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HIVERY Attracts Top Industry Talent Once Again

Dec 02, 2021 | By

HIVERY

Sydney, NSW, Australia — December 2nd, 2021 — Meeting growth and expansion demands, HIVERY continues to move forward, attracting key hires at the industry's forefront. Humble beginnings in 2015 launched HIVERY to the cutting-edge global force that it is today. From Australian roots, it branched to North America, Asia, and Europe. To keep up with its unprecedented success, HIVERY needs top talent to match its state-of-the-art development. Over the years, HIVERY has added raw talent to its force of AI innovators. Now, two more seasoned professionals have joined the team. To meet the increase in customer demand, representatives from industry leaders want to be a part of HIVERY's revolution. HIVERY is pleased to announce the hiring of Matt Schilb, VP of Product and Dirk Herdes, VP of Retail,  to help drive the next generation of assortment retail analytics.  Matt Schilb Schilb comes with an impressive record of success. Previously employed by Walmart, RSi, and most recently as Vice President of Product & Technology at NielsenIQ, he's aware of the need for data in decision-making, and its benefits for both companies and consumers. "HIVERY’s motto of Data has a better idea™ is something that really resonates with me," Schilb said. "People are flooded with information, and the ability to make effective decisions has become super difficult. We have decision fatigue, which in retail can lead to subpar assortment outcomes or a bad shopper experience. The ability to simulate different assortment strategies using AI and then quantify those scenarios in minutes is where HIVERY excels." Committed to ever-evolving AI technology, Schilb is familiar with its vast scope of results. His proven leadership and passion for design-driven innovation are the perfect forward-thinking fit for HIVERY to meet client needs while producing high-quality output. Dirk Herdes Herdes joins HIVERY following a successful 15 year run at The Nielsen Company where he rose to  Senior Vice President of Retail. An expert in leveraging data and analytics, he sees the massive opportunity and need for merchandising solutions to adapt to both current and future demands of the industry. "Retailers are inundated with data, never-ending merchandising rules, and SKU proliferation," Herdes noted. "Combined with increased supply chain complications and rising consumer demands, this is making optimal assortment planning and execution very challenging. The current process is labour-intensive and too slow to respond to evolving customer needs. HIVERY was created to change this, providing a simple interface but powerful AI model that can simulate scenarios at store level to scale, quantify the impact of those decisions, and then automate planogram generation at the most granular level. This is where the industry is heading and I want to be part of the transformation." Herdes has a passion for helping companies leverage their data and technology in new ways.  Finding the right AI-powered solutions, that enable users to easily interact with their data and make decisions that help customers fuel their growth - which has been HIVERY's belief from the start.  HIVERY is Different Schilb and Herdes recognize that HIVERY takes a unique approach to data, and this method of using artificial intelligence in assortment planning is the way of the future. Wanting to be a part of this growth mindset, they're perfect for the revolutionary development that HIVERY continues to deliver. With HIVERY Curate, for instance, users, with a few clicks, can make rapid assortment scenario simulations to determine the best possible decision to make around SKU rationalization, SKU introduction and space simultaneously. Simulations take into account any category goal, merchandising rules entered by the user with the impact of cannibalization and other key metrics considered to deliver optimal assortment planograms from store-level and up. About HIVERY HIVERY is a pioneer of hyper-local retailing and offers retail AI-driven strategy assortment simulation & optimization solutions to a growing number of CPG companies and retailers in North America. For more information, press only:    Address: HIVERY, Level 2,15, Foster St, Surry Hills, NSW 2010, Australia, Email ID: franki@hivery.com, Contact number: +61 409 213 683 Download PDF version
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Red Bull's John Showalter Joins HIVERY to Bring AI Assortment Simulation to More CPG and Retailers
Nov 18, 2021 | By

