{"id":9145,"date":"2026-09-03T14:09:26","date_gmt":"2026-09-03T11:09:26","guid":{"rendered":"https:\/\/www.lf.com.tr\/?page_id=9145"},"modified":"2026-09-03T14:56:40","modified_gmt":"2026-09-03T11:56:40","slug":"case-studies","status":"publish","type":"page","link":"https:\/\/www.lf.com.tr\/tr\/case-studies\/","title":{"rendered":"Vaka Analizleri"},"content":{"rendered":"
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INSIGHTS \/ CASE STUDIES<\/h6>\n<\/div><\/div>
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Work we can point to,
\nnot just describe<\/span>.
\n<\/strong><\/h1>\n<\/div><\/div>
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A selection of engagements across public institutions, healthcare and e-commerce \u2014 the problem, what we built, and what changed.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

27<\/span>
\ncity hospitals scored in one national report<\/span><\/div>\n<\/div><\/div><\/div><\/div><\/div>
150<\/span>
\ndormitory directorates covered across 7 provinces<\/span><\/div>\n<\/div><\/div><\/div><\/div><\/div>
300+<\/span>
\nactive Google Ads accounts under management<\/span><\/div>\n<\/div><\/div><\/div><\/div><\/div>
3<\/span>
\nsectors: public institutions, healthcare, e-commerce<\/span><\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>
CASE 01 \u2014 PUBLIC HEALTHCARE<\/h6>\n<\/div><\/div>
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Scoring 27 city
\nhospitals nationwide.<\/h2>\n<\/div><\/div>
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A ministry-level reporting need with no existing dataset: no unified way to compare patient experience across the country’s city hospitals. We built the collection pipeline and scoring model, and delivered a standing report.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

\n

THE CHALLENGE<\/span><\/p>\n

Patient experience data was scattered across review platforms and doctor-review sites, with no consistent way to compare hospitals against each other.<\/p>\n

WHAT WE BUILT<\/span><\/p>\n

A four-source data pipeline and a weighted scoring model \u2014 a quantitative perception score plus a separate qualitative theme score per hospital, with a confidence flag for low-volume records.<\/p>\n

THE OUTCOME<\/span><\/p>\n

A finished report ranking all 27 city hospitals, with hospitals grouped by opening-year cohort and a shared institutional format ready for the Ministry of Health.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

CASE 02 \u2014 PUBLIC HOUSING<\/h6>\n<\/div><\/div>
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Mapping 150 student
\ndormitories.<\/h2>\n<\/div><\/div>
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A directorate needed the same rigor applied to a different network: student dormitories spread across seven provinces, each with its own director and gender-split blocks.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

\n

THE CHALLENGE<\/span><\/p>\n

150 dormitory directorates across 7 provinces, with feedback data that had to be matched at the individual facility level \u2014 not just the city level \u2014 to be useful.<\/p>\n

WHAT WE BUILT<\/span><\/p>\n

A province-by-province collection process, starting with a smaller pilot province to validate the matching method before scaling to the full national list.<\/p>\n

THE OUTCOME<\/span><\/p>\n

A completed baseline report covering all 150 directorates, built to the same institutional standard as the hospital report, ready for the relevant ministry.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

CASE 03 \u2014 E-COMMERCE<\/h6>\n<\/div><\/div>
<\/div>

Rebuilding a storefront
\naround real conversion.<\/h2>\n<\/div><\/div>
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A gaming peripherals brand needed a storefront that matched how customers actually shop for its product range \u2014 not the theme’s default assumptions.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

\n

THE CHALLENGE<\/span><\/p>\n

The default Shopify variant picker didn’t reflect how customers browse and compare gaming peripherals, creating friction right at the point of decision.<\/p>\n

WHAT WE BUILT<\/span><\/p>\n

Custom theme modifications and a redesigned variant picker, built directly into the storefront rather than bolted on as an app.<\/p>\n

THE OUTCOME<\/span><\/p>\n

A storefront experience that matches the product line’s actual shopping behavior, maintained on an ongoing basis as the catalog grows.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

WHAT THESE HAVE IN COMMON<\/h6>\n<\/div><\/div>
<\/div>

The same method,
\napplied to different problems.<\/h2>\n<\/div><\/div><\/div><\/div><\/div>

Different sectors, different deliverables \u2014 but every case study starts and ends the same way.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div>

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\n

01<\/span><\/p>\n

Start From the Real Constraint<\/h3>\n

Not a generic template \u2014 the actual data gap, workflow or friction point the institution or brand was facing.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

\n

02<\/span><\/p>\n

Build for the Actual Scale<\/h3>\n

Whether it’s 27 hospitals, 150 dormitories or a single storefront, the approach is sized to the real scope \u2014 not padded or under-built.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

\n

03<\/span><\/p>\n

Leave Something That Lasts<\/h3>\n

A report format, a scoring model, a storefront pattern \u2014 built to be reused and extended, not a one-off deliverable.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

TRUSTED BY ORGANIZATIONS<\/h2>\n<\/div><\/div>
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