Platform Specific Strategies

Defining Social Media Platforms

Social media platforms are defined as digital networks that enable users to create, share, and engage with content. They serve as the infrastructure for online interactions and brand–audience connections. The strategic value of a platform depends on how its unique properties align with marketing objectives.

Online Communities and Their Influence

An online community is a group of users who interact around shared interests, identities, or goals on a platform. These communities shape:

• Content creation – what content is produced and how it resonates with members.
• Engagement – the depth and frequency of interactions (likes, comments, shares).
• Brand strategy – how brands position themselves within the community’s norms, language, and expectations.

Community dynamics directly affect virality and long-term loyalty; content that aligns with community values spreads further and faster.

Network Structure and its Effects

The network structure of a platform (e.g., graph density, algorithm-driven feeds, connection types like symmetric vs. asymmetric) determines:

• Content reach – how far a post travels beyond immediate followers.
• Virality – the likelihood of rapid, exponential sharing.
• Influence – which users or content types gain authority and visibility.

Understanding network structure allows marketers to predict performance and adjust posting strategies accordingly.

Comparing Major Social Media Platforms

Platforms differ along key dimensions. The module compares them using:

Exam tip: When comparing platforms, map each dimension against your campaign objectives. A platform strong in user demographics but weak in engagement style may not deliver conversions.

Constructing Buyer Personas and Platform Alignment

A buyer persona is a semi‑fictional representation of your ideal customer based on demographic and behavioral data. The module teaches how to:

• Detail personas (age, interests, pain points, online habits).
• Align each persona with platforms where those users are most active.
• Tailor campaign strategies to the persona–platform fit.

Selecting the Right Platform: Strategic Thinking

Platform selection is a strategic decision driven by three factors:

• Audience behavior – where they spend time, what they do there, how they engage.
• Content type – the format that best communicates the message (e.g., video for tutorials, text for thought leadership).
• Campaign goals – awareness, conversion, retention, or community building.

The module applies critical thinking to integrate these factors into a coherent, platform‑specific strategy.

Key Takeaways

• Social media platforms are digital networks; online communities within them drive content and brand strategy.
• Network structure influences reach, virality, and influence – essential for planning.
• Compare platforms on demographics, content formats, engagement styles, and marketing goals.
• Buyer personas bridge audience understanding to platform selection.
• The right platform emerges from aligning audience behavior, content type, and campaign goals.
• No single platform is universally best; strategic fit is everything.

The Community Ecosystem Mindset

Social media is first and foremost a community ecosystem — not a distribution channel. The traditional megaphone approach treats platforms like Facebook, Instagram, or TikTok as one‑way broadcast tools: brands push content, assume passive reception, and focus on reach and frequency. This view is flawed because it ignores the participatory, interactive nature of social media.

[Megaphone mindset] (outdated)
  Brand posts → Audience passively receives
  Focus: reach, frequency, one‑way broadcast

[Community ecosystem mindset] (correct)
  Brand participates → Community interacts, creates, converses
  Focus: co‑creation, norms, belonging, two‑way engagement

What Is an Online Community?

An online community is a group of individuals who interact regularly in a shared digital space, bonding over common interests, goals, values, or experiences. They create, share, and respond to content collaboratively, and over time establish norms, roles, and rituals.

Characteristics of an online community:

Community Logic

Community logic is the unwritten set of expectations, behaviors, tones, and cultural signals that govern how people interact within a platform or niche. It is implicit — not posted as guidelines, but intuitively understood by members.

Platform Examples

Exam tip: A brand that succeeds on one platform may fail on another if it ignores community logic. Example: Zomato’s sassy tone works on Twitter but would tank on LinkedIn.

Case: Skincare Brand

• On Instagram → a picture‑perfect flat lay works.
• On TikTok → a funny, relatable “pimple at the wrong time” skit may go viral; the polished post would be ignored.

Why Community Logic Matters for Marketers

Ignoring community logic leads to:

• Content falling flat (wrong tone, wrong timing).
• Audience backlash (seen as out of touch).
• Wasted budget (content does not feel native).

Best practice – instead of interrupting:

1. Observe and learn the community’s values, norms, and cultural language.
2. Contribute — don’t just broadcast. Interruptions must be rare and well‑timed.
3. Match tone, timing, and norms.
4. Create space for interaction — promote two‑way conversation.

