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5 Major Retail Digital Transformations to Watch For in 2024

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How is retail digital transformation changing the industry?

Retail digital transformation has fundamentally changed the way retail works, from the structure of internal operations to customers’ expectations of the retail experience.

Although e-commerce gets all of the attention, the past two decades of technological change have transformed every aspect of the retail business — from planning, inventory, pricing, and promotions — all the way down to customer service and the in-store experience.

The good news is, that the rise of online channels has not completely condemned brick-and-mortar retail to the history books.

In fact, retailers that successfully adopt appropriate technologies (and are able to flexibly assimilate to change), find they can harness the digital transformation to see their brick-and-mortar businesses thrive.

Advanced analytics and AI have accelerated the retail digital transformation.

The top ways digital transformation is changing retail

1. Advanced analytics & retail AI

Retail has always been a data-driven business, but the scale of today’s retail data environment is unparalleled (as will be tomorrow’s).

More and more data is gathered using new technology, including inventory systems, customer behaviour systems, product and store performance, and even weather reporting.

This flood of data must then be processed for hundreds of thousands of SKUs to generate actionable information in real time. Even with an army of analysts, the sheer volume of work is simply too much.

Success in modern retail requires moving from a data-driven paradigm to an analytics-driven paradigm.

Advanced analytics software powered by artificial intelligence (AI) can collate data from a variety of sources and automatically analyze it to make profitable recommendations.

These new tools change the way retailers approach their business.

In the data-driven paradigm, retail analysts use historical data to forecast sales and identify patterns — a process that has proven to be unreliable for accurately predicting future events.

In the analytics-driven paradigm, advanced analytics software forecasts true customer demand for each SKU, in each store — based on hundreds of input variables. It can analyze billions of data points and predict demand at a level of granularity that’s simply impossible to reach using Excel.

Another way advanced analytics levels up a retail business is by breaking down the siloes in large retail companies.

Traditionally, retailers have treated forecasting, planning, pricing, inventory, and promotions (marketing) as completely separate domains, often with competing mandates. This often leads to lost margins, as these functional siloes don’t effectively optimize across the entire product lifecycle.

For example, retailers know that a promotional event impacts way more than just the sales of a promoted SKU.

Promotions can increase foot traffic and sales of market basket items, while simultaneously cannibalizing sales from a variety of other SKUs.

However, traditional spreadsheet analytics cannot account for store-by-store variations in the promotion’s effectiveness or secondary effects such as demand cannibalization.

And because no one in the organization can effectively predict these things, decisions made by one department often have negative, unforeseen consequences for other departments.

Advanced analytics has the capacity to integrate every channel of a multi-channel business into its forecast to maximize the return on promotion investments.

For example, as soon as the AI knows that a promotion is coming up, it will calculate all of the downstream impacts of the promotion (including sales uplift, product cannibalization, etc.) to optimize inventory for gross margins. In effect, this means a reduction of total inventories, maximized sales, and reduced markdowns.

More importantly, an analytics-driven retailer no longer reacts to sales and inventory reports, but instead proactively optimizes its business. Users are not staring at large data aggregates, Instead, they are provided with profitable recommendations that are optimized holistically across their specific business — and they determine how deep into the data they want to delve into.

2. E-commerce

When brick-and-mortar retailers adopted e-commerce, online sales served as a complement or extension to the retailers’ core operations. Now, e-commerce is no longer on the retail periphery. Online sales are as mission-critical as in-store sales to today’s retail business.

According to Digital Commerce 360, American consumer online spending in 2020 increased 44% to $861 billion. Online sales now account for more than 20% of total retail sales.

While pandemic-era safety concerns contributed to this growth, the selection and convenience that online shopping offers to consumers are the primary drivers. This number will continue to grow.

E-commerce lets a retailer extend its product selection and create endless aisles while minimizing carrying costs. However, retail digital transformation is about more than expanded assortments.

Retailers now integrate their online and brick-and-mortar operations to become omnichannel businesses. This frees physical stores to serve as showrooms for the broader assortment, or better yet, provide customer experiences and events. While at the same time adding to the online fulfillment system, by providing in-store pickup and local same-day delivery. 

