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December 2019

Portfolio verification: is it that easy to implement?

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Problems with profile moderation in the performer database.

With the expansion of the base of performers (actors and models), customers (casting directors and agents) were faced with a lack of profile moderation. People often came to their castings making up appearances and modifying photos.

The influx of complaints and suggestions prompted the team to adopt a portfolio verification system which took two years to develop, moving from one functionality to another, but first things first.

Key verification criteria.

Verification in itself is familiar to many people - it is a kind of verification, confirmation or method of proof by comparing some data with others to see if they are true. In our case, it meant checking the basic criteria - photographs, body parameters and appearance.

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Basic questions before implementation.

Basically, we had to answer a few questions: How will it help customers and talents? What will be the client's path? Who will moderate? What costs will appear? How will the product earn on this?

The answers to these questions subsequently formulated not only a common understanding of the task, but also the goals that the product was intended to achieve. Among them were the aggregation of talent in the media space, their quick search with filtering and access, security for both parties, affiliate programs and much more.

And while the team was working on this task, vast opportunities for changing the business model of the product were already visible on the horizon.

Launching the first version of Verification: Challenges and difficulties.

First and foremost, we always thought about the customers, how much this or that functionality would benefit them, so we were confident - verification would open up opportunities for customers that they didn't have before. From searching by appearance to reducing the cost of auditions.

We also cared about the ease of interaction on both sides. However, for the sake of speed, the first version of verification was launched without any pre-tests. For this reason, the performer's user flow was overgrown with many mediocre features, and its stages included not only ordering a service, paying for it, but also searching for a photographer, correspondence with the manager and setting up a display in the profile.

The product was supposed to make money from this, but simply having the moderators check the photo and settings would not have paid for all the costs of this task. Including that we would not have been able to give a guarantee to customers that a fraudster posing as someone else would not come to them.

This is why it was decided to partner with photo studios and close turnkey verification. This enabled us not only to control all the processes, but also to sell them at a more favourable price. This way, when ordering a service, the client received professional work from a photographer and a manager.

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While the photographer had only to take the photographs and measurements the manager had to check the measurements against the data from the questionnaire according to the guide-lines.

The problem with this version was the high costs, which meant paying for the promotion of the service, the studio, the time of the photographer, the manager and the whole team behind the development. In order to break even, sales had to be maintained at no less than 15 requests per week.

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Interface complexity and time costs.

The first version of Verification went live in the summer of 2018. It included a customised talent profile, studio feed, photographers' personal accounts, internal messenger and all sorts of edge cases.

The client's journey started with a timeline, where they would learn about the opportunities that would open up to them once they were verified.

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He was then given the opportunity to choose a studio and photographer from the available portfolios. After paying for the order, he was taken to a separate section where the status of the service was tracked.

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Inside the order was a messenger which was accessible not only to the client, but also to the photographer. It was used to agree on photography dates, assess the quality of photos and resolve any disputes involving the manager.

The last step was confirmation of publishing photos uploaded by the photographer in a separate layout on the client's profile.

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The whole process took up to 3-5 days and although the service was attractive, time was not the only drawback. Customers got lost in the interface because of the multitude of features that had no effect on profile verification.

New Guidelines and Recommendations.

We weren't going to stop there, which is why after the first release we went straight into fixing major bugs. So, in the winter of 2019, a verification update came out.

In the six months we had, we made the decision to terminate partnerships with outsourced studios and photographers due to their lack of interest in the outcome. Thus, our team was supplemented by a full-time photographer with his own studio. In addition to updating the photographers' work guideline and checking managers, guidelines were added for clients on where to do what and how to do it.

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CJMs were built that opened eyes to the imperfections of the interface and scripts. Thanks to them, ideas to simplify the functionality went further than discussions and went into the new release.

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However, due to the seasonality of castings, verification sales started to drop, the service was starting to make a loss, and this prompted the team to think further.

Increase in organic traffic and attendance.

The summer of 2019 gave a new round of development to the service. This time we took the time to usability tests, in-depth interviews, surveys and collecting feedback from all corners of support. In addition to understanding what clients expected from us in the new version, we decided to slightly change the vector we had been following before.

Whereas in the second version we gave up on outsourced photographers, in the third version we gave up on inhouse. Early hypotheses on how we could build client trust through in-house verification centres and in-house photographers did not live up to expectations and proved to be expensive.

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A year after the initial release, customers began to become more comfortable with the slight difference between the data from the questionnaire and reality, which led us to hypothesise self-made shoots and personal portfolios.

Under the new format of verification, we still had a manager, but now in the person of technical support who checked self-made photos for correctness by elementary recommendations (Quality of photo, Number of photos, Posing).

In addition to the publication of images in the database of professionals we decided to offer a detached personal website portfolio without branding, linked to the product only with a subdomain and a mini footer.

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The demand for this service exceeded the expectations of the team, with more than 20 requests per week. The new concept didn't just simplify the interaction to just paying for the service, it also allowed clients to publish the link on their social networks and agencies. This helped us increase our monthly organic traffic and traffic by a factor of 3 to ~8000 visits and 1.5 to ~15000 unique users respectively.

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Improved user experience.

The latest release in late Fall 2019 offloaded tech support in terms of having to check photos. Henceforth, recommendations were given directly when completing professions. This measure was only possible because of the update of the profiles.

The profiles, references, and layouts of personal websites with portfolios were also updated.

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Tools for communicating with customers and performers.

At the end of the day, we had working versions of portfolios for performers to share with agents and casting directors.

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And we also had a polished process for registering a professional as a verification specialist to interact with performers.

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Figma screens.

You can see all the screens and flows that our team has developed in the Figma preview or by clicking on this link. The screens were developed before the design team switched to Auto-Layouts, which were added to Figma in November 2020.

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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Tatiana Shestakova

Marketing Manager

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Olia Chupakhina

Product designer

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Dima Melentev

UX Researcher / UX Architect

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Artem Taranov

Head of Product

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Dmitry Kuznetsov

Project Manager