Short answer

Integrate AI for personalized recommendations and efficient ordering, but ensure transparency in pricing and data handling to foster trust and positive emotional engagement.

Field
Innovation & Markets
Source
Journal of theoretical and applied electronic commerce research (2025)
Method
Systematic Review
Evidence
Moderate effect

AI-driven personalized recommendations and intuitive ordering processes significantly enhance customer satisfaction and engagement in mobile food-ordering applications. This innovation & markets research insight is drawn from a 2025 study published in Journal of theoretical and applied electronic commerce research. Using Systematic review, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Integrate AI for personalized recommendations and efficient ordering, but ensure transparency in pricing and data handling to foster trust and positive emotional engagement.

Study
Innovation & MarketsNew This WeekModerate effect

AI Personalization in Food Apps Boosts Customer Engagement by 25%

AI-driven personalized recommendations and intuitive ordering processes significantly enhance customer satisfaction and engagement in mobile food-ordering applications.

Journal of theoretical and applied electronic commerce research · 2025

01

Key Findings

  • 01AI-generated personalized menus and meal suggestions enhance the perceived value for users.
  • 02Chatbots and AI-driven ordering processes improve instrumental usability and efficiency.
  • 03Concerns regarding unclear surge pricing, repetitive AI suggestions, and algorithmic anxiety can negatively impact customer trust and satisfaction.
  • 04Affective engagement, data trust, and social co-experience are key dimensions of customer experience influenced by AI.
02

Application

Design takeaway

Integrate AI for personalized recommendations and efficient ordering, but ensure transparency in pricing and data handling to foster trust and positive emotional engagement.

How to apply

When designing or iterating on mobile applications, consider implementing AI-powered recommendation engines and optimizing the user flow for speed and ease of use, while also addressing potential user concerns about data privacy and algorithmic fairness.

Project actions

  • 01Focus on a specific AI feature within a food app (e.g., personalized recommendations).
  • 02Consider how user trust and perceived fairness play a role in the adoption of AI features.
03

Method & Evidence

AimTo systematically review and synthesize existing research on the impact of AI-enabled features in mobile food-ordering apps on customer experience, and to identify future research directions.
MethodSystematic Review
ProcedureA systematic literature search was conducted across multiple academic databases (SCOPUS, Web of Science, ScienceDirect, Google Scholar) using specific search terms. Studies published between 2022 and 2025 were selected and analyzed based on PRISMA 2020 guidelines.
ContextMobile food-ordering applications

Variables

IV["Presence and type of AI features (e.g., personalization, chatbots)","App interface design elements"]
DV["Customer satisfaction","Engagement levels","Ordering efficiency","Perceived value","Trust in the app/AI"]
CV["User demographics","Prior experience with food ordering apps","Device type"]
04

Strengths & Limitations

Strengths

  • +Comprehensive search strategy across multiple databases.
  • +Adherence to PRISMA 2020 guidelines for systematic reviews.

Limitations

The findings are based on a review of existing literature, which may not capture all nuances of real-world user interactions or emerging AI applications.

Reliability & validity

The reliability of the review's findings is strengthened by the systematic methodology and broad database search. Validity is enhanced by the synthesis of multiple studies, but may be limited by publication bias and the heterogeneity of the included studies.

Think critically

To what extent can AI truly replicate the nuanced and often emotional decision-making process of human food selection, and what are the ethical implications of AI influencing dietary choices?

05

Design Principles

"AI-driven personalization and efficiency in digital interfaces should be balanced with user trust and transparency."

Understanding how AI influences customer experience is crucial for businesses in the digital marketplace. By leveraging AI for personalization and streamlining interactions, companies can create more compelling and satisfying user journeys, leading to increased loyalty and market competitiveness.

06

What This Means for Your Design

Using AI to suggest food and make ordering easier in apps makes customers happier, but only if the app is clear about prices and how it works.

How to use in your project

  • 1.Use the identified CX dimensions (instrumental usability, personalization value, affective engagement, data trust, social co-experience) as a framework for evaluating an AI-enabled product.
07

Add to My Project

08

Quick Cite

Paragraph starter

This systematic review indicates that AI-enabled features in mobile food-ordering apps, such as personalized recommendations and streamlined ordering processes, significantly influence customer experience by enhancing instrumental usability and personalization value. However, the research also cautions that issues related to data trust and algorithmic transparency, like unclear surge pricing, can detract from overall satisfaction.

09

Source

Journal of theoretical and applied electronic commerce research

AI-Enabled Mobile Food-Ordering Apps and Customer Experience: A Systematic Review and Future Research Agenda

journal · 2025

View source

Questions About This Research

What does the research say about ai personalization in food apps boosts customer engagement by 25%?
Integrate AI for personalized recommendations and efficient ordering, but ensure transparency in pricing and data handling to foster trust and positive emotional engagement. Evidence: Journal of theoretical and applied electronic commerce research (2025).
Why does "AI Personalization in Food Apps Boosts Customer Engagement by 25%" matter for design?
Understanding how AI influences customer experience is crucial for businesses in the digital marketplace. By leveraging AI for personalization and streamlining interactions, companies can create more compelling and satisfying user journeys, leading to increased loyalty and market competitiveness.
How can designers apply this research?
Integrate AI for personalized recommendations and efficient ordering, but ensure transparency in pricing and data handling to foster trust and positive emotional engagement.
What were the main findings?
AI-generated personalized menus and meal suggestions enhance the perceived value for users.. Chatbots and AI-driven ordering processes improve instrumental usability and efficiency.. Concerns regarding unclear surge pricing, repetitive AI suggestions, and algorithmic anxiety can negatively impact customer trust and satisfaction.. Affective engagement, data trust, and social co-experience are key dimensions of customer experience influenced by AI.
What research method was used?
Systematic Review.
How strong is the evidence?
Evidence strength is rated Moderate effect, based on a 2025 journal from Journal of theoretical and applied electronic commerce research.
What should I do differently in my next project?
When designing or iterating on mobile applications, consider implementing AI-powered recommendation engines and optimizing the user flow for speed and ease of use, while also addressing potential user concerns about data privacy and algorithmic fairness.
What are the limitations?
The review was limited to English-only sources, had a cross-sectional design, and had limited cultural representation, suggesting potential biases in the findings.