Nimble’s Role in Transforming Retail Data: 3 Use Cases That Drove Results

Advancements in AI and real-time data technology are causing a data revolution in the retail industry. As markets become more complex, faster moving, and more saturated with competitors, it’s more important than ever for retailers to leverage real-time analytics and robust retail data management tools to stay ahead. 

But how do you access these tools, what do you use them for, and how can you ensure proper implementation?

Keep reading to learn how cutting-edge retail data solutions like Nimble’s Knowledge Cloud and Online Pipelines can drive smarter decision-making for 3 common use cases in the retail industry.

The Growing Need for Real-Time Insights in Retail Data Analytics

A lot has changed in the retail world since the concept of collecting and using data to inform business decisions came on the scene in the early 2000s.

With e-commerce sales making up around 22% of all retail sales, advanced data on everything from logistics to consumer behavior becoming widely available, and an increasingly globalized market, retailers now operate in a world where market changes, competitive pricing, and shifting customer expectations demand agility.

And yet—many retailers still rely on data solutions and workflows from 20 years ago that simply can’t accommodate the rapid fluctuations, scale, and speed of the modern market. 

4 Common Problems With Traditional Retail Data Solutions

Traditionally, retailers have relied on static datasets to deliver much-needed insights on market conditions, competitor activity, and customer sentiment. This traditional approach to data causes the following problems:

1. Stale or Outdated Data

Static datasets are delivered after the data is generated—sometimes, with a lag of 5 weeks or more. This failure to capture real-time market fluctuations leaves retailers blind to critical shifts in pricing, trends, and customer preferences. By the time you get the data, it’s too late. 

2. Dataset Rigidity

Fixed structures in datasets make it hard to adapt to new data needs. Often, when retailers want to explore new markets, get more data on a specific topic, or adjust data collection frequency, they’re forced to seek out a completely new dataset, sometimes with another data provider. 

3. Fragmented Systems and Vendors

Between managing multiple data sources, processing technologies, and storage systems, retailers often need to juggle dozens of different data intelligence providers. Managing multiple tools complicates data integration, leading to data silos and inefficiencies in decision-making processes.

4. Complexity in Handling Vast Data Volumes

These days, there is more valuable data out there than ever before. Retailers need scalable, organized solutions to process massive datasets without compromising speed or accuracy. Traditional data processes often leave you wading through a messy data lake or figuring out a complex internal organization system.

How Real-Time Data Helps

Real-time data addresses these issues by delivering up-to-the-minute insights, enabling faster decisions, and simplifying data management. It equips retailers with the agility to respond dynamically to market conditions, ensuring a competitive edge in an ever-evolving landscape.

Want to learn more about how real-time data differs from traditional data? Read: “What Is Real-Time Data, and Why Does It Matter for Retail”.

How Nimble’s Retail Data Solutions Beat Legacy Systems: 5 Key Features

Nimble’s Online Pipelines and Knowledge Cloud redefine retail data management by offering unified, up-to-the-minute flexible, and scalable insights using data that are highly relevant to your business. This is possible via these 5 key features:

1. Real-Time Collection and Processing

While many traditional data solutions offer real-time raw data scraping, Nimble offers real-time collection and processing. Instead of getting data on a weekly or monthly basis, you can get a constant stream of data that is instantly processed into a ready-to-use format—so you can act on the most current information without delays.

2. Agility and Ability to Tailor to Your Business

Nimble’s low engineering complexity and flexibility make it easy to alter your data needs as your business requirements change. With Nimble, you can easily add or remove:

• Data sources like new websites or new page types (product pages, search pages, category pages, etc.).
• Parameters or data types to existing sources to capture new relevant information.
• Interactions to web sources like pagination, clicks, or text inputs.
• Post-processing logic to add value and context, such as product matching across websites.

3. Diverse Data Within a Single Source

Nimble’s retail data solutions are source agnostic, allowing the collection of any type of data from any source on the web. Instead of working with dozens of fragmented data providers with narrow scopes that cause data siloes and ill-informed analysis, Nimble allows you to see the big picture of how all your data fits together in one unified place.

4. Streamlined Integration

Nimble’s Online Pipelines and Knowledge Cloud offers integration with every application you use to work with data, including:

• Native integration with data storage solutions like Databricks, Microsoft Azure, and Snowflake. Your data automatically gets delivered to your storage provider in the format and schema of your choice. 
• Business apps like Salesforce, Slack, and MS Teams to send alerts, insert business rows, and other custom logic flows.
• Communication and integration between Nimble’s Agents and agentic workflow platforms like Agentforce and Copilot. 