HIVERY

Sydney, NSW, Australia — November 17, 2021 — HIVERY is delighted to announce that Red Bull's John Showalter will be joining them to deliver AI assortment simulation to more CPG and Retailers. HIVERY is proud to announce that John Showalter (Red Bull) is joining the company with the aim of bringing AI assortment simulation to more retailers and CPG. "Red Bull Core Values are all about having an entrepreneurial mindset, looking for better, smarter ways of doing things and differentiating ourselves” said Showalter.  “In the last five years at Red Bull, I started asking the question of myself and of the team, where does data science meet category?  What new and emerging technology was coming into the marketplace where we could continue down the path of making us differentiated -  HIVERY did just that." "Over the past thirty years, we have progressed a lot as an industry, but I don't think we've encountered anything revolutionary, until now. I feel that AI augmentation of human decision-making around assortment strategy and planning is going to have a major impact on the industry moving forward." said Showalter, VP of Client Services. John is a seasoned professional with more than thirty years of experience in the category management and insight niche. In the past, he has held senior roles at Bayer, Kellogg’s, the Coca-Cola company and Red Bull. He is committed to enhancing capacity and capability in category insights, space planning, shopper research and insights, and training & capabilities.  John is always looking for ways to embrace new technology and do things "smarter". When HIVERY partnered with John, they recognised there was synchronicity in their approach to technology within the sector. John appreciated the potential of the HIVERY technology, specifically what HIVERY Curate has to offer, prompting him to move to the company. HIVERY employed John to help support and drive the company's continued customer growth.  HIVERY's customers have increased by over 900%  (from five to fifty-four)  over the past few years. With John's assistance, HIVERY is on track for a Series B target in mid-2022. Their aim is to reach the target by demonstrating continued strong growth to hit about $10 million ARR. In his capacity as a CMA-certified professional strategic advisor, John has worked on the Omnichannel Project and CMA's Evolution of Category Management.  HIVERY provides AI-powered solutions for retailers and CPGs. HIVERY aims to assist its clients through providing options for category management, vending machine technology, assortment optimization, promotional calendars and planograms. HIVERY Curate is one of HIVERY's most advanced AI solutions. It provides store level assortment simulation and optimization, enabling retailers to create rapid, straightforward options for complex situations. It is prescriptive and conversational in nature, requiring little domain expertise to use, augmenting users' ability by navigating the assortment optimization cycles rapidly. This is significantly faster than traditional methods. About HIVERY HIVERY is a pioneer of hyper-local retailing and offers retail AI-driven strategy assortment simulation & optimization solutions to a growing number of CPG companies and retailers in North America.   For more information, press only:    Address: HIVERY, Level 2,15, Foster St, Surry Hills, NSW 2010, Australia, Email ID: franki@hivery.com, Contact number: +61 409 213 683 Download PDF version
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Webinar: IDC Research's Next-Gen Merchandising Solutions Are Coming: New Approaches to Meet the Coming Challenges of Retail
Nov 10, 2021 | By

Category Management Association

In this webinar hosted by Category Management Association; IDC’s Jon Duke, Vice President of Research and Retail Insights, and HIVERY's John Showalter, VP of Client Services, discuss the coming merchandising challenges for retailers and CPGs as well as the next generation of software solutions that help solve them. As investment in AI in retail accelerates, and its adoption increases, we are rapidly moving from the future-focused, more-visionary-than-practical approach into a world where next-gen tools deliver practical value. International Data Corporation (IDC) is the premier global provider of market intelligence and advisory services. IDC examines consumer markets by devices, applications, and services for clients. Jon Duke, IDC's Vice President of Research and Retail Insights Jon leads the Intelligent Product Merchandising and Marketing Strategies practice and is responsible for delivering IDC Retail Insights’ authoritative perspective on how retailers can leverage technology solutions to achieve key operational, tactical, and strategic objectives across merchandising and marketing functions. Jon provides global, fact-based, retailer-driven research and analysis that IT buyers and merchant users can use to gain an advantage. International Data Corporation (IDC) is the premier global provider of market intelligence and advisory services. IDC examines consumer markets by devices, applications, and services for clients.  John Showalter,  HIVERY’s VP of Client Services John is a seasoned category management and shopper insights professional with 30+ years of experience. John has held senior roles at Kellogg, Bayer, The Coca-Cola Company and Red Bull driving business outcomes and capabilities in Category Insights, Shopper Research and Insights, Space Planning as well as Training and Capabilities. He is a CMA Certified Professional Strategic Advisor and has worked on CMA's Evolution of Category Management in an Omnichannel World project. Get the IDC research report when available? Sign up, and we'll send you the latest IDC research report on this topic once available in a few weeks.
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podcasts
How recipes can engage retail shoppers, increase their basket size and reduce waste
Nov 08, 2021
In this podcast you will learn: • How and why Michael startedwww.plantjammer.com, a dynamic way to engage your retail shoppers with recipes; • How AI is being applied to food recipes to help shoppers and retailers. • Why food recipes on retailers' websites can generate a win-win: a win for shoppers as well as a win for retailers with one line of code; • What effect the demand for recipes can have on retailer's assortment; • and more.
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Webinar: Next-Gen Merchandising Solutions Are Coming: New Approaches to Meet the Coming Challenges of Retail
Oct 26, 2021 | By

