Your Retail Data Is Worth Gold. Here’s How To Mine It: 7 Strategies For The Modern Retailer

It’s a familiar narrative: Retail giants are buckling under pressure, unable to keep up in an increasingly competitive landscape. These are the same organizations that have been pumping millions into R&D, seeking that elusive competitive edge. So, what’s going wrong?

The answer is in what they’re consistently overlooking: a treasure chest of existing data from ERP, CRM, and other business systems at their disposal.

Here are seven strategies for you to mull over...

Strategy 1:?Unify Multiple Data Sources

Data in the retail industry flows from a multitude of sources. You have sales data, customer feedback, online behavior analytics, in-store traffic, and the list goes on. While each source offers a different perspective, together, they form a coherent, comprehensive picture of your retail operations.

But making sense of this multi-source data and using it to make informed decisions is a challenge, especially when this data sits in silos, disconnected, and difficult to align.?

Consider this example.

> Your customer, May, visits your online store and spends time browsing through the shoes section.

> Next, She likes a pair, adds it to her cart, but for some reason, doesn’t go ahead with the purchase.

> A couple of days later, she walks into one of your physical stores and buys a different pair of shoes.

In the data world, this event creates multiple data points across online behavior analytics, sales data, and in-store traffic data. Alone, they don’t tell much.?

But when these data points are brought together, you get a holistic picture of?May’s buying journey.

• You can learn about her preferences,
• her decision-making process and
• even identify points where she might have needed some assistance.

That’s precisely what?Pluto7’s Data Platform?offers. By acting as a bridge between systems like?Google Cloud and SAP,?it can pull together disparate data sources, offering a unified, cleansed, and enriched data view. This unified view empowers you to understand your customers like May at a much?granular?level, enabling personalized experiences and informed decision-making.

Strategy 2:?Improve Demand Forecasting with AI

Traditionally, demand forecasting has relied on historical sales data and some educated guesswork.

But with AI, the guesswork can be significantly reduced.

AI can crunch vast volumes of data in no time and consider a multitude of variables that could influence demand, from seasonal trends and market fluctuations to consumer behavior and competitor activity.

Let’s dive a bit deeper into this.

Imagine you are a fashion retailer, and one of your products is ‘Cotton Summer Dresses.’ The AI platform not only analyzes the historical sales data of this product, checks for seasonal trends, and studies customer feedback but also?taps into Google’s search trends?to understand the latest consumer preferences.

For instance, if ‘Cotton Summer Dresses’ are trending on Google, the AI platform takes this as an external demand signal and integrates it into its prediction model.

This way, it predicts a surge in demand for ‘Cotton Summer Dresses’ in your downtown store while projecting regular demand at your suburban outlet.

Strategy 3:?Personalize the Customer Experience with AI

Every customer expects to be treated as an individual, not just another sales number.?

But how can you provide personalized experiences to thousands, if not millions, of customers? Here’s where AI does the magic.

AI can analyze?individual customer behavior?– their preferences, past purchases, browsing history, and even responses to promotional campaigns. It can then use this information to personalize their shopping experiences, both online and offline.

For instance, if a customer has a?history of purchasing craft beers, an AI platform can recommend other craft beers in their preferred taste profile, perhaps even suggesting new arrivals or limited edition brews that align with their tastes. It can even alert them about upcoming beer-tasting events or exclusive promotions.

Based on the browsing history and past purchases, Marketing ML can?recommend the ‘Limited Edition Barrel-Aged Stout’?to Jane and also suggest that she might like a?new range of artisanal cheeses?that pair well with her favorite brews.

Strategy 4:?Streamline Supply Chain Operations with AI

An efficient supply chain is the backbone of any successful retail business. From procurement and warehousing to logistics and inventory management, each stage of the supply chain plays a critical role in keeping your shelves stocked and your customers happy. But managing a complex supply chain can be challenging, especially in today’s unpredictable retail environment.

This is where AI and Machine Learning can revolutionize supply chain management. AI can forecast demand, optimize inventory, enhance logistics, and even predict potential disruptions. It can help retailers make data-driven decisions, reduce wastage, improve efficiency, and ultimately, deliver better customer service.

Strategy 5:?Revamp E-commerce with AI

In the e-commerce domain, AI’s powerful capabilities can make a significant difference in enhancing the customer experience, boosting sales, and notably,?reducing search abandonment,?a problem that?costs the retail industry over?$2 trillion annually globally.?

Let’s consider the case of a fast-paced online grocery store that wants to improve its user experience and reduce search abandonment. Here’s how ‘Planning In A Box’ could help:

Enhanced End-User Experience

Scenario:?It’s Saturday morning and Emma, a regular customer, logs in to quickly order her weekly groceries.