Real‑World Examples

Duolingo on TikTok

• Brand voice: humorous, self‑aware, weird — aligned with TikTok humor.
• Mascot (Duo the owl) does chaotic dances, parodies, trends; replies to comments.
• Rarely posts directly about language learning.
• Outcome: millions of followers, high engagement, viral recognition – all without heavy ad spend.
• They became part of the community, not just a poster.

Glossier

• Started with Into the Gloss blog, spotlighting real people’s routines.
• Encouraged followers to co‑create products (e.g., “What do you want in a cleanser?”).
• Turned customers into brand ambassadors via a rep program.
• Outcome: >80% of sales came from organic social interactions – community trust built before product push.

Platform Community Logics

The platform examples summarise community values as follows:

• Facebook – purpose‑driven groups.
• Reddit – topic‑based subreddits with strong norms.
• Instagram – aesthetics, curation.
• TikTok – realness, humor, trends.
• LinkedIn – professional thought leadership.
• Twitter/X – snark, speed, opinion.

Each platform’s community logic determines what content feels native and what backfires.

Key takeaways

• Social media is a community ecosystem, not a megaphone or distribution channel.
• Online communities share purpose, interaction, UGC, norms, and belonging.
• Community logic is the unwritten set of platform‑specific expectations (e.g., polished vs. raw).
• Ignoring logic → content fails; respecting it → co‑creation and loyalty.
• Duolingo and Glossier exemplify brands that became part of the community rather than interrupting it.
• Marketers should ask: How can we contribute meaningfully to this conversation?

What are Networks

Social media platforms are not just publishing tools—they are networks that determine how content spreads. A network is a graph composed of nodes connected by edges.

• Nodes: The participants – people, pages, brands, influencers, groups. Each node creates, shares, or amplifies content.
• Edges: The relationships – friendships, follows, group memberships, likes, mentions, comments, content inspirations, tags.

Network structure impacts who sees content, how fast it spreads, how far it goes, and who influences whom.

Example nodes: User 1 (a regular, low-activity user), an influencer (popular figure followed by many), a brand page, a group member active in a niche interest.

Example edges: A user following an influencer, a brand tagged in an influencer’s post, a user sharing content to a friend, a brand posting in a group where members engage.

Types of Networks

Different platforms exhibit different network structures. Choosing the right platform requires understanding these structures and their strategic implications.

1. Centralized Network

Intuition: A few powerful nodes (influencers, brand pages) act as central hubs. Most users are connected to content through these hubs. Content flows top-down from hub to periphery.

Characteristics:

• Content visibility depends on influencer endorsement.
• Brands pay for influencer reach or rely on celebrities.
• Top-down distribution system.

Platform examples: Instagram, YouTube (when popularity is driven by visibility).

Campaign example: Nike’s “You Can’t Stop Us” campaign. Built around sports icons (Serena Williams, LeBron James) and released on YouTube/Instagram. Content was shared by Nike itself and influencer pages. Result: 50 million+ views in 48 hours via large node amplification (central to peripheral audience).

2. Decentralized Network

Intuition: Content flows through multiple medium-sized communities rather than a single hub. Users cluster around shared interests; information is less filtered through a few celebrities.

Characteristics:

• Several clusters (sub-communities) each with their own micro‑influencers or groups.
• Brands insert themselves into niche communities or leverage micro‑influencers.
• Information disseminates through these parallel channels.

Platform examples: Facebook groups, Reddit subreddits, Telegram channels, niche forums.

Campaign example: Glossier’s growth through beauty forums and user‑generated content. Instead of A‑list influencers, Glossier encouraged regular users to share content and reviews on Facebook groups, subreddits like r/SkincareAddiction, and beauty blogs. They created a “Glossier Rep” program to reward loyal community members. Content seeded in multiple independent communities.

3. Distributed Network

Intuition: Peer‑to‑peer communication with no central hub or hierarchy. Every user has equal power to send or receive content.

Characteristics:

• No central hub or hierarchy.
• Content spreads through direct messaging.
• Best for hyper‑personalized communication.
• Virality depends on forwarding chain reactions.

Platform examples: WhatsApp, Signal, email, Snapchat (when tab‑based).

Campaign example: Spotify Wrapped – users receive a personalized wrap‑up of listening habits and share it via stories and private messaging. Zomato’s end‑of‑year WhatsApp story posts on most‑ordered dishes. Both campaigns rely on millions of micro‑sharing events with no central node.