HIVERY

Webinar: In this webinar hosted by Category Management Association; IDC’s Jon Duke, Vice President of Research and Retail Insights, and HIVERY's John Showalter, VP of Client Services, discuss the coming merchandising challenges for retailers and CPGs as well as the next generation of software solutions that help solve them. As investment in AI in retail accelerates, and its adoption increases, we are rapidly moving from the future-focused, more-visionary-than-practical approach into a world where next-gen tools deliver practical value. International Data Corporation (IDC) is the premier global provider of market intelligence and advisory services. IDC examines consumer markets by devices, applications, and services for clients. Hosts: Jon Duke, IDC's Vice President of Research and Retail Insights Jon leads the Intelligent Product Merchandising and Marketing Strategies practice and is responsible for delivering IDC Retail Insights’ authoritative perspective on how retailers can leverage technology solutions to achieve key operational, tactical, and strategic objectives across merchandising and marketing functions. Jon provides global, fact-based, retailer-driven research and analysis that IT buyers and merchant users can use to gain an advantage. International Data Corporation (IDC) is the premier global provider of market intelligence and advisory services. IDC examines consumer markets by devices, applications, and services for clients.  John Showalter,  HIVERY’s VP of Client Services John is a seasoned category management and shopper insights professional with 30+ years of experience. John has held senior roles at Kellogg, Bayer, The Coca-Cola Company and Red Bull driving business outcomes and capabilities in Category Insights, Shopper Research and Insights, Space Planning as well as Training and Capabilities. He is a CMA Certified Professional Strategic Advisor and has worked on CMA's Evolution of Category Management in an Omnichannel World project. This is now available on-demand.
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#thankyou to Business NSW for the recognition - Excellence in Export
Oct 25, 2021 | By

HIVERY

Thank you to Business NSW for the recognition. HIVERY is proud to be the winner for Excellence in Export in the Sydney City Business Awards!  Learn more.
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blogs
A five (5) min guide that will walk you through what you need to know about assortment, simulation, optimization & AI
Oct 11, 2021 | By

