Borrowing ideas from deep learning methods, 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.

Groceryshop Spring Meetup Whitepaper Download

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AI Models Transferable Demand With Unparalleled Accuracy 

If you get the fundamentals right, everything else often falls into place. And in retail analytics, there are a number of fundamentals to grasp.

Check out our latest blogs on AI, retail, big data, shopper insights, category management, trade promotion optimization and more

Relax and enjoy our diverse range of podcast on our Retail Maverick channel

Other resources you might find interesting...

Grocery Shops - Transferable Demand White Paper Download Request

Transferable Demand White Paper Download Request

Coresight Research Retail-Tech Landscape comprises selected startups globally that can help retailers improve their digital offerings and the overall customer experience.

To view more of Coresight's Retail-Tech Landscapes spotlighting innovators that are disrupting the retail industry, click here.

Retail-Tech Landscape: Retailers’ Technology Shopping List for Holiday 2021

Five Key Trends in Retail Technology for Holiday 2021

Retail-Tech Landscape: Retailers’ Technology Shopping List for Holiday 2021—Infographic

Retail-Tech Landscape: Retailers’ Technology Shopping List for Holiday 2021, by Category

Download the full Coresight Research report titled: The Age of Precision Category Management: Hyper-Localized Assortment Optimization Using Advanced Technologies

Summary-Coresight-Research-x-HIVERY-The-Age-of-Precision-Category-Management—Technology-Driven-Assortment-Optimization-Jun-17-2021.pdf

Watch full webinar with Deborah Weinswig, CEO & Founder of Coresight Research,and HIVERY’s VP, Client Services, NA, Steve Weir, and Director of Customer Success, Zach Simpson, as they discuss how retailers and CPG companies can use advanced technologies in machine learning (ML) and data science (DS) to simulate merchandising strategies and find new incremental value. You can also download this webinar's key takeout  summary.

Download Coresight Research Retail-Tech Landscape comprises selected startups globally that can help retailers improve their digital offerings and the overall customer experience.

Coresight Research Retail-Tech Landscape Report

On May 12, 2021, Deborah Weinswig, CEO and Founder of Coresight Research, hosted an online event in conjunction with HIVERY, provider of an artificial intelligence (AI) and data science (DS)-powered solution that harnesses store-level data for category management optimization, enabling precision in category management and localized assortment.

Learn how HIVERY is pioneering hyper-local retailing, and offers simulation & optimization solutions to a growing number of retail and CPG clients in North America. 

In this free report, Coresight presents three key insights from the event, which explored the age of precision category management.  

The full report is available for free and can be accessed by registering details here.

Click here to watch the full on-demand webinar or download the summary.

Download Our Free Webinar Summary No registeration Required. Coresight Research x HIVERY: The Age of Precision Category Management and The Power of Retail Simulation & Optimization

Summary: Coresight Research x HIVERY: The Age of Precision Category Management and The Power of Retail Simulation & Optimization

There’s an old adage: You get what you get, and you don’t get upset. Clearly, that doesn’t apply to retail. For some time now, the axiom has been customers want what they want, when they want it. And COVID-19 didn’t seem to change that. Apparel shoppers want choices, and they want the stores and clothes to reflect their local tastes and demands.

Coresight Research says the pandemic “accelerated consumer disinterest in homogeneous physical retail experiences.” Instead, shoppers are seeking experiences that are local, distinctive and diverse. The firm advises retailers consider localizing in-store experiences and product offerings. Coresight adds that mall owners can support its tenants with localized center experiences. They good at adding datasets but lack the ability to model based on goals and constraints - this is HUGHE difference....Read More

Meeting Shopper Demand with Localized Assortment Optimization  

In this podcast you will learn:
• What Operations Research and Optimisation is about and how most of the models used today assume one thing: consumers are rational!

• How can statistics explain consumer choice? Dr Berbeglia is working on new models to help predict what consumers will choose given certain events or triggers. This research has applications for policy marketers, category management and shopper insights professionals.