Why Network Structure Matters for Marketers

Network structure affects:

• Reach – Can you reach many via few nodes (centralized) or need multiple communities (decentralized) or micro events (distributed)?
• Virality – Is the campaign built to be forwarded (distributed) or shared by influencers (centralized)?
• Influence strategy – Do you need influencers (centralized), ambassadors (decentralized), or grassroots sharing (distributed)?
• Paid vs. organic – Centralized often involves paid influencer reach; decentralized relies on organic community seeding; distributed depends on user forwarding.

Exam tip: When asked “Which platform should I use?”, first evaluate the network structure of the platform (centralized, decentralized, distributed) and match it to your campaign objective (awareness, trust, personal sharing).

Key takeaways – What are Networks

• Networks consist of nodes (participants) and edges (relationships).
• Network structure determines content visibility, spread speed, reach, and influence.
• Social media platforms are networks – think of them as graphs.

Key takeaways – Types of Networks

• Centralized: Few powerful hubs; top‑down; Instagram/YouTube. Best for brand awareness.
• Decentralized: Multiple medium‑sized communities; bottom‑up; Facebook groups/Reddit. Best for community trust.
• Distributed: Peer‑to‑peer; no hierarchy; WhatsApp/Signal. Best for personal sharing.
• Each structure affects reach, virality, influence strategy, and platform choice.

Network Structure of TikTok and Instagram

Network structure determines how content is discovered, shared, and goes viral. Two dominant models emerge: centralized (follower-dependent) and decentralized (content-dependent). TikTok leans toward a hybrid but primarily decentralized structure; Instagram is centralized.

Definitions

• Centralized network: Content visibility is tied to the creator's follower base. Popularity concentrates among users with many connections.
• Decentralized network: Content spreads based on its own merit and algorithmic signals, independent of a user's follower count. Anyone can achieve high reach.
• Hybrid: Elements of both, but TikTok’s core discovery mechanism (the For You Page) is decentralized.

Decentralized discovery means a piece of content is surfaced to audiences based on engagement signals (watch time, likes, replays) rather than pre-existing social ties. This lowers the barrier to virality.

Platform comparison

Worked examples

Khaby Lame (TikTok)

• Former factory worker, started creating silent mocking videos during COVID.
• Had zero followers at the start; his content reached millions via the For You Page.
• Rose to become one of the top-followed creators globally purely on content appeal and engagement.

Boat Lifestyle (brand campaign)

• On TikTok: Launched a dance challenge with micro‑influencers; regular users recreated it. Within 3 days → 210M+ views. Zero reliance on Boat’s own followers.
• On Instagram: Posted polished product photos + influencer posts. Engagement came mostly from existing followers, with limited discovery beyond that.

Why network structure matters for strategy

The same brand must adapt its strategy to each platform’s network structure. TikTok rewards content-first approaches (decentralized), while Instagram rewards community-building and follower growth (centralized). Reach, virality, and influence objectives drive platform choice.

Key takeaways

• TikTok’s algorithm enables decentralized discovery; Instagram remains follower‑centric.
• On TikTok, virality depends on engagement signals (watch time, replays), not follower count.
• On Instagram, visibility still correlates strongly with follower size and brand loyalty.
• A single campaign can achieve wildly different results across platforms if the strategy ignores network structure.
• Decentralized networks lower the entry barrier for new creators and micro‑influencers.

Virality of Content

Virality describes content that spreads rapidly and widely through a social network, amplified by user-to-user sharing, community participation, and platform algorithms. It reaches audiences far beyond the original intended scope. It is not simply about high view counts — the key is how content travels across networks and accelerates through communities.

Network Perspective: The Structural Path

Social media platforms are networks composed of:

• Nodes — users, influencers, brands
• Edges — relationships (follows, mentions, shares, likes)
• Clusters — groups of users who interact frequently (often communities in a decentralized network)

The virality process through a network follows a cascade:

1. A node (person or brand) posts content.
2. Content reaches connected edges (followers, friends) through shares and comments.
3. Engagement (likes, shares, comments) prompts the algorithm to boost the content.
4. The content reaches a central or highly connected node (influencer, niche leader) that can bridge to other clusters.
5. From there, content cascades across the network, jumping from one community to the next — producing the exponential sharing curve recognized as virality.

Community Perspective: The Emotional Engine

Every platform contains micro-communities — groups united by shared interests, values, or identity. These communities act as amplifiers for content they relate to.

• High engagement within a community (likes, retweets, fan edits, fast-paced sharing culture).
• Strong emotional connection to the content drives voluntary sharing.
• As content crosses into other communities, it gains cross-community virality.