HIVERY

Retail is a tough game, and optimizing your choices can be incredibly difficult. With the ever-growing number of SKUs to choose from, limited shelf space, and supply chain complexity, retailers and Consumer Packaged (CPG) companies are increasingly under pressure to get assortment right. Enter Artificial Intelligence (AI).   You can develop assortment strategies or review how your stores are doing, and hope for the best, but that may not give you the best results.  Question: Have you considered using computers to simulate and help you optimize your category assortments? Analytical assortment optimization powered by machine learning can greatly improve both decision and execution in rapid time. Here are a few key facts about this field and how you can use it in your category assortment planning.   What Is Machine Learning?  This is a segment of the field known as Artificial Intelligence (AI) and is designed to mimic the ways humans can learn things by importing data. While AI is a favorite topic in science fiction, the goal is to let computers improve their results through data and algorithms. Machine learning (ML) is a subset of AI that uses special algorithms or models to conduct data analysis, finding patterns in data and relationships within the dataset, in order to make predictions. Predictions get better over time as more data is analyzed. Trial and error plays a big part in ML. As the model finds errors or discrepancies between its prediction and the actual dataset, it tries to rectify its thinking so its predictions are close to what is actual. This process is often called "training the model". Actual datasets are split into training sets and validation sets, generally a 90/10 split with 90% for training and 10%  for validation of its prediction or error rate. This is where data scientists might change the features of what the model should be learning from such as price, product, location and/or the model's parameters; which are the properties of the training datasets that are learned during training. Oftentimes, parameters are something that a model learns on its own and adjusts automatically as it tries to reduce its prediction error rate. It is this ML trial and error that is important because it sees the world from a machine construct, not a human construct. This difference allows retailers and CPGs to tap into a new way of looking at, for example, assortment optimization. Below is an illustration of this process of learning:   How Is It Used in Retail?  ML can help retailers optimize their supply, product, and sales. Retailers and CPG brands generate tons of data, and ML can look through this data to find new actionable insights for businesses to achieve their goals. Many retailers use data analysis, and you've probably seen examples work in real-time when you're shopping or visiting a store. If you buy something online and get a "customers who liked this also like..." message, or if you see recommended items that match what you're shopping for, that's an example of a type of ML model. However, there's also a lot of analysis and modelling that goes on behind the scenes. The location of stock on the shelves, and even what stock is in the store, can be improved with machine learning. Retailers and Consumer Packaged (CPG) companies can use ML models to find out where best to put items, how to shelve and advertise, and what things to restock.  ML algorithms can effectively improve profit margin by ensuring a better product mix and uncover previously neglected customer needs.  This means superior SKU rationalization and new product introduction as well as optimal space allocation and localization for those assortments. Basically, the ML algorithms can be made to look at the data and help retailer/CPG assortment teams find out what moves stuff off the shelves. Do people buy a particular item more when it's on an endcap and is it worthwhile to have that item there instead of something else? ML models that are used for assortment optimization can perform core SKU analysis, letting you figure out your optimal SKU introduction for each store.  Some retailers also use ML to help them with loss prevention. If you've ever tried to buy something locked away in a special part of the store, you've seen this idea in action.  ML algorithms can be trained to pick items that are likely to be stolen. The stores then lock them up, cutting their losses on those stock items. While it can be frustrating, it serves as an important tool for keeping costs low.    What Can Analytical Assortment Optimization Do?  Analytical assortment optimization is a specific way to use machine learning to help you make decisions for your business. It can perform "retail simulation," giving you a virtual idea of the impact of your category or merchandising assortment decisions and recommendations on how to improve them.  Historical data is a key aspect of this kind of demand or assortment forecasting. ML algorithms will look at the sales and volume numbers from your entire universe of stores, trying to find patterns in the data. Did something sell really well in one store that can be sold in another? Which stores will this new SKU introduction do better in? The decision can be simulated rapidly and the impact quantified to inform decision making. Again, more data is always better. However, the reality is there are also merchandising rules or constraints like POD (Point of Distribution) thresholds and ensuring certain SKUs get at least, say, 1.5 cases on the shelves. As you begin using analytical assortment optimization to track your sales and store's performance, you'll begin changing these constraints and be able to see the true impact of your decisions. As this happens, the algorithm will be able to better analyze what sort of changes are beneficial at store-level or national-wide.   How Can You Implement It? There are a few ways to go about using data analysis and ML to improve your assortment decisions. If you feel confident about your statistics and programming skills, you can do the analysis on your own and try to improve your store. But if you're like most people and barely know anything about statistics or programming, or simply don’t have time, you may have to seek outside help. Whether you want some planogram analysis, SKU rationalization, or retail optimization, it might be a good idea to pay someone else to help take care of things. Tech companies offer data analysis on all types of business data. From your products to your advertising choices, the analysis can improve your profit margins and get your products moving. Everything from small things all the way up to the big picture with your macrospace allocation and localization can be covered. It doesn't matter if it's big or small; data analysis can help you save money and improve your business!   Learn More If you'd like to learn more about how analytical assortment optimization can help your business, we'd love to help!  You can learn more about our solution, HIVERY Curate which enables you to run SKU rationalization, SKU introduction and optimization at store-level and up. HIVERY Curate can incorporate any merchandising constraints, allowing you to simulate strategic scenarios with accuracy and reliability, guaranteeing executable store-specific recommendations for every cluster dimension or count; eliminating the averages of averages approach. Feel free to contact us with any questions or concerns about machine learning, AI, or data analysis you may have or just see a live demo. Seeing is believing! Get this guide emailed? Want this guide email to you for later reading? No problem, request it here
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HIVERY Curate Now Available on Microsoft AppSource
Oct 05, 2021 | By

