Digital Marketing and Brand Performance Analysis of Selected Diabetes Apps
Omolade, Oluwaseun (2022)
Omolade, Oluwaseun
2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022090920009
https://urn.fi/URN:NBN:fi:amk-2022090920009
Tiivistelmä
Background:
With the increase and rapid proliferation of mobile health (mHealth) apps, clinical validation efforts are well ongoing to provide guidance and information to health care providers and the public about which products rely on evidence-based medicine. However, there is not much with regards to the market and brand performance of these apps.
Objective:
The overall objective of the thesis is to validate some selected diabetes apps regarding the needs of their users; and analyse both the value and market performance of these selected apps.
Methods:
Diabetes apps were identified from three app platforms namely, SlideME, Google Play Store and Apple app store. Selection was done using content analysis technique with focus on the PRECEDE- PROCEED Model (PPM) and Digital Health Scorecard. For analysis, sentiment analysis, value and market performance analysis were done.
Results:
1100 apps were obtained from the three app platforms, with 37 apps passing through the two selection stages. However, using the number of available reviews per app and Digital Health Scorecard as criteria, only two apps were used for further analysis.
For the sentiment analysis, about 1000 reviews were extracted for both Glucose Buddy Tracker app and Carb Manager app. 54.1% and 69.5% of the reviews were categorized as positive for Glucose Buddy Tracker and Carb Manager app respectively. In contrast, 14% and 16.7% of the reviews were categorized as negative for Glucose Buddy Tracker and Carb Manager app respectively.
The BAR and PAR values of both selected apps were very low indicating that the apps are not optimally performing in the conversion of their users’ awareness for both performance action and advocacy. However, at +83% Net Sentiment Score (NS) the overall sentiment for both apps were positive. In addition, as part of brand equity the co-occurrence results, which is an indication of brand association, using positive reviews indicate that for both apps the overall positive NS score is associated with the usage of the app and other functional benefits involving tracking and logging of blood glucose values.
Conclusions:
This research confirms that there is the possibility to develop a framework combining both theoretical models and brand performance models to be able to validate the performance of mobile apps. In addition, for matured indication like diabetes, the finding indicates the potential value the diabetes app provides in the self-management of diabetes. Relatedly, the use of digital health apps provides a welcome and needed comfort to both healthcare providers and the patients towards a value delivery form of healthcare.
Key findings:
1. For both selected apps, there was a significant increase in positive reviews that coincided with the app version upgrades. The app upgrade is a form of a change in the brands’ marketing strategy.
2. The value and market performance of both apps by comparison are very similar, an indication of both brands using similar strategy to navigate their industry landscape.
3. Both apps did not meet the defined usability and user-requirement needs of their
targeted users.
With the increase and rapid proliferation of mobile health (mHealth) apps, clinical validation efforts are well ongoing to provide guidance and information to health care providers and the public about which products rely on evidence-based medicine. However, there is not much with regards to the market and brand performance of these apps.
Objective:
The overall objective of the thesis is to validate some selected diabetes apps regarding the needs of their users; and analyse both the value and market performance of these selected apps.
Methods:
Diabetes apps were identified from three app platforms namely, SlideME, Google Play Store and Apple app store. Selection was done using content analysis technique with focus on the PRECEDE- PROCEED Model (PPM) and Digital Health Scorecard. For analysis, sentiment analysis, value and market performance analysis were done.
Results:
1100 apps were obtained from the three app platforms, with 37 apps passing through the two selection stages. However, using the number of available reviews per app and Digital Health Scorecard as criteria, only two apps were used for further analysis.
For the sentiment analysis, about 1000 reviews were extracted for both Glucose Buddy Tracker app and Carb Manager app. 54.1% and 69.5% of the reviews were categorized as positive for Glucose Buddy Tracker and Carb Manager app respectively. In contrast, 14% and 16.7% of the reviews were categorized as negative for Glucose Buddy Tracker and Carb Manager app respectively.
The BAR and PAR values of both selected apps were very low indicating that the apps are not optimally performing in the conversion of their users’ awareness for both performance action and advocacy. However, at +83% Net Sentiment Score (NS) the overall sentiment for both apps were positive. In addition, as part of brand equity the co-occurrence results, which is an indication of brand association, using positive reviews indicate that for both apps the overall positive NS score is associated with the usage of the app and other functional benefits involving tracking and logging of blood glucose values.
Conclusions:
This research confirms that there is the possibility to develop a framework combining both theoretical models and brand performance models to be able to validate the performance of mobile apps. In addition, for matured indication like diabetes, the finding indicates the potential value the diabetes app provides in the self-management of diabetes. Relatedly, the use of digital health apps provides a welcome and needed comfort to both healthcare providers and the patients towards a value delivery form of healthcare.
Key findings:
1. For both selected apps, there was a significant increase in positive reviews that coincided with the app version upgrades. The app upgrade is a form of a change in the brands’ marketing strategy.
2. The value and market performance of both apps by comparison are very similar, an indication of both brands using similar strategy to navigate their industry landscape.
3. Both apps did not meet the defined usability and user-requirement needs of their
targeted users.