• Does social influence impact consumer choice? Dr Berbeglia illustrates, for example, how popularity of media can influence consumer rationality and hence choice.

• What new consumer rationality experiments are being performed by Dr Berbeglia in his labs. One interest is "the compromise effect". The effort that dictates that a consumer will choose a middle option over a given set of choice alternatives as it's easier to justify that choice, it reduces cognitive dissonance and loss aversion.

• Another phenomenon Dr Berbeglia is exploring is the "the decoy effect", the effort going into consumer choice when the third option is presented against existing two options.

• Dr Berbeglia talks about applications and effects of these models from choice of COVID19 vaccine to organ donation to retail and assortment, category and merchandising planning.

• Hear what Dr Berbeglia thinks about how these consumer choice models will be used in machine learning and AI models in the future.

Interesting further reading and watching:

• Compromise effect and consideration set size in consumer decision-making, Jaewon Yoo, Hyunsik Park & Wonjoon Kim 

• The decoy effect: how you are influenced to choose without really knowing it, Gary Mortimer, Associate Professor in Marketing and Consumer Behaviour, Queensland University of Technology

• Dr Dan Ariely classic experiment Pricing the Economist 

Dr Berbeglia specialises in Operations Research, Game Theory, Transport Optimisation, Revenue Management, Pricing Optimisation, Impact of Social Influence In Markets. Gerardo’s research has been published in leading journals and conference proceedings, including Transportation Science, INFORMS Journal on Computing, European Journal of Operational Research, Operations Research Retters, ACM conference on Economics and Computation (EC), Conference on Web and Internet Economics (WINE) and the International Joint Conference on Artificial Intelligence. His recent research focuses on revenue management and quantitative models that account for social influence in online markets (such as iTunes or Google Play). Gerardo teaches Operations, Optimisation and Decision Making, and Supply Chain Analytics on the MBA programs and Master of Business Analytics program.

Are consumers rational really? How does this impact shopper insights, category management, marketing and future AI models? Dr Gerardo Berbeglia, Associate Professor of Operations, shares his views and predictions

Are consumers rational really? How does this impact shopper insights, category management, marketing and future AI models? In this podcast, Dr Gerardo Berbeglia, Associate Professor of Operations, shares his views and predictions.

Meet Dr Gerardo Berbeglia:

Dr Berbeglia specialises in Operations Research, Game Theory, Transport Optimisation, Revenue Management, Pricing Optimisation, Impact of Social Influence In Markets. Gerardo’s research has been published in leading journals and conference proceedings, including Transportation Science, INFORMS Journal on Computing, European Journal of Operational Research, Operations Research Retters, ACM conference on Economics and Computation (EC), Conference on Web and Internet Economics (WINE) and the International Joint Conference on Artificial Intelligence. His recent research focuses on revenue management and quantitative models that account for social influence in online markets (such as iTunes or Google Play). Gerardo teaches Operations, Optimisation and Decision Making, and Supply Chain Analytics on the MBA programs and Master of Business Analytics program.

In this podcast you will learn:
• What Operations Research and Optimisation is about and how most of the models used today assume one thing: consumers are rational!

• How can statistics explain consumer choice? Dr Berbeglia is working on new models to help predict what consumers will choose given certain events or triggers. This research has applications for policy marketers, category management and shopper insights professionals.

• Does social influence impact consumer choice? Dr Berbeglia illustrates, for example, how popularity of media can influence consumer rationality and hence choice.

• What new consumer rationality experiments are being performed by Dr Berbeglia in his labs. One interest is "the compromise effect". The effort that  dictates that a consumer will choose a middle option over a given set of choice alternatives as it's easier to justify that choice, it reduces cognitive dissonance and loss aversion.

• Another phenomenon Dr Berbeglia is exploring is the "the decoy effect", the effort going into consumer choice when the third option is presented against existing two options.

