In today’s data-driven environment, the retail business faces both tremendous potential and problems. As e-commerce grows and consumer expectations shift, retailers need to come up with new strategies to maintain their profitability and competitiveness.

“Every company today is a data and tech company, whether it realizes it or not.”  

— Dr. Katia Walsh, Chief Global Strategy and AI Officer, Levi Strauss & Co.

Business intelligence (BI) has evolved as an effective tool for retailers to get important insights about their operations, customers, and markets, with the potential to alter the industry as a whole. So it’s no wonder that the retail business intelligence solutions market is expected to increase by 22%, reaching $7.7 billion by 2029, according to the Retail Analytics Market Size and Share Forecast report.

Retailers can improve customer experience, improve pricing and promotions, and make data-driven decisions by utilizing data analytics and visualization.

While many retailers have embraced artificial intelligence and business intelligence for their disruptive effects, many continue to underestimate the significance of retail business intelligence.

Well, if you are one of the retailers who want to know more about it, how it works, and its use cases for your business, we have got you covered. Let’s get started. 

What is Retail Business Intelligence? 

The process of transforming data into insights in the retail sector is known as retail business intelligence or BI. It includes various tools and systems that help retailers understand and act on the vast amounts of data generated in the retail environment.

Retailers that use BI can make better judgments about pricing, marketing, inventory, and other areas. Retailers may improve their business intelligence (BI) with a variety of modern technologies.

These include: 

• Data Collection
• Text Analytics
• Predictive Analytics
• Prescriptive Analytics
• Dashboards and Visualizations

Every one of these solutions has advantages of its own, so retailers must choose the appropriate tools for their particular requirements.  

Let’s find out about how it works: 

1. Data Collection: Retail BI systems gather data from various sources such as point-of-sale (POS) systems, customer relationship management (CRM) systems, supply chain management (SCM) systems, social media, online transactions, and in-store sensors.
2. Data Integration: This involves consolidating data from different sources into a single, unified view. This step often includes data cleaning, transformation, and loading into a data warehouse or data lake.
3. Data Analysis: Using various analytical tools and techniques, retailers analyze the integrated data to uncover patterns, trends, and insights. This analysis can be descriptive (what happened), diagnostic (why it happened), predictive (what will happen), or prescriptive (what should be done).
4. Visualization and Reporting: Retail BI tools provide visualization and reporting capabilities that allow stakeholders to easily understand and interpret the data. Dashboards, charts, and graphs are commonly used to present insights in a clear and actionable manner.
5. Decision Support: The insights gained from retail BI are used to support decision-making across various functions such as inventory management, pricing strategies, marketing campaigns, customer service, and more. This helps retailers optimize operations, enhance customer experiences, and increase profitability.

How does the BI help Retail Businesses? 

Comprehensive Inventory Management 

Retail business intelligence provides precise inventory control by analyzing sales patterns, seasonal trends, supplier lead times, and other relevant data.

Retail BI enables enterprises to quickly track inventory throughout all channels and locations, including in-stock, out-of-stock, and obsolete inventory, in real-time. Retailers may attain ideal inventory levels, prevent stockouts and overstocking, and make sure their cash isn’t being tied up needlessly with the help of this capacity.

This aids in starting and running an omnichannel company. Retailers can compute carrying costs and monitor inventory profitability with the use of this data.

Macy’s, for instance

One of the biggest retail chains in the US, Macy’s, decided to use BI to revamp inventory management across both physical and digital channels. After the implementation, Macy’s can now collect and analyze the data needed which helps to improve inventory allocation and speeding up product delivery to customers.

Effective Staff Management 

Staff is the greatest assets of any organization and takes up a huge chunk of total expenses and these are no exception fo retail businesses. Well, BI can also help retail businesses to manage their workforce effectively. Retail companies subsequently use the analysis’s findings to boost employee engagement and retention, expedite hiring, and manage their workforces better.

