Giant Eagle, AI is changing category management 

Determine which Giant Eagle stores should carry what specific category SKUs. Drive new incremental profits at store-level all in minutes, not months

The world’s first truly hyper-local category management solution, offering the simultaneous optimization of assortment and space at store-specific level and rapid scenario planning.  For the first time you can, either at a national and or store-specific level, generate rapid category scenarios while factoring the impact of events like transferable demand and merchandising constraints

HIVERY Curate -  AI Category Management Solution with powerful rapid category scenario planning

According to Forrester Research, retailers & CPGs should focus on backend operations and augment decision making with smart analytics to frequently asked questions.

Forrester Research: AI In retail needs to start at the backend with smart automation

We often hear that the future of Consumer Packaged Goods and retail sectors begins with Artificial Intelligence (AI), but how exactly can AI shift category management? 

New capabilities required to remain indispensable to your shopper

The pandemic has brought significant changes to the formats and operations of supermarkets. It is expected, then, that variations around shelf space and product assortment will also arise.

Four (4) shifts in supermarket space that are going to change retail forever

Giant Eagle_Flyer_Curate_Retail_FNL.pdf

HIVERY Curate is a retail category management tool that leverages artificial intelligence and operations research techniques to optimize shelf space and assortments – reducing the time involved in category relays from months to minutes. 

HIVERY Curate incorporates your own unique business rules and constraints. 

Product information

Since it launched in 2015, we have been at the leading edge of category management technology. We help some of the world’s biggest manufacturers predict how shopper demand will transfer when products are added to or deleted from a store’s shelf. The key is deciphering a store’s unique purchase behavior. 

Borrowing ideas from deep learning method, HIVERY is able to generate data from random noise (i.e. random numbers) to infer incrementality and demand transferability. It's the world’s first AI driven cannibalization model, and it drives Hivery's assortment recommendations.

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David Buckley, Vice President of Retail 
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Please select a time with David Buckley, Vice President of Retail at HIVERY North America, to see a live demo or answer any questions.

Giant Eagle - David Buckley - HIVERY Curate & AI-driven category management

Taking this opportunity to explain HIVERY Curate and what it can do in retail

AI is changing category management - HIVERY Curate

A high-tech aroma recovery manufacturer, a medical device innovator, a drone detection technology exporter and a dance company are among the fifteen NSW businesses to be recognised at the 2020 Premier’s NSW Resilient Export.  HIVERY was one of the fifteen.   

The Premier’s NSW Export Awards have honoured the achievements of outstanding local exporters for the past 57 years. In 2020, the NSW Government adapted the awards program as a platform to celebrate and promote stories of resilience, perseverance and adapting under pressure from the NSW export community.

Investment NSW CEO Amy Brown said the Awards shine a spotlight on stories of innovation and quick-thinking pivots by determined business leaders in the face of unprecedented challenges.


HIVERY recognised at the 2020 Premier’s NSW Resilient Export Award

A high-tech aroma recovery manufacturer, a medical device innovator, a drone detection technology exporter and a dance company are among the fifteen NSW businesses to be recognised at the 2020 Premier’s NSW Resilient Export Awards

• What new retail trends we can expect to stick and which ones are temporary and would go back to what they were pre-COVID. Specifically, Ken shares interesting insights into reimagining how the stores will evolve and what it means for brick and mortar retail.

• The research that is being completed by Coresight around economic benefits of assortment localisation and what it means for both retailers and CPG companies.

• Ken shares his predictions regarding what stores of the future would look like and challenges some of the old assumptions we often hold as true. Some surprising insights.

• Who is experimenting with such things as in-store flying-blimps, shelf edge personalised messaging, computer vision, robotics, smart check out, and hyper local assortments.

• How technologies such as AI and AR are being used by retailers, and how latent demand will change the way we predict shopper demand.

• Interesting startups who are bringing amazing innovation to retail spaces from USA to Israel to Australia.

Ken is the President of Research & Advisory at Coresight Research, which delivers data-driven insights at the intersection of retail and technology. Coresight provides leading retailers, brands, technology companies, and investors with insights, advice, and tools to anticipate change and profit from the disruption reshaping the global retail landscape. Coresight has offices in the US, China, Europe, and India.

Ken is a leading expert on omni-channel retail, subscription e-commerce, retail innovation, and loyalty. He regularly speaks at industry events including Shoptalk, Groceryshop, FMI, and with the media, including CNN, CNBC, BBC, NPR, Inc., and Forbes.

Ken was previously a senior consultant at McKinsey & Company. He led Consumer Markets for Fuel, McKinsey’s startup practice, where his clients included subscription, DTC, marketplace, and retail tech companies. He also served leading retailers, brands, and private equity firms on loyalty, personalization, and the future of retail.

Ken is the President of Research & Advisory at Coresight Research, which delivers data-driven insights at the intersection of retail and technology. Coresight provides leading retailers, brands, technology companies, and investors with insights, advice, and tools to anticipate change and profit from the disruption reshaping the global retail landscape. Coresight has offices in the US, China, Europe, and India.

Ken is a leading expert on omni-channel retail, subscription e-commerce, retail innovation, and loyalty. He regularly speaks at industry events including Shoptalk, Groceryshop, FMI, and with the media, including CNN, CNBC, BBC, NPR, Inc., and Forbes.

Ken was previously a senior consultant at McKinsey & Company. He led Consumer Markets for Fuel, McKinsey’s startup practice, where his clients included subscription, DTC, marketplace, and retail tech companies. He also served leading retailers, brands, and private equity firms on loyalty, personalization, and the future of retail.

Future of retail is here: from in-store flying-blimps, shelf edge messaging, computer vision, robotics, smart checkouts to hyper local assortments

Future of retail is here: from in-store flying-blimps, shelf edge messaging, computer vision, robotics, smart checkouts to hyper local assortments.