5. Enterprise-Grade Data Governance

Nimble always ensures your data is secure, compliant with all relevant regulations, and never leaves your organization's boundaries. We also offer integration into your existing data security frameworks. 

Want to learn more about how Nimble can enhance your retail data analytics? Talk to our team.

3 Use Cases of Nimble’s Online Pipelines and Knowledge Cloud for Retail 

Use Case #1: Using Real-Time Data for Competitive Pricing Strategies

Overview

Competitive pricing is essential for driving sales and protecting profit margins. By using real-time online public data, businesses can dynamically adjust prices based on current market conditions to ensure prices are constantly optimized. 

The Problem

Traditional retail data systems don’t support real-time updates for tracking shifts in competitor pricing, consumer trends, or market conditions. Without a continuous flow of accurate data, retailers can’t proactively adjust their pricing in response to these fluctuations. 

This results in pricing decisions based on outdated or incomplete data, with adjustments made only after manually checking competitors’ prices or relying on static reports. Such delayed responses can lead to lost sales opportunities and diminished competitiveness in the market.

Nimble’s Solution

Nimble’s Knowledge Cloud addresses this gap by creating and maintaining a real-time representation of competitor product prices, supply trends, and other relevant data points across all relevant channels.

All competing products are accurately "matched" across different channels and are stored in a searchable database accessible by Nimble's engine, Azure, or custom Agents and LLMs. This dynamic, up-to-date view of competitor pricing enables retailers to automatically adjust their own prices in line with real-time market shifts, ensuring that they remain competitive and maintain profitability.

How It Works

Step 1: Data Gathering

Relevant data is gathered from a variety of online channels. Examples include:

• Competitor prices, promotions, and discounts on similar products.
• Historical price changes.
• Market trend insights from search trends, social sentiment, and consumer interest in specific products.
• Customer behavior data from reviews, ratings, and buying patterns.
• Regional variations like geographic pricing differences or local demand fluctuations.

Step 2: Processing and Analysis

Once the data is collected, it is cleaned, categorized, and structured for analysis. AI models and rule-based systems are used to identify relevant patterns, such as matching products with competitors based on SKUs, prices, titles, images, ratings, and other attributes.

Step 3: Leveraging

The processed data is then fed back into the business’s data stack in real-time or at customizable intervals to power automated dynamic pricing tools.

Customer Example

A large global grocery delivery platform used Nimble to understand how their grocery delivery prices compared to competitors. With the help of contextualized insights and AI agents that provided flexible and tailored dashboards, this company was able to see how competitor pricing changed in real time while eliminating much of the time and energy they normally spent on pricing analysis.

Results

• Reduced pricing analysis time by 40%, empowering faster, smarter decision-making.
• Improved pricing accuracy by 25%, directly contributing to measurable revenue growth.

Use Case #2: Consumer Voice and Retail Sentiment Analysis

Overview

Real-time consumer voice data solutions allow retailers to have an accurate picture of their customer’s feedback, emotions, and opinions expressed online and in-store. These insights can be used to enhance product offerings, improve customer service, and refine marketing strategies. 

The Problem

Consumer insights are sprinkled throughout review websites, social media platforms, customer service interactions, and countless other channels. The sheer scale and diversity of this data can easily overwhelm traditional methods, leading to fragmented and mismatched information. 

Analysis is equally challenging—human insights are so personal, variable, and context-dependent, that traditional systems often struggle to sort and categorize this data. This leaves valuable insights buried in a mountain of unstructured data, making it impossible to leverage consumer insights to inform better product, marketing, or pricing decisions.

Nimble’s Solution

Nimble’s Knowledge Cloud offers a comprehensive, real-time cloud of consumer voice data that is updated continuously. Online Pipelines pull and process relevant data from dozens of relevant channels, like social media, review sites, and more.

Then, Nimble’s AI-powered tools analyze text, images, and audio to categorize data by emotion, sentiment, and topic, allowing for instant insights. This cloud can be also accessed via third-party Agents, AI platforms, and sentiment analysis tools, making integration into existing workflows easy.

