Top trends and highlights from NRF 2025

This year’s NRF was again a hub of innovation and excitement, attracting over 40,000 attendees and more than 1,000 exhibitors. The focus this year was on how businesses are adapting to both macroeconomic and microeconomic changes, emphasizing the importance of getting back to basics while still embracing new technologies.

Top trends and highlights from NRF 2025

At NRF 2025, Fractal showcased its top AI-based retail solutions focusing on Test and Learn, Hyper-Personalization, and AI Agent-based pricing at Microsoft’s booth.

But, beyond Fractal’s own solutions, here are some highlights from our team.

AI’s prominence: AI was a major topic at NRF 2025, but with a new twist. While last year’s LLM and chatbot tests were lackluster, AI was still prevalent in other areas.

    • Vision at the edge: AI was used for vision at the edge in solutions like shrink loss prevention and smart mirrors.
    • Advanced personalization: AI was integral to the next generation of advanced personalization of the shopper experience in solutions like Fractal’s Customer Genomics.
    • AI-based pricing recommendations: Agentic AI is reshaping dynamic pricing and can dramatically impact retail operations.

LLM-powered solutions: LLM-powered solutions stood out for faster insights and actions. Fractal’s Trial Run is an AI-powered solution for business experiment analysis, leveraging GenAI for quicker insights and actions.

Retail operations enhancements: Some exhibitors showcased a breadth of solutions that promised to make retail operations both more efficient and more effective. For instance, they demonstrated solutions to improve supply chain visibility, store-level optimization, and retail media networks.

Eco-system based solutions: The complexity of building impactful, scalable, and secure solutions means that collaboration across vendors is now more essential than ever. Cloud providers, application providers, system integrators, analytics and AI experts, and marketing specialists are working together to address retail industry challenges.

Learn more about the solutions Fractal showcased at NRF’25 here: go.fractal.ai/NRF.

Exploring the Successes and Challenges of Retail Media Networks

In retail, Retail Media Networks (RMNs) are proving to be highly profitable despite the industry’s typically slim margins.

RMNs are business entities where retailers sell ad space to brands, allowing them to target shoppers effectively based on their browsing and purchase history. It provides retailers with extra revenue while enabling brands to reach their target audience more efficiently in the digital space.

RMNs are becoming essential for retailers and brands to maximize their online presence and advertising efforts. As this sector grows, questions arise:

  • What distinguishes successful RMNs from struggling ones?
  • Do some retailers have inherent advantages?
  • What strategies lead to billion-dollar success?

Let’s explore these questions and uncover the key factors influencing RMNs’ performance.

Factors influencing RMN performance

 

1. Learning from Retail Media Network shutdowns

As the number of RMNs increase, it’s important to view closure of some of these RMNs as opportunities to learn. We need to understand why they closed to help us address challenges in the industry and develop proactive strategies.

As an example, GAP halted its RMN operations finding that the actual performance of the network did not live up to the promise, indicating that it hadn’t become a self-sustaining investment at scale.

By studying cases such as GAP, we can identify factors contributing to success or failure in the RMN landscape and adjust our approach accordingly to strengthen our market position. While RMNs may seem easy to set up for generating positive cash flow, running one comes with challenges like scaling technology and managing talent. Many RMNs face issues like unproductive technology or teams not equipped for growth.

To set up your RMN for success, ensure that it is supported by robust technology and a well-equipped team, and set realistic goals and benchmarks. You should also regularly monitor performance metrics to ensure the RMN is progressing towards self-sustaining growth.

2. Grocery vs. non-grocery dynamics

Grocery retailers have an advantage in Retail Media because their customers shop for essentials frequently, giving them many opportunities to advertise. This makes it easier for grocery-focused retail media networks to demonstrate to their CPG partners that their advertising works.
To take advantage of grocery retail dynamics, retailers should:

  • Use purchase data to create targeted advertising campaigns that show immediate results.
  • Highlight seasonal items and limited-time offers to drive sales.
  • Offer personalized promotions and coupons based on past purchase behavior.
  • Organize in-store events and tastings aligned with advertised products to increase engagement.

On the other hand, non-grocery retailers, such as those selling appliances or electronics, face challenges because their customers make purchases less often. Despite this, non-grocery RMNs can still do well by using slightly different strategies to build and grow. Even though purchases are less frequent, items like TVs cost more, so more money can be put into advertising without suffering a loss. This makes those advertisements more effective.

To succeed in the non-grocery environment, retailers should:

  • Offer premium ad spots for high-ticket items.
  • Create ads that emphasize the unique features and benefits of expensive items like electronics and appliances.
  • Use lifecycle marketing strategies to target customers at different stages of the buying journey.
  • Implement cross-selling campaigns that recommend complementary products.

