How much time is wasted by retailers and brands laboring through slow Excel-based reports trying to understand their sales performance? There’s a simple answer to that question: too much. In context, many midsized retailers from groceries to convenience stores and restaurants sell hundreds of thousands of line items every day, in which the sheer volume of sales exceeds the capabilities using Excel efficiently. Due to the timely and exhausting data-retrieval process from legacy vendors, our research indicates that analysts at retailers and brands spend between four and ten hours per week creating performance scorecards in order to inform category and item-level decisions. Eliminating this inefficiency is now possible due to three major technology developments: big data processing, web-based visualizations, and mobile-friendly dashboards. As a result, any employee on the go has powerful business intelligence tools to assist their day-to-day decisions.
Big Data Processing
One of the most significant catalysts for change is Apache Spark, which has been recorded mining billions of records at speeds 100 times faster than Hadoop. This is considerably faster than the SQL-based systems most retailers use today. With Spark, you can analyze billions of records of high volume, receipt-level point-of-sale data in seconds to extract hard-to-mine insights like dayparts and item co-occurrence patterns (e.g., what sells with what).
Humans are able to visually absorb information from plots or graphs more effectively than from tables of numbers, especially when drawing conclusions from complex data. This has been supported by scientific research; the human brain can interpret images in only 13 milliseconds, and other studies indicate that visuals are processed 60,000 times faster than text. Data visualization methods must be carefully chosen in order for data to be presented in a way that is interpretable, relevant, and novel. Visualizations must also include only relevant data, as irrelevant data can oversaturate the presentation and make it challenging to articulate the appropriate narrative for business executives. In the last several years, development of open-source tools like D3 and Google Charts offer a suite of basic and advanced web-based visualizations for presenting data.
People are becoming increasingly mobile, which has changed their daily preferences for processing information. Many employees, some of whom are executives, are investing in mobile devices with the intent of using them for work. According to the IDG Global Mobile Survey of 2014, 92 percent of executives own a smartphone and 77 percent of executives use their smartphone specifically to research a product or service. Without insights available anytime, anywhere, retailers and suppliers are facing significant competitive disadvantages by lacking the ability to make quick, informed decisions on the go. Automated dashboards that resize dynamically to be mobile-friendly are available in lieu of massive spreadsheets or manually-generated 50mb Excel files that are slow to open and difficult to read on small screens.
SwiftIQ uses high scale data processing and machine learning to deliver contextually relevant insights and digital experiences for retailers and brands. Its platform unifies and analyzes data primarily from in-store transactions as well as online behavior and third party sources to predict and inform category captains, shopper marketing, assortment, supply chain and content delivery decisions. SwiftIQ’s unique ability to process billions of basket-level transaction records in near real-time and convert that into on-demand mobile visualizations, dayparts, affinities and attribution fosters a new level of retailer/supplier collaboration and innovation.
Since launching its category captain and consumer behavioral analytics platforms in 2014, SwiftIQ has doubled in the first quarter of 2015 and now manages nearly $60 billion in offline, receipt-level point of sale data. The company provides software to 4 of the top 10 global CPGs and several billion-dollar retailers. SwiftIQ, named a Top Innovator twice by DataWeek, has also been recognized by Google, Forrester, Forbes, ProgressiveGrocer and ComputerWorld for its achievements. For more information, visit www.swiftiq.com.