Local Search & Discovery

INTRODUCTION

For over 3 years I have observed and validated a problem, there is friction in how we search for things to do with our time. Plenty are the resources for exposing us to things to do and places to be, but limited are the ones that help instill confidence in our journey. Without confidence, it is unlikely we will become the planner. Friends, family, and strangers all need a planner to come together. Empowering the planner creates more opportunity for coming together. For 12 weeks I focused on how people search for local events and locations, and how to create simplicity around the entire process.

As we are currently a mobile centric culture, I chose an app as my medium to build this new product. My inspiration came from a wide variety of search tools, innovative UX/UI, Calm Technology, and the psychology behind how people take in information. Building this experience gave me a wider view on how to be inclusive and thorough in order for it to be entirely valuable to the user.

CORE EXPERIENCE: SEARCH & DISCOVERY

Two area in which my research recognized opportunity were filtering and, if properly constructed, a smart algorithm. A review of potential competitors revealed that filters are a prevalent tool in sorting through events and locations. However every example proved to be rather cold, strictly utilitarian. By exploring options, I arrived at an approach comparable to Apple Music or Airbnb.

I found that simple navigation, bold headers, and a clean template could help accentuate each listing in a unique way. This also puts more control into the hands of the business, a long-term strategy of this product.

For filters, an audit highlighted the need for price, dates (for events), group size, and location. A unique addition in this space was mood and friend affiliation. In order for users to quickly sort out activities outside their interests, adding their mood would serve up only activities that fit that criteria.

By narrowing down to 6 moods, I was able to conduct a controlled in-person test to further simplify. I arrived at 3 general moods for going out: Energetic, Mischievous, and Chill. The friend affiliation is possible by connecting through Facebook and interaction in the app. The results change based on whether friends have visited/attended the activity or have favorited the listing though the app.

The algorithm would be centered around a few factors that will ideally provide a feed that suggests listings that are contextual for the user. Those factors include: user selected interests, listings tied to friends, users location, and time of day. All of these working together in order to shorten the time spent searching and inserting confidence in the final decision.

BRANDING

The name, Happnn, centers around one simple question, “what’s happening?”. The color choices? Vibrant & exciting. The first 3 being triadic colors and the green serving as an action color. Overall, the app is centered around social fun and should reflect that tone without distracting from the purpose it serves. The logo is symbolic of how surrounded we are with amazing places to be, incorporating a softer gradient of colors that speak to the journey of narrowing in.

INTERACTION

In order to stand out amongst current market options, I stayed true to keeping information layered. This plays into Hick’s Law which states that the time it takes to make a decision increases with the number of complexity of choices. As users move through the feed on the home screen they are exposed to more without being overridden with information they do not yet need. But for a more specific search they are exposed to more information to allow for quick actions.

In both the home feed and the search tab, listings are broken up by events. Events play into the Isolation Effect where, when multiple similar objects are presented, the one that differs from the rest are more likely to be remembered. This not only guides users to more social outings but also allows event managers to highlight upcoming events with confidence that it will receive visibility.

Finally, the navigation of the app is segmented by types of search. Providing different means by which users can explore their area, it become more personalized to the dynamic needs that surface when one enters into the journey of search. The home feed leans more towards open discovery, the profile acts as a means of retrieval for past interaction, and the search as a avenue to more specifics inquiries.

CONCLUSION

As this product continues to grow, I intend on holding to the goal I set early on, to invigorate people to be fall back in love with being area knowledgable. This goal covers many of my topic points from earlier, inserting confidence, diminishing friction, and adding value to the user. I hope that by continuously testing and adapting to new information, local search & discovery will help people become the planner and ultimately increase socialization on a broad scale.