Artificial Intelligence is extensively employed by 97% of retail marketing squads, as per study findings
In a recent report by Wunderkind, an AI-driven performance marketing solution, it was revealed that 97% of UK retail marketing teams have adopted AI, with the primary focus being on facilitating day-to-day and time-intensive jobs. However, the report also noted that the applications of AI in retail remain limited, with only 38% of teams using AI for advanced segmentation and personalisation.
Wulfric Light-Wilkinson, International GM of Wunderkind, commented on the limited applications of AI in retail, stating that while AI has achieved mass adoption, its uses in the industry are mostly generative and narrow. He suggests collaboration with third-party AI providers to optimize processes and deliver a solid return on investment.
To help retailers maximize the potential of AI, Light-Wilkinson offers five key strategies:
1. Leverage Behavioral Analysis and Predictive Analytics: AI tools can analyze vast amounts of customer data to uncover hidden patterns and preferences, enabling merchants to target audiences with unprecedented precision. Predictive analytics helps forecast future customer behaviours based on historical data, allowing retailers to proactively tailor marketing and engagement efforts to high-value segments.
2. Utilize Real-Time Data Processing for Dynamic Personalization: AI-driven real-time processing captures current behavioural signals and adapts marketing and personalization strategies instantly, ensuring relevance amid changing customer preferences and external conditions.
3. Implement Hyper-Personalization with Inclusive Data Sets: Moving beyond generic offers, retailers should incorporate diverse and inclusion-focused data points to enrich segmentation and personalization. This approach enables hyper-personalized interactions tailored to individual preferences, search intent, and context.
4. Integrate Customer Segmentation into Omnichannel Engagement: Segmenting customers by behaviour, value, lifecycle stage, and other attributes allows retailers to deliver tailored messages, offers, and content across multiple channels, thereby maximizing reach and conversion potential.
5. Automate Personalized Offers and Experiences: Advanced AI can automate the delivery of personalized discounts, replenishment reminders, and loyalty perks based on segment triggers or individual profiles, improving the customer experience while streamlining operations.
In addition, Light-Wilkinson advises retailers to focus on enhancing the quality of data fed into AI systems, as the quality of data is crucial for delivering valuable insights and meaningful results. AI providers can also help retailers improve the site experience and written marketing copy beyond the generative use cases mentioned earlier.
As retailers continue to adopt AI, collaboration with third-party providers and a focus on data quality and strategy will be essential for achieving meaningful outcomes and delivering personalized, engaging customer experiences.
News of Wulfric Light-Wilkinson, International GM of Wunderkind, suggests that while AI has been widely adopted in retail, its uses are primarily generative and narrow. Insights from Light-Wilkinson reveal five key strategies for retailers to maximize AI's potential: leveraging behavioral analysis and predictive analytics, utilizing real-time data processing for dynamic personalization, implementing hyper-personalization with inclusive data sets, integrating customer segmentation into omnichannel engagement, and automating personalized offers and experiences. Additionally, he advises focusing on enhancing the quality of data fed into AI systems to deliver valuable insights and meaningful results. For retailers, collaborating with third-party AI providers and having a strategic focus on data quality will be essential for achieving meaningful AI-driven marketing outcomes and delivering personalized, engaging customer experiences.
