An interview with Scott Miller, independent consultant in the grocery industry, and Prem Kiran, CEO at Hypersonix, looking at the role AI is playing in improving ecommerce performance in online grocery stores.
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Tl;dr
- How online grocery businesses typically approach ecommerce performance analysis
- How online grocery retailers are using generative AI to help improve analysis and profitability
- Using Hypersonix to improve data connectivity and protect margin
- The business case for investment in generative AI
Online grocery is an interesting industry when looking through a technology lens. Retailers operate in a highly competitive market with perishable product that needs smart algorithms and merchandising strategies to maximise sell through. Omnichannel selling stepped us massively during COVID lockdown, and Click & Collect and Ship To Store customer journeys are more important than ever.
Add to this mix demands from CPG brands selling via online grocery websites, requiring intelligent digital shelf analytics and merchandising tools to improve product visibility and sales rate. The lessons learned in online grocery are relevant and useful to other ecommerce teams.
In this episode we sit down with industry veteran Scott Miller, an independent consultant in the grocery industry and ex COO of Rouses and Pyramid Foods. Scott is joined by Prem Kiran, CEO at technology partner Hypersonix, who provide generative AI solutions to many industries including online grocery.
Discussion notes
- Let’s take the bird’s eye view – how have online grocery businesses typically approached performance analysis – what are the challenges, what toolkits have they relied upon?
- Online grocery has invested quite heavily in digital store analytics platforms like Profitero, eFundamentals etc. – what does generative AI do differently, as in why should online grocers consider this type of tooling?
- Let’s walk through common challenges and risks for retail grocery, and explore how an online grocery business like Rouses is using/can use Hypersonix to drive change and value:
- Pricing strategy: reacting to market pressures, avoiding the race to the bottom – how does AI do this better, what value does it add?
- Product discovery; with algorithms biassed towards sales rates, how can AI be employed to avoid pushing the same products all the time and encourage shoppers to explore across a wider product set?
- Inventory management: identifying runs, tracking bottlenecks etc – how can AI speed up the identification of issues and improve stock coverage, what does it do differently than a standard trading report that calculates stock coverage based on sales rate?
- A key issue I’ve seen is the disconnect between operations and merchandising, for example merch campaigns pushing products that have supply chain issues because they convert well on the website: how are you using Hypersonix to help plug this sort of gap & what impact does it have?
- Let’s look through a brand lens selling into an online grocer, as most brands I work with are hugely frustrated at the lack of data shared by retailers; are you using Hypersonix to provide any intelligence to brands to help them make smarter investments and product placements in the digital store?
- How does the AI avoid false flags based on focusing on the wrong metrics e.g. you can drive a higher conversion rate by killing your margin through heavy discounting, what sense checks are built-in?
- How do you make an investment in a generative AI tool pay off, instead of being another tool that people don’t extract value from – whos’ the right business owner and how should an ecommerce business be using it?
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