• Dr Berbeglia talks about applications and effects of these models from choice of COVID19 vaccine to organ donation to retail and assortment, category and merchandising planning.

• Hear what Dr Berbeglia thinks about how these consumer choice models will be used in machine learning and AI models in the future.

Interesting further reading and watching:

• Compromise effect and consideration set size in consumer decision-making, Jaewon Yoo, Hyunsik Park & Wonjoon Kim https://www.tandfonline.com/doi/abs/10.1080/13504851.2017.1340567

• The decoy effect: how you are influenced to choose without really knowing it, Gary Mortimer, Associate Professor in Marketing and Consumer Behaviour, Queensland University of Technology
https://theconversation.com/the-decoy-effect-how-you-are-influenced-to-choose-without-really-knowing-it-111259

• Dr Dan Ariely classic experiment Pricing the Economist https://www.youtube.com/watch?v=xOhb4LwAaJk

Dr Gerardo Berbeglia on consumer irrationality impact on category management and future AI models by Retail Mavericks

Not one, but 10: that’s the number of venture debt deals now completed by Dr Michelle Deaker’s OneVentures first debt fund, which has now put half of its $80 million in capital to work...Read more.

HIVERY scores debt from OneVentures in 10th credit deal

• 2:00 - 7:02: What current challenges are faced by the category management discipline. Key insight is how time consuming and extremely labour intensive the process is as well as variability from team to team and time to time.

• Why the industry has limited to clusters planograms generation and how this generates an average of averages approach.

https://soundcloud.com/retail-mavericks/jeff-ireland#t=2:00

• 7:03 - 10:15: How artificial intelligence/machine learning techniques have been solving for these category management challenges: speed in delivery, speed in category strategy simulation, running unlimited tests and what-if scenarios, and optimising for them.

https://soundcloud.com/retail-mavericks/jeff-ireland#t=7:03

• 10:16 - 14:54: The shifts in category management: from clusters based on averages to clusters based on store-level analysis and insights.

• What "space-assortment aware" means and how it is applied at HIVERY.

https://soundcloud.com/retail-mavericks/jeff-ireland#t=10:15

• 16:12 - 22:25: What the most common constraints or business rules are used by retailers or CPGs before building planograms. For instance, shopper safety and global deletes or additions, forcing in new products or minimising assortment churn.

https://soundcloud.com/retail-mavericks/jeff-ireland#t=16:11

• 22:25 - 24:35: How a machine learning model is used to challenge these constraints or business rules by running different and rapid scenarios. For example, if you removed a particular SKU or brand, it would present the outcome of those scenarios.

https://soundcloud.com/retail-mavericks/jeff-ireland#t=22:25

• 24:36 - 29:57: What the benefits of store-level analysis are for any cluster dimension or count you use.

With 18 years in category management, Jeff Ireland is an Analytic Consultant at HIVERY. Before HIVERY Jeff was the Senior Manager of the Category Strategy and Analytics Team at The Coca-Cola Company focusing on the creation of revolutionary AI products deployed at Walmart. This was HIVERY Curate. So, Jeff decided to leave Coke to join HIVERY to continue to bring this revolutionary solution to retailers and CPGs.

During Coke, Jeff was the Category Advisor to Walmart in the sports drinks category where he focused on helping provide effective store level space recommendations for Walmart. Jeff also worked at Retail Solutions Inc. as a Senior Product Manager and Senior Analytical Consultant as well as at Newell Brands as a Category Advisor.

With 18 years in category management, Jeff Ireland is an Analytic Consultant at HIVERY. Before HIVERY Jeff was the Senior Manager of the Category Strategy and Analytics Team at The Coca-Cola Company focusing on the creation of revolutionary AI products deployed at Walmart. This was HIVERY Curate. So, Jeff decided to leave Coke to join HIVERY to continue to bring this revolutionary solution to retailers and CPGs.