Autonomous mobile robots contribute to the retail digital transformation through order fulfillment automation.

3. Order fulfillment automation

In the world of omnichannel retail sales, the most successful companies automate their order fulfillment.

Retail AI identifies the fulfillment options that balance customer satisfaction with the cost of shipping and handling by accounting for inventory levels, transportation costs, and other factors, in real time.

These systems proactively forecasted fulfillment demand and brought the product to the right place.

The instant a customer hits the checkout button the AI technology evaluates every viable fulfillment option and recommends the optimal choice.

Similarly. Retail AI can apply this process when customers return their purchases.

Often, returning products to the store that fulfilled the original purchase will create inventory excesses and lead to markdowns. Arbitrarily sending all products to a warehouse also carries needless costs and takes longer to re-sell the product.

Retail AI systems evaluate a variety of factors including future demand, inventory levels, and upcoming shipments at stores and DCs to determine the best place for the returned merchandise.

Optimizing returns lets retailers improve their sales and inventory metrics while also reducing waste and improving the environment.

AMR, autonomous mobile robots, is another technology that is becoming a common order fulfillment aid.

Large warehouses such as those operated by Amazon, use AMR to maximize time efficiency while keeping labour costs low. Canadian award-winning retailer, Simons, leverages the best of both worlds with AMR in operations along with Retalon’s AI for forecasting and inventory management. (check out their story here)

Automated fulfillment improves the in-store experience by significantly reducing manual labour, inconsistency, and inventory imbalances by giving sales associates more visibility into inventory levels throughout the business.

4. Digital technology in retail stores

Digital technology in retail stores helps retailers turn their boring, old physical locations into competitive advantages.

Unlike their pure e-commerce competitors, retailers that use digital technology can create innovative customer experiences (that make in-person shopping faster and more pleasant) while reducing costs.

Examples of these new experiences are already appearing in retail stores all over the world and include:

  • Self-checkout: Smart sensors linked with product databases let customers avoid long lines at the register while minimizing loss prevention risks.
  • Walk-out Shopping: Smartphone apps, RFID tags, and computer vision technologies let customers pick up a product and walk out of the store without stopping at a register.
  • Robot Assistants: Customers do not need to hunt down an associate when robots can answer their product questions and direct them to the right aisle.

More fundamentally, digital technology is reshaping in-store merchandising strategies by integrating stores and e-commerce.

Stores become showcases where customers can touch, feel, and learn about products as they make their buying decisions.

The storefront provides an uncluttered experience while the online marketplace provides the variety and choice to match the customer’s preferences.

5. Customer experience optimization

New technologies are letting retailers extend their customer experience beyond the store.

Giving customers ways to interact with their brands while improving the shopping experience reinforces brand loyalty. At the same time, helping customers make the right purchasing decision increases sales and reduces returns.

Some retail customer experience technologies to keep an eye on include:

  • Innovative mobile apps: immersive, curated shopping experiences, AI customized loyalty programs, and gamification and rewards systems
  • Recommendation Engines: Machine learning and large customer data sets let recommendation engines make more relevant suggestions that are personalized to the customer and encourage purchases.
  • Chatbots: Natural language processing engines optimized for a retailer’s unique mix of products generate human-like “conversations” that convert sales and resolve customer service issues
  • Augmented/Virtual Reality: Extended reality apps let people see how the furniture fits in their homes or how clothes fit on their bodies before making a purchase. According to Shopify, products with extended reality content have a 94% higher conversion rate than those without.

Transform your retail business with the right technology

Digital technology in retail stores can improve sales, lower costs, and boost profits. Yet chasing every new technology is a recipe for failure.

Retailers must do their homework. Each new advancement has strengths and weaknesses which must align with a retailer’s strategy and brand identity.

Among the many options, advanced analytics generates returns across all retail sectors. The right analytics solution will immediately make concrete, measurable improvements.

Advanced Analytics lets you plan assortments, manage inventory, and execute promotions holistically across your business to reduce costs and increase sales while improving customer experience and satisfaction.

Embrace the retail digital transformation for your retail business by talking to Retalon’s analytics specialists today.

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