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Our Thought Provoking Insights

AI in Retail

In the ever-evolving world of retail, traditional paradigms are being challenged by a confluence of factors, including rising costs and softening demand. Retailers like Farfetch, Matches, Ocado, Net-a-Porter, Superdry, Boohoo, Morrisons, and ASOS all face publicly acknowledged trading pressures. As costs outpace revenues, retailing is becoming a lower-profit business. 

The natural response from leadership teams facing pressure on margins is to cut costs. However, this often creates a negative cycle where value-added is eroded, sales are impacted and margins are further diluted. So, how do retailers break free from this downward spiral? 

At its core, profitability in retail hinges on added value delivered through operational excellence. This requires investment across the entire supply chain, the product itself, and the customer experience at the point of sale. Tech in general has facilitated the move from analogue to digital operating models but now Generative AI offers the opportunity to knit the key components together and accelerate performance. 

The transformative potential of AI in retail cannot be overstated from dynamic price optimisation to material improvements in demand forecasting accuracy. While in communications, Generative AI can transform personalised marketing content creation. Every facet of the industry can potentially be reshaped and very significantly enhanced. 

Key insights gleaned from our recent roundtable discussions with retail leaders underscore AI's strategic imperative: 

  • Not A Zero-Sum Game: AI is not just another tool; it's turbo-charged machine learning that adapts to each business's unique challenges and opportunities. 

  • Strategic and Tactical: AI empowers retailers to transform data into actionable insights, enhancing tactical agility through dynamic pricing and accurate demand forecasts. It also enables strategic planning through scenario modelling and risk assessment. 

  • Personalising: Leveraging AI-driven personalisation, retailers can tailor product recommendations to individual preferences, driving customer engagement and boosting sales. 

  • Embracing AI's Impact: AI's transformational potential parallels the internet revolution, necessitating preparation for profound shifts in operational models and organisational structures. 

  • Strategic Implementation: Retailers can realise rapid gains by integrating AI into critical trading areas such as forecasting and pricing optimisation while maximising returns with minimal investment. 

  • Synergistic Collaboration: AI complements human capabilities, fostering collaboration between data science insights and business acumen to drive actionable intelligence. 

  • Optimisation and Adoption Focus: Harnessing the power of data assets and instilling trust in AI outputs are crucial for widespread adoption. Precision pricing strategies enabled by AI optimisation ensure maximal revenue generation across products and channels. 

  • Continuous Improvement and Leadership Empowerment: By embracing AI, retailers can continuously refine their operations through iterative learning and empower leadership decision-making with enhanced agility and insight. 

Embracing AI isn't just about keeping pace—it's about leading the charge, innovating, and dominating the retail landscape. By strategically harnessing AI's disruptive potential, retailers can secure a commanding competitive edge and drive sustained growth in today's relentless market. 

Appendix: Recent Thought Provoking Consulting AI implementations across Retailers and Suppliers 

  1. Generative AI and Local Language Models at a major pure-play department store: Utilising face detection algorithms, computer vision-based dress type detection, attribute extraction, and image segmentation, AI streamlines operations and reduces redundancies in image databases. 

  1. Dynamic Price Optimisation at leading health, hygiene and nutrition FMCG manufacturer: Deploying a multichannel optimisation algorithm based on online learning, Reckitt Benckiser optimises prices across all channels to maximise net revenue and gross margin. Recommendations, generated nightly and fed into a Power BI dashboard, are based on competition data and channel feeds, piloted successfully in Brazil with a 9% incremental net revenue increase. 

  1. Markdown Optimisation at Fashion Retailer: Through the adoption of machine learning and neural net models, improvements in markdown strategy, planning and execution are generating cash margin improvements of over 20% and associated improvements in sell-through. 

  1. Demand Forecasting at a major international food and household brand: Achieving an 11% accuracy improvement with the same bias, Unilever now utilises AI-based demand forecasting for 70% of its product lines, optimising inventory management and supply chain efficiency. 

  1. Generative AI at leading international pharma group: Roche's fine-tuned generative AI model generates personalised marketing content, including image icons and inspirational graphics, swiftly responding to market demands with 100 images produced in just two hours, significantly improving from the previous 13-week creative cycle. 

  1. Built AI Algorithm to manage product images for pan-European household goods retailer: Processing and editing product images across vast and diverse supplier base, each vendor generating multiple images for multiple products, a previously manual highly labour-intensive process. 



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