March 3, 2023
According to Deloitte's 2023 Retail Industry Outlook, only one-third of retail C-suite and senior executives are confident about maintaining or improving their profit margins this year, despite mounting inflation and diminished consumption. However, many retailers have turned to BI consulting services to deal with constant demand fluctuations and other business challenges as well as transform their legacy siloed systems into smart business intelligence solutions with sense-and-respond capabilities.Â
Let’s see how business intelligence solutions can transform the retail sector and what capabilities are crucial for a retail business intelligence solution. We’ll also learn what BI integrations with other retail software are essential and how to choose the optimal BI solution for your online business.
of consumers expect companies to deliver personalized interactions
McKinsey
increase in top-line sales is due to analytics applications in retail
McKinsey
revenue is generated by companies that excel at personalized marketing
McKinsey
cut infrastructure costs
The customer is an online fashion retail company with 20+ million registered customers. With 200,000+ website and mobile app users daily, the customer had to process large amounts of data to know their customers’ needs. This is why the retailer decided to get a centralized BI solution that would collect data, store, and analyze user behavior as well as build predictive models to forecast buyer conversion rates, product interest, and future sales.
Itransition developed a solution that gathers and analyzes clickstream data, mobile data, server events, and email campaign engagement data in near real-time mode, enabling predictive analytics along with website and mobile app personalization. Implementing a retail-specific BI solution for data collection and analysis has helped the customer decrease monthly infrastructure costs by 50%, better understand online user behavior, and increase sales through AI-powered personalization, which resulted in the visitors-to-buyers conversion rate increasing by 8%.
To draw up an optimal retail BI technology stack, companies need to carry out a careful analysis of their unique business needs, goals, and requirements for business intelligence. The wrong technology choices might not only prove more expensive than expected but also frustrate business users, turning them against the whole idea of business intelligence. To help companies stick to the budget, guarantee faster returns, and facilitate quicker user adoption, we outline the must-have functionalities to look for in BI platforms:
for connecting to, querying, and ingesting data from all the required cloud and on-premises data sources
including support of user-driven data aggregation from different data sources
including user administration, platform access audit, and authentication
to automatically generate analytics insights for end users with ML techniques
including the support for common chart forms (bar/column, line/area, pie, and geographic maps) as well as highly interactive dashboards
for combining interactive data visualization with narrative techniques and presenting analytics content compellingly and comprehensively
to create and distribute reports to colleagues and customers on a scheduled or event-triggered basis
for tracking a BI platform usage and managing business sharing
for users to quickly access analytics content
to enable users to ask questions, query data, and get insights in natural language
Retail business intelligence platforms need to be integrated with multiple types of retail-related software to import data, analyze it, and export analytics insights further across the enterprise.
Retail POS
CRM software
Pricing software
Ecommerce platform
Marketing campaign management software
Supply chain management software
IoT devices
Import sales data, inventory data, customer purchase history, and customer personal information to:
Retail BI helps companies track and analyze customers behavior across all touchpoints. Drawing on this analysis, retailers can create and run hyper-personalized customer campaigns and loyalty programs, create unique shopping experiences by personalizing every step of the customer journey, design eye-catching store layouts, and deliver consistent user experience across multiple channels.
Retail BI benefits companies that want to track customer spending behavior and patterns to identify their motivations as well as monitor and assess how customers respond to marketing incentives. Equipped with these insights, retailers can enhance their marketing initiatives to retain the most profitable customers and acquire new ones.
Business intelligence solutions for retail help address most common supply chain challenges such as long supply cycles, fluctuating product demand, under-, and over-stocking, balancing inventory between several stores/across multiple channels, and high inventory costs by enabling near-real-time insight into supply and demand dynamics and accurate demand forecasting.
Retailers can leverage business intelligence to adjust floor plans and product placements and encourage consumers to shop longer, simplify product searches, and trigger impulsive buying by displaying popular product bundles.
A retail BI solution allows you to get an insight into your competitors' offerings and pricing, benchmark your company's performance against competitors, determine missed opportunities, fine-tune product assortment, and optimize pricing strategies.
Retail BI automates business data gathering, cleansing, and analytics activities and helps improve customer retention, devise store-specific or channel-specific marketing strategies, and optimize in-store operations. Such automation level leads to quicker and smarter business decisions and data democratization, which becomes an unmatched advantage over competitors who majorly rely on manual data processing or guesswork.
Retail BI adoption costs depend on multiple factors, including:
Retail BI platforms ingest a significant volume of sensitive data – personal data, financial data, intellectual property, and trade secrets – which should never be compromised.
To prevent data breaches and unauthorized access to business information, as well as to ensure business continuity and regulatory compliance, comprehensive data governance and data security practices and rules should be applied when implementing and managing a BI platform. Business intelligence software should offer capabilities for:
Lack of interactive data visualization, static reports, and inconsistent experience from various devices hinders users from deciphering valuable insights and stalls BI adoption.
Companies should take into account good data visualization design practices and self-service BI capabilities from the start of the BI project. We recommend companies consider the following features:
Retail data for BI often comes from siloed systems, which results in inconsistent, duplicated, inaccurate or outdated data used for analytics.
To prevent data quality from compromising business insights, we recommend companies incorporate data quality assurance into all BI functions and processes. That implies appointing dedicated team members to manage data quality, establishing a solid data quality measurement and management framework, and adopting suitable data quality management software.
These days, retail business intelligence is seen as an important solution to both address future opportunities and solve current business challenges, such as inflationary pricing, economic uncertainty, and geo-political factors. Still, successful BI adoption requires not only significant investments but also a solid BI implementation framework. With 15+ years of experience delivering full-scale custom and platform-based BI solutions, we are ready to design and implement an effective BI solution for retailers within the set time and budget frames for retailers.