Retail BI solutions for employee performance monitoring and analysis help to identify areas for improvement as well as acknowledge employees’ accomplishments. Additionally, staffing optimization, employee engagement strategies, and training programs are informed by insights into workforce dynamics and productivity trends. 

Increased employee productivity boosts overall business efficiency and improves customer satisfaction by showcasing workers’ exceptional customer service.

Walmart, for instance     

The international retail giant Walmart utilizes a business intelligence (BI) tool that gathers employee data automatically and uses built-in artificial intelligence (AI) to evaluate it. Walmart can now predict potential changes in the workforce ahead of time thanks to artificial intelligence (AI)-powered business analytics. This allows the retailer to better target its hiring efforts and prevent skill gaps. 

Data security 

Data security is critical in business intelligence. You must guarantee that your data is shielded from theft, illegal access, and other security breaches. In the retail industry, where sensitive client data may be handled, this is extremely crucial.

Implementing access controls and other security measures will help to assure data security and protect the retail business intelligence system from unwanted access and cyber threats. These include encryption, access limits, and conducting audits regularly. 

It entails creating secure passwords, restricting access to private information, and encrypting data while it’s in motion and at rest. Additionally, you want to keep an eye out for any indications of illegal access or other security lapses with your data. 

Data Democrazition 

Data democratization refers to the practice of making data more available to more people within an organization. This may enhance decision-making and lead to improved business results. However, if not done correctly, it can present security problems.

To achieve data democratization while ensuring security, role-based access controls should be implemented. This implies that depending on their position within the company, multiple individuals will have access to various types of data. Data governance guidelines should be put into place to guarantee that information is handled properly and that private information isn’t disclosed to unauthorized parties.

Furthermore, consider adopting data visualization tools to assist users in understanding and analyzing data. It enhances decision-making while lowering the possibility of mistakes or misinterpretations.

Customer Data Tracking, Segmentation & Predictive Intelligence 

Retail business intelligence helps companies understand their customers’ preferences and purchasing habits by analyzing customer data. With the use of these data, merchants can better predict customer needs, gauge customer sentiment, and find new chances for cross- and up-selling.

Retailers then make use of this information to closely connect their marketing tactics and product offerings with the preferences of their customers. As a result, there is an increase in consumer satisfaction and loyalty.

Retail BI allows companies to see their customers from all angles without requiring them to invest time and energy in laborious manual data analysis. Retailers may assess customer happiness, track conversions, compute LTV, create customer decision trees (CDTs), segment their client base, and conduct in-depth analysis using business intelligence (BI).

Example: Lowe’s The US-based home improvement shop uses business intelligence (BI) to centralize heterogeneous data sources and expedite decision-making. Specifically, the business automatically gathers and examines user feedback on social media sites like Facebook and Twitter. The retailer enhances the quality of its service based on the feedback received as well as marketing and sales data.

Omni-Channel Integration

Business Intelligence (BI) tools play a crucial role in integrating data from various sales channels, such as in-store, online, and mobile platforms. By consolidating this data, retailers can gain a comprehensive and unified view of customer interactions and sales performance across all touchpoints. 

This integration is vital for understanding customer behavior, preferences, and the effectiveness of different channels. BI enables retailers to deliver a seamless and cohesive shopping experience, ensuring that customers can move effortlessly between channels without encountering inconsistencies or disruptions. 

For example, A retail brand uses BI to integrate data from its website, mobile app, and physical stores. This integration allows the retailer to track a customer’s journey across multiple channels.

For instance, a customer might browse products on the mobile app, add items to their cart on the website, and complete the purchase in-store. BI tools analyze these interactions to provide insights into the customer’s shopping behavior, preferences, and overall experience.

Sales & Marketing 

Business Intelligence (BI) helps retailers optimize their sales and marketing efforts by providing detailed insights into campaign performance, customer segmentation, and channel effectiveness. By understanding which campaigns are driving sales and which customer segments are the most profitable, retailers can allocate resources more efficiently and improve ROI.

For example, a retail chain might analyze the performance of email marketing campaigns versus social media ads to determine where to focus more for their marketing to get the best ROI. 

