Introduction: Navigating the Competitive Landscape of Retail Analytics
Retail analytics is experiencing an unprecedented growth spurt, driven by the rapid uptake of new technology, the changing expectations of consumers, and the new demands of regulators for greater transparency and efficiency. IT systems suppliers, start-ups, and traditional retail leaders are all competing to offer the most advanced retail analytics capabilities, based on AI-driven insights and automation. In addition, the new IoT and biometrics are bringing the whole shopping experience together, with seamless, personal shopping experiences for the tech-savvy consumer. In addition, as the issue of sustainability is becoming increasingly important, green IT initiatives are becoming a differentiator between suppliers. North America and Asia-Pacific are the regions with the greatest growth prospects, with the strategic deployment of retail analytics focused on data-driven decision-making and the personalization of the customer experience. Looking ahead to 2024-25, these trends will shape the competitive landscape, bringing both challenges and opportunities for the players in the retail analytics industry.
Competitive Positioning
Full-Suite Integrators
These vendors provide end-to-end retail solutions, combining various retail analytic functions.
| Vendor | Competitive Edge | Solution Focus | Regional Focus |
|---|
| IBM Corporation |
Strong AI and analytics capabilities |
AI-driven retail analytics |
Global |
| Oracle Corporation |
Robust cloud infrastructure |
Cloud-based retail solutions |
Global |
| Salesforce.Com Inc. |
Customer relationship management integration |
CRM and analytics solutions |
Global |
Specialized Technology Vendors
These vendors focus on specific retail analytic solutions and specialized technology.
| Vendor | Competitive Edge | Solution Focus | Regional Focus |
|---|
| NielsenIQ |
Extensive consumer insights database |
Market and consumer analytics |
Global |
| Fractal Analytics Inc. |
Advanced AI and machine learning |
Predictive analytics solutions |
Global |
| Retail Insights |
Focus on actionable insights |
Retail performance analytics |
North America |
Infrastructure & Equipment Providers
These suppliers provide the necessary tools and platforms to support retail analytics.
| Vendor | Competitive Edge | Solution Focus | Regional Focus |
|---|
| Snowflake Inc. |
Scalable cloud data platform |
Data warehousing and analytics |
Global |
| Wipro Limited |
Comprehensive IT services |
IT and analytics solutions |
Global |
| Tech Mahindra |
Strong digital transformation focus |
IT and analytics services |
Global |
| MRI Software |
Real estate and property management expertise |
Real estate analytics |
North America |
Emerging Players & Regional Champions
- DataSpark (US): specializes in customer behavior modeling and predictive analytics. Recently teamed up with a major retailer to enhance their inventory management system, challenging the established vendors with more agile and cost-effective solutions.
- Retail iQ (UK): Specializes in real-time data analysis and individualized marketing strategies, recently implemented its platform at a large retail chain, complementing the conventional vendors with advanced AI-driven insights.
- This Indian company offers a tool for analyzing the location of consumers and the measurement of foot traffic. It recently signed a contract with a local mall to optimize the location of the tenants, thus becoming a local champion among the larger competitors.
- MarketMinds (Germany) – Provides a high-level price optimization tool and competitor analysis, and recently teamed up with a fashion company to improve its pricing strategy, enabling it to compete against the major players by focusing on the niche markets.
- InsightRetail (AUS): Delivers customer journey mapping and sentiment analysis solutions, recently launched a pilot with a local grocery store, complements existing customer analytics platforms by focusing on customer experience.
Regional Trends: In 2023, there will be a notable increase in the adoption of artificial intelligence and machine learning across the retail analytics market, especially in North America and Europe. The retail analytics market will be driven by the need to personalize the customer experience and the need for real-time data insights. The emergence of new players offering niche solutions for specific needs will challenge the established players. In addition, the growing popularity of e-commerce and mobile shopping in Asia-Pacific will drive the demand for location-based retail analytics.
Collaborations & M&A Movements
- The two companies have teamed up to provide enhanced retail insights and improve their positions in the retail market.
- The acquisition of Signavio was made in order to extend the range of possibilities for gaining an understanding of the process of production and the processes of the business, so that it could be more widely applied.
- In a joint announcement, IBM and Salesforce said they were collaborating to combine their artificial intelligence and customer relationship management systems to give retailers better insight into customer trends and to help them compete better.
Competitive Summary Table
| Capability | Leading Players | Remarks |
|---|
| Customer Behavior Analytics |
Nielsen, IBM, SAS |
The Nielsen Company is able to draw on its vast reservoir of information on the buying habits of consumers, while the IBM Watson provides insights into a shopper’s behaviour that can be used to create a bespoke marketing strategy. The SAS system is renowned for its powerful statistical analysis, which can be used to predict a shopper’s behaviour with great accuracy. |
| Inventory Management |
Oracle, SAP, Blue Yonder |
Oracle Retail Cloud makes it possible to monitor the availability of goods in real time, thereby facilitating the reshaping of the supply chain. With its Integrated Business Planning, SAP ensures dynamic inventory management, while Blue Yonder optimizes the stock and reduces wastage using machine learning. |
| Sales Forecasting |
Microsoft, Tableau, Qlik |
Microsoft's Azure Machine Learning offers powerful prediction tools that fit into existing systems. Tableau offers visual analysis of sales trends, while Qlik's associative model gives deeper insights into the sales figures. |
| Omnichannel Experience |
Salesforce, Shopify, Adobe |
The Customer 360 platform enables a unified view of customer interactions across all channels. The Experience Cloud enables you to deliver a seamless experience from the digital world to the physical world. |
| Pricing Optimization |
PROS, Zilliant, Pricefx |
The PROS system uses artificial intelligence to analyze the market and optimize prices in real time. Zilliant specializes in business-to-business (B2B) price solutions that increase profits, while Pricefx offers a flexible price platform that can quickly adapt to market changes. |
| Fraud Detection |
FICO, SAS, Riskified |
FICO’s Falcon Fraud Manager uses machine learning to identify and prevent fraudulent transactions. Riskified is a specialist in fraud prevention for e-commerce and ensures that legitimate transactions are not blocked. |
Conclusion: Navigating Retail Analytics: Key Insights
The retail analytic market in 2023 is characterized by a high degree of competition and a significant degree of fragmentation. The market is a battlefield for the competition between established and new players. The regional trends show an increased tendency towards localized retail analytic solutions, as analytic vendors are adapting to the diversity of customer behavior and preferences. The established players are using their well-established platforms and integrating newer capabilities, such as automation and artificial intelligence, to improve their offerings. Meanwhile, the new players are focusing on scalability and flexibility, positioning themselves as agile alternatives in the rapidly evolving market. In a maturing market, the ability to use artificial intelligence, implement automation and implement sustainable practices will be key for vendors that want to secure a leadership position. These capabilities should be the focus of the analytic decision-makers who want to effectively navigate the complex market.
