TURKISH-LANGUAGE RESEARCH / RESEARCH ARTICLE

Why would your customer use a chatbot?

In an online survey of 435 adults in Türkiye, what was associated with favourable attitudes towards chatbots? Perceived usefulness, ease of use and trust were associated with favourable attitudes; no significant relationship was found for novelty-seeking. For businesses, a chatbot’s value appears connected to the benefits, ease and trust customers perceive.

ACADEMIC WORK REVIEWED

Teknoloji Kabul Modeli Kapsamında Sohbet Robotlarına Yönelik Tüketici Kabulü Üzerine Bir Araştırma

Researchersİnci Onuk, Hilal Öztürk Küçük.

Pazarlama ve Pazarlama Araştırmaları Dergisi · 20 May 2026 · 19(2):370–397 · Source language: Turkish

Open the original publication Find on Google Scholar

ENGLISH REVIEW AND COMMENTARY: DIJITALPI

We explain the paper in plain English, discuss what it may mean for organisations and identify our own examples separately.

Read the explanation Go to 3 business examples

English review: 22 September 2026 · The source date appears in the citation above.

Editorial review draft

The source has been checked; the review still carries its original editorial status. DijitalPi did not conduct a customer experiment for this paper.

LET'S READ THE RESEARCH TOGETHER

We first explain the researchers' question, method and findings. We then discuss how to interpret the results, clearly separating DijitalPi's commentary from the source.

01 / WHAT DID THE RESEARCHERS WANT TO UNDERSTAND?

What helps customers accept a chatbot?

The study examines consumer attitudes towards chatbots.

Explaining the context · DijitalPi commentary

DijitalPi explanation: Opening a chat window does not mean a problem has been solved. Define the task you expect the customer to complete first.

02 / HOW WAS THE RESEARCH CONDUCTED?

How did they test the question?

An online survey uses a convenience sample of 435 adults living in Türkiye.

Understanding the method · DijitalPi commentary

DijitalPi explanation: A survey collects evaluations. An association alone cannot establish causation, and these participants are not a representative national sample.

03 / RESEARCH FINDINGS

Usefulness, ease and trust matter together

Usefulness, ease and trust relate to favourable attitudes; novelty-seeking shows no significant relationship.

Source: Original Turkish publication and source record ↗

04 / DIJITALPI'S EXPLANATION

How should we interpret these findings?

DijitalPi commentary: Explain what customers can accomplish rather than repeating the technology’s name. Check expectations against actual operation.

Review first-use obstacles alongside support records. Starting prompts, accurate information and human handover can be assessed separately.

05 / CONCLUSION AND OPEN QUESTIONS

What did we learn, and what do we still not know?

The survey does not prove a sales gain or causal effect.

Our question: which tasks can your customers complete without help? Investigate behaviour in your own product.

Return to the researchers' original publication

Original Turkish publication and source record

DIJITALPI'S APPLICATION COMMENTARY

How can we use this in marketing?

We created these scenarios to make the topic concrete. They are not cases from the paper or measured client results.

EXAMPLE 01

Product selection: where do I start?

A customer needs help choosing, but the chatbot only says hello.

Is its purpose clear?

Open the recommendation for example 01

Offer a concrete starting task

Suggest finding a product by budget or intended use. Track completion, unsuitable recommendations and abandoned steps. Starting a conversation alone is not success.

EXAMPLE 02

Delivery information: too many steps

The customer repeats a question to find one answer.

Is the process actually easy?

Open the recommendation for example 02

Find unnecessary steps

Try different versions of a delivery question. Record steps and what happens when information is missing. Make the route to a relevant page or a person clear.

EXAMPLE 03

Trust: a confident wrong answer

The assistant gives definite stock information from outdated data.

Is fluency mistaken for accuracy?

Open the recommendation for example 03

Make information limits visible

Compare answers with approved product data. Test the explanation and handover when current information is unavailable. Record false certainty and correction time separately.

TRY IT WITH YOUR TEAM

Try one customer task together

Choose product selection or delivery information. Track completion, steps, wrong answers and help requests. This proposed DijitalPi exercise is not a replication of the survey or a proven sales increase.

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Source and ownership

İnci Onuk, Hilal Öztürk Küçük.
Artvin Çoruh Üniversitesi, Lisansüstü Eğitim Enstitüsü; Artvin Çoruh Üniversitesi, Hopa İktisadi ve İdari Bilimler Fakültesi.

Pazarlama ve Pazarlama Araştırmaları Dergisi · 20 May 2026 · 19(2):370–397. Open the original publication · Find on Google Scholar

The academic work belongs to the researchers named above. This page contains DijitalPi's explanatory review and original business examples; it is not a full translation of the paper.

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