3. Harnessing BYOD (Bring Your Own Data)

BYOD allows RMNs to integrate external datasets, improving their capacity to target audiences and enhance campaign performance. Examples of first-party data include product subscription data (email-shipping address pair) utilized to exclude existing subscribers/shoppers and acquire new ones. This helps enhance targeting capabilities and campaign effectiveness.

Through the integration of external datasets via BYOD, retailers and advertisers can develop advertising campaigns that are more customized and personalized. This results in enhanced audience segmentation, increased ad relevance, and overall improved campaign performance.

4. Strategic in-store investments

While online retail brought retailers early wins, those revenues are now flattening and relying solely on it may not be the best approach for any RMN. Some networks are adapting their strategies to focus on in-store efforts, aiming for comprehensive omnichannel measurement throughout the entire sales funnel.

In-store retail media formats encompass a variety of options, such as endcap screens, self-scan devices, point-of-sale ads (e.g., on self-checkouts), screens on fridge/freezer doors, and mobile app engagement while customers are in-store.

These formats are complemented by in-store measurement, which closes the feedback loop and creates additional opportunities for brands to connect with customers at the moment of conversion.

5. Cracking the cookie-less measurement nut

Undoubtedly, precise measurement is crucial for the success of any RMN. However, browsers like Chrome are moving to restrict the use of third-party cookies making measurement more difficult. The shift into a 3P cookie-less environment emphasizes the importance of unified measurement approaches that incorporate robust frameworks like incrementality, Marketing Mix Modeling (MMM), and attribution models.

With these tools, RMNs can assess campaign effectiveness from both a top-down and bottom-up perspective. This allows them to fine-tune strategies and drive sustainable growth for both their own retail business and advertisers’ ROI.

An RMN’s success depends on understanding industry dynamics, adapting strategies, and using data for optimization. By mastering these aspects, RMNs can overcome challenges, discover new revenue opportunities, and achieve long-term success in the ever-changing retail media landscape.

Fractal’s Retail Media Networks Analytics in action

Ready to elevate your Retail Media Network? Fractal’s Retail Media Networks Analytics accelerator is your key to unlocking unparalleled insights and strategies.

With our analytics-driven solutions, backed by industry experts, we empower networks of all sizes—from grocery to specialty retailers in health, beauty, and personal care. Fractal tailors to your unique business needs, ensuring you maximize ROI and reduce time to market.

Contact us today and discover how our customized approach can transform your Retail Media Network into a powerhouse of profitability and efficiency.

Fractal’s Trial Run: Elevating Retail Excellence at Microsoft Innovation Hubs

TR at the MTC LI post

 

We are thrilled to announce a significant milestone in our partnership with Microsoft. Fractal’s retail business experiments solution, Trial Run, is now featured as a self-standing demo at all Microsoft Innovation Hubs globally. We are proud to stand alongside Microsoft’s and other leading partners’ technologies, showcased in over 40 Hubs across the Americas, Europe, Asia, and Australia. 

Trial Run is an Azure-based SaaS solution for in-store, in-market, and shopper-focused business idea testing. Powered by AI and advanced analytics, it delivers unique, actionable, and statistically significant insights that can empower retailers’ various business functions.

Trial Run enables retailers to build, develop, and scale their experimentation capabilities efficiently and affordably. It also allows businesses to make informed, data-backed decisions on pricing, promotions, and merchandising. 

We invite retailers to experience firsthand Trial Run capabilities under the guidance of Microsoft’s Technology Architects during their next Hub visit.  

Together, let’s shape the future of retail, one experiment at a time. 

Learn more about Trial Run on Azure Marketplace. 

Three pillars of the retail industry: Replenishment, allocation, and transportation 

The retail industry is one of the most dynamic and fast-paced sectors, comprised of a variety of stakeholders engaged in selling finished products to end-user consumers. In 2022, the U.S. retail sector was estimated at more than seven trillion dollars. The sector is projected to continue to grow, and by 2026 U.S. retail sales are expected to reach approximately USD 7.9 trillion. With the increased demand for consumer goods in different sectors and the ever-increasing choices of products at low costs, investments in the retail sector have also grown over the past few years.

As there is always an element of change in this industry, new challenges are encountered every day. Take product stockouts, for example. Suppose a customer walks into a grocery store to purchase items of their favorite brand but discovers that the product is not available. Frustrated by this, the customer chooses to either buy another brand or postpone the purchase; both scenarios are unfavorable to the business. The brand image and sales of the product are damaged because of this out-of-stock issue. The out-of-stock situation occurs when the inventory of a particular product is exhausted; this causes a problem for both suppliers and retailers.

There can be multiple reasons that would cause the product stockout, such as inaccurate inventory data, lack of demand forecasting, or an unseasonal spike in purchasing. Many of these underlying causes of stockouts can be avoided if the business implements adequate processes to be carried out every month.

