Here’s why you need smarter BI for retail operations
Retail is one of the most data-driven industries in the world, so using business intelligence (BI) software to estimate inventory needs, understand customer behavior, and build forecasts is the life’s blood of any retailer. As technology advances, so does customer expectations.
Nowadays, consumers are less likely to reward retailers with long-term loyalty, so being able to accurately anticipate what they will do next and then quickly react is the name of the game. For that, you need real-time input from all data sources in your organization — from the traditional, such as point-of-sale data, to the new, such as Internet of Things (IoT) sensors or cameras monitoring stock in warehouses. You also need the right tools to convert that wealth of data into compelling insights.
Unfortunately, the self-service BI tools that have entered the marketplace in the last decade haven’t really delivered on that need. It’s true that their beautiful dashboards give everyone from merchandisers to buyers to small shop owners a quick answer for “What is happening?” on the sales floor and online. But that’s not enough if you want to please that fickle customer, open a new store in the perfect location, or make sure you don’t order the wrong product because of out-of-date information, because the prettiest visualization ever is still not going to answer the all-important question: “Why is it happening?”
Using BI for retail to understand why customers buy.
Basic BI tools cannot help you ensure that you respond to customer whims and events as they occur. To win over customers, you need to get beyond quick, pretty vignettes to deeper insights, for example, to demonstrate the effects of a regional marketing campaign, or to show customer buying trends at certain times of the year.
Also, some of the people using these basic tools might not have the right skills or might be using old-fashioned or misguided approaches. Examples include using correlations to prove causation or KPIs to explain results. Then there is the most persistent danger of all: Those who look at results and data through the lens of their own bias, potentially blinding themselves to something game-changing. Ask yourself this: Are your management teams hearing what they want to hear or what they need to hear?
A new kind of analytics for retail.
So, how can your retail organization make the unbiased decisions that increase revenues and profits, reduce costs, produce optimized sales forecasts, and allow you to offer trendsetting products? It takes a new breed of analytics, one that infuses traditional BI for retail with “smarts.” This term might seem lighthearted, but underneath it is serious technology: augmented intelligence. Augmented intelligence delivers data analytics tools that can learn and adapt to individual needs and, more importantly, give users precise answers based on contextual recommendations. Meanwhile, automated pattern detection helps users find better answers by reducing human bias.
Aberdeen Research predicts that 50% of best-in-class retail organizations are more likely to use artificial intelligence (AI) or AI-enabled platforms in support of their retail organization. To learn more about how best-in-class retail organizations are using AI, click here to access the full Aberdeen report.
Smart analytics like these allow you to go way beyond descriptive dashboard reporting because they put advanced analytics, smart data discovery, natural language queries, and sophisticated data storytelling abilities in the hands of professionals across your retail organization. Everyone works more efficiently and effectively, and your company is better able to increase profits while delivering exemplary customer satisfaction.
One real-world example is a premium shoe company that uses smart analytics to discover new sales insights, detect regional preferences, and make smarter decisions about which items to place in which stores. As a result, the company is boosting sales, customer satisfaction, and loyalty, even while reducing inventory levels.
IBM Cognos Analytics is a next-generation BI tool that has been completely reconceived to include machine learning, automated pattern detection, intelligent and interactive dashboards, and simple, reusable, drag-and-drop reporting. Beautiful visualizations help you find hidden patterns that can lead to breakthrough insights on customer behavior, staffing, inventory, product mixes, and more.
This post is sponsor content from IBM and was created by IBM and Insider Studios.