• Emma initiates a search for “organic cleaning supplies.” ‘Planning In A Box’s’ AI-powered search leverages Generative AI to understand Emma’s query and presents a selection of?top-rated organic cleaning items,?effectively reducing search abandonment.
• As she navigates to the fruits and vegetables section, the platform dynamically personalizes her interface, presenting her?frequently purchased items at the top?and highlighting?in-season fruits and vegetables on discount.
• As Emma moves to check out, her cart gets an upgrade with an?intelligent recommendation?generated by the platform – a popular organic salad dressing that pairs well with her choice of vegetables.

More insights for the Retailer?

• The retailer gets insightful visibility into Emma’s entire journey –?from her searches to her final purchases.
• Such granularity enables the retailer to?optimize their inventory at an SKU-level,?ensuring that they always have the right stock of each specific product. can adjust their inventory levels accordingly.
• The platform’s AI doesn’t just look at past purchasing patterns, it?blends this data with external data like market trends and seasonality.?

Leveraging the platform’s generative AI capabilities, the retailer can query their data with questions like “What specific SKUs are frequently bought together with SKU X of organic cleaning supplies?” This allows for smart,?SKU-specific product placement?and?bundling strategies.

By introducing AI into your e-commerce strategy, you can create a more fluid, personalized, and engaging shopping experience for your customers, reducing search abandonment and boosting sales.

Strategy 6:?Tap into Real-time Shelf Monitoring?

In the physical retail environment, keeping track of on-shelf inventory in real-time is a challenging task. A lack of real-time insight leads to stock-outs, overstocking, and misplaced items, which impact customer satisfaction and store operations. AI, through its advanced?vision and machine learning capabilities, can be a game-changer here.

Here’s how AI can aid in real-time shelf monitoring:

• Tackle Stock-outs & Overstocking with AI:?Inventory mismanagement like stock-outs and overstocking can cost retailers heavily. AI can help address these issues by providing real-time insights into shelf inventory.
• Planogram Compliance & Misplaced Items:?AI can monitor compliance with planograms and quickly identify misplaced items. This enables retailers to maintain an optimal product arrangement and offer an enhanced shopping experience.
• Product Arrangement’s Impact on Sales:?By analyzing product placement and arrangement on the shelves, AI can identify trends and patterns that can help boost sales.

Let’s take the case of a large supermarket chain, ‘SuperMart,’ that wishes to optimize its in-store operations and improve customer experience. Here’s how Pluto7’s?Planning In A Box?could assist, leveraging?Google Cloud’s Vision AI, Shelf Checking AI, and Event-driven automation?capabilities:

• SuperMart achieves?SKU-level visibility across all its outlets?using data consolidation. This forms the foundation of their efficient inventory management, reducing overstocks and stock-outs.
• By leveraging Vision AI-integrated cameras, SuperMart can?identify and refill empty or low-stock shelves promptly,?enhancing store readiness and preventing potential sales loss.
• SuperMart can ask complex questions to their real-time data, such as “Which products are often bought together with organic cereals in the morning hours?” or “What are the most purchased items during holiday season sales?”?thereby enhancing product bundling strategies.
• SuperMart can effectively anticipate demand fluctuations by blending?internal and external data,?allowing for quick adjustments to inventory levels.

Strategy 7:?Enhance Workforce Efficiency with AI

Using Google Cloud solutions like?Vision AI, you can automate routine tasks like?tracking?inventory, reducing manual errors, and freeing up your employees’ time. Suppose you have an IoT device in place for inventory tracking, Vision AI can analyze the data generated by the device to ensure accurate inventory levels, minimizing manual checks.

• AI-powered virtual trainers?can offer an engaging training experience for new employees, speeding up their onboarding process.
• Predictive analytics?can help with staffing. For instance, based on historical sales data and foot traffic patterns,?Planning in a Box?can predict busy periods, enabling you to optimize staff allocation.
• Predictive?Maintenance: Leveraging AI, you can forecast equipment maintenance needs across manufacturing units, preventing unexpected disruptions and keeping operations smooth.

The scope of AI in retail is vast, and we’ve touched upon just seven key strategies. The priority is to?understand the business problem first and then bring in AI as a solution. Remember, AI is a tool, a powerful enabler that can become a game-changer when used effectively and cost-efficiently.

That’s where we step in. If you’re looking to delve deeper into these technologies and their strategic application, to understand where to start and how to progress on your AI journey, we invite you to?join our upcoming workshop. Our focus is on demystifying the complexities of AI, making it not just understandable but?truly accessible, irrespective of your technical background or expertise.

Let’s innovate and adapt together.

This article was originally published here.