# Verticals: General Research, Fashion, Ad Testing

What the three verticals on the home page are for, why populations are tied to a vertical, which methods each vertical offers and how to choose the right one.

Every study is set up in a vertical. The **Choose a vertical** screen, which opens when you log in to SCL, offers three verticals: **General Research**, **Fashion** and **Ad Testing**. The vertical determines which population the study runs with, which methods are offered and which groups the report breaks the results down by.

## The vertical screen

You open this screen with the **New Research** item in the sidebar or by clicking the SCL logo. The cards appear in this order:

| Vertical | Card description | When you click the card |
| --- | --- | --- |
| **General Research** | "General-purpose research with market segmentation." | The **Choose Your Research Type** screen opens. |
| **Fashion** | "Apparel comparison on an archetype-based panel." | A method screen titled **Fashion** opens. |
| **Ad Testing** | "Test a video ad with a synthetic consumer panel." | The vertical has only one method, so method selection is skipped and the population step opens. |

[Starting a new study](/en/docs/research/new-study) covers the rest of the setup. On the **Quick Research** screen, you choose the vertical in the **Research Type** field instead; for details, see [Quick Research](/en/docs/research/quick-research).

> [!NOTE]
> The older verticals (FMCG (Non-Food), Banking, Consumer Electronics, Personal Care) have not appeared on the home page since 27 August 2026. Studies and populations you created in them still appear under **General Research**; you can't start new studies in these verticals.

## General Research

General Research works for any product, service or category and offers seven methods. Choose this vertical for anything other than clothing and ads.

A population is the group of synthetic consumers (personas) that a study runs on, and you can save it and reuse it. Personas in a General Research population are sampled from Türkiye's population and income data. In the form, you enter the number of personas, filters such as age, gender, province and socio-economic status (SES), and a **Research topic**.

The system finds a segmentation that fits this topic; when you accept it, each persona is assigned a market segment. In reports, you can break results down by market segment and by demographic dimensions. For details, see [Creating a population](/en/docs/populations/creating-a-population) and [Segmentation](/en/docs/results/segmentation).

## Fashion

Fashion is the vertical for clothing products. Although its card description mentions comparison, Fashion has all seven methods from General Research; some appear under different names (see the methods table below). A Fashion population is also built with filters and a segmentation, as in General Research, with two additions.

### Fashion Attributes tab

The Fashion population form has an extra tab called **Fashion Attributes**. Here you set two distributions as percentages:

- **Primary Shopping Channel**: **Online Ağırlıklı** (Mostly online), **AVM Ağırlıklı** (Mostly shopping malls), **Outlet Ağırlıklı** (Mostly outlets), **Karma** (Mixed), **Pasif** (Passive).
- **Style Confidence**: **Yüksek** (High), **Orta** (Medium), **Düşük** (Low).

Each group must add up to 100%. If you leave a group blank, the default distribution is used.

### Fashion archetypes

An archetype is a vertical-specific consumer type assigned to a persona. When a Comparison or Multiple-Choice Survey study starts in Fashion, each persona is assigned one of the 12 fashion shopper types below. You don't choose the archetypes; the population form has no field for them.

| Archetype | In brief |
| --- | --- |
| **Trendyol Pragmatist** | Shops mostly online; looks at price and product ratings first and has little brand loyalty. |
| **AVM Flanörü** (Mall Flâneur) | Treats mall shopping as a social outing; touches and tries things on in store and buys from mid-priced mall brands. |
| **Instagram Takipçisi** (Instagram Follower) | Gets their style from Instagram and TikTok; is swayed by influencers and is ready to spend on trending pieces. |
| **Kalite Avcısı** (Quality Hunter) | Buys few but expensive pieces; looks at fabric, stitching and durability. |
| **Klasik Muhafazakâr** (Classic Conservative) | Dresses modestly out of faith or cultural preference; their taste is shaped within that frame. |
| **Hızlı Moda Döngücüsü** (Fast-Fashion Cycler) | Buys a lot, doesn't get attached to clothes and refreshes their wardrobe often. |
| **Marka Sadığı** (Brand Loyalist) | Sticks to one or two brands; switching brands feels like a risk. |
| **Outlet Avcısı** (Outlet Hunter) | Knows the brands but looks for discounts; follows outlet stores and seasonal sales. |
| **Minimalist Modern** | Follows a capsule-wardrobe approach and picks neutral-coloured pieces without logos; stays away from trends. |
| **Statü Göstericisi** (Status Signaller) | Uses clothing as a social signal; logos and recognisable designs matter to them. |
| **İşlevselci** (Functionalist) | Buys clothes because they need them; looks at fit, durability, comfort and price. Sees shopping as a chore. |
| **Sezon Alışverişçisi** (Seasonal Shopper) | Goes shopping for occasions such as weddings, religious holidays, summer or back to school; spends on special occasions and is thrifty in everyday shopping. |

You see archetypes in reports in these places:

- In the Comparison report, the **By archetype** panel in the **Audience profile** section and the **Archetype** filter in the **Persona details** list.
- In the Multiple-Choice Survey report, the **Archetype**, **Channel** and **Style Confidence** breakdowns.

The other five methods in Fashion use market segments instead of archetypes, as in General Research.

### Design screens adapted for clothing

In the Price Analysis (WTP) design, the product's image and description can be read from a product page link. The Comparison screen lists the supported fashion sites, and you pick the category from a list of clothing categories. For details, see [Price Analysis (WTP)](/en/docs/research/price-analysis) and [Comparison](/en/docs/research/comparison).