Ken is the President of Research & Advisory at Coresight Research, which delivers data-driven insights at the intersection of retail and technology. Coresight provides leading retailers, brands, technology companies, and investors with insights, advice, and tools to anticipate change and profit from the disruption reshaping the global retail landscape. Coresight has offices in the US, China, Europe, and India.

Ken is a leading expert on omni-channel retail, subscription e-commerce, retail innovation, and loyalty. He regularly speaks at industry events including Shoptalk, Groceryshop, FMI, and with the media, including CNN, CNBC, BBC, NPR, Inc., and Forbes.

Ken was previously a senior consultant at McKinsey & Company. He led Consumer Markets for Fuel, McKinsey’s startup practice, where his clients included subscription, DTC, marketplace, and retail tech companies. He also served leading retailers, brands, and private equity firms on loyalty, personalization, and the future of retail.

In this podcast you will learn:

• What new retail trends we can expect to stick and which ones are temporary and would go back to what they were pre-COVID. Specifically, Ken shares interesting insights into reimagining how the stores will evolve and what it means for brick and mortar retail.

• The research that is being completed by Coresight around economic benefits of assortment localisation and what it means for both retailers and CPG companies.

• Ken shares his predictions regarding what stores of the future would look like and challenges some of the old assumptions we often hold as true. Some surprising insights.

• Who is experimenting with such things as in-store flying-blimps, shelf edge personalised messaging, computer vision, robotics, smart check out, and hyper local assortments.

• How technologies such as AI and AR are being used by retailers, and how latent demand will change the way we predict shopper demand.

• Interesting startups who are bringing amazing innovation to retail spaces from USA to Israel to Australia.

Ken Fenyo on the future of retailing: shelf edge messaging, hyper local assortments and more by Retail Mavericks

HIVERY Curate is on track to grow client sales over $1 billion and has been named in the Gartner Market Guide for Retail Assortment Optimization Applications in Merchandising

SYDNEY, AUSTRALIA, April 30, 2021 - HIVERY has been recognized in the Market Guide for Retail Assortment Optimization Applications in Merchandising1  by globally recognized independent IT research and advisory company, Gartner.

HIVERY is a multi-award winning pioneer of hyper-local retailing, combining artiﬁcial intelligence (AI), operations research, and human-centered design to help consumer packaged goods (CPG) manufacturers and retailers generate a return on retail space investments by discovering each store's space and product assortment digital fingerprint.  HIVERY Curate is the world’s first true category management software that offers store-level optimization and rapid strategic category simulation and planogram generation.

The research report has pointed out that “assortment optimization applications can provide powerful inventory management that minimizes excessive and “dead” inventory, enabling dramatic improvement of free cash flow to fund broader digital investments.” What sets HIVERY Curate apart from others is that it can achieve this level of superior optimization by starting at the store level. HIVERY Curate identifies the unique ﬁngerprint of each store’s consumption patterns, across all items sold, then recommends the optimal assortment for each store to meet the localized consumer demand. Additionally, HIVERY Curate leverages artificial intelligence to enable our clients to perform rapid testing of different assortment options or category strategies, and predict the financial outcome of each, with unparalleled accuracy. 

Over the last year, clients have seen annual incremental sales growth of up to 10% by leveraging HIVERY Curate. In the coming months, projected client sales growth from using HIVERY Curate is on track to exceed $1 billion. In addition to incremental sales, clients have been able to streamline their category management processes and reduce resource hours by as much as 80%. The combination of sales growth and labor reduction has resulted in an unprecedented 10x return on investment for our clients 

HIVERY CEO, Jason Hosking, said that the company’s recognition by Gartner demonstrates how HIVERY’s unique artificial intelligence capability drives new brand and sales value for major CPG manufacturers and retailers in the North American market.

“HIVERY’s aim is to be the market leader in retail enabled AI solutions. Our background in deep tech and data science really sets us apart from other players. Our core focus right now is retail assortment and space optimization with our product, HIVERY Curate. Based on HIVERY’s significant growth in North America, the company plans to scale into other global markets over the next 18 to 24 months.” 

According to the Gartner report, “by 2024, Tier 1 retailers in North America and Europe will reduce inventory carrying costs by 30%, dramatically improving free cash flow for digital investment while revamping balance sheets. By 2025, the top 10 retailers globally will leverage AI to facilitate prescriptive product recommendations, transactions and forward deployment of inventory for immediate delivery to consumers.”

HIVERY is unique in that the business has the backing of the Australian Government through its national science agency, the CSIRO’s Data61. Additionally, HIVERY collaborates on research projects with universities, providing clients with unique access to the latest scientific data. HIVERY’s investors include The Coca-Cola Company, the CSIRO, and Blackbird Ventures (Australia’s pre-eminent Venture Capital firm) who successfully backed Australian billion dollar start-ups such as Canva, Zoox, Safety Culture and Culture Amp.  HIVERY has been operating for six years and has offices in Australia (Sydney), Japan (Tokyo) and the United States (Bentonville, Arkansas).

You can learn more about HIVERY Curate and view the video explainer here https://www.hivery.com/products/curate or download the latest research report by Coresight Research titled “The Age of Precision Category Management: Hyper-Localized Assortment Optimization Using Advanced Technologies” https://www.hivery.com/age-of-precision-category-management 

Source: 
1 Gartner, "Market Guide for Retail Assortment Optimization Applications in Merchandising", Robert Hetu, October 2020 

Disclaimer: 
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. 

For further information and media inquiries please contact:

Franki Chamaki, Co-founder, Marketing Director M: +61 409 213 683 E: franki@hivery.com

Founded in Sydney in 2015, HIVERY uses artificial intelligence (AI) models to help retailers maximize revenue. HIVERY's solutions use technologies which originated in laboratories run by the CSIRO and its data innovation affiliate, Data61. These solutions generate AI-driven recommendations for CPG suppliers & retailers, enabling truly unprecedented hyper-local retailing, the simultaneous localization and optimization of product mix at the physical store level. Today, the company’s growing team of data scientists, engineers and designers are taking its applications to a global customer base. HIVERY has offices in Australia, Japan and the US.  hivery.com 

HIVERY was founded on the vision that Data Has A Better IdeaTM - and we’re working together with our clients to uncover its full potential.

