Chapter 3 – Online Marketplace Analysis (Micro-Environment) – Detailed Study Notes

Situation Analysis for Digital Marketing

• Situation analysis = systematic collection, review & interpretation of information about a firm’s external environment + internal resources/processes ➔ refines digital strategy.
• Two complementary scopes:
– External (covered here): customers, marketplace actors, competitors, macro forces.
– Internal (covered in later chapters): performance auditing, capabilities, resources, processes.
• Recommended flow (outside-in):

  1. Customers – behaviours, needs, wants ➔ shapes digital value proposition & comms.

  2. Marketplace actors – intermediaries, influencers, partners ➔ understand traffic flows & collaboration options.

  3. Competitors – benchmark propositions & digital tactics ➔ identify gaps/opportunities.

  4. Macro-environment – social, legal, environmental, political, technological (SLEPT/PESTLE) ➔ anticipate change.
    • Key disciplines employed: environmental scanning, SWOT/TOWS, customer insight generation, competitor intelligence, digital analytics.

Digital Marketing Environment

• Split into two analytical lenses:
– Micro-environment: immediate marketplace stakeholders whose interactions shape firm response (customers, competitors, suppliers, intermediaries, publics, the organisation itself).
– Macro-environment: broad forces affecting all organisations (social, technological, economic, political, legal, ecological). Often monitored via PESTLE or SLEPT frameworks.
• Digital context intensifies interactivity & transparency within both spheres.

Understanding Customers in Digital Markets

• Four marketplace map elements:

  1. Customer segments – discrete groups differentiated by needs, behaviour, media usage.

  2. Search intermediaries – engines/vertical search (Google, Bing, Baidu, Yandex, Naver, etc.).

  3. Intermediaries, influencers & media sites – portals, social networks, bloggers, affiliates, aggregators, comparison sites.

  4. Destination sites/platforms – brand-owned transactional, service, brand-building or community sites.
    • Further distinctions inside customer base:
    – Web-savvy vs non-web-savvy.
    – Demographic, psychographic, lifecycle, behavioural segmentation.
    – Persona development: fictional, evidence-based archetypes representing key audiences.

Online Marketplace Mapping

• Visual tool (Fig. 2.3) positions actors & flow of traffic/attention:
– Flow A: users ➔ search intermediaries (organic & paid) ➔ target site.
– Flow B: users ➔ various intermediaries (social, blogs, portals, affiliates) ➔ target site.
• Purpose: assess actor importance, relative visibility, overlap across customer journeys.
• Core performance ratios (Fig. 2.4):
– Awareness efficiency =target web usersall web users=\frac{\text{target web users}}{\text{all web users}}
– Attractability efficiency =individual visitsseekers=\frac{\text{individual visits}}{\text{seekers}}
– Engagement efficiency =active visitorsvisits=\frac{\text{active visitors}}{\text{visits}}
– Conversion efficiency =purchasesactive visits=\frac{\text{purchases}}{\text{active visits}}

Customer Journey & Purchase Decision Flow

• Hybrid journey combines traditional & digital touchpoints (TV ➔ search ➔ mobile remarketing ➔ in-store interactive ➔ social sharing).
• McKinsey’s circular model:
– Trigger ➔ Initial Consideration Set ➔ ZMOTZMOT (research) ➔ First Moment of Truth (shelf/site) ➔ Purchase ➔ Second Moment of Truth (experience) ➔ Loyalty Loop & Advocacy ➔ feeds next shopper’s ZMOT.
• Digital media roles across stages (new purchase framework):

  1. Generate awareness of need/offer.

  2. Position benefits & brand while consumer forms specification.

  3. Lead generation during supplier search.

  4. Assist evaluation & selection.

  5. Facilitate purchase (UX, payment, security).

  6. Support usage, solicit feedback, encourage retention.

Customer Analysis

• Two complementary angles:

  1. Demand analysis – size & behaviour of traffic, conversion to outcomes (sales/leads).

  2. Digital consumer behaviour – deeper insight into needs, motivations, experiences.
    • Typical data sources: web analytics, social listening, surveys, CRM, ethnography.
    • Outputs: segments, personas, journey maps, value propositions.

Consumer Choice & Digital Influence

• Customer characteristics:
– Demographics: age, gender, income, education, location, ethnicity.
– Psychographics & behavioural: interests, lifestyle, attitudes, technology readiness, online shopping intention.
• Influence mechanisms:

  1. Information Processing (IP) – attention, comprehension, elaboration of online stimuli.

  2. Perceived Ease of Use (PEOUPEOU) – core construct of Technology Acceptance Model; easier interfaces raise attitude & intention.

  3. Perceived Usefulness (PUPU) – relevance to daily tasks boosts adoption.
    • Social & emotional drivers: social proof, FOMO, community connection, endorsement, sentiments on social media.
    • Personas distil above variables into vivid, actionable profiles.