## Ad Testing

You use the Ad Testing vertical to have personas watch an ad and measure their reactions. The vertical has a single method: Ad Test. [Ad Testing](/en/docs/research/ad-testing) covers the ways to add your ad, placement selection and the report.

An Ad Testing population is also built with filters and a segmentation. The form has an extra tab called **Reklam Testi Attributes**, where you set two distributions:

- **Kategori İlgilenimi** (Category Involvement): **Yüksek**, **Orta**, **Düşük**.
- **Reklama Açıklık** (Ad receptivity): **Yüksek**, **Orta**, **Düşük**.

As in Fashion, each group must add up to 100%; a group left blank uses the default distribution.

When the population is created, each persona is assigned an archetype that describes how they view ads, such as **Kanıt Arayan** (Evidence Seeker), **Fırsatçı** (Deal Seeker), **Şüpheci** (Sceptic) or **Reklam Atlayan** (Ad Skipper). In the report, the archetype appears on the **Persona Sesleri** (Persona Voices) cards and in the **Tüm arketipler** (All archetypes) filter of the **Persona Kanıtları** (Persona Evidence) list. If the population is segmented, the **Segmentte ne değişti** (What changed in each segment) chart shows what the ad changed in each market segment.

## Methods by vertical

The same method can appear under a different card name in General Research and Fashion. The cards are in the same order in both verticals.

| Method | General Research card | Fashion card | Ad Testing |
| --- | --- | --- | --- |
| [Price Analysis (WTP)](/en/docs/research/price-analysis) | **Price Analysis** | **Fiyat Analizi (WTP)** (Price Analysis) | none |
| [Competitive Analysis (Conjoint)](/en/docs/research/competitive-analysis) | **Competitive Analysis** | **Rekabet Analizi (Conjoint)** (Competitive Analysis) | none |
| [Comparison](/en/docs/research/comparison) | **Comparison** | **Comparison** | none |
| [Priority Ranking (MaxDiff)](/en/docs/research/priority-ranking) | **Priority Ranking** | **Özellik Tercihi (MaxDiff)** (Feature Preference) | none |
| [Feature Price Impact](/en/docs/research/feature-price-impact) | **Feature Price Impact** | **Feature Price Impact** | none |
| [Multiple-Choice Survey](/en/docs/research/multiple-choice-survey) | **Survey** | **Multiple Choice** | none |
| [Real-Time Focus Group](/en/docs/research/focus-group) | **Real-Time Focus Group** | **Gerçek Zamanlı Odak Grup** (Real-Time Focus Group) | none |
| [Ad Testing](/en/docs/research/ad-testing) | none | none | No card; the vertical card opens this method directly. |

Abbreviations: WTP is willingness to pay; MaxDiff is best–worst scaling. [Choosing the right method](/en/docs/research/choosing-a-method) compares which question each method answers.

## Populations are tied to a vertical

A population you create in one vertical can only be used in that vertical. For example, you can't select a Fashion population in General Research or Ad Testing.

- You can reuse a population in other methods of the same vertical. To do so, choose the **Select Existing Population** card in General Research, or the **Use existing population** card in Fashion and Ad Testing.
- In Fashion and Ad Testing, the list shows only populations that are complete and ready for the method you chose. If there is no suitable population, the card reads "No populations yet — create one first".
- Creating a population doesn't spend credits. Even so, to submit the form your balance must be at least 500 credits in General Research and at least 50 credits in Fashion and Ad Testing. For details, see [Credits](/en/docs/account/credits).

[Population library](/en/docs/populations/population-library) describes the **Populations** screen, which lists your saved populations.

## Differences in the flow

The setup steps are almost the same in all three verticals. Apart from Ad Testing skipping method selection, the difference to know about is the credit check before you start. In Fashion and Ad Testing, if your balance is below the estimated credits, the **Start** button on the **Research Preview** page stays disabled. In General Research, the button stays enabled, so check the **Credit Usage** value yourself before you start.

> [!WARNING]
> The Comparison method in General Research has no preview step: the **Next Step** button on the design screen starts the study immediately. Check the cost beforehand in the **Estimated cost** badge on the same screen.

## Choosing the right vertical

| Your situation | Vertical |
| --- | --- |
| You'll ask a price, feature, messaging or focus group question about a product, service or brand other than clothing. | General Research |
| You'll test a clothing product and want to see the results by archetype, shopping channel or style confidence. | Fashion |
| You'll compare two clothing products using their images. | Fashion |
| You'll measure whether an ad is watched to the end, how much it is liked and its effect on the brand. | Ad Testing |

When choosing, also keep the following in mind:

- **You can also use General Research for clothing products.** If you choose Fashion, you also get the archetypes, the **Fashion Attributes** tab and design screens adapted for clothing.
- **Set up studies you'll compare with each other in the same vertical.** Populations aren't shared across verticals; to run several methods with the same personas, all the studies need to be in the same vertical.
- **Ad Testing has no pricing method.** To measure the price of the product in the ad, set up a Price Analysis in General Research or Fashion; this needs a separate population in that vertical.

[Accuracy and limitations](/en/docs/getting-started/accuracy-and-limitations) explains how to interpret the results.

## Related pages

- [Starting a new study](/en/docs/research/new-study)
- [Choosing the right method](/en/docs/research/choosing-a-method)
- [Creating a population](/en/docs/populations/creating-a-population)
- [Comparison](/en/docs/research/comparison)
- [Ad Testing](/en/docs/research/ad-testing)