Retalon, Inc.

Retail strategies based on unified commerce and unified analytics provide the seamless experiences customers want. Behind the scenes, retailers become more efficient and more responsive to a dynamic market.

What is unified commerce?

Unified commerce solutions link a retailer’s front-end and back-end systems within a single platform that centralizes all customer and product data.

Tearing down channel-specific silos puts the customer first. With every channel using the same inventory data, for example, customers can buy, pick up, and return products through any channel they choose. Business operations also improve as retailers consolidate payment, inventory, and other back-end systems to reduce costs and improve efficiency.

To get these benefits, a unified commerce platform must be more than a centralized database. Correctly optimizing that data with unified analytics is what lets these strategies drive retail performance.

The unified commerce impact

As mentioned earlier, disruptions in the customer journey caused by disjointed omnichannel systems cost $2.2 trillion in lost sales. Unified commerce eliminates this friction and creates opportunities for another $1.1 trillion in revenue uplift. What is unified commerce doing to create this impact? Let’s take a look.

Working with a single truth

Keeping all customer and product data in one place creates a single source of truth for the entire company. Every team, store, and customer service rep can access the same information. Communication with and between sales channels improves when everyone speaks the same language, resulting in faster and more accurate decision-making.

Streamlining operations

Unified commerce allows retailers to consolidate back-end systems and improve information flow throughout the company. Everyone gets a clearer picture of the business as measuring KPIs becomes simpler and more consistent.

Enabling more dynamic business

Unified commerce platforms provide real-time visibility into customer behavior, sales, and inventory. Having more complete information means business groups need fewer back-and-forth conversations to understand what is happening. Issues can be addressed before they have a chance to grow. And retailers can make the most of every opportunity cutting wasted time.

Reducing errors

Omnichannel retailers make costly mistakes when separate back-end systems fragment information across the organization. Duplicate orders lead to overstocks on some SKUs while missed orders let locations run out of inventory. With more accurate data in a central system, a unified commerce company avoids these errors and their financial impacts.

Simplifying vendor management and integration

A legacy of separate, channel-specific back-end systems places a significant burden on retail IT operations. Integration projects are never complete since compatibility issues could cause errors at any time. Managing these systems and their vendors consumes limited resources. With unified commerce, however, retailers can make their infrastructure easier to manage, making way for smoother operations. 

Improving the customer journey

No matter how customers shop with a unified commerce retailer - whether online, in-store, or through any number of channel combinations - they get consistent, seamless experiences. Retailers deliver accurate information as well as more relevant targeted promotions. Add in the freedom to buy, receive, and return products any way they want, and the only surprise is how pleasant the retailer is to shop with.

How is unified commerce achieved?

Achieving unified commerce can be done through the use of an AI-driven analytics platform such as Retalon’s Unified Commerce Analytics. 

Your data is consolidated and processed into a single platform using cloud-based technology. Having clear visibility into the current state of your business will enable team leaders to develop a consistent company roadmap. 

At this stage a unified outline of company values, mission, goals, and parameters can be re-evaluated and agreed upon. 

These parameters are then added to Retalon’s system to facilitate connecting retail operations from planning to order management and returns to achieve the most optimal unified commerce.

What is unified analytics?

Analysts simply cannot keep up with the volume of data modern retail generates every second. A cloud-native unified analytics solution from Retalon, powered by AI, will process huge, interconnected datasets quickly to support faster, more accurate decision-making.

Think about what happens when an inventory analyst changes a restocking order date. That decision has small and large effects throughout the organization. Channel by channel and store by store, Retalon’s unified analytics will instantly adjust:

• Order quantities
• Replenishment allocations
• Sales forecasts
• Inventory availability
• Impacts on promotions
• Markdown forecasts

Retalon’s retail analytics solution supports better long-term decisions as well. Using hundreds of related variables, retail analytics forecasts true customer demand. These demand forecasts let retailers explore scenarios such as:

• Testing new inventory mixes
• Evaluating pricing decisions
• Understanding market expansion impacts

Generating these scenarios with unified analytics takes minutes rather than months, letting your planners run and compare more scenarios. By developing more robust strategies, your business becomes more responsive to whatever the future holds.

