For information and reference only – not to be submitted as your own work. Use this extract to see how a group can structure a content-strategy video and deck, then build your own analysis from your team’s audit of the live Instagram accounts and your own AI-use log.
This model-answer extract covers the SUSS MKT373 Strategic Content Management Group-Based Assignment (July 2026 presentation): a video of up to 15 minutes and a deck of up to 15 content slides on PropertyGuru, delivered to the Group CMO. It shows a slide-and-timing plan, two content plans, a content-portfolio split, an influencer evaluation framework, a format adaptation and the generative AI attribution table.
How the group splits 15 minutes and 15 slides
Four members must each present, so the plan below gives every person a block of roughly three to four minutes and one question each, with equal weight per question. Cover, thank-you and reference slides sit outside the 15-slide count.
| Slides | Content | Time | Presenter |
|---|---|---|---|
| 1–2 | Context: PropertyGuru as a dual-sided platform; the low visibility of GuruGPT and AIME | 1:30 | Member A |
| 3–5 | Q1(a) GuruGPT segment, channel, sample post, KPIs | 3:00 | Member A |
| 6–7 | Q1(b) AIME segment, channel, sample post, KPIs | 2:30 | Member B |
| 8–10 | Q2 Instagram representation audit, evaluation and portfolio split | 3:30 | Member B and C |
| 11–12 | Q3 creator evaluation and two proposed creator profiles | 2:00 | Member C |
| 13–14 | Q4 account comparison and new content series | 2:00 | Member D |
| 15 | Roadmap, risks and decision requested from the CMO | 0:30 | Member D |
Total speaking time is 15:00, so rehearse to 14:30 and keep the margin. A video that overruns is usually penalised on the presentation component, not the content component.
Frame the whole talk with a definition your CMO will recognise. Rowley (2008) frames digital content marketing as a management process that uses digital content to engage audiences, and Pulizzi (2012) argues that story-led content builds the relationship that sales messages cannot. Both ideas justify leading with buyer questions and agent concerns instead of product features.
Q1: two short content marketing plans
(a) GuruGPT for first-time buyers
GuruGPT is described in Deeptech Times (2026) as a conversational assistant, still in testing, that helps users understand housing policy, compare properties and assess their own scenario. The segment that benefits most is the first-time buyer who is unsure how the process works. That choice is defensible because the product solves a confidence problem, and content can demonstrate that in seconds.
| Element | Plan |
|---|---|
| Segment | First-time buyers, couples aged roughly 27–35 researching a first purchase |
| Objective | Awareness first, then trial: move people from “never heard of GuruGPT” to “asked it one question” |
| Channel | Instagram Reels and Stories, with a link into the app; short-form video suits a question-and-answer product |
| Content pillar | “Ask Guru”: real buyer questions answered on screen, showing the assistant working |
| Sample piece | A 25-second Reel: a couple types “Can we afford a resale flat on our combined income?”; the screen shows the follow-up questions GuruGPT asks, then a plain-language summary, ending on a prompt to try their own question |
| KPIs (illustrative targets) | Reel completion rate, saves and shares, click-through to GuruGPT, number of first questions asked |
(b) AIME for listing agents
PropertyGuru’s own help centre describes AIME as its AI Moderation Engine, which checks listing images against platform guidelines, with uncertain cases passed to human moderators (PropertyGuru, n.d.). Its most affected audience is the agent uploading photos. A seeker-facing message about “trust” is possible, but the more specific segment is agents, because their behaviour determines what AIME can improve.
| Element | Plan |
|---|---|
| Segment | Individual agents with active listings who upload their own photographs |
| Objective | Understanding and reassurance: AIME is a quality tool, not a penalty system |
| Channel | LinkedIn posts and the agent-facing newsletter or help-centre channels, where agents already look for platform updates |
| Content pillar | “Photo rules, explained”: what gets flagged, why, and how to avoid it |
| Sample piece | A five-slide LinkedIn carousel, “Why was my listing photo flagged?”, showing three common causes in plain language and one before/after example (illustrative) |
| KPIs (illustrative targets) | Carousel saves, newsletter click-through, fewer repeat flag queries to support, agent sentiment in comments |
Notice what the two plans share: each ties an invisible AI feature to a visible benefit for a named person. A plan that says “raise awareness of AI” scores poorly because nobody can act on it.
Hire a Professional Essay & Assignment Writer for completing your Academic Assessments
Native Singapore Writers Team
- 100% Plagiarism-Free Essay
- Highest Satisfaction Rate
- Free Revision
- On-Time Delivery
If your group is stuck on the segment choice or the slide timings, our team can review your outline through marketing assignment help in Singapore before you record.
Q2: dual-sided Instagram content
(a) Evaluating the current representation
A dual-sided platform needs both sides to grow together, which is the core argument in Eisenmann, Parker and Van Alstyne (2006). For PropertyGuru, seekers bring demand and agents and developers bring supply. Your audit should code every 2026 @propertyguru post by which side it addresses, then report the counts. This extract does not report counts, because they must come from your own audit. Take a sample of recent 2026 posts, note the dates you sampled, tally the three groups (seeker-oriented, agent or developer, both sides) and record the split in a small table on your slide.