During Coke, Jeff was the Category Advisor to Walmart in the sports drinks category where he focused on helping provide effective store level space recommendations for Walmart. Jeff also worked at Retail Solutions Inc. as a Senior Product Manager and Senior Analytical Consultant as well as at Newell Brands as a Category Advisor.

Based in Bentonville, Arkansas, Jeff Ireland ex Coke, Newell Brands and IRI talks about the challenges and future of category management analytics

Based in Bentonville, Arkansas, Jeff Ireland ex Coke, Newell Brands and IRI talks about the challenges and future of category management analytics.

With 18 years in category management, Jeff Ireland is an Analytic Consultant at HIVERY. Before HIVERY Jeff was the Senior Manager of the Category Strategy and Analytics Team at The Coca-Cola Company focusing on the creation of revolutionary AI products deployed at Walmart. This was HIVERY Curate. So, Jeff decided to leave Coke to join HIVERY to continue to bring this revolutionary solution to retailers and CPGs. 

During Coke, Jeff was the Category Advisor to Walmart in the sports drinks category where he focused on helping provide effective store level space recommendations for Walmart. Jeff also worked at Retail Solutions Inc. as a Senior Product Manager and Senior Analytical Consultant as well as at Newell Brands as a Category Advisor.

In this podcast you will learn:
• 2:00 - 7:02: What current challenges are faced by the category management discipline. Key insight is how time consuming and extremely labour intensive the process is as well as variability from team to team and time to time.

• Why the industry has limited to clusters planograms generation and how this generates an average of averages approach.
https://soundcloud.com/retail-mavericks/jeff-ireland#t=2:00

• 7:03 - 10:15: How artificial intelligence/machine learning techniques have been solving for these category management challenges: speed in delivery, speed in category strategy simulation, running unlimited tests and what-if scenarios, and optimising for them.
https://soundcloud.com/retail-mavericks/jeff-ireland#t=7:03

• 10:16 - 14:54: The shifts in category management: from clusters based on averages to clusters based on store-level analysis and insights.

• What "space-assortment aware" means and how it is applied at HIVERY.
https://soundcloud.com/retail-mavericks/jeff-ireland#t=10:15

• 16:12 - 22:25: What the most common constraints or business rules are used by retailers or CPGs before building planograms. For instance, shopper safety and global deletes or additions, forcing in new products or minimising assortment churn.
https://soundcloud.com/retail-mavericks/jeff-ireland#t=16:11

• 22:25 - 24:35: How a machine learning model is used to challenge these constraints or business rules by running different and rapid scenarios. For example, if you removed a particular SKU or brand, it would present the outcome of those scenarios.
https://soundcloud.com/retail-mavericks/jeff-ireland#t=22:25

• 24:36 - 29:57: What the benefits of store-level analysis are for any cluster dimension or count you use.
https://soundcloud.com/retail-mavericks/jeff-ireland#t=22:25

Jeff Ireland on the challenges and future of category management analytics by Retail Mavericks

Australia is a vibrant country with exciting energy, and the local startup scene is booming. Australia’s economy is strong. It’s the world’s 13th-largest economy with the ninth-highest income.

Sydney is the largest of the Australian startup hubs with 35% of the nation's startups, followed by Melbourne. The area is filled with incubators and accelerators with one spreading 11 floors and 16,722 square meters. Best of all, it's right in the heart of the city.

HIVERY is mentioned in Valuer.ai's article The 50 Best Startup Cities in 2021!

The age of precision category management is upon us. Effective assortment and space localization can be a very challenging task for CPG companies and retailers, but if done right with the right methods, the incremental value generated is significant. Whether they are using a cluster approach or not, the ability for retailers and CPG companies to leverage store-level data in new ways opens up new opportunities to have the right product assortment to meet shopper demand across any store.