Unified analytics will help you deliver seamless customer experiences to avoid lost sales and generate more revenue across every sales channel. Contact us to learn more and get a demonstration of Retalon’s unified analytics in action using your own data.

The most stubborn, expensive issues retailers face are due to poor demand forecasting. 

Approximated demand disappoints customers and bleeds profits. Tackling the challenges in demand forecasting, however, is not easy.

Why is demand forecasting important?

The forecast of future sales demand informs almost all of the decisions a retailer makes throughout the product journey:

Planning

An accurate forecast enables you to order the most in-demand assortment mix, down to size, color, and version of each product. So, you can meet demand without being left with overstock.

Inventory/supply chain

Demand forecasting at store/SKU levels leads to better allocation of inventory across the entire business from the start. 

Pricing

Accounts for price elasticity of demand, meaning the effect that a set price will have on demand, is an important consideration when setting prices, running promotions, or markdowns. 

Customer experience

Order fulfillment becomes more efficient; meeting consumer expectations by enabling lower shipping costs, faster fulfillment, in-stock inventory, and a greater variety of fulfillment options.

Major demand forecasting challenges?

1.  Retail is Dynamic

There are a host of factors that influence demand, and these factors are in constant flux. Basing a sales forecast on what happened in the year prior yields inaccurate results. Consider just a few things that change from year to year:

• Changes in product mix
• Channels and locations open, close, or move.
• Changes made by competitors
• Changes in geodemographics
• Changes in promotional calendars and strategies
• Changes in seasonality
• Changes in vendor pricing

A shift in any of these, or other relevant factors has a domino-like effect on the business, from supply chain to SKU-level demand. 

2.  Identifying/accounting for all factors

A successful forecast must consider every relevant factor for each SKU at each unique location to identify how their interplay will affect demand.

This is why demand forecasting is more effective than sales forecasting.

Of all the challenges faced in demand forecasting, this one is very difficult to confront for two key reasons.

A. It is very difficult to identify all of the variables influencing demand. 

B. Each additional variable makes computing demand exponentially more complicated. 

In fact, an omnichannel retailer with 100s of thousands of SKUs across multiple channels is facing millions of data points.

Traditional spreadsheet-based forecasting relies on analysts to manually sift, organize, and compute all that data. Time-consuming, expensive, and prone to errors, this approach is difficult to scale.

3. Fragmented approach

Multi-channel business often leads to a ‘divide-and-conquer mentality, creating siloed channels and departments. A fragmented structure yields inefficiency:

• Time-consuming operations
• Miscommunication and lack of visibility
• Human error and missed opportunities
• Constant manual intervention, making it hard to scale
• Category-level planning
• Inability to account for all necessary variables

A unified approach across the entire product life-cycle enables retailers to get the most accurate demand forecast.  

Benefits of AI-driven Demand Forecasting

Unified AI-driven solutions easily handle the factors impacting demand. McKinsey & Company found that advanced analytics let retailers outperform their competitors by 68%.

Benefits of The System:

1. Improved Visibility - You make better decisions with a clear picture of demand and inventory across your business. Ordering the right quantities for each store’s demand cuts off most inventory problems. If issues do happen, AI-powered analytics notice them faster so you can respond more effectively.

2. Reduced inventory cost - Hedging your forecasts with safety stock is expensive. It ties up inventory dollars, undermines inventory KPIs, and leads to overstocks. With an optimized forecast, logistics costs fall, open to buy grows, and inventory KPIs improve.

3. Reduced markdowns - With more accurate forecasts, you're not forced into drastic last-minute markdowns to sell off overstock. You’re able to proactively plan price drops and set optimal discount prices to maximize ROI.

4. Increased sales - Stores have the product your customers want when they are ready to buy. Moreover, prices are optimized to increase demand by accounting for the price elasticity of demand. 

5. Increased inventory turnover - Stores get just enough product to meet demand without risking empty shelves. Forecasting demand at store/SKU level accounts for variables like geodemographics, which means retailers are not stuck with fringe sizes, styles, or colors. 

6. Improved collaboration - A unified analytics system gives your teams a shared view of each department, channel, and store location. With everyone on the same page, communications improve, and your teams work together more effectively.