For example, Nike used Business Intelligence (BI) to improve its sales and marketing by analyzing data from various sources like online sales, store transactions, social media, and email campaigns. BI revealed that email marketing worked best during product launches and sales events, so Nike focused more on this channel.

They also found that young professionals were the best customers for premium running shoes, while teenagers preferred influencer-led campaigns for casual sportswear. By using these insights, Nike tailored its marketing strategies, boosted campaign effectiveness, and improved sales.

Making the right pricing strategy 

To be successful, retailers must continually change their pricing tactics.

What is the right pricing for your goods? Try to outperform your competitors. Make sure you always make money. Make use of industry averages? There are several aspects that go into choosing the appropriate pricing, but a data-driven strategy will always be superior to going with your intuition.

In order to swiftly adjust prices, oversee promotions, and preserve profitability, business intelligence (BI) systems examine demand flows, pricing strategies of competitors, buyer behavior, and internal expenses.

By evaluating rival items, predicting market trends, and monitoring consumer behavior, business intelligence (BI) solutions help retailers optimize real-time pricing and tactics. To increase their overall sales and profit margins, it can provide merchants with customized promotions and competitive pricing.

BI uses real-time data on rivals and inventory levels, as well as seasonality and price elasticity, to calculate the best pricing for various products.

Forecasting the Demand (Accurately) 

Retail companies understand how important it is to forecast demand precisely because it affects how various retail activities are planned and carried out. 

With Business Intelligence for Demand Forecasting solutions, retailers can gain valuable insights into customer habits and preferences, allowing them to manage inventory levels, reduce stock-outs, and increase overall efficiency.

Real-World Example: To improve consumer interaction and inventory planning, Amazon, one of the biggest retailers, has been using business intelligence (BI) in demand forecasting. Amazon uses business intelligence (BI) to evaluate massive volumes of data, such as past sales, consumer behavior, purchase trends, and other variables, to forecast future demand and develop plans accurately.

By altering the variables, BI systems may simulate situations and help retail decision-makers determine the optimal course of action. It also assists with effective sales target setting and incentives and compensation strategy for the sales team.

Store Performance Analysis

BI tools enable retailers to evaluate the performance of individual store locations by analyzing sales data, foot traffic, and conversion rates. This analysis helps identify underperforming stores and the factors contributing to their performance, allowing for targeted improvements.

A retailer uses BI to compare the performance of different stores. For instance, a clothing retailer might analyze sales per square foot and customer foot traffic to determine why some stores are outperforming others.

Target utilizes BI to analyze store performance metrics such as sales, customer foot traffic, and conversion rates. By identifying underperforming stores, Target can delve deeper in understanding the underlying issues, such as poor location, inadequate staffing, or ineffective merchandising.

For example, if a store in a high-traffic area is underperforming, BI insights might reveal that it lacks popular product lines or has poor customer service. Target can then take corrective actions such as training staff, improving product assortments, or enhancing the store layout.

Leverage the BI to level up your retail game! 

Business Intelligence (BI) is truly a game-changer for retail businesses. Retail firms can improve their operations by leveraging new, dynamic technologies, allowing them to compete in a digital-centric competitive environment.

Some of the leading names in the market – Nike, Starbucks, Walmart, Sephora, etc are leveraging AI to streamline their operations and boost thier revenues.   

Think about it: with BI, you can dive deep into customer preferences and tailor your marketing efforts to what they actually want. No more guessing games. You can also manage your stock levels like a pro, ensuring you have the right products at the right time. And with omni-channel integration, you can offer a seamless shopping experience at all touchpoints. These are just the tip of the iceberg, there are so many BI benefits. 
Here’a reminder: to get the most out of BI for your retail business, choosing the right tool is essential. It needs to be personalized to your specific business needs, highly functional and easy-to-use. To ease down your search, you can try your hands on Livelytics – an AI powered data platform, that is personalized for retail businesses. Don’t just believe us, book a free consultation call & get started.