To avoid situations like the stockout example above, retail companies need to develop a methodology for streamlining the following operations:

  1. Replenishment
  2. Allocation
  3. Transportation

3 pillars of retail industry

    These three operations create the three pillars of the retail industry that help monitor real-time insight into customer behavior and understand their buying patterns hence strengthening the retail foundation.

    Replenishment

    Replenishment refers to a situation where the amount of stock left in the store is counted so that the right products are available at an optimal quantity. It is considered an essential aspect of inventory management as it ensures that the right products are being reordered to meet the customer demand.

    In operational terms, the efficiency of store replenishment has a significant impact on profitability. The effectiveness and accuracy of store ordering affect sales through shelf availability and storage, handling, and wastage costs in stores and other parts of the supply chain. By optimizing demand forecasting, inventory management, and setting of order cycles and order quantities by making them more systematic, the gains obtained are significant, often amounting to savings of several percent of total turnover.

    For companies that must manage a large number of SKUs, one of the most effective ways of making store replenishment more accurate, efficient, and cost-effective is by using a replenishment system specifically tailored to business operations. When many different products need to be managed, manual ordering is highly labor-intensive and expensive; this results in companies using the replenishment system.

    An efficient replenishment system reduces process costs, improves inventory turnover, and provides higher service levels. The system constantly monitors the stock, sales, and demand while considering the forecast changes in demand and adjusting the replenishment orders. Recognizing the sales frequency, sales value, or profit margin, the company can control its inventory in such a way that ensures long-term profitability. The replenishment system calculates the safety stock level for each SKU separately and sets them to meet the service level targets with efficiency, considering the predictability of demand.

    Allocation

    In allocation, the new stock of products is distributed to individual store units, such that they maximize the sale of the product and prevent any stock out situation in the future. This process enables the assigning of supplies so that they support the organization’s strategic goals. Having sufficient stock levels is an essential component for any retail business; with the changing consumer habits, it becomes crucial for the stock to be available in the right place at the right time.

    To meet new and increasing demands, retailers need an efficient process to gather, interpret, and analyze data from customer behaviors and habits, which would help get a more localized and specific idea of what is sold at a larger quantity in different locations. Items that are high sellers in one particular area may not sell well in others, so recognizing and monitoring this can ensure that the stock is allocated to the most needed location. Due to this, an opportunity is provided for the retailers to encourage sales by pushing stock of a similar type that a customer may favor at a particular location.

    Transportation

    Transportation plays a significant role in delivering the right stock of products at the right point of delivery. It connects the business to its supply chain partners and influences the customers’ satisfaction with the organization. With the ever-changing customer preferences and as their expectations continue to evolve, the transportation industry is undergoing a dramatic transformation to meet these demands.

    Today, data plays a vital role in shaping how the industry will progress amidst tough competition. Due to the maturation of automation technologies, AI will help the transportation industry to manage drivers and fleet managers. By employing the techniques of AI, fleet and truck adjustments will offer data in real-time, eventually improving the industry’s standard. The safety and retention of the drivers will also increase from these newly acquired standards, and with enhanced access to data, there will be transparent communication between drivers and carriers.

    The average time between goods purchasing and delivery decreases by using real-time findings, making retailers focus on transportation to improve their business performance. The ability to automate insights, alerts, and data exchange more quickly will be the game-changer for this industry.

    These three pillars of retail can be strengthened by adopting in-house solutions and capabilities like Trial Run, customer analytics, supply chain analytics, and store operation analytics.

    How could these solutions help the retail industry?

    Trial Run is a data-driven, cloud-based test management product used to test business ideas for sites and markets using Google Cloud capabilities combined with advanced technologies to improve customer experience, enhance product recommendations, streamline operations, optimize inventory, and enhance the supply chain.

    Trial Run helps in scientific and systematic testing, which can unlock insights and provide direction with the following tests:

    • Marketing and Merchandizing tests
    • In-store experience tests
    • Store operations tests

    Customer Analytics is an AI-driven suite that helps a retailer to know their customers in a better way by understanding the customer needs and preferences from every angle, like acquisition, engagement, retention, and growth, gaining insights that can fuel growth in marketing initiatives, loyalty programs, or eCommerce platforms.

    Supply-chain Analytics is an advanced analytics and intelligent automation solution that helps in end-to-end supply chain visibility to stay competitive, keeping the distribution networks customer-oriented and efficient while reducing environmental impact. It helps in streamlined operations, which results in better cost savings, ultimately delivering more value in every step of the supply chain process.

    Store Operation Analytics helps boost sales productivity and reduce costs across every facet of store operations – from labor, facilities, and inventory management to enhanced customer service and satisfaction.

    All these solutions and capabilities help understand the customer motivations, preferences, and desires to meet their demands and increase sales effectively, hence strengthening the pillars of the retail industry.

