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August 2020

Work on mistakes with customer research.

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Fixing hidden problems through research.

Research is an integral part of the product development process, capable not only of finding and fixing invisible or non-obvious problems, but also of radically changing the vector of product development.

In our case, the research involved two products, similar in functionality but different in scale and importance to the company, so methods and hypotheses flowed seamlessly from one service to the other.

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Understanding customer needs.

Complex fintech research is an opportunity to see your own processes and products through customers' eyes, to understand what difficulties and inconveniences users face today, what are the consequences and what actions need to be taken to provide customers with a better and more modern service.

More often than not, fintech research is needed to: Identify unworkable or unused scripts or products; Identify inconvenient or unclear processes for the customer; Identify the customer profile, the target audience for the product or service.

Studying existing banking processes and a typical user profile helps: Prioritise the products and features that a particular user needs; Test processes and interfaces on audiences, understand the most critical issues and highlight changes that can be implemented quickly and with great impact; Accelerate engagement and understanding of the product, build «Friendliness» perceptions; Understand what's on the market, how much it costs and what problems aren't closed to find a new value and price proposition.

There are different ways of conducting research, but the most common are: In-depth interviews; Usability tests; Mystery shopping; Shadowing.

Assessment of resources for the study.

Before forming the objectives and describing the research methodology, it was necessary to understand whether we could manage on our own or whether it would be more convenient to involve someone from outside.

Searches and enquiries of the bank respondents have not given positive results, absolutely all the information about the clients was either under NDA which leads to stretching the already tight deadlines, or completely unavailable for data safety reasons, cutting off all communication with the clients.

Outsourcing was chosen, to be more precise Angry.LLC. We had a few meetings with them and received an offer which was not satisfactory for us, both in time and cost.

But soon McKinsey & Company came to our search, with the right team, tools, respondents and an attractive offer that we simply could not refuse.

Discussion on research methods and objectives.

The team that joined us immediately began by discussing research methods and objectives.

While we initially understood that we would only need in-depth interviews on business registration and usability tests on two products, the objectives were a little more complicated.

The bottom line was that we needed to: Assess VTB Start's current customer journey, pains and opportunities for improvement; Evaluate the usability and completeness of the upgraded VTB Start service; Understand the advantages or disadvantages of the functionality/interface of competing remote business registration services to improve the bank's internal solution.

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In addition to the objectives, we also formed hypotheses: Is speed of processing and current experience with the selected bank one of the main criteria for choosing a service for business registration? Is there a standard, among current services, business registration process? Do clients open an account at the same bank where they register their business? Does the seamless and convenient process of business registration, as well as additional features (chat rooms, non-banking services, etc.) affect the conversion of users into opening a current account, within the selected service?

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Evaluation of the service's usability and functionality.

When discussing the sample interview route, we agreed on the idea of not dividing sessions into in-depth interviews and usability tests, but to try to fit both methods into one meeting, if possible, in order to collect maximum data and reduce overall research time.

Flow of in-depth interviews represented: Introductions (Which included introducing and explaining the purpose of the interview, setting up the software, notifying the formality of the interview and requesting a recording); Narrative of the business from the respondent (Reasons for setting up and registering the company, opening a current account and presence at other banks as an individual); Main part with focus on details of business registration (Time spent for registration, stages, choosing the service, filling in the data and uploading documents, submitting documents to the tax authorities and their signing with the Enhanced Qualified Electronic Signature); General impressions from using the service (What you liked, what was especially useful and valuable, were there any wow-moments, and what was missing and could have made the experience better); Functionality hypothesis test, which was not discussed in the main part (More precisely, were there any questions to the service specialists' support and was there a need to contact the technical support, how did you choose the form of taxation and consulted earlier, were there any non-banking gifts offered when opening an account and was it important when choosing the service, and was there any experience with the chat-bot).

The usability test, which is the testing of a production/stage version or even a prototype, involved going through a customer journey, during which the interviewer had to ask questions to evaluate the usability, intuitiveness and functionality of the service.

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Problem detection and problem solving.

The research helped to find many regularities and solve many unnoticed problems, because we managed to collect a huge number of insights and comments from customers of 8 different banks, the leaders of which of course are Tinkoff Bank, Sberbank, Alfabank and Tochka Bank.

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Both VTB Start's showcase product and VTB's in-house solution were significantly influenced by the research. In the first case, it was possible to update the service, increase metrics, attract more customers and test hypotheses. In the second case, we optimised resources to implement the remaining functionality, as well as refine scenarios and communications with the client.

Article credits.

The list of persons reflects those who provided support and cooperation in the process of developing the feature and the article. Also the list indicates all those who are responsible for the content of the article.

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Aleksei Matveev

Lead Product Designer

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Svetlana Dementieva

Business Lead

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Ksenia Zakharchuk

Product Owner