How to sift through your research and pull out the right information and insights to guide your process.

Editor’s Note: This is part 2 in a series of posts outlining the Lenfest Lab’s step-by-step approach to UX research through the lens of our next project with The Philadelphia Inquirer about scaling reliable hyperlocal coverage.

Evaluate, sure. But first, Explore.

Before you can start the evaluation phase of your user experience research, you first need to explore lots of concepts related to your product idea and browse around at what your competitors are doing. This helps make sure you’re building something people will eventually want and also makes sure that you don’t build something that already exists. You can read about how we explored ideas here.

Step 2: Evaluate — How?

The second step in our user experience research process was to evaluate the results of our initial explorations and use what we learned to define the product.

The two research methods we used to explore were in-person interviews and competitive analysis—and the tools we used to evaluate them were survey analysis and a simple Post-it note exercise to help map and rank our priorities. We then used the output of those of those exercises to develop a persona of our average newsletter subscriber.

1. Survey analysis

With all thirty survey responses back from Fishtown residents, we could start to see some general trends in their behavior and news consumption habits. The top five insights below helped shape our prototyping process.

Insight #1: How most Fishtowners spend time in the neighborhood: Going out to eat or spending time at a park / walking

➤ How this insight translates to the product:

We will experiment with ways to incorporate restaurant and bar content and/or advertising in the newsletter given their popularity with residents. We’ll also spend extra time sourcing events and information about various parks and outdoor spaces in Fishtown.

Insight #2: What neighborhood news and information most Fishtowners are most interested in: Construction news and updates and neighborhood projects and neighborhood events, specifically art and design events.

➤ How this insight translates to the product:

We will tap into and automate content based on public data available about planned construction, demolition and development in the neighborhood. We will also take extra care to source information about neighborhood events that have art or design themes.

Insight #3: The types of neighborhood-specific data* most Fishtowners are most interested in: Locally grown food products and construction issues (i.e., building demolitions)

➤ How this insight translates to the product:

We will take a deeper dive into the data that Philadelphia makes available about locally grown food and construction in OpenDataPhilly and explore ways to automatically seed that content within the newsletter. We’ll also double our efforts to cover construction in the neighborhood from every angle.

Insight #4: How most Fishtowners currently get news and information: Social media (i.e. Twitter, Instagram)

➤ How this insight translates to the product:

We will pay close attention to the content shared on social media by neighborhood residents, businesses, elected officials and other hyperlocal voices and curate and add context to the most useful or interesting content or conversations within the newsletter.

Insight #5: Whether most Fishtowners are satisfied with the current way they get news and info: Most people feel somewhat satisfied, but still feel like they are missing things.

➤ How this insight translates to the product:

We will make sure that the newsletter pulls in the best and most compelling content from various sources that people already rely on to get information about the neighborhood — but put our focus on being comprehensive, so people can spend less time finding the information that really matters to them about where they live, work and spend time.

These survey results helped us to get to know our audience better and inform the types of news and information we’ll prioritize in the newsletter. You’ll see later in this post that the topics and information that resonated the most with residents — primarily construction, public parks, events and neighborhood history — are included in the prototypes we’ll test before launching.

Microtrends within the survey analysis

Beyond looking at the general trends of what residents care about, we also thought it would be interesting to parse the data to see if any preferences varied by length of residency or a resident’s age. We did this because we realized that general trends might not be enough to tell the full story about our audience, especially since Fishtown has had an influx of younger residents over the past decade.

We’ll keep these trends in our back pocket for after we launch the newsletter. If we see that any of these groups makes up a meaningful percentage our of subscribers, we might shift the content to adapt to their preferences.

