Retail Mavericks Podcast

Retail Mavericks is HIVERY’s official podcast channel showcasing discussions on AI, technology, culture, innovation, and the future of retailing. It features our team of experts, academics, business leaders, and maverick thinkers in the retail, customer package goods and category management.

At HIVERY, we are passionate about bringing to life new thinking, ideas and the technology behind them. We believe this can help change attitudes, lives, and ultimately the world.

  • Host, producer and editor

Milena Salmon

  • Creator and director

Franki Chamaki, HIVERY’s Co-founder and Head of Marketing & Design

  • Academia-focused episodes feature co-host

Dr Alvaro Flores, Mathematician and Data Scientist at HIVERY

If you like what you hear, subscribe on your favourite platform

podcasts

Discover new emerging retail risks and why even the biggest retailers continue to face inventory management challenges

Sep 06, 2021 | By

Brand Elverston

In this podcast you will learn: • Why "new retail disruptors" are going to be those that can give intelligence around inventory. This is a competitive imperative, it's not an advantage. • What emerging risks that are invisible at the moment retailers are facing as the new normal takes its effect. For example, with decline in human interaction and traffic in physical stores due to Buy online, pick up in store (BOPIS) and mobile checkout, discovery opportunities and cross sell opportunities are reduced. • What new technologies retailers should be investing in and integrating in order to meet new shopping habits of the "frictionless" shoppers. Conventional legacy technologies in store today will not do. • Why retailers are relying on technology suppliers to bring new innovations? Why some retailers who traditionally have not built their own physical technology are starting to use artificial intelligence (AI) algorithms? • What new, smarter technologies in retail are being developed to help with risk mitigation. • Why AI/machine learning models really "force multipliers", accelerating everything inside the retail box and more.
Read more Right Arrow
podcasts
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
Jul 23, 2021
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 
Read more Right Arrow
podcasts
Based in Bentonville, Arkansas, Jeff Ireland ex Coke, Newell Brands and IRI talks about the challenges and future of category management analytics
May 25, 2021
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
Read more Right Arrow
podcasts
Future of retail is here: from in-store flying-blimps, shelf edge messaging, computer vision, robotics, smart checkouts to hyper local assortments
Apr 28, 2021
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.
Read more Right Arrow
podcasts
Dr. Felipe Maldonado on the truth behind consumer rating influencing our buying decisions
Mar 02, 2021
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
Read more Right Arrow
podcasts
Dan Sturman on category management in a world of constant change
Jan 19, 2021
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.
Read more Right Arrow
podcasts
Mark Lawrenson on the science of retail optimization methods and solving real-world problems more optimally
Jan 05, 2021
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
Read more Right Arrow
podcasts
Zach Simpson on shifts in category management, artificial intelligence and making career changes
Nov 19, 2020
What you will learn from this podcast: • Zach's career journey from baseball to Walmart to his own company and HIVERY. Zach shares his insights into the lack of advancement of retail technology during this journey in category management. • Zach explores the "snowflake" effect of product categories and space; how each store is so different (as a snowflake), yet when it comes to space assortment, the retail industry continues treating each store and their SKU supply the same. • Why Zach, after over 11 years at Walmart with titles like Frozen Food Senior Buyer, Merchandising Director, and VP of Beverages Merchandising decided to "jump ship" to HIVERY, a young AI startup? • Zach provides a sneak preview of product innovation at HIVERY; and how customers play a critical role in this process. •. Zach dives into key problem sets faced by a wide retail segment from wholesale networks to traditional grocery stores in space, assortment, and category scenario planning. • Lastly, Zach gives career advice and shares his insights into personal and professional development, innovating from within and facilitating change.
Read more Right Arrow
podcasts
Why Food Retailers Need To Embrace AI
Nov 08, 2020
Why Food Retailers Need To Embrace AI? In this Lost in the Supermarket episode, Phil Lempert talks with Jason Hosking, CEO & Co-Founder of HIVERY, The worlds first category management optimization solution.
Read more Right Arrow

Subscribe to HIVERY updates