HIVERY

Sydney, NSW, Australia — October 5, 2021 — HIVERY today announced the availability of HIVERY Curate on Microsoft AppSource, an online cloud marketplace providing tailored line-of-business solutions. HIVERY was established in 2015 with the motto “Data Has A Better Idea”. It is the company's expertise in data science and heritage from the renowned CSIRO's Data61 that makes HIVERY special. CSIRO is Australia's national science agency who also invented Wi-Fi technologies and helped NASA reach the Moon, sending TV images to 600 million people around the world. The company has had remarkable success in providing powerful retail assortment strategy simulation and optimizations to complex assortment challenges to global CPG brands and retailers like The Coca-Cola Company and Walmart. "The market reaction to HIVERY Curate is extremely exciting, so we are expanding our operations aggressively in North America with the help of our investors and business partners like Microsoft,” said Jason Hosking, CEO, HIVERY Toby Bowers, General Manager, Business Applications Group, Microsoft Corp., said, “We’re happy to welcome HIVERY Curate to Microsoft AppSource, which gives our customers access to the best solutions available from our extensive partner ecosystem. Microsoft AppSource offers partner solutions such as HIVERY Curate from HIVERY to help customers meet their needs faster.” Learn more about HIVERY Curate at its page on AppSource. About HIVERY HIVERY is a pioneer of hyper-local retailing and offers retail AI-driven strategy assortment simulation & optimization solutions to a growing number of CPG companies and retailers in North America. For more information, press only:  Address: HIVERY, Level 2,15, Foster St, Surry Hills, NSW 2010, Australia, Email ID: franki@hivery.com, Contact number: +61 409 213 683 Download PDF Version
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HIVERY announced as a finalist for the 2021 Premier’s NSW Export Awards
Oct 04, 2021 | By

HIVERY

The Premier’s NSW Export Awards is an annual program that acknowledges the achievements, hard work and commitment of Australian companies engaged in international business. This award recognizes the important contribution exporters make to Australia’s economy by strengthening the workforce and boosting prosperity for both the community and the state. HIVERY finds itself amongst other prestigious and hard-working organizations in the Advanced Technology category, all having not only survived but thrived and innovated despite the challenges of the pandemic. We are proud to stand beside them as we advance to the finals together. Being one of the finalists for the Premier’s NSW Export Awards means that, today, HIVERY has reached another significant milestone. This recognizes our passion for and dedication to revolutionizing merchandising management and retail analytics through cutting-edge technology. Our team wishes to express our gratitude to the panel of judges - Export Council of Australia - and our fellow finalists.  See video and list here It is a huge privilege for HIVERY to be part of such a prestigious award and to also be distinguished as one of the top businesses for exports in the country. We are looking forward to hearing the outcome of this event which will be held in late October. This year has brought HIVERY into the limelight with The Financial Times Asia-Pacific naming us as one of the high growth top 500 companies with a rank of 77, Forbes Asia putting us amongst the 100 To Watch List and being announced as a finalist for AmCham’s Alliance Award in Artificial Intelligence. Driven to make a greater impact in the retail industry and beyond, HIVERY has developed a new category space in retail analytics. Using the world’s most advanced machine learning and operations research techniques, our goal is to consistently empower global FMCGs, CPGs and retailers to make more informed decisions that will enhance customers’ shopping experiences, optimize shelf space utilization and maximize profits. If you would like to know more about this solution and our other products, contact us
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