You can watch the full recorded session with Deborah Weinswig, CEO & Founder of Coresight Research, with HIVERY’s VP, Client Services, NA, Steve Weir, and Director of Customer Success, Zach Simpson, in which they discussed the signiﬁcant incremental value to retailers and CPG companies in optimizing assortment at the store level using advanced technologies in machine learning (ML) and data science (DS). 

In this on-demand mini-webinar, we cut to the question: 

On-demand mini-webinar: How machine learning and applied mathematics is used to discovery potential items to add to specific stores

The age of precision category management is upon us. Effective assortment and space localization can be a very challenging task for CPG companies and retailers, but if done right with the right methods, the incremental value generated is significant. Whether they are using a cluster approach or not, the ability for retailers and CPG companies to leverage store-level data in new ways opens up new opportunities to have the right product assortment to meet shopper demand across any store.

Recorded on Wednesday, May 12, Deborah Weinswig, CEO & Founder of Coresight Research, was joined by HIVERY’s VP, Client Services, NA, Steve Weir, and Director of Customer Success, Zach Simpson, to discuss the signiﬁcant incremental value to retailers and CPG companies in optimizing assortment at the store level using advanced technologies in machine learning (ML) and data science (DS).

They will explore the following:

1. Key industry trends that are impacting CPG and retailers with a focus on effective product localization, in-store execution and harnessing the power of data to meet shoppers’ expectations

2. How both retailers and their suppliers can achieve the goal of shopper-centricity through the hyper-localization of assortment and space

3. The power of ML and DS models for driving effective localization and space planning. A key to driving category share and incremental revenue lift

Watch full version here for free here 

https://www.hivery.com/case-studies/coresight-webinar-age-of-precision-category-management

How do you understand the potential items not carried in stores?

On-demand mini-webinar: How do you understand the potential items not carried in stores?

How AI goes about simulating the impact of items being carried in store?

What are some of the key barriers faced when switching to store-specific analysis?

What are some of the key barriers faced when switching to store-specific analysis.mp4

How do analytical thinking and technology/data literacy complement each other when working with large data sets to draw shopper or category insights? 

How do AI recommendations factor in online (i.e. e-commerce) vs offline (in-store) purchases

On-demand mini-webinar: How do analytical thinking and technology/data literacy complement each other when working with large data sets to draw shopper or category insights?

How do analytical thinking and technology/data literacy complement each other when working with large data sets to draw shopper or category insights?

Why is there lower than expected usage of advanced analytical methods by the retailer/CPG industry?

Why is there lower than expected usage of advanced analytical methods by retailer/CPG industry

What is the financial benefit to retailers of such store-level analysis compared to clustering?

What is the financial benefit to retailers of such store-level analysis compared to clustering.mp4

Why do many retailers choose to take the top-down approach vs clustering?

How do AI recommendations factor in online (i.e. eCommerce) vs offline (in-store) purchases?

On-demand mini-webinar : How do AI recommendations factor in online (i.e. eCommerce) vs offline (in-store) purchases

How do AI recommendations factor in online vs offline purchases?

How are retailers using technology to draw shopper insights, how can machine learning help CPG companies and retailers adapt to fast changing consumer needs?

How are retailers using technology to draw shopper insights & how can machine learning help CPG companies?

On-demand mini-webinar: How are retailers using technology to draw shopper insights, how can machine learning help CPG companies and retailers adapt to fast changing consumer needs?

On-demand mini-webinar  How are retailers using technology to draw shopper insights, how can machine learning help CPG companies and retailers adapt to fast changing consumer needs?

On-demand mini-webinar : How are retailers using technology to draw shopper insights, how can machine learning help CPG companies and retailers adapt to fast changing consumer needs?

How is analytical thinking going to transform category management? 

On-demand mini-webinar: How is analytical thinking going to transform category management?

What should be the correct approach to draw actionable shopper insights from their data?

We are seeing retailers being overwhelmed with large amounts of data.mp4

On-demand mini-webinar: What should be the correct approach to draw actionable shopper insights from their data?