To learn more about how we help decision makers fuel the future of business, visit gartner.com.

Media Release - HIVERY Named For Gartner 27.04.21.pdf

The Financial Times (FT), in cooperation with international data partner, Statista and its sister publication, Nikkei Asia, has released its third edition of the FT High-Growth Companies Asia-Pacific ranking.

Our team is honoured to announce that HIVERY has once again made it to this prestigious list – climbing 5 points from last year to position 77, ranking us amongst the top companies in the region.

We are pleased to be included in this latest FT ranking, which celebrates 500 companies in the Asia-Pacific region that have achieved the highest compound annual growth in revenue between 2016 and 2019. This is mostly powered by our  HIVERY Curate solution -  transforming category management with hyper optimized assortments for our global retailers and CPG companies. This also comes with the news of Gartner Research naming HIVERY Curate in their annual retail assortment optimisation industry guide. 

Maxine Kelly, FT Editor, shared that many countries in Asia-Pacific continue to struggle due to the effects of last year’s COVID-19 pandemic, along with further challenges around inequality, unemployment and gaps in social welfare.

She has noted, though, that these 500 companies are well-prepared to overcome such crises, being in a strong position to take their organisations to even greater heights.

“This gives them enough momentum or resilience to survive — or, in the case of some tech start-ups, to thrive.” 

We’re proud to embody these attributes both this year and going forward.

At HIVERY, we aim to take full advantage of our ongoing growth and blaze new trails – not just to accomplish breakthroughs for our business, but also to help our clients generate impressive returns from their retail shelf space investment through the power of AI in category management.

Using the world’s most advanced machine learning and operations research techniques, we will consistently empower global FMCGs, CPGs and retailers to make more informed decisions that will enhance customers’ shopping experiences, optimise shelf space utilisation and maximise profits.  

Hyperlocal retailing, our solution that offers simultaneous localization and optimization of product mix, space and promotion/price at the individual store level, will guarantee that data has a better idea to help you succeed. If you would like to know more about this solution and our other products, contact us here. We’d love to hear from you. 

We wish to express our gratitude to everyone who has helped us get this far and thank you our incredibly talented team of scientists, engineers and designers are all overjoyed to know that we are creating a positive impact.

HIVERY climbs to rank 77 from 82 in The Financial Times Asia-Pacific High Growth Companies of 2021 powered by its AI category management optimization solution -  HIVERY Curate

HIVERY climbs to rank 77 from 82 in The Financial Times Asia-Pacific High Growth Companies of 2021 powered by AI Category management solution -  HIVERY Curate

HIVERY climbs to rank 77 from 82 in The Financial Times Asia-Pacific High Growth top 500 Companies of 2021

駅構内などで自動販売機を運用するJR東日本ウォータービジネス（東京・品川）が、AI（人工知能）を活用して売り上げ向上、オペレーション最適化を図っている。AIの指示で品ぞろえを見直した自販機では、比較対象機と比べて最大約40％の販売増を記録。コロナ禍で移動需要が減少する中でも、好調な実績をたたき出している... learn more

日経クロストレンド:  AIの指示で売り上げ最大約40％増　駅ナカ自販機のAI革命

At HIVERY, we get a lot of questions about HIVERY Curate and how an AI-driven true store-specific category management solution can transform category and brand professionals' roles at major CPGs and retailers.  

In the below video you will find Heather Martin, Vice President of Sales at HIVERY, answering:  What do we mean by "AI"  optimized category assortment.

Watch the video below and see a live demo by Heather

At HIVERY, we get a lot of questions about HIVERY Curate and how an AI-driven true store-specific category management solution can transform category and brand professionals' roles at major CPGs and retailers.

In the below video you will find Heather Martin, Vice President of Sales at HIVERY, answering the question: What do we mean by A”  optimized category assortment?

HIVERY Curate Q&A Series: What do we mean by AI optimized category assortment?

HIVERY Curate Q&A Series -What do we mean by "AI"  optimized category assortment?

HIVERY Curate Q&A Series -  What do we mean by "AI"  optimized category assortment?

HIVERY Curate Q&A Series: What do we mean by "AI"  optimized category assortment?

What do we mean by "AI"  optimized category assortment

Category management is a highly competitive exercise in today’s face-paced retail environment, with each company seeking to increase their brands’ category market share and leadership presence through innovation and superior category strategy. 

Rarely are brands distributed according to their fair share of space at any given retailer, especially when assortment is optimized using a top-down approach that leverages averages of averages to push assortment into space available at each store. Even a small percentage of growth or loss can equate to millions of dollars. Therefore, it is equally important for all brands and Consumer Packaged Good Companies (CPGs) to protect & grow shelf space, regardless of whether they are below or beyond fair share.  

Artificial Intelligence (AI) is the ideal tool to optimize assortment from the bottom up, looking at each store individually and using this analysis to determine the right assortment for each store or cluster. This approach allows CPGs to protect and grow revenue by maximising retail space investment, all while uncovering growth opportunities for the category and improving the retailer / CPG strategic relationship.

Two-Prong Strategy: Protect & Grow category assortment 

Category management and retail sectors have always been dynamic, and every (Points of Distribution) POD is fought for in every relay. Direct to consumer brands and new innovation are fighting for the same space you are, with less on the line. To cope with the evolving competition amongst brands, HIVERY Curate helps CPGs identify the right strategy based on a predictive analysis of the most granular of data points through the two-prong “protect and grow” strategy:

Protect - Defending your category share & strategic value to your retailer

At HIVERY, we are often asked what happens if the AI recommends reducing a CPG’s space - and usually this question comes from CPGs whose brands are well distributed and at (or above) a fair share of space. The answer is simple. With store-level assortment analysis taking into account store specific cannibalization, category advisors and non-advisors alike can protect their relationship and space by:

Uncovering growth for their brand, optimizing existing space and recommending SKU rationalization of products whose demand will transfer within the brand portfolio. This newly created space allows for increasing holding power to reduce out of stocks, or swapping lower-performing products for those ‘sleeper products’ that will drive brand growth.

