Culture Booster

Sharing feedback, making goals, increasing collaboration, and capturing innovation.

Role: UX/UI Designer, UX Researcher

Methods: Competitive Audit, Stakeholder Interview, User Persona, User Journey Map, Low Fidelity Wireframes, Feature Concepts, Kano Analysis, Annotated Designs, Stakehoder Report.

Tools: Figma, Figjam, Excalidraw, Google Sheets, Zoom.

Client: Culture Booster is a local, bootstrapped, B2B startup organization on a mission to improve people’s work lives. Their founder believes that the best way to achieve this is by helping organizations create environments that are conducive to people bringing their best selves to work each day—enabling employees to consistently give their head, heart, and hands to their work and workplace. To achieve this vision, they’ve created an employee engagement software (EES) platform that helps organizations share feedback, improve collaboration, make goals, and capture innovation amongst their employees. Since their launch in June 2021, Culture Booster’s client roster has expanded to include many notable organizations, including Headway Emotional Health Services, People Serving People, and St. Paul Public Schools.

The Problem

Culture Booster is a new startup with big goals. They need to better understand their users so they can develop new features that encourage employee engagement, innovation and growth. Culture booster’s DEV team has allotted 20points to this project. They’d like to focus on two key areas:

Stars: Stars serves as a recognition tool. It is well-understood that positive reinforcement is necessary for motivation on the job and yet it has a woefully low presence in most organizations. The overall goal of Stars is to ensure that the feedback given “sticks” or otherwise resonates with those who receive it. It should be easy for recognition to be delivered from every direction in the organization.

Suggestions: Essentially a virtual, democratized suggestion box. Suggestions is more of a differentiator to the platform than Stars (which the EES market is saturated with, conceptually) and is intended to be a way to capture employee ideas and encourage innovation. Borne out of powerful results seen when using this during consulting days, the founder envisions this as a multi-step, highly visual sequence that guides employees through the process of suggesting an idea.

How can we design Culture Booster’s new “Stars” and “Suggestions” features to help people within an organization feel valued, recognized, and heard to better empower people in the workplace and set Culture Booster apart from other ESS tools?

The Competitive Audit

To gain a better understanding of general ESS tool functionality, my team and I explored Culture Booster’s competition and documented the spectrum of their features. We discussed key features and documented how well competitors performed in each area.

Our findings gathered through this competitive audit helped inform our priorities moving forward with Stars and Suggestions.

The Stakeholder Meeting

To gain a better understanding of Culture Booster’s primary users and to detail project goals, our team met with Culture Booster’s founder, Stephen Moore. We learned he’s passionate about creating a meaningful workplace and a supportive, innovative, and transparent workplace culture. He made his primary users and project goals known:

Primary Users

  • Executives - looking for data to inform their strategy

  • Managers - looking for support to reach their goals

  • Employees - looking for true empowerment to increase engagement

Project Goals:

  • Design Stars and Suggestions features based on user’s needs

  • Gain insights into the site’s potential pain points and opportunities

  • Use existing feature successes as a guide to building Stars and Suggestions

  • Do not exceed a 20pt DEV time allotment

The User Journey Map

A persona was created to help identify and empathize with Culture Booster’s primary users. Placing this persona within a specific scenario helped to gain perspective of the user when interacting with Culture Booster, and identify pain points to improve the product and the user’s overall experience.

Meet Pat!

Pat Martinez is an office administrator at a public elementary school in Saint Paul, Minnesota. She’s a hard worker who cares deeply about her job and for the students at her school. She has two cats, loves puzzles, and walks outside every day at lunch.

Scenario:
March is reading month! The school district is encouraging students to read a series of books this March. Pat noticed some families are concerned with the pricing of these books. Being a proactive employee, she begins brainstorming ways to encourage reading month participation, while keeping it low-cost to families. Pat would like to bring these ideas to the attention of her boss.

