May 12 | 09 min read
“Retail analytics turns the art of understanding customers into a science empowering businesses with the ability to drive growth.”
Nestlé successfully achieved multimillion-dollar inventory reductions by employing demand forecasting analytics, (a key component of retail analytics) rather than relying on human intuition.
The system could not only consider seasonal patterns but could also conduct “what-if” analysis on different demand indicators. Ultimately, this reliable approach allowed Nestlé to decrease its inventory safety stock by 20%.
This represents just one of the many successful implementations of retail analytics, a market forecasted to exhibit a CAGR of 21.2% and attain a market value of $11.1 billion by the end of 2025.
Implementing proper retail analytics solutions can substantially boost a business’s growth. This article explores the diverse utilization scenarios of retail analytics, followed by their impact on industries and what the future holds for them.
Though certain retail companies depend on intuition for making business choices, it has been observed that this is not an optimal approach for operating a successful store. That’s why it is crucial to base decisions on retail analytics.
Any business must employ retail analytics to evaluate sales performance and streamline operations. By utilizing a retail intelligence platform, a business can delve deeper into retail sales data, analyze trends and relationships, and detect anomalies through visually engaging and user-friendly retail dashboards.
Missing a sales opportunity due to stock-outs negatively impacts not only retailers’ sales but also the customer experience and the manufacturer’s profits. A retail analytics solution can forecast sales for various products based on historical trends, reducing opportunity costs. Leading retailers employ sophisticated ‘Demand Forecasting Models’ that take into account multiple driving forces of change.
Note- Bizom’s Retail Intelligence platform provides real-time information through integrated reports and dashboards, enabling quicker and more intelligent decision-making, planning, and prediction.
It involves analyzing historical data to determine trends in customer behavior, such as purchase patterns and preferences. By understanding these trends, retailers can adjust their pricing and promotions to better target and appeal to their customers.
For example, if the data shows that customers tend to purchase a certain product more frequently during a particular time of year, the manufacturer can offer promotions or discounts on that product during that time to boost sales.
This approach can help retailers improve their overall revenue and profitability by aligning their pricing and promotions with customer preferences and behavior.
Effective supply chain planning is crucial for retailers to manage crises and shortages, and ensure a seamless experience for customers. Poor inventory management results in an annual cost of $300 billion for retailers.
Retailers and e-commerce decision-makers can use retail analytics systems to establish a consistent and objective framework for evaluating vendors. This may involve creating a vendor evaluation scorecard that assesses critical factors such as cost-margin, lead time, credit rating, distribution network, and other essential considerations.
A successful marketing strategy requires addressing customer challenges, using their natural language, and reaching them through preferred channels. Retail analytics can be used to gain insights into consumer behavior and develop marketing strategies that effectively target them.
For instance, by analyzing data from various touchpoints before a transaction takes place, marketers can create more comprehensive customer personas and better understand customer needs and preferences. This information can be used to tailor marketing strategies and improve customer engagement.
Pro Tip- Bizom’s Retail Intelligence platform enables retail businesses to monitor competitor activity and track buyer behavior in real-time using in-store data. Additionally, companies can measure brand visibility across all retail touchpoints through the platform’s AI capabilities.
“We aim to have at least a 60% customer retention rate, and anything over 50% can be considered above the industry average for us. Customer retention rate is an important metric for many reasons, and it’s really easy to track both in retail and online stores”.
-Kelly, CEO of NuLeaf Naturals
One practical way to increase profitability and drive growth in the retail industry is to prioritize customer retention. Businesses can use retail analytics to predict customer churn and develop strategies to retain them. For instance- retail businesses can leverage ‘What-if cost analysis’ and ‘Purchase analysis’ to gain valuable insights into their business operations, customer behavior, and market trends.
By employing analytical customer churn models that analyze various behaviors, such as purchase intervals, upgrades, cancellations, follow-ups, and overall engagement, companies can identify unique scores for each customer and forecast their likelihood of continuing to use their products or services. They can further use this information to make data-driven decisions to improve customer retention and boost their bottom line.
“If you are able to determine how many of your customers are converting, you will be better able to pinpoint areas for improvement. These could include new client retention techniques, inventory items, or a new point of sale system for improved service.”
-Dan Lee, Head of Marketing at Sealions.
Retail businesses can maximize revenue through price optimization, using data and analytics to determine how customers respond to different prices across channels. A combination of historical and current pricing data and consumer buying behavior is necessary to develop an effective pricing model. The more relevant data gathered, the more accurate the model, enabling retailers to determine optimal price points and remain competitive.
Building and maintaining customer trust is critical to driving growth and profitability in the retail industry. However, fraudulent activities can undermine that trust, leading to significant losses for retailers.
By leveraging retail analytics, businesses can identify and prevent fraudulent behavior, thereby safeguarding their customers and reputation. This not only helps build customer trust but also contributes to the long-term success and sustainability of the business.
For instance- An analytics solution helped a fashion retailer save $10,000 worth of merchandise from fraud by flagging 93 separate orders going to the same address. While humans could also identify such red flags, analytics software can do so more quickly and effectively, helping prevent potential losses before they occur.
Businesses are making significant investments in their data and analytics strategies. Let’s explore the industry’s current direction and how retailers can leverage technological advancements to optimize their operations and drive growth.
Retail companies can engage with customers through various touchpoints before purchasing, including social media, in-store visits, and online platforms. By using omnichannel retail analytics, companies can gain insights into popular routes to purchase and promote strategies such as “buy online, pick up in-store” to drive foot traffic.
Additionally, sending email carts to in-store browsers can increase sales through eCommerce platforms. Retail businesses can optimize sales strategies and boost revenue by training retail associates to use this feature.
For instance, Target’s statisticians identified if a customer was pregnant based on their purchase behavior, allowing the store to send them coupons for baby-related products and encourage their shopping. Today’s advanced analytics algorithms can perform similar analyses on a much larger scale and with greater speed.
Retail companies can utilize the power of artificial intelligence (AI) to make data-driven decisions and improve their profitability in several ways. For example, they can implement machine learning algorithms to price products dynamically based on seasonality, demand, and competitor prices.
Additionally, optimizing local delivery routes using AI can reduce strain on the supply chain and minimize carbon emissions and fuel consumption. Companies can also create AI chatbots to automatically answer frequently asked questions and provide customer support.
Note- Bizom’s Retail Intelligence platform provides comprehensive sales and distribution analytics for consumer packaged goods (CPG) companies, covering all aspects from end to end. The platform’s core features can be categorized into business intelligence, AI/ML Capabilities, and Data Capabilities.
Big data refers to datasets too large to be processed in raw form. Companies like Office Depot are utilizing big data to enhance their operations. By consolidating data from various sources, such as offline catalogs, call centers, fulfillment systems, and enterprise resource planning (ERP) software, Office Depot Europe can personalize its customer communication and gain a competitive edge. As a result, Office Depot Europe gains a competitive edge over its rivals and improves its operational efficiency.
Retail and consumer goods industries rapidly adapt to digital acceleration by adopting a data-driven approach to enhance business operations and gain a competitive edge. Digital transformation in retail can lead to higher customer retention and satisfaction by providing tailored services and products.
Bizom’s Business Intelligence solution is a powerful tool for retail businesses seeking deeper insights into their operations and driving growth. The solution also offers seamless integration with other components of the Bizom platform, including Retail Execution and Supply Chain Management solutions. This allows businesses to view their operations completely and make data-driven decisions across the entire value chain using retail analytics.
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