Quantifying the value of each business and brand strategies through rapid SKU stimulation and seeing the impact before executing. AI can, in fact, provide data driven, revenue-quantified recommendations to execute the strategies. This levels up the conversation with the retailer in ways not possible today and ensures the strategies are executable in store and predicted to drive category growth.

Identifying growth for their retailer, even within existing clusters which protects the strategic relationship and everything that comes with it.  

Once existing space is protected, brands beyond their fair share can fight for additional space through new innovation, and HIVERY Curate can predict the success of the launch while pinpointing the best stores to launch in.

Grow – Capturing more category sales and space

AI-powered algorithms are able to optimize assortment at the store level by determining the unique ‘data fingerprint’ of each store, and leveraging this to identify the assortment needs of each specific store. Even when executed at a cluster level, using this bottom up analysis to identify what to add, remove or retain uncovers new opportunities for both brands and retailers. 

Where brands are below their fair share of space and expanded distribution would grow not only your brand but also the category, HIVERY Curate’s AI optimization provides specific recommendations on where to expand points of distribution (PODs), it identifies which SKUs to expand, and quantifies the revenue impact to the retailer. And, because HIVERY Curate’s optimization is aware of the actual space on the shelf, the AI often identifies room for additional facings or SKUs just by knowing how many inches are available.

Case Study: the two-pronged approach in action

Working with a large multinational company across two categories at a single retailer, HIVERY Curate was used to identify and implement this two-pronged strategy. In one category where our CPG client had significant distribution, Curate identified growth for the category and a risk of reduced PODs to the CPG. With this information, our customer’s brand and sales teams have an opportunity to identify protective portfolio strategies, simulate their impact on the category and their revenue and use this data-driven story to propose their programs to the retailer.

In another category where private label products have significant distribution, HIVERY Curate identified an opportunity for our CPG client to grow the category by also growing their distribution - a true win/win for all parties! 

Backed by the power of machine learning and proprietary algorithms developed over 5 years, together with  an in-depth operations research method (often called applied mathematics)  within HIVERY Curate, the CPG client was able to effectively plan and distribute optimal product assortments for each retail store.

As expected, the financial benefit was significant. Across both categories, HIVERY Curate identified a $16M revenue growth opportunity for the CPG Client.

The next generation of category management solution

With the constant battle between category leaders and non-category leaders, the brands that are able to protect and grow their market share are the ones that survive and thrive. HIVERY Curate offers businesses an efficient way to do this.

As an intuitive AI-powered and user-friendly tool, it equips businesses with effective and compliant planograms that deliver the best results from physical retail space investment. 

In the end, it’s not just about earning more slices of the pie, but rather about growing the pie itself. HIVERY Curate delivers accurate, effective and executable store-specific recommendations to improve and ensure the growth of the whole category.

HIVERY is the pioneer of hyper-local retailing – combining artificial intelligence, machine learning, optimization and design to help CPGs and retailers generate an increased return on physical retail space investment.    

To learn more about me or schedule a chat, please visit my page here

Win or retain category captaincy: How AI can augment category management with a two-sided “Protect & Grow” strategy

Microsoft has officially launched the Microsoft Retail Innovation Club. Discover HIVERY and 28 other innovators from Australia and around the world new technologies that are disrupting stores, supply chains, customer and employee experiences.

From March to May 2021, you can access a series of videos showcasing what’s new from 28 of the industry’s most disruptive thinkers – and we’re very proud to be part of this club.

Available on-demand for a limited time only, secure your spot!

HIVERY makes the Microsoft Retail Innovation Club!

At HIVERY, we get a lot of questions about HIVERY Curate and how an AI-driven true store-specific category management solution can transform category and brand professionals' roles at major CPGs and retailers.

In the below video you will find David Buckley, Vice President of Retail at HIVERY, answering the question:

What are some of the new benefits unlocked by retailers or CPGs that weren't the case before HIVERY Curate?

David Buckley, Vice President of Retail at HIVERY, answers the question: What are some of the new benefits unlocked by retailers or CPG that once wasn't the case before HIVERY Curate

The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing all at store level.

HIVERY Curate Q&A: What are some of the new benefits unlocked by retailers or CPG that once wasn't the case before HIVERY Curate

The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing all at store-level.

HIVERY Curate Q&A Series: What are some of the new benefits unlocked by retailers or CPG that once wasn't the case before HIVERY Curate?

What are some of the new benefits unlocked by retailers or CPGs that weren't the case before HIVERY Curate? 

At HIVERY, we get a lot of questions about HIVERY Curate and how an AI-driven true store-specific category management solution can transform category and brand professionals' roles at major CPGs and retailers. 

How does HIVERY Curate protect data across CPGs and retailers to ensure only agreed information is shared?

HIVERY Curate Q&A: How does HIVERY Curate protect data across CPGs and retailers to ensure only agreed information is shared? 

The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing all at store-level

HIVERY Curate Q&A: How does HIVERY Curate protect data across CPGs and retailers to ensure only agreed information is shared?

HIVERY Curate Q&A Series -  The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing all at store-level.

HIVERY Curate Q&A Series: How does HIVERY Curate protect data across CPGs and retailers to ensure only agreed information is shared?

In the below video you will find Greg Jensen, Sales Director at HIVERY, answering the question:

How does HIVERY Curate help CPGs who are category advisors and those who are not?

Greg Jensen, Sales Director at HIVERY, answers the question: How does HIVERY Curate help CPG’s who are category advisors and those who are not?