7. Reduced manual labor - The heavy lifting is done in the background to produce faster and more accurate forecasts of what your customers want to buy. The agile nature of the technology lets retailers run scenarios and make quick changes without real-world risk. 

8. Easier scalability - These cloud-based platforms process millions of data points in seconds, which allows them to scale with your business on-demand. Add more stores, add new channels, use more variables. Advanced retail analytics seamlessly integrate every aspect of your growing business.

Leverage The Retail Demand Forecasting System

The Retail Demand Forecasting System helps you:

• Squeeze costs and inefficiencies from your planning processes.
• Increase revenue, profits, and market share.
• Unify your sales channels.
• Improve collaboration and communication.

For a more in-depth understanding of retail analytics definitions, types, examples, and tips, discover the Ultimate Guide to Retail Analytics. 

Today’s retailer is faced with a number of supply chain challenges:

• Supply chain breakdowns
• Rising cost of storage and operations
• Consumers value ethical operations over cheap production
• Raw materials and overseas production prices have been rising
• The world is feeling the impact of supply chains on climate change, and retailers are feeling the pushback 

Despite the challenges, consumer markets continue to grow. Leading retailers are seizing the opportunity by adopting AI and advanced analytics technology to optimize supply chains.

AI for Supply Chains Leads to Success

Investing in AI for Supply Chain means overcoming the above-mentioned challenges and gaining market share.

In addition to saving costs by streamlining operations, retailers will also gain the support and loyalty of today’s ‘sustainable shopper’.

Of course, making the world a better place is important. The fact is, though, retailers are businesses. Being able to make a profit while being more sustainable is the only way to move forward.

Why is AI for Supply Chain Important?

Obviously, sustainable retailers are not working against their own interests. They are benefiting on many fronts, top among them are financial gains, brand image, and market share. 

E-commerce, omnichannel retailing, and new order-fulfillment options necessitate innovation in the way business is run.

Today’s retailers bleed cash at every stage of the product journey because of inefficiencies intrinsic to operations. For example, Category level planning results in either lost sales due to out-of-stocks or costly overstock. 

Retailers are losing market share to green-retailers as consumers choose a value-driven shopping experience. The shift in consumer preferences is real. Since 2015, half of the CPG industry’s growth came from sustainability-marketed products.

Making supply chains more efficient will stop the bleeding and consequently be more sustainable.

Adopting new innovations in operations management sustainability and supply chain management efficiency.

Forecast accuracy is the first step toward supply chain responsibility. Retailers are using AI-driven analytics to forecast demand down to SKU/store level.

• Reduce the reasons for trucks to be on the road.
• Generate fewer replenishment orders
• Less inventory rebalancing,
• Handle returns better
• Reduces the company’s global carbon footprint.

AI for Supply Chain provides a unified platform. This means the retailer gains the panoramic visibility they need to make their supply chains more responsive. Retailers are able to identify small inefficiencies that drain resources and may be hindering potential growth. 

A pervasive example of retail inefficiency is overproduction of goods:

Bob wants to introduce a new backpack into his back-to-school assortment but figuring out how many units to order is complicated by a slew of factors.

In an effort to avoid lost sales, Bob decides to air on the safe side and orders safety stock. Unfortunately, Bob overshot and ordered significantly more inventory than was in demand.  Bob’s Emporium spent time and money on manufacturing, transporting, and storing goods that will never be sold. They’ve wasted resources and further damaged the environment. 

Bob would have avoided this mess if he’d invested in a predictive analytics solution. 

AI for Supply Chain is a precision tool.

• Retailers are able to uncover true demand at store/SKU level enabling granular planning, which yields greater accuracy.

• By unifying all retail channels under one solution, retailers gain an understanding into the interconnected influence of each location, warehouse, transport route, and so on. 

• Visibility aids retailers in transparently sharing their performance across business channels as well as with regulators, investors, and consumers.

Optimize the supply chain – Gain Profit and Sustainability

Ultimately, supply chain efficiency leads to supply chain sustainability and business profitability. AI for Supply Chain lets you do both. After all, making the world a better place is good business:

• By only sourcing resources for products in demand, you cut overstock costs. 
• By reducing your carbon footprint, you’re spending less on fuel and electricity.
• By building a sustainable supply chain, you gain customer loyalty.
• By delivering on sustainability goals, you’ll be winning market share.