Example: A meme that starts inside a K-pop fandom on X (Twitter) quickly spreads within that community due to shared interest, then jumps to fashion fans or Gen Z humour pages, achieving wider reach.

Combining Both Lenses

A table reconciles the two perspectives:

Virality is best understood as the interplay: the network provides the logistical pathway; the community provides the motivational fuel.

Worked Example: Nike “You Can’t Stop Us” Campaign

• Network structure: Centralized launch via official Nike post and influencer accounts (central nodes). The content spread to followers, then algorithm boost, then across clusters.
• Community activation: Sports fans, social justice advocates, and fitness communities felt emotionally invested in the ad’s message. They re-shared, commented, made reaction videos.
• Result: Campaign went viral across Twitter, Instagram, YouTube — tens of millions of views within days.

This illustrates that content starts from a single originator, spreads to followers and influencers, gets boosted by algorithms, and reaches new nodes across different audiences and communities — the hallmark of true virality.

Exam tip: Virality is not random. You must explain both the network mechanisms (nodes, edges, algorithm boost, cluster bridging) and the community drivers (emotional resonance, shared identity, social proof). The Nike campaign is a classic example to combine both lenses.

Key Takeaways

• Content goes viral through a network cascade: node → edges → algorithm boost → central node → cluster bridging → exponential sharing.
• Communities amplify content via emotional investment, fast sharing culture, and cross-community migration.
• Two complementary perspectives: network (structural/algorithmic) and community (emotional/cultural) are both necessary for full explanation.
• Viral content is typically emotionally charged, easy to share, and culturally/socially relevant.
• To design for virality: identify connectors (influencers, active group members), understand which communities care, and trigger actionable emotions (humour, outrage, pride).

Target Audience Differences Across Platforms

Major social media platforms—Facebook, Instagram, Twitter (X), LinkedIn, TikTok, YouTube—differ along the basic targeting parameters: demographic, psychographic, and behavioral. Understanding these differences lets brands choose the right platform for a campaign.

Facebook

• Demographic: Slightly older audience; largest segment 25–44 years.
• Psychographic: Community‑driven, family‑focused, values brand trust and consistency; uses Facebook for news consumption.
• Behavioral: Joins groups for hobbies/local events; responds well to long‑form content, personal stories, live videos, promotions.
• Example: Amul (India) uses nostalgic comic‑style storytelling to engage family‑based audiences during cultural festivals, IPL, etc. It runs contests asking users to share stories of cooking healthy meals with Amul products.

Instagram

• Demographic: Younger audience (18–34), heavily urbanized, mobile‑first.
• Psychographic: Trend‑conscious, highly visual, values aesthetics and self‑expression.
• Behavioral: Scrolls Reels for inspiration/entertainment; follows influencers for fashion, food, travel; likes and saves stories; shares Reels with friends.
• Example: Tanishq Jewellery launched a wedding‑story series on Instagram Reels, encouraging millennials to share their wedding experiences, leveraging glamour and emotion.

Twitter (X)

• Demographic: Older side (25–49, largest chunk), metro‑dwelling, media‑savvy, professionals.
• Psychographic: Curious, opinionated, follows politics/technology/news, tech‑forward.
• Behavioral: Uses hashtags to follow real‑time trends; engages in debates, customer‑service conversations with brands; quick to share thoughts and links.
• Example: Swiggy and Zomato tweet food puns, react humorously to trending news, keeping the brand top‑of‑mind during viral moments.

LinkedIn

• Demographic: Oldest demographic (largest 30–55); working professionals, job seekers, entrepreneurs, students.
• Psychographic: Career‑oriented, knowledge‑seeking, credibility‑driven.
• Behavioral: Seeks leadership insights, connects for hiring/B2B partnerships, engages with thought‑leadership content.
• Example: Brands like Unilever (e.g., vPro) post about corporate innovations and DEI initiatives to position themselves as a future‑ready workplace.

TikTok

• Demographic: Youngest audience (16–30), Gen Z and young millennials.
• Psychographic: Values humor, authenticity, trends, creativity.
• Behavioral: Recreates viral audio trends; follows micro‑influencers; prefers quick, authentic storytelling; UGC challenges.
• Example: Boat (lifestyle) collaborated with music influencers to launch dance challenges showcasing headphone bass features.