How does HIVERY’s approach to clustering incorporate economic concepts such as transferable demand into the model?

How does HIVERY’s approach to clustering incorporate economic concepts such as transferable demand into the model.mp4

On-demand mini-webinar: How does HIVERY’s approach to clustering incorporate economic concepts such as transferable demand into the model?

Can you run analysis on multiple categories to help retailers reallocate store-level macro space planning?

Run analysis on multiple categories to help retailers reallocate store-level macro space planning

On-demand mini-webinar: Can you run analysis on multiple categories to help retailers reallocate store-level macro space planning?

On-demand mini-webinar: Can you run analysis on multiple categories to help retailers reallocate store-level macro space planning??

What are some of the advantages of looking at store-level data when looking to expand the category share?

What are some of the advantages of looking at store-level data when looking to expand the category share.mp4

Recorded on Wednesday, May 12, Deborah Weinswig, CEO & Founder of Coresight Research, was joined by HIVERY’s VP, Client Services, NA, Steve Weir, and Director of Customer Success, Zach Simpson, to discuss the signiﬁcant incremental value to retailers and CPG companies in optimizing assortment at the store level using advanced technologies in machine learning (ML) and data science (DS). 

1. Key industry trends that are impacting CPG and retailers with a focus on effective product localization, in-store execution and harnessing the power of data to meet shoppers’ expectations

2. How both retailers and their suppliers can achieve the goal of shopper-centricity through the hyper-localization of assortment and space

3. The power of ML and DS models for driving effective localization and space planning. A key to driving category share and incremental revenue lift

Meet Shopper Demand

The age of precision category management is upon us. Effective assortment and space localization can be a very challenging task for CPG companies and retailers, but if done right with the right methods, the incremental value generated is significant. Whether they are using a cluster approach or not, the ability for retailers and CPG companies to leverage store-level data in new ways opens up new opportunities to have the right product assortment to meet shopper demand across any store.

On Wednesday, May 12, Deborah Weinswig, CEO & Founder of Coresight Research, joined by HIVERY’s VP, Client Services, NA, Steve Weir, and Director of Customer Success, Zach Simpson, to discuss the signiﬁcant incremental value to retailers and CPG companies in optimizing assortment at the store level using advanced technologies in machine learning (ML) and data science (DS). They will explore the following:

1. Key industry trends that are impacting CPG and retailers with a focus on effective product localization, in-store execution and harnessing the power of data to meet shoppers’ expectations

2. How both retailers and their suppliers can achieve the goal of shopper-centricity through the hyper-localization of assortment and space

3. The power of ML and DS models for driving effective localization and space planning. A key to driving category share and incremental revenue lift

Webinar (On Demand) Coresight & HIVERY on Age of Precision Category Management

Watch on-demand webinar: Age of Precision Category Management: Using Hyper-Localized Assortment Optimization to Meet Shopper Demand

HIVERY (Sydney, Australia) has been highlighted as a leader in providing category management simulation and optimization—using its novel approach to leveraging store-level data—by Coresight Research, a research and advisory firm specializing in retail and technology. 

Coresight Research’s report on precision category management features discussion of HIVERY’s Curate solution, which leverages a novel store-level (bottom-up) approach, powered by advanced machine learning (ML) and data science (DS) technologies originated in laboratories run by the CSIRO and its data innovation affiliate, Data61

HIVERY’s solution effectively analyzes store-level sales data to discover “latent shopper segments”— purchase behaviors across different shopper segments — which cannot be seen by traditional methods used today.

According to a Coresight Research survey of 200 global grocery retail decision-makers, more than half of grocery retailers globally (51%) lose 5–10% of sales due to poor in-store execution, including infrequent stock replenishment, non-compliance with planograms and cannibalization of demand due to the inability to leverage data and effective analytical tools.