You wouldn’t go to a dentist who uses outdated tools; why subject your business to the same painfully ineffectiveness? 

Connect with our team, come to our booth #4583 and let us guide your retail business toward building a sustainable supply chain.   

Optimizing Order Management - 5 retail operations

Imagine if you knew how much of a particular SKU will be sold in a certain region or store during the sales season. 

AI for Order Management has made this possible by providing highly accurate demand forecasts to optimize the flow of the entire fulfillment process.

1.    Purchasing

Remember when you were caught eating in class, and the teacher asked, “Did you bring enough for everybody?” 

For optimal order management, the retailer has to purchase the product customers want to buy and bring enough for everybody. 

Purchase order management is often the first stumbling block to a smooth fulfillment process.

Deciding the right breadth and depth of an assortment to be purchased is important and requires an accurate demand forecast. 

An accurate forecast must account for how relevant factors, such as geodemographic changes, seasonality, and shifting prices, will affect each SKU at the store level.

Ai-driven analytics provide the most accurate demand forecasts, enabling retailers to purchase the inventory they will actually sell. What does this look like for order fulfillment?

• Provide product customers actually want - satisfy consumers and increase sales
• Bring enough inventory to meet demand - satisfy consumers and avoid lost sales

2.              Allocation

The fact that you have a warm winter coat in-stock at the Portland location, won’t be much consolation to the cold customer in Toronto looking at an empty shelf. 

Order fulfillment can get very expensive if a retailer is constantly shipping inventory from low-demand locations to high-demand locations. Worse still, customers will simply go to a competitor, and the retailer will suffer lost sales.

A generalized approach for allocation, like category-level inventory management. Of course, anyone who’s looked for a large t-shirt in a stack of Mediums knows that generalized allocation is ineffective. 

AI-driven analytics optimizes allocation enabling a cost-effective and efficient order fulfillment process.

3.              Order Processing

Given the nature of order processing, fulfillment professionals do everything they can to eliminate or automate manual steps.

Reducing labor costs through automation is only one benefit. Automation can improve workplace safety and give employees more productive things to do.

Further automation is achieved by pre-emptively sending inventory to its optimal location. Cutting transportation, storage, and unnecessary processing costs.

4.              Shipping

An envelope with a pair of socks can be stuffed into your mailbox, but nobody wants a refrigerator dropped outside their apartment building. 

Some considerations for optimizing shipment include:

• Location from which to ship
• Type of carrier and best route
• Cost of shipment/labor
• Can shipments be consolidated
• Last-mile delivery method
• Door-front or in-home delivery
• Delivery to non-home location

Smart Allocation evaluates all possible inventory sources from fulfillment centers to store locations to vendor warehouses; to identify where inventory can be consolidated for shipment to save time and money.

Customers get the product they want, and retailers don’t break the bank when trying to compete with the fulfillment speeds of Amazon.

5.              Returns

Product returns are inevitable, especially with online sales. Even if nothing is wrong, the product’s style may not be what the customer expected. AI for Order Management Sets up the right reverse logistics processes to minimize the impact of product returns.

Too often, however, retailers look at returns as a cost of doing business rather than as the opportunities they are. 

Resalable products should not go back to the original fulfillment center. Instead, the product should go somewhere that still has demand, and it can still be sold at full price.

AI-driven analytics selects that destination based on demand and inventory across every sales channel. Balances that destination’s shipping cost with the expected selling price. All this happens in real-time as the customer enters their return request and generates the shipping label.

The order management process varies from retailer to retailer, influenced by the business structure and consumer needs, but there is no need to reinvent the wheel. 

Let’s take a look at some of the most common order fulfillment models. 

Leverage your fulfillment into a competitive advantage  

Optimizing the process of getting a product into the hands of the shopper is key to keeping pace in today’s retail market. 

Investing in AI for Order Management is the first step in an ongoing process.