The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing

HIVERY Curate Q&A: How does HIVERY Curate help CPG’s who are category advisors and those who are not?

HIVERY Curate Q&A Series -The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing all at store level.

HIVERY Curate Q&A Series -  The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing all at store level.

HIVERY Curate Q&A Series: How does HIVERY Curate help CPG’s who are category advisors and those who are not?

What has been the impact of HIVERY Curate in facilitating better CPG/retailer collaboration?

David Buckley, Vice President Of Retail at HIVERY, answers the question:  What's been the impact of HIVERY Curate in facilitating that better CPG/Retailer collaboration? 

The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing.

HIVERY Curate Q&A: What's been the impact of HIVERY Curate in facilitating that better CPG/Retailer collaboration?

HIVERY Curate Q&A Series: What's been the impact of HIVERY Curate in facilitating that better CPG/Retailer collaboration?

When you optimize for store-specific, how do you balance localization against costs such as labor?  

The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing.

HIVERY Curate Q&A: When you optimize for store-specific, how are you balancing localization against the costs such as labor?

HIVERY Curate Q&A Series - The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing

HIVERY Curate Q&A Series -  The world’s first true AI-driven hyper local category management optimization solution delivering rapid category simulation, space-assortment aware and planogram drawing

HIVERY Curate Q&A Series: When you optimize for store-specific, how are you balancing localization against the costs such as labor?  

HIVERY is a multi-award winner pioneer of hyper-local retailing, combining artificial intelligence (AI), operations research, and human-centred design to help consumer packaged goods (CPG) manufacturers and retailers generate a return on physical space investments.

NSW Treasury’s Global Markets team wanted to capture the story of what HIVERY is doing in international markets, especially in Japan and our participation in the NSW Going Global Program and Japan Innovation Leaders Summit 2021

HIVERY is only one of two companies in all of NSW to be selected to be part of this exciting program. What a great honour, and to celebrate and share our story, the team at NSW Treasury’s Global Markets have produced this video.

HIVERY is a multi-award winner pioneer of hyper-local retailing,  combining artificial intelligence (AI), operations research, and human-  centred design to help consumer packaged goods (CPG) manufacturers  and retailers generate a return on physical space investments. HIVERY  is transforming category management and retail trade promotion with  innovative algorithms sourced from Australia’s national science agency, CSIRO’s Data61. HIVERY is venture-backed and headquartered in Sydney, Australia, with offices in the USA and Japan.

HIVERY was founded on the vision that Data Has A Better IdeaTM and  we’re working together with our clients to uncover its full potential.

NSW Treasury - HIVERY - Going Global Starts With Being Specific, Store-Specific!

NSW Treasury & HIVERY are going global

Can previous consumers and their star rating/feedback really influence our buying decision? Find out the truth.

What you will learn from this podcast:
• Decision science in retail. Felipe investigates how consumers make choices in online marketplaces (i.e Amazon)and the key features (e.g. product display, order, and ranking).

• The effects of online social influencer signals and how previous buyers, their star rating and comments influence buying decisions.

• Demand predictions and how it impacts decisions on what to put in stores (regardless online or offline).

• This opens up the question: can social influencers (i.e rating and feedback) be a more effective demand signal (hence, demand prediction tool) than traditional demand signals like seasonality? How can brand managers and category management professionals leverage this model to impact the likelihood of success of new product releases? What strategies can product brand managers and category management professionals leverage when their new products have no social proofing yet? Should product brands and marketers invest more of their funds into contacting external social influencers and get them to review a new product, seed ratings, and influence future online shoppers?

• You can download and read Felipe's research "Modelling consumer behaviour in the presence of network effects"  here: https://openresearch-repository.anu.edu.au/bitstream/1885/200952/1/thesis_submission_Felipe_Maldonado.pdf

Felipe Maldonado is a Postdoctoral Researcher in the areas of Artificial Intelligence, Game Theory, Applied Mathematics, and Market Design. In his latest research, he covers the scientific approach to determine how social influence can impact demand and demand predictions. Felipe also provides his insight on how social influence can impact new product innovation and launch a new product into the market.


In September 2019 Felipe graduated with his doctorate degree from the School of Computer Science at ANU. During his 4 years there, Felipe has worked in the Computational Media Lab and was also part of CSIRO/Data61. Since October 2019, Felipe has been 
working as a Postdoctoral Researcher at the Technical University of Munich in the Decision Sciences & Systems at the Department of Informatics.

Felipe Maldonado is a Postdoctoral Researcher in the areas of Artificial Intelligence, Game Theory, Applied Mathematics, and Market Design. In his latest research, he covers the scientific approach to determine how social influence can impact demand and demand predictions. Felipe also provides his insight on how social influence can impact new product innovation and launch a new product into the market.

In September 2019 Felipe graduated with his doctorate degree from the School of Computer Science at ANU. During his 4 years there, Felipe has worked in the Computational Media Lab and was also part of CSIRO/Data61. Since October 2019, Felipe has been working as a Postdoctoral Researcher at the Technical University of Munich in the Decision Sciences & Systems at the Department of Informatics.

Dr. Felipe Maldonado on the truth behind consumer rating influencing our buying decisions

Can previous consumers and their star rating/feedback really influence our buying decision? Find out the truth.

Felipe Maldonado is a Postdoctoral Researcher in the areas of Artificial Intelligence, Game Theory, Applied Mathematics, and Market Design. In his latest research, he covers the scientific approach to determine how social influence can impact demand and demand predictions. Felipe also provides his insight on how social influence can impact new product innovation and launch a new product into the market. 

Meet Dr. Felipe MaIdonado:
In September 2019 Felipe graduated with his doctorate degree from the School of Computer Science at ANU. During his 4 years there, Felipe has worked in the Computational Media Lab and was also part of CSIRO/Data61. Since October 2019, Felipe has been 
working as a Postdoctoral Researcher at the Technical University of Munich in the Decision Sciences & Systems at the Department of Informatics.