Global retailers such as Walmart have also started testing new, small-format stores, significantly increasing the importance of localization in product assortment planning to respond to consumer purchasing trends and behaviors.

Coresight Research’s report highlights that HIVERY leverages store-level data, taking consumer preferences and merchandising rules into account at the store level, to help retailers better understand incremental revenue opportunities at each store. HIVERY Curate can generate optimized assortment and space recommendations as well as generate planograms at both cluster and store level. Because HIVERY Curate’s engine is able to be instructed with both assortment and space rules, the optimized assortment actually fits within the exact space available at each store. This is what truly unlocks store-level assortments and can then be rolled up into any cluster count. This report follows HIVERY’s recent listing in global agency Gartner’s Market Guide for Retail Assortment Optimization Applications in Merchandising.

A shopper-centric, store-level approach to assortment and space planning can help CPG companies and retailers to ensure effective and rapid retailer-supplier collaboration and decision-making augmented by ML/DS. This improves the shopper experience, increases overall sales and builds brand loyalty. The Coresight Research survey found that increased sales conversion emerged as the topmost benefit of effective retail merchandising. 

Deborah Weinswig, CEO and Founder of Coresight Research, said there was much excitement about the discovery of new disruptive companies such as HIVERY that are looking for problems to address category management in retail chains through speed, accuracy, flexibility, extending bottom up and localizing assortment of consumer goods.

“There is a clear gap between shopper expectations and retailers’ ability to understand or fulfill them. A data-driven approach to localization and product assortment planning is critical in today’s new retail environment. HIVERY’s ML/DS solutions can deliver significant benefits for retailers and CPG companies by leveraging store-level data in a unique way, discovering those latent shopper segments and optimizing assortment and space accordingly," Ms Weinsig said.

Scott Anderson, Chief Revenue Officer at HIVERY, said that by leveraging cutting edge technology with store-level analysis, CPG manufacturers and retailers can simulate and execute effective category strategies during their joint business planning (JBP) process to create “win-win” category strategies that grow sales and improve the shopping experience. 

“We are absolutely honored to be highlighted by Coresight Research as a leader in AI solutions for category management. With HIVERY Curate, we can now help our customers predict the impact of assortment changes, planned price changes and the incrementality of their new product innovations. This powerful predictive capability enables brand marketing, sales, and category management teams to collaborate on strategies that will grow sales for both the brand portfolio and the category. We have seen a reduction in category managers' time to execute assortment recommendations and planogram generation from weeks to hours.” Mr. Anderson said.

The Coresight Research report notes that effective localization of assortment and space planning is a challenging task, with many retailers falling short of harnessing the true potential of technologies such as modern approaches in ML and DS.

“By adopting these technologies, category management and retail merchandising professionals do not need to change their planning process. The power of AI enabled analytics enables them to be faster, smarter, and more strategic in how they leverage store-level data” Mr Anderson said.

You can download the full report here: https://www.hivery.com/age-of-precision-category-management 

HIVERY is a pioneer of hyper-local retailing, and offers simulation & optimization solutions to a growing number of retail and CPG clients in North America. 

For further information and media inquiries please contact:

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

HIVERY is a multi-award winning pioneer of hyper-local retailing, combining machine learning, 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.

Coresight Research, is a research and advisory firm that provides future-focused analysis and consulting to organizations navigating the intersection of retail, technology and fashion.

The team, led by Deborah Weinswig, an award-winning retail and technology analyst, delivers cutting-edge research on topics such as the evolving retail landscape, changing consumer behavior, disruptive retail technologies and the future of supply chains in sectors such as apparel, beauty, grocery and furniture.

Coresight Research, with a global presence, including offices in New York, Hong Kong and London. Its services range from research and consulting to partnership building and events.

Coresight-Hivery media release.pdf

HIVERY, provider of retail simulation & optimization solutions, highlighted as involving new methods in precision category management  by Coresight Research

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 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. 

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

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