Competitor Analysis & Benchmarking

• Assess market structure: direct vs indirect competitors, category disruptors, substitute offers.
• Benchmark dimensions:
– Online value proposition (OVP): relevance, differentiation, proof.
– Traffic/share of voice (Search visibility, social share, referral traffic).
– UX & content quality.
– Pricing, product range, service levels.
– Technology stack & innovation cadence.
• Tools: SimilarWeb, SEMrush, social listening platforms, user testing, mystery shopping.

Suppliers & Digital Intermediaries

• Supplier relationships shift under digital: real-time data sharing, drop-shipping, platform connectivity.
• Digital marketing intermediaries include ad networks, DSPs, influencers, affiliate platforms – they play supplier role for traffic, data & content.

New Channel Structures (Disintermediation & Reintermediation)

• Traditional chain: Producer ➔ Wholesaler ➔ Retailer ➔ Consumer.
• Internet enables:
– Disintermediation: Producer sells direct (D2C) removing layers – lower cost, more data.
– Reintermediation: new tech-enabled intermediaries (Amazon, Airbnb, comparison sites) create value via aggregation, curation, logistics, escrow.
• Strategic decisions: own channel vs marketplace presence vs hybrid.

Digital Business Models for E-commerce

• SmartInsights model = adaptation of Osterwalder’s Business Model Canvas to digital context.
• Emphasises integration of online value creation, capture & delivery.

Customer Segments

• Segmentation bases: Geographic, Demographic, Psychographic, Behavioural.
• Digital nuance: micro-segments defined by real-time behaviour, intent data.

Value Propositions

• Core promise solving customer job/problem with distinct benefit (e.g., Galaxy’s “new shape for a smoother taste”, Snickers’ hunger satisfaction message).
• Digital layer: personalised content, convenience, speed, omnichannel consistency.

Customer Relationships

• Types: Transactional, Self-service, Dedicated Personal Assistance, Community, Co-creation.
• Automation & AI (chatbots, recommendation engines) shift balance toward scalable personalisation.

Channels

• Paid, Owned, Earned media; device contexts (desktop, mobile web/app, in-store screens); fulfilment modes (digital download, physical delivery, click-and-collect).

Revenue Streams

• Fixed pricing: list, feature-based, segment-based, volume.
• Dynamic pricing: bargaining, yield management, auctions, real-time market.
• Recurring: subscription, SaaS, rental.
• Ancillary: advertising, data monetisation, affiliate commissions.

Key Resources

• Physical (warehouses, servers), Human (talent), Intellectual (brands, patents, data), Financial (capital, credit lines).

Key Activities

• Production, Problem-solving (service/support), Platform/network orchestration.

Key Partnerships

• Strategic alliances, coopetition arrangements, joint ventures, supplier relationships; API ecosystems.

Cost Structure

• Variable vs fixed costs, CAC, COGS, hosting, R&D, marketing spend.

Alternative Perspectives on Business Models (Fig. 2.15)

• Marketplace position perspective: Manufacturer, Reseller, Marketplace/Exchange, Media Owner, Supply Chain Integrator, Not-for-profit.
• Revenue model perspective: direct sales, subscription/rental, commission (affiliate/auction), advertising, syndicated content.
• Commercial model perspective: fixed-price, negotiated, auction/spot, bundling, loyalty pricing.
• Example mapping: Amazon (Marketplace & Reseller using commission + direct sales + subscription Prime), Yahoo! (Media owner using advertising + content syndication).

Conversion Metrics & Key Ratios Recap

• Awareness, Attractability, Engagement, Conversion efficiencies (see formulas above).
• Funnel analysis extends to ROASROAS, CLVCLV, CACCAC, attribution modelling.

Case Study: Boo.com (Largest Dot-com Failure)

• Strategic assumptions/decisions leading to failure:
– Overestimation of broadband penetration; heavy 3-D & Java scripts slowed UX.
– Global launch vs phased roll-out; massive burn rate (>$120 million>\$120\,\text{million} in <18<18 months). – Focus on brand glamour > basic retail fundamentals (logistics, sizing, returns).
– Complex interface requiring plug-ins & avatar assistance – intimidating for 1999 users.
• Contrast with lastminute.com success:
– Leaner cost structure & clear, time-sensitive value proposition (late deals).
– Simple booking engine; fast page loads.
– Staged geographic expansion; partnerships with travel suppliers for inventory.
• 4 Ps appraisal of Boo.com:
– Product: fashionable sports apparel with virtual try-on (innovative).
– Price: premium; lacked clear competitive pricing strategy.
– Place: solely online, yet poor accessibility (tech barriers).
– Promotion: lavish global campaigns, PR buzz, but failed expectation management.
• Ideas ahead of time now commonplace: 360° product views, size-guides, personalised assistants, multi-currency support, global fulfilment.