What you will learn from this podcast:
• Decision science in retail. Felipe investigates how consumers make choices in online marketplaces (i.e Amazon)and the key features (e.g. product display, order, and ranking).  

• The effects of online social influencer signals and how previous buyers, their star rating and comments influence buying decisions.

• Demand predictions and how it impacts decisions on what to put in stores (regardless online or offline).  

• This opens up the question: can social influencers (i.e rating and feedback) be a more effective demand signal (hence, demand prediction tool) than traditional demand signals like seasonality? How can brand managers and category management professionals leverage this model to impact the likelihood of success of new product releases? What strategies can product brand managers and category management professionals leverage when their new products have no social proofing yet? Should product brands and marketers invest more of their funds into contacting external social influencers and get them to review a new product, seed ratings, and influence future online shoppers?

• You can download and read Felipe's research "Modelling consumer behaviour in the presence of network effects" here: https://openresearch-repository.anu.edu.au/bitstream/1885/200952/1/thesis_submission_Felipe_Maldonado.pdf

Dr. Felipe Maldonado on the truth behind consumer rating influencing our buying decisions by Retail Mavericks

What you will learn from this podcast:
• What next-generation shoppers are looking for on the supermarket and grocery store shelves. Dan advises on how category management should prepare for this change.

• How can category management professionals get better at predicting in a world of constant change? Dan sheds light on the shopper behavior during the Super Bowl. What happens if there are no games or the game happens at a different scheduled date and time? What alternative product categories will be impacted and need to be considered? How does this impact no social gathering and tailgating at the football game? What other "stay-at-home" products will be demanded instead? How does it impact food spoilage? Dan answers all of these questions.

• How companies prepare for key events, competition moves, and retail reaction. Hint: "war games" scenarios. Is there a way to see the impact of each scenario? As a side note, HIVERY Curate can allow users to easy model these scenarios in the AI engine to present the impact at category, SKU or brand levels or by distribution such as by cluster store or store-specific levels.

• Dan shares useful tactics and insights on how CPG manufactures and retailers can enhance shopper expectations and maintain retailer relationships. Dan talks through a fascinating story about how intelligence on shoppers can transform your sales. Make sure you listen to the "Target store and sales of multi-serve meals" story.

• How CPGs and retailers can address the "The Paradox of Choice" and why sometimes less is actually more.

• How data science can help with better predictions by looking at the relationship with seasonal events such as hurricane season and impact on category assortment.

• How forecasting is currently done. Generally, there are several different business groups involved. It all starts with the account team who are closest to the customer. They factor in key events such as promotions and allow other internal teams (i.e. demand planning and supply chain) to add their view. This can be a very intense and time consuming process but generally works well until an event that has not been planned occurs. Responding to change can be an extreme challenge. As a side note again, HIVERY Curate helps. Rapid scenario planning can be conducted to quickly inform new strategy and articulate it to all stakeholder groups.

• Dan finally covers what he believes the future of category management is. With the increase in online purchasing, Dan talks to us about the need to have an optimized omnichannel strategy. While shopper convenience (i.e. delivery, in-store pick-up, curbside pick-up) and choice are good, it leads to additional costs. Dan shares a few real examples (Walmart, Kroger) and discusses best practices.

Dan is a CPG Industry professional with Experience in Headquarter Support, Product Development, Category/Brand Strategies, Retailer Dedicated Sales Support, Account Management, Team Development, and Coaching. In his 10+ years with Nestle USA, he has worked closely with almost every major grocer and mass retailer in the US including Walmart, Target, Albertson’s/Safeway, Publix, HEB, and Meijer.

Dan’s passion lies in his leading and developing the future leaders in the CPG industry on how to think differently and always keep one eye focused on what the next big trend or consumer disruption in the industry will be. He also strives to consistently help retailers elevate their thinking above the day to day category management, and take action on national trends within the confines of their retail brand, and strategy. As a father of 2, he enjoys spending time with his wife and kids, is a self-proclaimed foodie, sports junkie, and travel aficionado.

Dan is a CPG Industry professional with Experience in Headquarter Support, Product Development, Category/Brand Strategies, Retailer Dedicated Sales Support, Account Management, Team Development, and Coaching. In his 10+ years with Nestle USA, he has worked closely with almost every major grocer and mass retailer in the US including Walmart, Target, Albertson’s/Safeway, Publix, HEB, and Meijer.

Dan’s passion lies in his leading and developing the future leaders in the CPG industry on how to think differently and always keep one eye focused on what the next big trend or consumer disruption in the industry will be. He also strives to consistently help retailers elevate their thinking above the day to day category management, and take action on national trends within the confines of their retail brand, and strategy. As a father of 2, he enjoys spending time with his wife and kids, is a self-proclaimed foodie, sports junkie, and travel aficionado.

Dan Sturman on category management in a world of constant change

Dan is a CPG Industry professional with Experience in Headquarter Support, Product Development, Category/Brand Strategies, Retailer Dedicated Sales Support, Account Management, Team Development, and Coaching. In his 10+ years with Nestle USA, he has worked closely with almost every major grocer and mass retailer in the US including Walmart, Target, Albertson’s/Safeway, Publix, HEB, and Meijer.
 
Dan’s passion lies in his leading and developing the future leaders in the CPG industry on how to think differently and always keep one eye focused on what the next big trend or consumer disruption in the industry will be. He also strives to consistently help retailers elevate their thinking above the day to day category management, and take action on national trends within the confines of their retail brand, and strategy. As a father of 2, he enjoys spending time with his wife and kids, is a self-proclaimed foodie, sports junkie, and travel aficionado.

What you will learn from this podcast:
• What next-generation shoppers are looking for on the supermarket and grocery store shelves. Dan advises on how category management should prepare for this change.