🎂 Audience trends by Age

Residents ages 18–24

  • More interested in retail and business news than other groups
  • Most interested in insider info or tips from locals
  • Most interested in public data about locally grown food
  • Most familiar with bulletin boards in local businesses and walking around

Residents ages 25 -34

  • Very likely to attend community meetings

Residents ages 35–44

  • Most familiar with BillyPenn.comFacebook groups and social media

Residents ages 45–54

  • Most familiar with neighborhood organizations (i.e. Fishtown Neighbors Association)

Residents ages 55–64

  • Very likely to spend time at a park or walking outside
  • Very interested in events for kids and families
  • Much more interested in crime news
  • Very interested in data about parking tickets
  • Most familiar with neighborhood news apps (i.e. NextDoor)

Residents ages 65+

  • Very likely to go shopping in the neighborhood
  • Much more interested in crime news
  • Most familiar with newspapers (The Star and Inquirer) and crime report apps (i.e. Citizen)

🏡 Audience trends by Residency

Newer residents of 1–5 years

  • are more likely to go to local events than people who have lived in Fishtown 20+ years
  • are interested in updates about public spaces (playgrounds/parks)
  • are most interested in alternative transportation (i.e. bike trails, public transit routes and schedules)
  • are most familiar with Facebook groups

Residents of 5–10 years

  • are the most interested in local politics

Residents of 10–20 years

  • are more interested in public safety news than other groups
  • are most interested in social events/happy hours
  • are most familiar with neighborhood organizations (i.e. FNA)

Residents of 20+ years

  • are the most likely to spend time at a park or walking outside
  • are much more interested in crime news than other groups
  • are more interested in public safety news than other groups
  • are much more interested in events for kids and family
  • are most familiar with talking to friends and family
  • are familiar with newspapers

2. Newsletter persona

The survey results also allowed us to build a profile of a typical reader of our newsletter. To visualize this I created a “persona” of a reader. This profile will help our team stay focused on the reader’ needs as we continue to iterate on the newsletter.

3. Post-it note exercise

The goal for doing competitive analysis was to map elements that commonly appear in other popular neighborhood news and information products. We knew we might miss some things, and doing this landscape analysis would help us refine our strategy and expand our thinking. At the end of exercise we found ourselves with a long list of new ideas, but we needed to make sure that we only considered additions that would be valuable to our audience.

An important thing to do while doing competitive analysis is to not get overwhelmed. Competitive analysis can often lead to wanting to build all-the-things, but after looking around at your competition it’s critical to focus your work back on your original mission and be smart about what you decide to build or pursue.

To prioritize these new ideas we did a simple Post-It note exercise. The newsletter elements we already had in mind were written on orange Post-Its. The new ideas were written on yellow Post-Its and we put them side-by-side. This is how that looked:

Next we grouped the newsletter elements into categories, since up until this point we had mostly only discussed the content and advertising that would appear in the newsletter—but there was more to the newsletter equation. In addition to content and advertising, we saw other elements such as engagement calls to action, community information, subscriber information, event listings, other forms of monetization, reader surveys, feedback loops and general information. We also took note that some elements were more suited for websites and apps than newsletters. Here’s how the groupings of the categories looked:

Here are a few elements we decided to add to our newsletter prototype that we thought would appear to our average subscriber:

  • Bus schedules
  • An ‘Invite a friend’ feature
  • Weather outlook for the week
  • Call out to potential advertisers and businesses
  • Obituaries
  • Search (if we build a web component)

In the next post in the series we outline our third step: iterating on versions of the product idea to sharpen focus before launch. Click below to read.

Part 3| Iterate: A step-by-step guide to using UX research for local news product development.

The Lenfest Local Lab is a multidisciplinary product and user experience innovation team located in Philadelphia supported by The Lenfest Institute for Journalism.

The Lenfest Institute for Journalism is a non-profit organization whose mission is to develop and support sustainable business models for great local journalism. The Institute was founded in 2016 by entrepreneur H.F. (Gerry) Lenfest with the goal of helping transform the news industry in the digital age to ensure high-quality local journalism remains a cornerstone of democracy.

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