 You will find opportunities to improve performance throughout the system:

• Granular analysis of retail data can reveal insights that let you maintain optimal assortments.
• Visibility across your business will let you reduce the impact of vendor delays, storage overflow, inconsistent or broken assortment, and other disruptions.
• Constantly aligning purchasing and inventory with true demand lets you optimize how you allocate and store your fulfillment system’s inventory.
• Automation reduces manual activities, letting you streamline order processing and boost worker productivity.

Advanced order fulfillment software enables you to optimize your fulfillment process as a whole. On top of the benefits we talked about earlier, the right AI-powered systems can:

• Give real-time recommendations for fast, cost-effective fulfillment.
• Protect against product cannibalization
• Recommend replenishment orders based on true market demand.
• Minimize out-of-stocks across all sales channels and inventory locations.
• Identify the ideal returns destination based on product demand.

Discover how AI for Order Management can help your retail business connect with our team, come to our booth #4583.

AI for MFP and Assortment Planning is an end-to-end planning software for the full retailing life cycle. Providing the most accurate demand forecasts to aid you in profitable planning.

Retalon’s software helps retailers build a truly integrated plan, automatically feeding data and targets downstream, giving you the tools to execute.

Our software doesn’t just help you optimize high-level financial, store, merchandise, and assortment targets using the world’s most accurate demand forecast — it uses those same targets to automatically generate and continually optimize POs for every store.

Retalon’s retail planning software will help you:

• Take the guess-work out of setting your yearly sales, margin, and inventory targets with accurate demand forecasting
• Automatically turn high-level targets into granular store and merchandise plans with retail AI
• Confidently know how many unique items you should have in each category with state-of-the-art retail science
• Eliminate manual reconciliation, data entry, and PO generation with intelligent automation

A Retail Planning Process for the 21st Century

Gain an edge over your competition with a retail planning solution that leverages big data and advanced analytics

Leverage AI - Intelligently automate time-consuming and repetitive data processes so your planners can focus on planning.

Gain New Visibility - Upgrade legacy business intelligence by unifying your analytics – giving you unprecedented visibility.

Plan Confidently - Eliminate guesswork and gain strategic clarity with the world’s most accurate demand forecast.

Cut Inventory Costs - Shrink bloated assortment, eliminate inventory distortion, and prevent unnecessary markdowns with better data.

Improve Your Sales - Use our demand forecast to calculate lost opportunity and ensure you won’t make the same planning mistakes twice.

Deploy Quickly - No two retailers plan the same way. That’s why Retalon is highly configurable to any retail planning process.

Financial Planning

All of the advanced analytics you need to confidently plan your high-level financial targets, including:

• Sales
• Margins
• Inventory
• And even your turn

Our financial planning solution connects your high-level data all the way to your individual stores and channels — flagging exceptions in your plan and automatically reconciling your data from beginning to end.

This means that you can divide planning by categories and departments — and reconcile all plans at the click of a button.

Merchandise Planning

Turn your high-level financial targets into a granular, actionable, and fully optimized merchandise plan — broken up by week or month.

In practice, you’ll be able to automatically generate optimized OTB budgets, instantly link budgets to POs, and push the data into Retalon’s purchasing module.

If you purchase too much, our system will also flag or hard-stop purchases (based on your settings) — easily preventing over-purchasing, deadstock, and unnecessary markdowns.

Assortment Planning

Using cutting-edge retail science, advanced analytics, and artificial intelligence, Retalon’s software analyzes your assortment to make real, actionable recommendations.

This ensures that all of your assortment planning decisions are based on data and accurate forecasts — giving you a major leg up on the competition.

This not only allows you to optimize your existing assortment — you’ll also be able to proactively shrink or expand your assortment for maximum GMROI.

Open-to-Buy Planning

Eliminate the headache of manually creating, managing, reconciling, and executing on your open-to-buy budgets.

Our advanced analytics system will automatically account for dozens of factors (including demand, seasonality, price, inventory, events, promotions, etc.) to provide optimized purchasing recommendations. Furthermore, the system will also automatically generate POs based on your OTB budget, automating a very time-consuming process.

This will let you not only reduce costs and minimize markdowns — but also increase sales by proactively investing into inventory with demand.

Discover how AI for MFP and Assortment Planning can help your retail business connect with our team, come to our booth #4583.