• How can category management professionals get better at predicting in a world of constant change? Dan sheds light on the shopper behavior during the Super Bowl. What happens if there are no games or the game happens at a different scheduled date and time? What alternative product categories will be impacted and need to be considered? How does this impact no social gathering and tailgating at the football game? What other "stay-at-home" products will be demanded instead? How does it impact food spoilage? Dan answers all of these questions.

• How companies prepare for key events, competition moves, and retail reaction. Hint: "war games" scenarios. Is there a way to see the impact of each scenario? As a side note, HIVERY Curate can allow users to easy model these scenarios in the AI engine to present the impact at category, SKU or brand levels or by distribution such as by cluster store or store-specific levels.

• Dan shares useful tactics and insights on how CPG manufactures and retailers can enhance shopper expectations and maintain retailer relationships. Dan talks through a fascinating story about how intelligence on shoppers can transform your sales. Make sure you listen to the "Target store and sales of multi-serve meals" story.

• How CPGs and retailers can address the "The Paradox of Choice" and why sometimes less is actually more.

• How data science can help with better predictions by looking at the relationship with seasonal events such as hurricane season and impact on category assortment. 

• How forecasting is currently done. Generally, there are several different business groups involved. It all starts with the account team who are closest to the customer. They factor in key events such as promotions and allow other internal teams (i.e. demand planning and supply chain) to add their view. This can be a very intense and time consuming process but generally works well until an event that has not been planned occurs. Responding to change can be an extreme challenge. As a side note again, HIVERY Curate helps. Rapid scenario planning can be conducted to quickly inform new strategy and articulate it to all stakeholder groups.

• Dan finally covers what he believes the future of category management is. With the increase in online purchasing, Dan talks to us about the need to have an optimized omnichannel strategy. While shopper convenience (i.e. delivery, in-store pick-up, curbside pick-up) and choice are good, it leads to additional costs. Dan shares a few real examples (Walmart, Kroger) and discusses best practices.

Dan Sturman on category management in a world of constant change by Retail Mavericks

What you will learn from this podcast:
• When optimization or applied mathematics was first used to solve real-world problems. We go back to 1947 and George B. Dantzig, when not only the first computer program was written but also new applied mathematics methods were invented, now called linear programming.

• The fascinating world of Applied Mathematics. Mark breaks down everything from Operations Research, Linear Programming (using 1 and 0.5 as inputs), Complete Methods (solving problems optimally), Heuristic Methods (solving problems faster although not always optimally), and Genetic Algorithms (inspired by nature's way of optimizing) to relatively modern methods like Integer Linear Programming (using 0, 1 or 2 as inputs). These methods have previously advanced the military to optimize the distribution of weaponry. Now, these methods are used by commercial industries and have found their way into category management to ensure the right products are in the right, specific shelf space at the right, specific store.

• Mark goes deep into explaining his fascinating research: "A model-based genetic algorithm framework for constrained optimisation problems"; and his new framework that solves real-world problems differently and more efficiently.

• Why HIVERY Curate (formally HIVERY Propel) is different to any other planogram category management optimization solution out there. Marks explains how he has applied and combined optimization techniques (i.e. how much of product X to put on that specific shelf in that specific store) with machine learning methods (what product to put (X or Y or Z) on that specific shelf in that specific store) along with the secret ingredient; the constraints that make HIVERY Curate category recommendations realistic and implementable at a store-level.

• If you are interested in learning about how our world can be run more efficiently, love maths and solving real problems. This is a must-listen.

Resources:
www.linkedin.com/in/mark-lawrenson/
dl.acm.org/doi/10.1145/3067695.3076041
https://news.stanford.edu/news/2005/may25/dantzigobit-052505.html

Mark Lawrenson has graduated with honours in mathematical applications and computations from The Australian National University and was previously a researcher at CSIRO/Data61, the world's leading Australian research and data science agency. At HIVERY Mark is the product lead of HIVERY Curate - the world’s first truly hyper-local category management solution. Mark has several patents under his name and has published many research papers, namely "A model-based genetic algorithm framework for constrained optimization problems" where he presents a new hybrid optimization framework that can be used to solve constrained optimization problems differently.

In this podcast, Mark explains the science of optimization methods; the science of finding the best alternative from many alternatives. From wars, supply chain distribution to bakers and their bread to real category optimization.

Mark Lawrenson on the science of optimization methods and solving real-world problems more optimally

In this podcast, Mark explains the science of optimization methods; the science of finding the best alternative from many alternatives. From wars, supply chain distribution to bakers and their bread to real category optimization. 

Mark Lawrenson has graduated with honours in mathematical applications and computations from The Australian National University and was previously a researcher at CSIRO/Data61, the world's leading Australian research and data science agency. At HIVERY Mark is the product lead of HIVERY Curate - the world’s first truly hyper-local category management solution. Mark has several patents under his name and has published many research papers, namely "A model-based genetic algorithm framework for constrained optimization problems" where he presents a new hybrid optimization framework that can be used to solve constrained optimization problems differently.  

What you will learn from this podcast:
• When optimization or applied mathematics was first used to solve real-world problems. We go back to 1947 and George B. Dantzig, when not only the first computer program was written but also new applied mathematics methods were invented, now called linear programming.

• The fascinating world of Applied Mathematics. Mark breaks down everything from Operations Research, Linear Programming (using 1 and 0.5 as inputs), Complete Methods (solving problems optimally), Heuristic Methods (solving problems faster although not always optimally), and Genetic Algorithms (inspired by nature's way of optimizing) to relatively modern methods like Integer Linear Programming (using 0, 1 or 2 as inputs). These methods have previously advanced the military to optimize the distribution of weaponry. Now, these methods are used by commercial industries and have found their way into category management to ensure the right products are in the right, specific shelf space at the right, specific store.

• Mark goes deep into explaining his fascinating research: "A model-based genetic algorithm framework for constrained optimisation problems"; and his new framework that solves real-world problems differently and more efficiently.