    Conclusion

    To meet these growing customer expectations, retailers should give priority to collecting the customer data and analyzing it to support business decisions throughout their value chain. The inventory stocking patterns and shipping routes will shift in relation to patterns informed by this data. Retailers should make a concentrated effort to leverage the data while making critical business decisions, and to remain efficient; they must remain flexible and transform their operations as they capture more insights from their data.

    Over the past 20+ years, Fractal has helped many retail companies make their replenishment, allocation, and transportation operations more efficient by leveraging AI, engineering, and design. If you would like to learn more about optimizing these aspects of your retail business, please contact us to speak with one of our experts.

    Find how Trial Run enabled decision-making and helped clients with increased accuracy in test analysis and better ROI measurement resulting in an annual financial gain of $25Mn.

    Trail Run illustration

    Nowadays, companies want to be able to test business decisions and ideas at a scale large enough to believe the results but also at a scale small enough to reduce the large investments and risks that come with full-scale execution.

    Trial Run helps conduct tests such as altering store layouts and remodeling, loyalty campaigns, and pricing to recommend the best possible tailored rollout to maximize gains. You can now implement new ideas with minimal risk and maximum insight with the power of business experimentation. Trial run helps you:

    • Test each business idea at scale to generate customer insights without excessive spending.
    • Find out why your customers behave the way they do.
    • Learn how your customers will react to your new big idea.

     

    What is Trial Run?

    Trial Run is a data-driven, cloud-based test management platform used to test business ideas for sites, customers, and markets. Trial run is built using Amazon EKS, Amazon Redshift, Amazon EC2, Amazon ElastiCache, and Amazon Beanstalk. It is intuitive for beginners and experts alike and helps companies scale experimentation efficiently and affordably.

    Trial Run supports the entire experimentation lifecycle, which includes:

    Trail Run illustration

     

     

    1. Design: Build a cost-effective and efficient experiment that gives you the data you need to proceed with confidence.
    2. Analyze: Work with variables that provide you with targeted and actionable insights.
    3. Act: Use the generated insights to ensure your new rollout provides your stakeholders with the precise ROI.

    Trial Run offers valuable support across various operational and administrative departments, including Retail, Consumer Packaged Goods (CPG), and Telecommunications.

    Through its scientific and methodical testing approach, Trial Run can uncover fresh perspectives and guide decision-making through a range of tests, including:

    • Marketing and merchandising strategies.
    • Enhancing the in-store experience.
    • Examining store operations and processes.

    These tests are carried out at the store operations and process, product, or consumer levels.

    Trial Run offers a dynamic, affordable, and modern way of experimentation so you can stay relevant in a rapidly changing business environment. Trial Run also helps you to drive experiments through:

    • Driver Analysis: Identify key factors that are significant in driving the business outcomes
    • Rollout simulator: Maximize the ROI of a campaign
    • Synthetic Control Algorithm: Determine the right number of control stores with appropriate weights to create the replica of the test store
    • Experiment calendar: Avoid overlaps in experiments
    • Clean search: Let Trial Run parse the experiment repository and find entities that are available for a test

       

      What you can expect from Trial Run

      • Graphical design elements make it easy to use the program as an expert or a beginner
      • Automated workflows can guide you through the process from start to finish
      • Highly accurate synthetic control results with automated matching processes that only require minimal human intervention
      • Experiments at speed and scale without the hassle of expert teams or expensive bespoke solutions
      • Training, troubleshooting, and best practices from the best in the business
      • Easy pilots to help your new idea go live in as little as 6 to 8 weeks

      Trial Run stands out from other solutions by offering a transparent methodology and easily explainable recommendations. Trial Run utilizes a cutting-edge technique called “synthetic control” for matching, ensuring precise results. Trial Run can be used as a SaaS offering that is easily scalable based on demand and can be hosted on the cloud of customer’s choice. With Trial Run software, customers have unlimited test capabilities, enabling them to design and measure numerous initiatives without any restrictions. Finally, Trial Run success is proven in enterprises, with over 1,000 use cases deployed on our platform.

      How do I get started?

      Are you ready to implement cutting-edge technology to help you build cost-effective and efficient experiments that provide you with the data you need to make decisions?

      If you want to achieve successful Trial Run implementation, get started on the AWS Marketplace.

      Interested in learning more about how Fractal can help you implement Trial Run, contact us to get in touch with one of our experts.

      Trail Run illustration

      Nowadays, companies want to be able to test business decisions and ideas at a scale large enough to believe the results but also at a scale small enough to reduce the large investments and risks that come with full-scale execution.

      Trial Run helps conduct tests such as altering store layouts and remodeling, loyalty campaigns, and pricing to recommend the best possible tailored rollout to maximize gains. You can now implement new ideas with minimal risk and maximum insight with the power of business experimentation. Trial run helps you:

      • Test each business idea at scale to generate customer insights without excessive spending.
      • Find out why your customers behave the way they do.
      • Learn how your customers will react to your new big idea.

