To address Parsley & Twine’s challenge of converting website visitors into engaged, high-quality leads, an AI-driven marketing strategy has been developed through the implementation of Bloom, a personalised digital retail assistant. Bloom is an online retail assistant designed to enhance the digital shopping experience while supporting lead generation. It operates as a menu/button-based chatbot, guiding users through structured interactions that simplify decision-making and ensure ease of use (IBM, 2024). Its primary goal is to convert website visitors into high-quality leads by offering personalised, guidance-led interactions that replicate the reassurance of in-store shopping (Huang & Rust, 2018). By combining conversational AI with data-driven personalisation, the strategy aims to reduce decision fatigue, increase user engagement, and encourage users to share their details through a seamless and value-led interaction (McKinsey & Company, 2025).

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Bloom is aimed at a digitally engaged, style-conscious consumer who primarily shops online via mobile or laptop. This consumer enjoys discovering unique, artistic products and values a considered shopping experience, often taking time to browse, save items, and seek inspiration before making a purchase, particularly when buying thoughtful gifts for friends and family (Mintel, 2025). Eager to communicate her individuality through style and create an aesthetically pleasing home, she is drawn to curated collections and personalised recommendations that reflect her individuality while supporting creative and independent brands (Bleier et al., 2019).

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Despite her interest in online shopping, this consumer often experiences decision fatigue due to an overwhelming number of product choices and may lack confidence when visualising how items, such as accessories or homeware, will look styled within her existing wardrobe or living space (Iyengar & Lepper, 2000). This can result in passive browsing behaviour, where users engage with the website but leave without making a purchase or providing their details (Deloitte, 2024). Bloom directly addresses these challenges by offering tailored recommendations, styling inspiration, and gentle, guided support throughout the shopping journey. This approach aligns with Cognitive Load Theory, which suggests that reducing the complexity of choices lowers mental effort and improves decision-making (Sweller, 1988). By simplifying the user journey into manageable, guided steps, Bloom reduces overwhelm and increases the likelihood of conversion.

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To address this challenge, the Bloom strategy utilises conversational AI to bridge the gap between anonymous browsing and meaningful customer engagement. By replacing traditional, high-friction contact forms with an interactive chatbot powered by Landbot, the strategy targets the “choice paralysis” often experienced by style-conscious consumers (McKinsey & Company, 2021). The core of this approach is guided conversion, where users are segmented into pathways such as gifting or personal styling, ensuring that each interaction is highly relevant and personalised. This reflects principles of personalisation in consumer behaviour, where tailored experiences increase perceived relevance and emotional engagement, ultimately strengthening purchase intention (Bleier et al., 2019). This process builds consumer confidence and facilitates a value exchange, where users are encouraged to provide their contact details in return for personalised recommendations, curated inspiration, or exclusive offers (Davenport et al., 2020).

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Bloom operates as an interactive chatbot embedded within the Parsley & Twine website, engaging users at key moments during their browsing journey. Upon entering the site, users are greeted with a soft, on-brand message such as, “Hi, I’m Bloom, your personal shopping assistant. What are you looking for today?” From this point, users are guided through a series of simple, intuitive questions relating to their needs, including whether they are shopping for a gift or their preferred style. The chatbot’s ease of use and conversational format correspond with the Technology Acceptance Model (TAM), which highlights that users are more willing to engage with digital technologies when they perceive them as being both beneficial and user-friendly (Davis, 1989). By ensuring a frictionless and intuitive interaction, Bloom increases the likelihood of sustained engagement and interaction.

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The implementation of Bloom is supported by the integration of key AI tools. Landbot enables the creation of structured, conversational flows that adapt dynamically to user inputs, ensuring a personalised and responsive interaction (Huang & Rust, 2018). While this project focuses on the development of the chatbot itself, the wider strategy proposes integration with tools such as HubSpot Free CRM to capture and manage user data, allowing leads generated through Bloom to be stored, segmented, and nurtured through targeted follow-up communication such as personalised email campaigns (IBISWorld, 2026). In addition, platforms such as Google Analytics could be used to support performance tracking by providing insights into user behaviour, engagement levels, and conversion rates, enabling continuous optimisation of the chatbot experience (Shankar, 2021).

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However, while Bloom enhances personalisation and engagement, its effectiveness largely depends on how well it is designed and on user acceptance. If interactions are perceived as overly automated or intrusive, this may reduce trust and limit engagement. Therefore, maintaining a balance between automation and authenticity is essential to ensure that the chatbot enhances, rather than detracts from, the brand experience (Lemon & Verhoef, 2016).

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Overall, this AI-driven strategy transforms the online shopping journey from passive browsing into an interactive and personalised experience. By guiding users through the decision-making process, Bloom reduces overwhelm, builds confidence, and enhances the perceived value of the brand. At the same time, it creates a natural and effective pathway for lead generation, enabling Parsley & Twine to capture and nurture customer interest more efficiently. Through the integration of conversational AI, customer relationship management, and data analytics, the strategy provides a cohesive and scalable solution that aligns both customer experience and commercial objectives (Deloitte, 2024).