in particular those with advanced analytics and artificial intelligence, go beyond efficiency – they support real-time optimization and smarter decisions.
A strategic selection process is key
In a rapidly paced environment, pricing dynamics are changing rapidly to harvest hidden revenue potentials: From static list prices with fixed rebate structures towards dynamic, situational and short-term price setting. This form of modern pricing requires digital support by CPG (configure, price, quote) tools, which comes along with significant investments in technology, implementation and upkeep.
Hence, choosing the right pricing and CPQ tool requires more than a technical feature comparison – it demands a structured and use-case-driven approach that aligns technology with pricing ambition, process maturity, and organizational readiness.
In many organizations, pricing is still treated more as a financial result than a strategic lever. Consistent price architectures, pricing automation, and analytics-powered quoting support are often lacking. Recognizing this, companies are increasingly launching comprehensive pricing transformations that combine price strategy, consistent global pricing architectures, and advanced analytics and AI, with a dedicated focus on selecting the right technology support.
Across various client contexts, at Horváth we’ve seen what matters most in successful pricing and CPQ vendor and solution selection:
Requirement Definition: Developing detailed functional and technical requirements based on strategic pricing goals, user needs, and IT integration scenarios
Tendering Process: Running a structured, criteria-driven evaluation – from longlisting to shortlisting
Use case-driven PoC: Simulating real pricing scenarios (e.g. list price setting, discount logic, international price variation, and quoting) in a proof of concept using real data and workflows
Recommendation and Roadmap: Aligning vendor selection with IT and business strategy – and defining a realistic, cross-functional rollout path
The future of pricing software
The pricing software landscape is evolving rapidly, and AI is at the heart of this transformation. No longer a futuristic buzzword, it is becoming a standard capability within leading pricing platforms, empowering companies to make faster, smarter, and hyper-contextual pricing decisions.
According to research from Technavio, the global AI platforms market is forecast to increase by $64.9 billion at a CAGR of 45% between 2023 and 2028, with predictive analytics among the fastest-growing application areas. Four areas that will emerge and grow rapidly are:
AI-based recommendations: Intelligent algorithms analyze sales patterns, market signals, and customer behavior to suggest optimal price points (B2C) or quotes (B2B).
Dynamic pricing: Systems automatically adjust prices across segments and channels in response to demand, competition, or inventory.
Predictive analytics: Forecasting revenue, margin effects, and churn risks helps teams proactively manage pricing and promotions.
NLP-driven insights: Conversational interfaces make data-driven decisions more accessible to sales teams, e.g., offers can be processed automatically after a client visit.
Conclusion
Choosing the right pricing software is a strategic move that impacts growth, margin, and customer experience. Making that decision goes beyond just the technology – it requires a systematic, use-case-led strategy that connects technological solutions with the company’s pricing goals, process development, and overall preparedness.