How It Works

Step 1: Data Gathering

Data is gathered from relevant online channels, including: 

• Public posts and comments from social media platforms like Twitter and Instagram.
• Online reviews from third-party review sites and e-commerce sites.
• Internal customer service data like surveys, support tickets, and chat interactions.
• Product ratings and other structured feedback.

Step 2: Processing and Analysis

Nimble’s AI-powered tools analyze text, images, audio, and other data formats to detect and categorize data by: 

• Sentiment (positive, negative, or neutral) and key themes.
• Specific emotions, such as anger or happiness.
• Topics, such as product quality, shipping experience, or customer service.

Step 3: Leveraging 

These actionable consumer voice insights can be used to identify recurring customer pain points, understand what product features or customer service practices consumers are happy or dissatisfied with, detect emerging preferences and market demands, and benchmark perceptions of competitors’ products or services.

These insights can then be strategically used to: 

• Refine product offerings, customer service protocols, and logistics processes.
• Develop targeted marketing campaigns emphasizing customer-endorsed features.
• Address negative feedback with tailored solutions, boosting customer satisfaction and retention.

Use Case #3: Utilizing Real-Time Analytics for Product Assortment and Digital Shelf Optimization

Overview

Online product catalogs must be continually optimized to ensure high visibility and strong sales. Real-time data analytics tracking competitor activity, search trends, and consumer behavior ensure retailers have all the information they need to optimize their product assortment.

The Problem

The digital shelf is impacted by rapidly changing trends in SEO, consumer preferences, competitor actions, and promotional events. To ensure products are displayed optimally, retailers need a continuous stream of relevant data that can handle these rapid fluctuations.

Legacy data systems can’t handle the scope, fast-paced nature, and complexity of data collection necessary to deliver insights quickly enough for retailers to act upon. As a result, retailers may miss opportunities to adjust assortments, respond to emerging trends, or optimize product placements on digital shelves.

Nimble’s Solution

Nimble’s Online Pipelines provide retailers and CPG companies with up-to-date data on product assortment, competitor activity, search trends, and other relevant data from a variety of channels. Examples include tracking the addition or removal of competitor products, changes in product variants, and shifts in rankings within searches and categories. 

When key opportunities or changes occur, Nimble can be configured to alert key stakeholders via Slack, MS Teams, email, or other business applications. This allows retailers to fine-tune their product assortments, reduce overstock, and increase ROI by ensuring that the right products are prioritized and displayed at the right time.

How It Works

Step 1: Data Gathering

Nimble collects data from a range of sources to offer a comprehensive view of the market, including: 

• Competitor product data like product assortments, price changes, promotions, and inventory levels.
• Product-specific customer feedback like reviews, ratings, and social sentiment.
• Search engine data like search trends and product rankings relative to competitors.

Step 2: Processing and Analysis

Once the data is collected, it is processed and analyzed to identify key insights:

• Gaps in product offerings like missing products, trending items, or new categories.
• Product search ranking within e-commerce platforms and within search platforms like Google. 
• Bestsellers and recommended products. 

Step 3: Leveraging

Retailers can use these insights to:

• Add new products.
• Refine product assortments.
• Optimize shelf space by allocating more visibility to high-performing or promotional products.
• Enhance product listings by optimizing titles, descriptions, and images to accommodate the latest SEO guidelines. 
• Unify pricing, promotions, and markdowns. 
• Ensure the availability of important products.

Customer Example

A popular sports shoe retailer and manufacturer used Nimble to troubleshoot their products losing rankings on Amazon and Footlocker. They used Nimble to conduct a deep analysis of how their rankings compared to competitors and discovered that the dip in visibility was caused by a competitor expanding their women’s running shoe offerings. 

Using this information, this retailer audited their women’s shoe listing compared to this competitor and developed two strategies to close the gap: 1 was to optimize their women’s listings, the other was to consider expanding their women’s product line.

Conclusion: Taking the Next Steps in Retail Data Analytics With Nimble

Real-time data and advanced AI data analysis are key to ensuring success in the retail world of the future. With the market becoming more complicated, saturated, and competitive than ever, Nimble’s streamlined, one-source solution offers a way for retailers to leverage real-time data to its fullest potential. 

With flexibility in data sources, data processing techniques, and integrations with your existing workflow, Nimble’s Online Pipelines and Knowledge Cloud are highly customizable to your unique needs as a retailer. 

To see how you can use Nimble to take your business to the next level, get in touch with our team.

Ready to transform your retail operations with the power of real-time knowledge? Book a call with us today.