       

      What is Trial Run?

      Trial Run is a data-driven, cloud-based test management platform used to test business ideas for sites, customers, and markets. Trial run is built using Azure Kubernetes Services, Azure Synapse Analytics, and Azure Virtual Machines. It is intuitive for beginners and experts alike and helps companies scale experimentation efficiently and affordably.

      Trial Run supports the entire experimentation lifecycle, which includes:

      Trail Run illustration

       

       

      1. Design: Build a cost-effective and efficient experiment that gives you the data you need to proceed with confidence.
      2. Analyze: Work with variables that provide you with targeted and actionable insights.
      3. Act: Use the generated insights to ensure your new rollout provides your stakeholders with the precise ROI.

      Trial Run offers valuable support across various operational and administrative departments, including Retail, Consumer Packaged Goods (CPG), and Telecommunications.

      Through its scientific and methodical testing approach, Trial Run can uncover fresh perspectives and guide decision-making through a range of tests, including:

      • Marketing and merchandising strategies.
      • Enhancing the in-store experience.
      • Examining store operations and processes.

      These tests are carried out at the store operations and process, product, or consumer levels.

      Trial Run offers a dynamic, affordable, and modern way of experimentation so you can stay relevant in a rapidly changing business environment. Trial Run also helps you to drive experiments through:

      • Driver Analysis: Identify key factors that are significant in driving the business outcomes
      • Rollout simulator: Maximize the ROI of a campaign
      • Synthetic Control Algorithm: Determine the right number of control stores with appropriate weights to create the replica of the test store
      • Experiment calendar: Avoid overlaps in experiments
      • Clean search: Let Trial Run parse the experiment repository and find entities that are available for a test

         

        What you can expect from Trial Run

        • Graphical design elements make it easy to use the program as an expert or a beginner
        • Automated workflows can guide you through the process from start to finish
        • Highly accurate synthetic control results with automated matching processes that only require minimal human intervention
        • Experiments at speed and scale without the hassle of expert teams or expensive bespoke solutions
        • Training, troubleshooting, and best practices from the best in the business
        • Easy pilots to help your new idea go live in as little as 6 to 8 weeks

        Trial Run stands out from other solutions by offering a transparent methodology and easily explainable recommendations. Trial Run utilizes a cutting-edge technique called “synthetic control” for matching, ensuring precise results. Trial Run can be used as a SaaS offering that is easily scalable based on demand and can be hosted on the cloud of customer’s choice. With Trial Run software, customers have unlimited test capabilities, enabling them to design and measure numerous initiatives without any restrictions. Finally, Trial Run success is proven in enterprises, with over 1,000 use cases deployed on our platform.

        How do I get started?

        Are you ready to implement cutting-edge technology to help you build cost-effective and efficient experiments that provide you with the data you need to make decisions?

        If you want to achieve successful Trial Run implementation, get started on Azure Marketplace.

        Interested in learning more about how Fractal can help you implement Trial Run, contact us to get in touch with one of our experts.

        NRF event Social post

        This year, Fractal is again pleased to be at NRF at Microsoft booth #4503, presenting its key AI-powered solutions for retail and consumer packaged goods (CPG).

        The solutions showcased at NRF 2024 are:

        • Trial Run, a solution to help execute ideas with minimal risk and maximum insight through business experimentation.
        • Crux, your Generative AI-powered personal analyst
        • Competitive Intelligence, which provides real-time insights into competition pricing and assortment strategies.

         

        1. Trial Run: Enhance decision-making leveraging business experimentation

        Unlock a world of possibilities with Trial Run, a cloud-based test management solution. The solution enables retail and CPG companies to gather valuable insights into customer behavior and market trends to help retail and CPG companies.

        Whether it is pricing, promotions, or store layouts, Trial Run empowers companies to make data-driven decisions for a seamless customer experience and increased revenue.

        2. Crux: Your generative AI-powered personal business analyst

        Crux Intelligence Copilot enables decision-makers to quickly gain insights about their KPIs to make informed decisions more easily and faster.

        This Generative AI-powered and voice-enabled solution allows users to interact with their data easily by asking questions in natural language.

        3. Competitive Intelligence: Real-time insights on your competition’s strategies

        Stay ahead in the retail game with Competitive Intelligence. This solution delivers real-time insights into your competitors’ pricing and assortment strategies.

        By harnessing online competitive information, organizing it, and presenting it in an actionable format, Competitive Intelligence empowers retailers to make smarter pricing and merchandising decisions for sustainable and profitable growth.

        Learn more about those solutions or book a slot for a private demo with our team at NRF here:  https://campaign.fractal.ai/NRF

        Trail Run illustration

        Nowadays, companies want to be able to test business decisions and ideas at a scale large enough to believe the results but also at a scale small enough to reduce the large investments and risks that come with full-scale execution.

