Jeff Cotrupe has just posted a video providing rapid-fire takes on three top technology trends organizations need to know about and act on today: privacy, including Mark Zuckerberg’s testimony to the US Congress, and enforcement of the GDPR in the EU; AI, including machine learning, deep learning, cognitive, chatbots, and more; and big data and analytics (BDA), with a focus on data preparation–which is consuming up to 80% of what he terms “data time” in most organizations today–and the emergence of the first end-to-end BDA platform. Companies mentioned include IBM (and IBM Watson), TIBCO, FreeSight, Solix, Collibra, Unifi Software, Facebook, and Google.
The Retail Death Star (a euphemism for whoever you think it is) has such a glowing reputation for its acumen with data that other companies clamor to know how the Death Star does it. Personal experience suggests myth does not match reality…and two rising stars signal that e-commerce just got a LOT more competitive. Read the full piece here.
Companies are starting to get a handle on Big Data, accessing all types of data from all relevant sources–but the pace of business, and of life itself, now demands they take it a step further by equipping their people with real-time insights. Jeff Cotrupe’s Stratecast report, Monetizing Core Big Data Technology: Real-time Analytics, is a 29-page analysis of arguably the hottest (and certainly the “fastest”) area of the Big Data and analytics (BDA) market.
The report asserts there is not a private or public organization on the planet that cannot benefit from real-time insights, and illustrates the point with many case study snapshots of companies, from large enterprises to SMBs, which are obtaining not just quantifiable but bankable results through the deployment of real-time analytics. The report tackles business factors shaping the need for real-time analytics; the technologies it takes to deliver it, including in-memory processing; and the need for a balanced view of real-time analytics as one of three “data speeds” companies need today (along with near-real-time and batch analytics).
The report also identifies more than 60 BDA providers, out of the nearly 400 that Stratecast tracks in the market, who deliver the most effective real-time analytics solutions. In addition, each case study snapshot identifies the vendor and specific solution(s) delivering this important capability to the client.
Can (and Should) Retail/Wi-Fi Analytics Help Retailers Survive in the Age of Amazon?
Stratecast has published Jeff Cotrupe’s report The Human Bounce Rate: Can (and Should) Retail/Wi-Fi Analytics Help Retailers Survive in the Age of Amazon? The report analyzes crucial issues facing the retail industry, which contributes approximately $4 trillion to the economy in the U.S. alone. This massive industry faces sizable challenges including the struggling global economy; The Age of E-tailing (or more brand-specifically, The Age of Amazon); “showrooming,” which occurs when consumers shop for items at retail stores, where they can see, touch, and even try out items, then buy the identical items online at lower cost; and The Battleground in the Aisles, where consumers with mobile apps on their smartphones compare items for sale in the store where they are shopping, not only with Amazon and other e-tailers but also with other retailers within easy driving distance.
“If retailers are to survive, they must find ways to engage with shoppers, or, at minimum, to better understand what shoppers want,” said Jeff Cotrupe, who leads the Big Data & Analytics (BDA) program for Stratecast | Frost & Sullivan. “A new Big Data-driven solution that offers specific, relevant insights retailers need is what we term Retail/Wi-Fi Analytics, or RWA.” RWA gathers data from the Media Access Control (MAC) addresses of mobile devices within a given area, applying location and other advanced analytics to the data to provide insights quite similar to those offered by online analytics systems. Arguably the most interesting metric, in Stratecast’s view, and one that inspired the title of the report, is whether a shopper spends enough time in a store to fit the retailer’s established profile of a likely buyer. If not, some RWA systems consider the shopper to have “bounced.” This is similar to online analytics platforms that consider a visitor who leaves a site too soon to be likely to make a conversion (such as a purchase, registering for an event, or requesting more information) to have bounced. Cotrupe terms the rate at which shoppers bounce The Human Bounce Rate.
The report also deals with the issues of privacy that such shopper data collection raises. It discusses efforts underway in governing bodies, such as the U.S. Congress, and by consumer watchdog groups, to protect consumers from what may be unwanted intrusion into their personal (or at least shopping) space. The report, which carries Stratecast product code BDA 1-05, analyzes the differences in how data is collected by different RWA systems, and opt-out mechanisms that vendors and their retailer customers are adopting to stay ahead of regulators. The report also makes some pointed recommendations about how retailers should turn privacy negatives into revenue positives.
This Stratecast report is designed to benefit a wide range of readers, including every retail or e-tail organization, and individual retailers of all types and sizes; every brand that sells through either the retail or e-tail channels; every brand that utilizes mobile technologies for sales and retention activity; and every company that plays a role, or could, in equipping retailers to better compete.
The stats helpers at WordPress.com mulled over how this blog did in 2010, and here’s a high-level summary of its overall blog health:
The Blog-Health-o-Meter™ reads This blog is doing awesome!.
The Leaning Tower of Pisa has 296 steps to reach the top. This blog was viewed about 1,200 times in 2010. If those were steps, it would have climbed the Leaning Tower of Pisa 4 times
In 2010, there were 16 new posts, growing the total archive of this blog to 26 posts. There were 37 pictures uploaded, taking up a total of 2mb. That’s about 3 pictures per month.