KLIKER market
Market intelligence and dynamic pricing for retailers and brands
Founded
2017
Starting Price
Free
Category
Market Research
Last updated April 26, 2026
About KLIKER market
KLIKER market is a cloud-based market intelligence platform that collects and analyzes online offers for selected product categories, delivering accurate data on competitor pricing, product placement, and promotional activity. Its dynamic pricing engine uses machine learning to suggest optimal prices in real time based on market trends, competitor moves, and demand signals.
Pros & Cons
Pros
- Specialized for retail, e-commerce, fashion, sports, and consumer electronics verticals
- Up to 2 years of historical price data per tracked product
- ML-driven dynamic pricing recommendations, not just monitoring
- Strong EMEA coverage with growing global reach
- Visualizes data through tables, graphs, and charts for quick decisions
Cons
Key Features
Price Comparison
Compare regular and promotional prices across competitors with up to 2 years of price history per product.
Competition Monitoring
Track competitor offers, assortment, and pricing across selected markets and product categories.
Dynamic Pricing Engine
Machine-learning-driven optimization that suggests optimal prices based on market conditions and demand.
Promotional Activity Tracking
Monitor promotions and discount campaigns across the market to spot trends and react quickly.
Real-Time Analytics
Live dashboards with tables, graphs, and charts that visualize market position and pricing performance.
Automated Trend Forecasting
Predictive analytics that surface emerging market trends and pricing opportunities.
Product Placement Insights
Visibility into how and where products appear across competitor catalogs and marketplaces.
Pricing
Free Demo
Free
- Trial of the KLIKER market platform
- Sample dashboards and reports
- Evaluation period before contract
Custom
Custom/month
Best For
Competitor Price Monitoring
Retailers track competitor prices and promotions across categories to defend margins and spot threats.
Dynamic Pricing Optimization
Brands use ML-driven recommendations to set optimal prices in response to live market conditions.
Promotional Strategy Analysis
Marketing teams analyze competitor promotion patterns to time and size their own campaigns.
Assortment Benchmarking
Category managers benchmark product assortment and placement against competitors in their markets.
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