The evaluation turns on one question: is Instagram the right place for agent messaging? A likely finding is that the feed is seeker-heavy, which is appropriate for a consumer channel but leaves agents and developers addressed mainly on other platforms. That is a missed opportunity only if agents are an Instagram audience and if their presence on the account lends seekers social proof. Argue both sides, then commit to a view.
(b) Recommended future portfolio
| Content type | Share | Justification |
|---|---|---|
| Seeker-focused | 45% | Instagram’s audience is largely consumers; guides, explainers and GuruGPT demonstrations earn attention |
| Agent and developer-focused | 25% | Spotlights, launch stories and AIME explainers build supply-side credibility and give agents a reason to follow |
| Both sides | 30% | Content showing a viewing, a transaction or a verified listing connects the two audiences and strengthens the network effect |
State the trade-off honestly: a 25% agent share will reduce seeker-only reach in the short term. Defend it with a measurable review point, for example reassess after one quarter using saves and follower growth by audience type.
Q3: creator partnerships
Do not judge creators by follower count alone. Hollebeek and Macky (2019) link digital content to engagement, trust and value, and Lou and Yuan (2019) show that message value and credibility shape trust in branded content. Score each creator with the same framework.
| Criterion | Evidence to collect | Existing creators (example reading) |
|---|---|---|
| Audience fit | Who comments; does the audience include likely buyers, renters or agents? | Rate each of the four handles from its comments and tagged audience, and note the date you checked |
| Content relevance | Share of posts about housing, money or urban life | Property-adjacent accounts score higher than a general lifestyle account; one named account is not property-focused |
| Engagement quality | Substantive comments, saves, shares | Read a sample of recent posts per handle and compare the share of substantive comments, rather than quoting totals |
| Credibility | Does the creator show expertise or lived experience? | Note whether each creator shows qualifications, a track record or personal ownership experience in the posts you reviewed |
| Objective match | Awareness, trust or conversion | Map each to GuruGPT trial, AIME education or brand trust |
The decision should be differentiated: continue the partnerships that score well on relevance and credibility, rework the one whose audience is not property-focused into a narrower brief, and say what you would measure to justify keeping it.
Two new creator profiles
Without verified account data, describe profiles rather than names. Profile 1: a personal-finance creator who explains Singapore housing grants and loan decisions to young couples, suited to the GuruGPT objective of trial among first-time buyers. Profile 2: a home-renovation or interior creator whose followers are new owners, suited to the brand-trust objective and the “both sides” content bucket. Replace these with named handles only after checking audience data.
Q4: Stackedhomes comparison and a new series
Follower gaps usually come from a narrow, repeatable promise rather than breadth. Compare the accounts on content vision: one can be read as a platform communicating its product range, the other as an independent voice that helps a buyer decide. Record your evidence for each reason, such as posting rhythm, format consistency, tone and level of opinion, rather than assuming it.
| Step | What to show |
|---|---|
| 1. Pick one format | One popular Stackedhomes post format with no PropertyGuru equivalent, chosen by reviewing the live feed and naming the format you saw repeated |
| 2. Illustrate its structure | Hook, evidence, verdict, call to comment |
| 3. Adapt | A PropertyGuru series that keeps the structure but uses the platform’s data and tools |
A defensible adaptation is a recurring series, for example “Guru Verdict”, in which a named analyst answers one buyer question per episode using listing data and GuruGPT output, with a clear recommendation and its limits. The series is worth proposing because it gives GuruGPT a regular showcase, which answers Q1.
Generative AI attribution table
| Tool | Prompt used | Output received | Group adaptation |
|---|---|---|---|
| e.g. a generative AI chatbot (example; list the real tool and version you used) | “Suggest five buyer questions a first-time buyer would ask” (illustrative) | List of questions | Kept two, rewrote them in our own wording, checked against the brief |
| e.g. a generative AI chatbot (example; list the real tool and version you used) | “Draft a script outline for a 25-second Reel” (illustrative) | Outline | Changed hook, added our KPI and tone |
Keep your real prompts and be ready to explain every number and claim in a viva.
For a structured check of your deck before submission, see our SUSS assignment help page, or browse the SUSS assignment questions. For planning advice behind this extract, read our guide to the MKT373 group video presentation plan, and see case study assignment help for company-case work.
References
Deeptech Times. (2026, July 14). AI enters the property hunt: How PropertyGuru is closing the information gap for homebuyers. https://deeptechtimes.com/2026/07/14/ai-enters-the-property-hunt-how-propertyguru-is-closing-the-information-gap-for-homebuyers/
Eisenmann, T., Parker, G., & Van Alstyne, M. W. (2006). Strategies for two-sided markets. Harvard Business Review, 84(10), 92–101.
Hollebeek, L. D., & Macky, K. (2019). Digital content marketing’s role in fostering consumer engagement, trust, and value: Framework, fundamental propositions, and implications. Journal of Interactive Marketing, 45, 27–41. https://doi.org/10.1016/j.intmar.2018.07.003
Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58–73. https://doi.org/10.1080/15252019.2018.1533501
Pulizzi, J. (2012). The rise of storytelling as the new marketing. Publishing Research Quarterly, 28(2), 116–123. https://doi.org/10.1007/s12109-012-9264-5
PropertyGuru. (n.d.). AI Moderation Engine (AIME) for listing images. https://www.agentofferings.propertyguru.com.my/help-centre/aime/
Rowley, J. (2008). Understanding digital content marketing. Journal of Marketing Management, 24(5–6), 517–540.