• Why HIVERY Curate (formally HIVERY Propel) is different to any other planogram category management optimization solution out there. Marks explains how he has applied and combined optimization techniques (i.e. how much of product X to put on that specific shelf in that specific store) with machine learning methods (what product to put (X or Y or Z) on that specific shelf in that specific store) along with the secret ingredient; the constraints that make HIVERY Curate category recommendations realistic and implementable at a store-level.

• If you are interested in learning about how our world can be run more efficiently, love maths and solving real problems. This is a must-listen.

Resources:
https://www.linkedin.com/in/mark-lawrenson/
https://dl.acm.org/doi/10.1145/3067695.3076041
https://news.stanford.edu/news/2005/may25/dantzigobit-052505.html

Mark Lawrenson on the science of optimization methods: finding the best alternative from many by Retail Mavericks

Mark Lawrenson on the science of retail optimization methods and solving real-world problems more optimally

実証実験では最大50％※以上の売上増加も！全体では5.27％※の増加を記録！！
飲料補充の効率化で、業界の働き方改革も実現！
※近似環境でAIシステムを使用しなかった自販機との同一期間比較 ... learn more

豪州AIスタートアップHIVERYがJR東日本ウォータービジネス社と事業展開〜「HIVERY Enhance」をエキナカ自販機に本格導入〜

The two companies have been collaborating since 2017, leveraging Hivery's AI technology to optimize product assortment and column space for individual vending machines in Japan. Validated results from proof of concepts increased sales by 5.27％overall, up to a maximum of more than 50%, as well as reducing replenishment trips and improving operational productivity... learn more

Hivery, an Australia based artificial intelligence provider, will roll out its AI driven vending machine management solution to 6,000 machines across East Japan Railway's train stations, according to a press release.

Retail AI pioneer, HIVERY (headquartered in Sydney, Australia) and JR East Water Business (headquartered in Tokyo, Japan), a subsidiary of East Japan Railway Company, have agreed to rollout HIVERY Enhance - an AI-driven vending machine optimization solution, to 6,000 vending machines across East Japan Railway’s train stations.

Validated results from numerous PoCs (proof of concepts) increased sales by 5.27％ [1] overall, up to a maximum of over 50%, as well as simultaneously reducing replenishment trips and improving operational productivity.  

HIVERY and JR East Water Business have been collaborating since 2017, leveraging HIVERY’s latest AI technology to optimize product assortment and column space for individual vending machines in Japan. During the winter of 2019, the results of HIVERY Enhance showed an overall increase in sales volume by 5.27%, up to a maximum of over 50%. Furthermore, given labor storages due to a declining population, there has been growing pressure to improve operational productivity within the Japanese vending industry. HIVERY Enhance enabled JR East Water Business to streamline operations and reduce replenishment trips by automatically recommending the optimal product assortment and quantity for their vending machines. Based on this success, JR East Water Business has agreed to rollout HIVERY Enhance across 6,000 vending machines on their train stations for East Japan Railway - a first in Japan.

Until now, product assortment selection had been decided by individual operators (drivers) who are responsible for replenishing the vending machines at their designated locations. Given those decisions have been based on the operator’s accumulated experience and intuition over many years, it has been an ongoing challenge to transfer that knowledge to new operators and maintain a level of quality. HIVERY Enhance leverages the power of AI and JR East Water Business’ point of sales (POS) data, to automatically determine which products need to be stocked in which vending machine, as well as the optimal timing to swap products for individual machines. This enables any operator to efficiently make the right product assortment choices that will lead to a profitable outcome. 

Select products that are likely to sell well – By analyzing the vast amount of sales data from the full fleet of vending machines, it identifies patterns in the sales data and identifies products that are likely to sell well in any particular location.

Optimize product assortment - By understanding the demand for individual products and the effects of cannibalization of demand between products in each location, it can determine which products should be inserted and which should be taken out, to lead to the optimal outcome.

Reduce replenishment trips - From the demand forecasts of products in any location, it can calculate the number of days before each product is likely to go out of stock and recommend the optimal quantity and column allocation to maximize the time between replenishment trips, thereby reducing labor costs.

Optimizing a  group of vending machines - Rather than only focusing on individual vending machines, it can also assess a group of banked vending machines in the same area at the same time, and optimize the products for the entire area as if it were one large vending machine.

By ingesting vast arrays of data and incorporating intricate operational rules as well as physical and business constraints into its algorithm, HIVERY Enhance can instantaneously provide executable recommendations for the optimal product assortment and column configurations for both an individual as well as a group of vending machines. Furthermore, by leveraging weather data, it can respond to changes in seasonal patterns and suggest the optimal time to insert hot and cold products, while taking into account the effects of cannibalization for the product mix at each location, thereby providing the optimal product assortment at any given time.

In March 2018, HIVERY invited JR East Water Business’s Vending Division team to its Sydney headquarters to meet with one of HIVERY's first customers, Coca-Cola Amatil, to exchange ideas and share their experience and best practice for implementing cutting edge technology for their respective vending businesses.

Hyperlocal retailing pioneer HIVERY (headquartered in Sydney, Australia) and JR East Water Business (headquartered in Tokyo, Japan), a subsidiary of East Japan Railway Company, have agreed to rollout HIVERY Enhance, an AI driven vending machine optimisation solution, to 6,000 vending machines across East Japan Railway’s train stations.

Australian AI startup HIVERY partners with JR East Water Business to optimise vending machines in Japan

Giant Eagle, AI is changing category management

Determine which Giant Eagle stores should carry what specific category SKUs. Drive new incremental profits at store-level all in minutes, not months

Industry research and insights

Forrester Research: AI In retail needs to start at the backend with smart automation

New capabilities required to remain indispensable to your shopper

Four (4) shifts in supermarket space that are going to change retail forever

HIVERY Curate for Giant Eagle

Novel approach to transferable demand

Me, Giant Eagle & AI - Lets chat

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