        Trial Run helps conduct tests such as altering store layouts and remodeling, loyalty campaigns, and pricing to recommend the best possible tailored rollout to maximize gains. You can now implement new ideas with minimal risk and maximum insight with the power of business experimentation. Trial Run helps you:

        • Test each business idea at scale to generate customer insights without excessive spending.
        • Find out why your customers behave the way they do.
        • Learn how your customers will react to your new big idea.

        What is Trial Run?

        Trial Run is a data-driven, cloud-based test management platform used to test business ideas for sites, customers, and markets. It is intuitive for beginners and experts alike and helps companies scale experimentation efficiently and affordably.

        Trial Run supports the entire experimentation lifecycle, which includes:

        1. Design: Build a cost-effective and efficient experiment that gives you the data you need to proceed with confidence.
        2. Analyze: Work with variables that provide you with targeted and actionable insights.
        3. Act: Use the generated insights to ensure that your new rollout provides your stakeholders with the precise ROI.

        Trail Run illustration

        Trial Run offers valuable support across various operational and administrative departments, including Retail, Consumer Packaged Goods (CPG), and Telecommunications.

        Through its scientific and methodical testing approach, Trial Run can uncover fresh perspectives and guide decision-making through a range of tests, including:

        • Marketing and merchandising strategies.
        • Enhancing the in-store experience.
        • Examining store operations and processes.

        These tests are carried out at the store operations and process, product, or consumer levels.

        Trial Run offers a dynamic, affordable, and modern way of experimentation so you can stay relevant in a rapidly changing business environment. Trial Run also helps you to drive experiments through:

        • Driver Analysis: Identify key factors that are significant in driving the business outcomes
        • Rollout simulator: Maximize the ROI of a campaign
        • Synthetic Control Algorithm: Determine the right number of control stores with appropriate weights to create the replica of the test store
        • Experiment calendar: Avoid overlaps in experiments
        • Clean search: Let Trial Run parse the experiment repository and find entities that are available for a test.

        What you can expect from Trial Run

        • Graphical design elements make it easy to use the program as an expert or a beginner
        • Automated workflows can guide you through the process from start to finish
        • Highly accurate synthetic control results with automated matching processes that only require minimal human intervention
        • Experiments at speed and scale without the hassle of expert teams or expensive bespoke solutions
        • Training, troubleshooting, and best practices from the best in the business
        • Easy pilots to help your new idea go live in as little as 6 to 8 weeks.

        Trial Run stands out from other solutions by offering a transparent methodology and easily explainable recommendations. Trial Run utilizes a cutting-edge technique called “synthetic control” for matching, ensuring precise results. Trial Run can be used as a SaaS offering that is easily scalable based on demand and can be hosted on the cloud of customer’s choice. With Trial Run software, customers have unlimited test capabilities, enabling them to design and measure numerous initiatives without any restrictions. Finally, Trial Run success is proven in enterprises, with over 1,000 use cases deployed on our platform.

        How do I get started?

        Are you ready to implement cutting-edge technology to help you build cost-effective and efficient experiments that provide you with the data you need to make decisions with confidence?

        If you want to learn more about the key concepts behind successful Trial Run implementation, check out the solution page: https://fractal.ai/partners/google/trial-run/

        Interested in learning more about how Fractal can help you implement Trial Run, contact us to get in touch with one of our experts.

        Transform Customer Digital Experience with AIDE

        High digital abandonment rates are typical for brands across domains, driven mainly by the experiential issues site users face during their journey. Identifying these friction points can be burdensome for businesses as they need help digesting the new wealth of granular data generated along their customer’s digital journey.

        Fractal’s Automated Insights for Digital Innovation (AIDE) is a smart digital solution for a broad range of industries, including retail, finance, insurance, and more, that uses a customizable open-source AI that works well with complex journeys, data security, and time-to-market needs for multiple industries. It helps make smarter decisions at every step and enables businesses to resolve issues quickly and increase potential revenue and leads.

        AIDE helps:

        • Analyze millions of digital consumer touchpoints to provide insights to increase revenue, engagement, and growth for the business.
        • Identify the root cause of friction from call, chat, and website errors and use AI to parse out critical signals from all the unstructured data in the customer journey.
        • Get the most comprehensive insights into the digital journey to drive data-driven hypotheses for supporting A/B tests to drive website design changes to improve the consumer experience.

         

        What is AIDE?

        AIDE is a digital optimization platform that helps detect and contextualize the issues faced by visitors on digital channels. It acts as an intelligent digital solution for various industries, including retail, finance and insurance, telecommunications, tech, media, and more. AIDE uses customizable, open-source AI that works well with complex journeys, data security, and time-to-market needs for multiple industries. It’s an insight-orchestrated platform supported by natural language-generated insights. AIDE:

        • Selects the sales or service flow to influence particular focus points.
        • Identifies the selected data domains to create a journey sensor.
        • Helps detect the most important anomalies across key performance indicators.
        • Finds the friction point on the website using various journey sensors.
        • Helps analyze the customer voice to add context to insights.