Pat’s persona informed the user journey map by focusing on a realistic micro-interaction with Culture Booster, within the Saint Paul Public Schools system. Plotting this journey helped to convey all the steps within the user’s process and the user’s experience (actions, thoughts, emotions) during each of those steps. I created a journey of before and after the new features are implemented.

Low Fidelity Wireframes

Using the information gathered through competitive analysis, stakeholder meeting, and journey mapping, it was time to start designing. Designs began with sketching low-fidelity wireframes based on Culture Booster’s new features: Stars and Suggestions. Excalidraw made the digital sketching process easy.

Feature Cards

I placed 5 design ideas into feature cards with a short description below each image. I focused more on suggestions, since this is Culture Booster’s differentiating feature from other similar companies.

The team compiled all of their ideas into a Figjam board before meeting again with Culture Booster’s founder and his DEV team. The lead developer helped us gauge the development timeline for building out each design idea. He assigned each design points according to their front-end and back-end time frames. Our designs were limited to 20 DEV points, roughly equal to one month of development work.

The Survey

As a team, we prioritized 10 key design features and included them in a Kano Analysis survey. This survey was sent to 7 current Culture Booster customers as a way to get their feedback on the implementation of new features. They were asked:

  • How would you feel if this feature was present? (Like, Expect, Neutral, Tolerate, Dislike)

  • How would you feel if this feature was absent? (Like, Expect, Neutral, Tolerate, Dislike)

  • How important is it to you that this feature is present? (On a scale of 1 to 7, 1 being not important)

The results of this survey were overall positive! Customers seem excited for the Stars and Suggestions rollout. We transferred their survey responses into Kano Analysis tables, one for each feature. Example shown for Feature 6, Suggestions Page:

A green dot indicates each customer’s reaction to the feature in question. The table shows Feature 6 is a combination of “Performance, “Attractive”, and “Must-Be” results. Result meanings detailed below:

  • Performance - likes having the feature and dislike not having it

  • Attractive - likes having a feature that is not expected

  • Must-be - customer dislikes not having a feature

  • Indifferent - neutral toward feature

  • Questionable - contradictory response pairs about a feature

The top right corner is where positive reactions lie, so we know Feature 6 is a hit! The Kano Analysis revealed clear insights into customers preferences with these features, which made decision making easy when selecting a few key features to move on to a higher-fidelity state.

The Annotated Wireframes

To relay these clear insights and designs to Culture Booster’s DEV team, I turned 5 key features into annotated, high-fidelity wireframes.

Since the Suggestions features came back with high likeability and importance ratings, I created most of my wirefreames around Suggestions, and one wireframe dedicated to Stars. The 5 Features selected were:

  1. Suggestions Dashboard (8 pt)

  2. Suggestions Expand Idea (2 pt)

  3. Suggestions Under Review (4 pt)

  4. Suggestions History (4 pt)

  5. Stars Confetti (2 pt)

These 5 features = 20 allotted DEV points. I designed wireframes in Figma for each new feature and described their functionality and meaning with annotations. Then I compiled them into a stakeholder annotated wireframe report. Included are insights from Suggestions Dashboard and Stars Confetti features. Click link below to view full report.

The Conclusion

Culture Booster’s new Suggestions and Stars features will likely be appreciated by their primary users, and enhance their site to significantly set them apart from competition. Kano Analysis showed the Suggestions wireframes were important to users, and rated as “Attractive” and “Performance” features (meaning current users like having the feature, and dislike not having them). The Stars Confetti feature is less important to users, but still deemed an “Attractive” feature (meaning users will like it, but not expect it).

It should be noted that these annotated wireframes were created to meet a DEV time allotment of 20 points, and some additional features should also be taken into consideration that were highly rated by users in the Kano Analysis.

Next Steps:

  • Meet with DEV team to discuss which features to prioritize.

  • Create prototypes of prioritized features and test with users before before finalizing and launching Suggestions and Stars.