People do crazy things, especially during the holiday season. On Black Friday – and even on Thanksgiving evening – customers will wait in line for hours to grab the best deals and knock items off their wish list. Retailers offer ridiculous discounts on high-priced items and keep doors open 3 days straight to cater to buyers around the clock, then web retailers kick in their own Cyber Monday promotions. Black Friday has remained the number one shopping day for the past decade, accounting for most of the sales that businesses reign in during the holiday season. But smart retailers don’t have to wait until Black Friday to ramp up their bottom line. Your analytical or business intelligence platform can keep a pulse on operations year round and help increase sales before the 11th hour. Here’s how:
1) Use analytics for in-store promotions
Analytics can help guide store layouts by tracking which products perform best on an aisle shelf vs. an endcap in various cities, and what products should go on sale in a given month and region based on sales history and inventory levels. Using business intelligence, you can run scenarios based on historical data and make predictions about programs designed to drive in-store business. For example, if you increase the circulation of your direct-mail flyer, how much additional business can you expect it to drive? Similarly, if you offer in-store coupons for a certain timeframe, what kind of sales uptick can you expect? Essentially, you can analyze past customer purchasing behavior to determine how to best influence future purchasing behavior.
arcplan’s retail customers use our platform to track KPIs and run what-if scenarios to ensure that products are priced appropriately. For retailers, one important KPI is the cost of goods sold (COGS) – the price paid for the product, plus shipping, handling and other expenses to get it ready for sale. By keeping track of COGS…
How BI facilitates a decision-making process that saves millions
At the core of every business decision is the desire to drive value for the company – whether that’s increased sales, higher margins, elevated profits, or return on investment. Decision makers should use all the resources at their disposal to drive this value, including their business intelligence software, which may include guided analytics (i.e. dashboards), ad-hoc analysis and collaboration capabilities that contribute to informed decision-making. Today I’ll explore how BI software facilitates decisions in a retail scenario. But this article isn’t just for retailers – anyone can extrapolate this information to their business to see how BI can provide concrete ROI.
arcplan serves a number of customers in the retail industry, including two of the largest grocery chains in the United States. Retailers are well-known for the small net revenue margins – on average, 3% across the globe for all types of retailers – which pose significant challenges on process controls and efficiency in supply chain decisions. One of the key areas of interest for all retailers, especially grocery chains, is the reduction of shrink – the loss of inventory due to product spoilage, waste, theft and other causes. It’s estimated to account for 2-3% of overall sales. Perishable shrink even goes up to 5% within a typical grocery chain. So for one of our customers, whose revenue reached $6.25 billion in 2012, a reduction in shrink of just 0.1% means $6.2 million to their bottom line.
So a simple question that would catalyze a decision-making process at this grocery chain might be: How can BI help reduce my shrink by 0.1% while balancing availability of goods and customer satisfaction? They would want to meet high customer expectations without over-ordering, which leads to shrink through spoilage.
According to industry forecasts, the world’s volume of data doubles every 18 months, and all forms of enterprise data will grow 650% over the next five years. The talk around big data is more than marveling at the mass of information we’re creating. As analysts and data scientists, we’re trying to find the good stuff – the trends, the data that allows us to make better decisions now and in the future, to predict the moves that will make our business more successful down the line.
Big data (explained in our previous article here) might be new to you, but I’ve seen some analyst reports referencing big data ideas as far back as 2001. However, the BI world is talking about it more and more as data volumes grow and we begin to see the potential knowledge to be gained in these data sets.
So maybe you’re thinking, how can big data benefit my company? It’s hard to think conceptually about it, so let’s take a look at some concrete examples of how companies are using big data today. We’ll start with the retail industry. Keep in mind that many of these ideas can be used on a smaller scale for retailers of any size.
Wal-Mart sifts through massive amounts of unstructured social media and search data to find out what products consumers are talking about. They use that information to set their ad buying strategy on sites like Google, with the goal of competing for e-commerce sales – currently dominated by Amazon.com.