What this lesson covers
Where does my audience actually spend attention, and how does each platform decide what they see?
- Platform selection by audience and goal
- Where social fits when demand already exists, and where it creates demand
- Local and professional networks: Nextdoor, community groups and LinkedIn
- How recommendation algorithms rank content
- Interest graphs vs. social graphs
- Organic reach and platform volatility
- Matching platform to journey stage
Why this matters now
Placeholder for the lesson's opening story: a vivid, real moment where a marketer or small-business owner meets this exact problem.
You can now
Choose the platforms that fit your audience and goal, and read how each one decides who sees your content.
For your own business or employer: Put the business where its customers already spend attention, not everywhere at once.
Industry case studies
Industry Case
Tepary Kitchen
Local restaurant · Local and offline
Case update 5.1
Module 5 of 8 in this case
Forty-eight thousand views, zero Tuesdays
Miguel's niece runs into the kitchen holding her phone. The cheese crisp reel has 48,000 views, the most Tepary has ever had. Everybody cheers.
Then Miguel opens the insights. Ninety-one percent of the views came from outside the state. Not one of those people will ever sit at a Tepary table on a Tuesday.
That's the interest graph at work. Instagram and TikTok show content to anyone who likes food videos, wherever they live. It's powerful for a brand that ships everywhere. For a restaurant that needs neighbors within three miles, a viral reel can be applause from the wrong audience.
So Rosa and Miguel ask where the weeknight neighbors actually spend attention, and the answer is closer to home. On Nextdoor and in two neighborhood groups, people ask the same questions every week: “Where's a good quiet dinner around here?” “Anywhere kid-friendly that isn't a chain?” That's the social graph: neighbors recommending to neighbors.
The new mix has three parts. Nextdoor and the neighborhood groups, where Miguel shows up as the owner, follows each group's rules, answers questions and invites people in, without spamming. Instagram, aimed at the city with location tags and local accounts, for discovery. And posts on the Google Business Profile, where the hungry searchers already are.
The 48,000 views were exciting. Twelve neighbors who come back every Tuesday would be worth more.
Artifact added
Platform choice and content mix for a three-mile radius
Industry Case
Bajada Plumbing & Drain
Local home service · Demand capture
Case update 5.1
Module 5 of 8 in this case
“Anyone know a plumber who actually answers?”
Nobody chooses an emergency plumber on social media at 2 a.m. But the planned decisions, and the recommendations that steer them, happen in neighborhood threads every week: “Anyone know a plumber who actually answers?”
Bajada's customers are in those threads. Bajada isn't. So Carmen claims the business page on Nextdoor and in the local groups that allow it. Ray answers do-it-yourself questions honestly, even when the answer is “you don't need a plumber for that.” And when neighbors ask for a recommendation, Bajada Care members are invited to share their experience, in their own words. Bajada never writes it for them.
Artifact added
Platform choice: neighborhood networks for trust, not emergencies
Industry Case
Ocotillo & Ash
DTC fashion · Demand creation
Case update 5.1
Module 5 of 8 in this case
Where strangers find you
For Ocotillo & Ash, the interest graph is the whole point. Andrea doesn't follow Lena, but the algorithm can show her a video about surviving a 108-degree commute because she watches videos like it.
So Lena puts short video on Instagram and TikTok first, for demand creation, and adds Pinterest, where women plan summer wardrobes and desert-wedding outfits weeks ahead.
She also writes one warning on her strategy page. Organic reach can disappear with one algorithm change. Every post should give people a reason to join the list she'll build in Module 7, because a list is the one audience no platform can take away.
Artifact added
Platform choice: Instagram and TikTok for discovery, Pinterest for planning
Listen
Podcast · Move at the Speed of Culture
How Algorithms Reward Cultural Relevance
Listen for why posting more often isn't the same as being relevant to the people a platform shows your content to.
More from Move at the Speed of Culture →
Listen online: moveatthespeedofculture.com/how-algorithms-reward-cultural-relevance
Key terms
- Algorithm: The set of rules and machine-learning models a platform uses to decide which content each person sees and in what order.
- Community group: An online group, such as a Facebook Group, organized around a place, interest or identity.
- Engagement: Actions people take on content, such as likes, comments, shares, saves and watch time.
- Interest graph: The map of topics a user has shown interest in through their behavior. Interest-graph feeds, like TikTok's For You page, show content from anyone the algorithm thinks they will like.
- LinkedIn: A professional social network used for careers, business networking and B2B (business-to-business) marketing.
- Nextdoor: A neighborhood-based social network where verified residents share local news and recommendations, important for many local businesses.
- Organic reach: The number of people who see content without paid promotion.
- Platform selection: Choosing which social platforms to use based on where the target audience spends attention and what the business is trying to achieve.
- Platform volatility: The risk that a platform changes its algorithm, rules or features, or loses users, which can wipe out a business's reach overnight.
- Recommendation algorithm: An algorithm that suggests content to a person based on predictions of what they will watch, like, share or comment on.
- Social graph: The network of people a user is connected to. Social-graph feeds mainly show content from friends and accounts the user follows.