        Leveraging the power of the AWS cloud, AIDE is built on Amazon RDS, Redshift, EMR, LaMDA, E2, S3 and can be deployed in your AWS environment.

         

        How can AIDE help my business?

        AIDE product architecture

        AIDE brings together data engineering, Natural Language Processing (NLP), machine learning, and UI capabilities to help clients:

        • Easily develop new data features from raw data to power downstream data analytics use cases.
        • Identify and locate precise points of friction on your company’s website, online events, or funnels.
        • Deep dive into the context of customer dissonance using the voice of customer analytics.
        • Prioritize the most critical areas based on value loss estimation.
        • Analyze Omni-channel customer journey analysis.
        • Provide user-friendly and intuitive UI for beginners and experts.
        • Provide root cause analysis of customer pain points/dissonance during the digital journey.

         

        What can I expect from AIDE?

        With AIDE, you can capture every in-page interaction and micro-gesture to understand the site user’s journey and identify frustrations and errors impacting conversion and self-serve rate.

        AIDE helps companies remove friction and errors that spoil the visitor’s experiences. It also helps leverage best-in-class AI/ML modules to identify struggle points and recommend changes to drive design improvements using multiple features such as:

        • Sensorize: An automated AI/ML pipeline derives meaningful business indicators using the click activity across customer journeys.
        • Detect: Deviations from expected behavior across digital journeys get captured by applying pattern recognition algorithms to the key digital indicators.
        • Locate: A suite of supervised machine learning algorithms identify drivers of key customer journey outcomes (drop-off, clear cart, etc.) and measure relative impact at a page and click level of a customer’s experience.
        • Reveal: NLP module performs sentiment analysis and entity extraction on the voice of customer data such as chat; feedback etc. to identify the root cause of the friction and generate actionable insights.
        • Prioritize: Quantify the insights with respect to loss in revenue or incremental overhead costs to prioritize hypotheses for improving website design.

        Overall, AIDE is adaptable and open source, making it a flexible solution for various needs and is effective at addressing the complex customer journeys of today’s digital world. It is secure and reliable, with a focus on data protection, and easy to use and deploy, with a quick time to market.

         

        How do I get started?

        AIDE is also available on AWS Marketplace. Contact us to learn how an AIDE solution can identify and reduce friction points, helping the business grow at scale.

        Three pillars of the retail industry: Replenishment, allocation, and transportation 

        The retail industry is one of the most dynamic and fast-paced sectors, comprised of various stakeholders engaged in selling finished products to end-user consumers. In 2022, the U.S. retail sector was estimated at more than seven trillion dollars. The sector is projected to continue to grow, and by 2026 U.S. retail sales are expected to reach approximately USD 7.9 trillion. With the increased demand for consumer goods in different sectors and the ever-increasing choices of products at low costs, investments in the retail sector have also grown over the past few years.

        As there is always an element of change in this industry, new challenges are encountered daily. Take product stockouts, for example. Suppose a customer walks into a grocery store to purchase items of their favorite brand but discovers the product is unavailable. Frustrated by this, the customer chooses to either buy another brand or postpone the purchase; both scenarios are unfavorable to the business. The brand image and sales of the product are damaged because of this out-of-stock issue. The out-of-stock situation occurs when the inventory of a particular product is exhausted; this causes a problem for suppliers and retailers.

        Multiple reasons could cause the product stockout, such as inaccurate inventory data, lack of demand forecasting, or an unseasonal spike in purchasing. Many of these underlying causes of stockouts can be avoided if the business implements adequate processes to be carried out every month.

        To avoid situations like the stockout example above, retail companies need to develop a methodology for streamlining the following operations:

        3 pillars of retail industry

        1. Replenishment
        2. Allocation
        3. Transportation

        These three operations create the three pillars of the retail industry that help monitor real-time insight into customer behavior and understand their buying patterns, hence strengthening the retail foundation.

        1. Replenishment

        Replenishment refers to a situation where the amount of stock left in the store is counted so that the right products are available in an optimal quantity. It is considered an essential aspect of inventory management as it ensures that the right products are being reordered to meet the customer demand.

        In operational terms, the efficiency of store replenishment has a significant impact on profitability. The effectiveness and accuracy of store ordering affect sales through shelf availability and storage, handling, and wastage costs in stores and other parts of the supply chain. By optimizing demand forecasting, inventory management, and setting order cycles and order quantities by making them more systematic, the gains obtained are significant, often amounting to savings of several percent of total turnover.

        For companies that must manage many SKUs, one of the most effective ways of making store replenishment more accurate, efficient, and cost-effective is by using a replenishment system specifically tailored to business operations. When many different products need to be managed, manual ordering is highly labor-intensive and expensive; this results in companies using the replenishment system.

