In the highly competitive financial sector, AI-powered conversational bots offer institutions a valuable opportunity to stand out. By enabling constant and personalized dialogue with customers, these tools strengthen brand engagement and loyalty. This regular and optimized presence meets the growing expectations of customers, while enhancing the brand image of financial organizations in a market where every interaction counts.
What is brand image?
Brand image is the perception that consumers have of a company, based on its values, communication, and the customer experience it offers. It strongly influences customer trust and loyalty.
An image of innovation and modernity
The integration of AI-based chatbots allows financial institutions to project a resolutely modern and technological image. According to Ubisend's 2017 Chatbot Survey, 43% of consumers associate the use of conversational bots with an innovative company image. For traditional banks, this is an opportunity to demonstrate their ability to adapt to new technologies and compete with neobanks in the field of innovation (Wube et al. 2022).
Thanks to its unique architecture modeled on Layer 2 generative AI and the integration of behavioral finance principles, LiLa offers an unparalleled experience. By enhancing credibility, accuracy, and competence, LiLa becomes a true guarantee of trust for savers.
Continuous availability
Chatbots offer 24/7 customer service, thus meeting the growing demand from customers for constant availability. This enhanced accessibility significantly improves brand perception, positioning the institution as responsive and attentive to its customers (Przegalinska et al. 2019).
Advanced personalization
Thanks to data analysis and machine learning, conversational bots can offer personalized recommendations and advice. This tailor-made approach strengthens the customer relationship and positions the bank as a true financial partner, capable of understanding and anticipating the specific needs of each client.
Thanks to its advanced understanding of emotions and behavioral biases, LiLa significantly improves overall customer satisfaction. This contributes to strengthening the quality of relationships with savers, thereby solidifying their loyalty. (Følstad et Brandtzæg, 2017).
Increased efficiency
Chatbots can quickly process a large volume of simple requests, thus freeing up human advisors for higher value-added tasks. This operational efficiency translates into improved customer satisfaction, with reduced response times and enhanced service quality (Xu et al. 2017).
Enhanced customer engagement
Conversational bots offer new opportunities for interaction with customers, allowing financial institutions to maintain a constant and personalized dialogue. This regular presence strengthens customer engagement and brand loyalty. LiLa's human-like attitude is a major asset, enabling it to create lasting bonds with savers. The latter particularly appreciate the convenience and reliability of the continuous assistance that LiLa offers.
A stronger and more recognizable brand image
The integration of chatbots in the financial services landscape contributes to making the brand stronger and more recognizable. Personalized interactions and improved customer experience reinforce the positive perception of the brand among consumers (Wube et al.2022).
Conclusion
The adoption of intelligent conversational bots represents much more than a simple technological evolution for financial institutions. It is a true lever for transforming brand image, allowing them to project a modern, efficient, and customer-centric image. In a sector where trust and customer relationships are paramount, chatbots are becoming an essential tool for banks and financial institutions wishing to remain competitive and attractive in the long term.
Sources
Følstad, A., & Brandtzæg, P. B. (2017). Chatbots and the new world of HCI. interactions, 24(4), 38-42.
Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P., & Mazurek, G. (2019). In bot we trust: A new methodology of chatbot performance measures. Business Horizons, 62(6), 785-797.
Wube, H. D., Esubalew, S. Z., Weldesellasie, F. F., & Debelee, T. G. (2022). Text-Based Chatbot in Financial Sector: A Systematic Literature Review. Data Science in Finance and Economics, 2(3), 232-259. doi: 10.3934/DSFE.2022011
Xu, A., Liu, Z., Guo, Y., Sinha, V., & Akkiraju, R. (2017). A new chatbot for customer service on social media. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 3506-3510).
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