This is an original Qintora portfolio project. It is designed to show the level of strategy, implementation detail and deliverables a client can expect. Where percentages are shown, they are explicitly modeled targets rather than claimed client results.
The brief
This project models a UAE consumer marketplace preparing for launch across iOS and Android. The challenge is not simply finding keywords; the listing needs to explain the value proposition quickly, localize for English and Arabic search behavior and create a screenshot sequence that improves install intent.
Research inputs
The working research set includes competitor titles and subtitles, review-language patterns, category terminology, UAE-specific marketplace phrases, branded vs non-branded search demand and the first-session actions that best predict activation. The ASO plan is tied to product analytics so installs are not treated as the final KPI.
What the launch package includes
The portfolio package contains a keyword architecture, English and Arabic metadata map, screenshot narrative, icon test hypotheses, review-prompt timing, launch measurement plan and an Apple Search Ads structure designed to feed real search-term data back into organic ASO decisions.
- Priority keyword universe and competitor map
- English + Arabic title, subtitle and description architecture
- Screenshot sequence and creative test hypotheses
- Review-prompt and rating-quality workflow
- Paid-search-to-organic learning loop
Measurement model
We would monitor store impressions, product-page views, listing conversion rate, keyword positions, paid search tap-through, install-to-registration and first-value-event completion. Version changes would be logged so movement can be tied back to specific metadata or creative experiments.
Modeled outcome
The showcase target is a 31% lift in store-listing conversion and a 58% increase in the number of priority terms reaching the top 20. These percentages are modeled to demonstrate the optimization logic; they are not presented as verified results for an unnamed client.
How we would validate it live
In production we would start from the app's existing baseline, run creative experiments with statistically meaningful traffic where possible and treat English and Arabic listing performance separately. Retention quality would decide whether a keyword remains valuable even if it drives strong install volume.