YouTube

• Demographic: Broad appeal – toddlers to retirees.
• Psychographic: Curious learners, DIY‑ers, infotainment seekers, entertainment seekers.
• Behavioral: Watches long‑form tutorials/vlogs; uses search for “how‑to” queries and reviews; subscribes to channels for regular updates; increasingly used as a search engine.
• Example: Mamaearth creates explainer videos and reviews about toxic‑free skincare, building trust through transparency (e.g., beauty pageant contestants share routines).

Key Takeaways

• Each platform attracts a distinct audience in age, psychographics, and behavior.
• Facebook = older, family‑focused, long‑form, trust‑based.
• Instagram = young, visual, trend‑driven, influencer‑heavy.
• Twitter = opinionated, real‑time, conversational.
• LinkedIn = professional, career‑oriented, B2B.
• TikTok = youngest, humorous, authentic, UGC challenges.
• YouTube = broad multigenerational appeal, educational/entertainment, long‑form.
• Matching platform audience to brand persona is critical for campaign success.

Differences Across Platforms from a Buyer Persona Lens

A buyer persona is a semi-fictional, data-driven representation of your ideal customer – a marketing avatar that humanizes the target audience. It goes beyond simple demographics by capturing psychographics, pain points, and online behavior. Understanding the type of buyer persona that dominates each platform lets you choose which platforms to invest in rather than spraying content everywhere.

Exam tip: Practitioner marketing exams love the phrase “semi-fictional representation based on real-world data.” That’s the standard definition.

Key Components of a Buyer Persona

Steps to Create a Buyer Persona

A three-step process is shown below:

1. Collect data – Sources include Google Analytics, CRM/sales insights, customer interviews, browsing patterns, or even subjective analysis when objective data is unavailable.
2. Segment and synthesise – Group similar behaviours and attributes into distinct personas.
3. Build a visual profile – Give the persona a name, picture, codes, and platform habits. Tools like Hootsuite (free/paid) automate this: input data, output a ready persona.

Example persona: Eco-conscious Aisha—age, profession, platforms used, goals, pain points, and decision drivers.

Buyer Personas by Platform — Six Examples

Platforms attract different buyer personas. The table shows one illustrative persona per platform and a brand that targets it.

Exam tip: You don’t need to memorise every example. Instead, understand why each platform attracts that persona – e.g., Twitter’s real‑time nature pulls news‑hungry users; YouTube’s long‑form suits learners and comparison shoppers.

Implementation Example — Targeting Eco‑conscious Aisha

If your brand’s target persona is Eco‑conscious Aisha, you choose platforms based on where similar personas are prevalent, then tailor the content format:

• Instagram → Show eco‑packaging (reels, posts)
• TikTok → Relatable skits on sustainability
• YouTube → Detailed ingredient breakdown videos (long‑form)

Why these platforms? They attract younger, cause‑driven, visual learners – Facebook and LinkedIn would be less effective for this specific persona.

Key takeaways

• A buyer persona is a semi‑fictional avatar built from real data – it humanises the audience.
• Components: name/backstory, demographics, psychographics, pain points, decision drivers.
• Create personas via data collection → segmentation → visual profile; tools like Hootsuite can automate.
• Each social platform attracts distinct buyer personas (e.g., Instagram → Trendy Tara; LinkedIn → Executive Priya).
• Match your target persona to platforms where similar personas dominate, then adapt content format to platform norms.
• The credibility of a brand’s platform strategy depends on this alignment – not on posting the same content everywhere.

Customer Journey Lens

People buy in stages; each stage has a distinct consumer need, action, and attention span. Platforms differ in their efficiency and relevance at each stage — a brand must match platform to the stage its target audience is in.

The Five Stages and Platform Fit

Exam tip: Platforms at the top of the funnel work with short‑form content; as the customer moves down, content lengthens and becomes more information‑rich. Mismatching formats (e.g., using a long review in the awareness stage) wastes reach.

Key takeaways – Customer Journey Lens

• Each decision‑journey stage has a distinct brand objective: reach (Awareness) → engagement (Interest) → trust (Consideration) → conversion → retention (Loyalty).
• Short‑form video dominates awareness; longer educational content fits interest/consideration; triggers and reminders drive conversion; community/UGC fuels loyalty.
• A brand should audit its funnel and deploy the platform most efficient at the customer’s current stage.
• Examples show real brands (LensKart, Byju’s, Mamaearth, Nykaa, Zomato) using platform‑stage alignment.