        An efficient replenishment system reduces process costs, improves inventory turnover, and provides higher service levels. The system constantly monitors the stock, sales, and demand while considering the forecast changes in demand and adjusting the replenishment orders. The company can control its inventory to ensure long-term profitability by recognizing the sales frequency, value, or profit margin. The replenishment system calculates the safety stock level for each SKU separately and sets them to meet the service level targets with efficiency, considering the predictability of demand.

        2. Allocation

        In allocation, the new stock of products is distributed to individual store units to maximize the product’s sales and prevent any stock-out situation in the future. This process enables assigning supplies to support the organization’s strategic goals. Having sufficient stock levels is an essential component for any retail business; with the changing consumer habits, it becomes crucial for the stock to be available in the right place at the right time.

        To meet new and increasing demands, retailers need an efficient process to gather, interpret, and analyze data from customer behaviors and habits, which would help get a more localized and specific idea of what is sold at a larger quantity in different locations. Items that are high sellers in one particular area may not sell well in others, so recognizing and monitoring this can ensure that the stock is allocated to the most needed location. Due to this, an opportunity is provided for the retailers to encourage sales by pushing stock of a similar type that a customer may favor at a particular location.

        3. Transportation

        Transportation plays a significant role in delivering the right stock of products at the right point of delivery. It connects the business to its supply chain partners and influences customer satisfaction with the organization. With the ever-changing customer preferences and as their expectations continue to evolve, the transportation industry is undergoing a dramatic transformation to meet these demands.

        Today, data plays a vital role in shaping the industry’s progress amidst tough competition. Due to the maturation of automation technologies, AI will help the transportation industry to manage drivers and fleet managers. By employing the techniques of AI, fleet and truck adjustments will offer data in real-time, eventually improving the industry’s standard. The safety and retention of the drivers will also increase from these newly acquired standards, and with enhanced access to data, there will be transparent communication between drivers and carriers.

        The average time between goods purchasing and delivery decreases by using real-time findings, making retailers focus on transportation to improve their business performance. The ability to automate insights, alerts, and data exchange more quickly will be the game-changer for this industry.

        These three pillars of retail can be strengthened by adopting in-house solutions and capabilities like StockView for retail, Edge video analytics, and Dynamics 365 customer insights.

        How could these solutions help the retail industry?

        StockView for retail helps retailers reduce lost sales and improve customer experience by automatically detecting out of stock items on shelves. It uses computer vision technology running at the edge to detect gaps on store shelves automatically. It also provides retailers with powerful insights and analytics into stock-out activities at both single-store and multi-store levels.

        Powered by Microsoft Azure Stack Edge, it offers a scalable, flexible, and cost-effective solution that brings the power of the Azure cloud platform down to the individual store, eliminating the need for costly and unreliable data transfers while offering a predictable and consistent TCO (Total Cost of Ownership).

        Edge Video Analytics solutions for retail typically leverage Azure Stack Edge devices, IoT devices, vision AI (Artificial Intelligence), and other technologies in conjunction with in-store cameras or other video sources.

        Insights gained from Edge Video Analytics can allow retailers to swiftly react to in-store customer behavior and product stock-outs while improving security and reducing shrinkage.

        Also, organizations can track store foot traffic, automatically notify employees to open more checkouts due to lengthy queues, and automatically detect product stock-outs. These insights can be used to help improve demand forecasting, optimize supply chains, and detect variances in population preferences down to the individual store.

        Dynamics 365 customer insights give you access to Microsoft’s extensive library of pre-built data connectors to help businesses gain faster time to value. Plus, you can power up your customer profiles with AI by leveraging Azure Machine Learning and Azure Cognitive Services, and Fractal’s library of custom AI models. So, we leverage this solution to maximize the potential of customer data.

        All these solutions and capabilities help understand the customer motivations, preferences, and desires to meet their demands and increase sales effectively, strengthening the retail industry’s pillars.

        Conclusion

        To meet these growing customer expectations, retailers should prioritize collecting customer data and analyzing it to support business decisions throughout their value chain. The inventory stocking patterns and shipping routes will shift in relation to patterns informed by this data. Retailers should make a concentrated effort to leverage the data while making critical business decisions, and to remain efficient; they must remain flexible and transform their operations as they capture more insights from their data.

        Over the past 20+ years, Fractal has helped many retail companies make their replenishment, allocation, and transportation operations more efficient by leveraging AI, engineering, and design. If you would like to learn more about optimizing these aspects of your retail business, please contact us to speak with one of our experts.

        Find how Fractal helped a global CPG company to operationalize an analytics engine designed and provide store recommendations for maximizing investments in their Azure environment. Read the full case study here: https://fractal.ai/casestudies/store-level-insights/