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Algorithm & Discovery Lens

Algorithms control how and when content reaches users. Understanding each platform’s discovery mechanism lets brands optimise reach and engagement — the algorithm can be leveraged, not feared.

Platform‑by‑Platform Algorithm Summary

Exam tip: TikTok’s content‑first algorithm means even a brand with zero followers can go viral if the content gets early traction. On LinkedIn, authority (being seen as a thought leader) matters more than follower count.

Key takeaways – Algorithm & Discovery Lens

• Each platform’s algorithm rewards different signals: TikTok = watch time; Instagram = saves; YouTube = search optimization; LinkedIn = engagement & authority; Twitter = real‑time trends; Facebook = live video & friend interactions.
• Brands should tailor content format and posting strategy to the algorithm’s triggers (e.g., create save‑worthy posts for Instagram, use trending hashtags for Twitter).
• Algorithms are not adversaries — they can be reverse‑engineered to maximise organic reach without paid promotion.

On Which Platform Should You Advertise

Choosing a social media platform is a data-driven, strategic, and contextually aware decision. Instead of guessing, marketers use a repeatable framework that considers where the audience lives, what they care about, what content the brand can produce, and where the customer is in their decision journey.

Step 1: Audience Research

Use built-in platform analytics (Google Analytics, Meta Business Suite, TikTok Insights, LinkedIn Analytics) or third-party tools to uncover:

• Demographics – age, location, gender, interests (e.g., skincare, eco-living, technology)
• Behavior – active hours, engagement types, buyer persona

This builds a precise picture of where the audience spends time and how they interact.

Step 2: Social Listening

Monitor trends and sentiment around your industry, product, or relevant topics. Tools like Brandwatch or Hootsuite Insights help answer: What are people saying? What are they loving or hating? Social listening reveals the conversation your brand can join.

Step 3: Match Content Type to Platform Strength

If the brand’s content spans multiple types, it may still be optimal to focus on only two platforms based on audience research and social listening.

Step 4: Align Goal with Funnel Stage

• Awareness → platforms with high organic reach (TikTok, YouTube Shorts)
• Engagement → platforms that build trust and community (Instagram, Facebook, LinkedIn groups)
• Conversion → platforms with strong purchase triggers (Facebook ads, Instagram Shopping, YouTube CTA overlays)

Step 5: Track KPIs & Optimize

Once a platform is chosen, monitor Key Performance Indicators (KPIs) such as reach, click-through rate (CTR), engagement rate, and conversion rate. Adjust posting times, ad budget, and content based on analytics.

Exam tip: The funnel-stage alignment is the most testable part of this decision framework. Always match the platform’s organic/paid strengths to whether the customer is discovering, considering, or ready to buy.

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Worked Example: Earth Glow Naturals

Brand: Sustainable skincare, eco-friendly products Target: Millennials and Gen Z women (18–35), urban, interested in sustainable living and skincare Objective: Raise awareness + generate e-commerce sales via education and community building

Step 1 – Audience Research

• Use Meta Audience Insights and Instagram Insights to confirm demographics.
• Identify influencers followed (e.g., Ankush Bahuguna, Hyram) and active hours (6–10 PM).
• Build buyer personas to narrow platform choices.

Step 3 – Content Strategy Alignment Content available:

• Visual (packaging photos, skincare routines)
• Educational (dermatologist reviews, myth-busting reels, product science)
• Emotional storytelling (testimonials, founder journey, eco-impact stats)

Step 4 – Funnel & Platform Selection

• Goal = Awareness. Shortlisted platforms: Instagram, TikTok, YouTube Shorts.
• Match content to platform tactics:

Step 5 – Analytics & Optimization

• Monitor engagement via Instagram Insights, TikTok Creator Dashboard.
• Optimise for discovery pages (short Reels <20 seconds, TikTok under-20s).
• Adjust post times to peak activity (6–10 PM).
• Redirect ad budget to retarget campaigns on Facebook and Instagram based on website traffic behavior.

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Key takeaways

• Choose platforms using audience research, social listening, content-platform fit, and funnel-stage alignment.
• Shortlist based on where the audience is and what content you can produce.
• Awareness → TikTok, Instagram, YouTube Shorts; Engagement → Instagram, Facebook, LinkedIn Groups; Conversion → Facebook Ads, Instagram Shopping.
• Always track KPIs and optimise using platform analytics.
• The worked example for a new sustainable skincare brand demonstrates the full pipeline: research → content match → platform selection → tactics → analytics.