Ohanian (1990) built the standard measure of a spokesperson's source credibility from three dimensions: expertise, trustworthiness and attractiveness. The model was developed for celebrity endorsers, but it transfers well to influencers, with one addition. Lou and Yuan (2019), surveying social media users who followed at least one influencer, found that the informative value of an influencer's posts, together with the influencer's trustworthiness, attractiveness and similarity to followers, increased followers' trust in branded posts, and that trust in turn raised brand awareness and purchase intention. Similarity matters because influencers are, in their followers' eyes, people like them who happen to be followed, not distant stars.

The second mechanism is relational. Horton and Wohl (1956) described parasocial interaction: the one-sided sense of intimacy that audiences develop with media figures who address them directly. A creator who talks to camera every day, answers comments and shares her own routine invites exactly that. Followers feel they know her, so her recommendation lands more like advice from a friend than an advertisement. The relationship is an asset the creator has built over years, and every sponsored post draws on it.

That is where the tension lies. Followers value influencers for apparently intrinsic, non-commercial motives, yet brand partnerships pay them to speak. Audrezet, de Kerviler and Moulard (2020) studied how influencers manage this and identified two strategies: passionate authenticity, in which the creator only takes on brands that genuinely fit their own interests and voice, and transparent authenticity, in which they are open about the commercial arrangement and their honest view of the product. The implication for brands is that over-scripted content makes both strategies harder to sustain.

The persuasion knowledge model (Friestad and Wright, 1994) explains why. Once people recognise a message as an attempt to persuade them, they draw on what they know about persuasion tactics and discount, scrutinise or resist it. Influencer content works partly because it does not look like advertising; the moment it reads as a brand's script, persuasion knowledge activates and the borrowed credibility drains away. Disclosure, which the law requires and which Module 5 covers, makes the commercial nature explicit, so brands cannot rely on concealment. They have to choose creators whose credibility survives being seen as paid.

For Moorfield Botanics the implication is direct. A reactive-skin audience that trusts other users' routines more than brand claims will be most persuaded by creators who are, or credibly understand, people like them.

The creator economy is the ecosystem of independent creators, the platforms that distribute and monetise their work, and the brands, agencies and tools that pay them. Understanding its structure tells a brand what it is actually buying and from whom.

Creators are usually grouped into tiers by following. Campbell and Farrell (2020) distinguish celebrity, mega, macro, micro and nano influencers and argue that the tiers differ not only in reach but in what they offer a brand: smaller creators tend to offer closer audience relationships and more niche credibility, larger ones reach and cultural visibility. The thresholds, however, are conventions, not standards. Agencies, platforms and academics draw the lines in different places, and a "mid-tier" band between micro and macro is common in practice. Moorfield, for instance, treats 10,000 to 50,000 followers as micro and 50,000 to 150,000 as mid-tier. Always state the thresholds you are using.

Creators earn money in several ways: fees for sponsored content, affiliate commission on sales, platform revenue sharing and creator funds, subscriptions and tips, and their own products. The mix shapes their incentives. A creator who depends on affiliate income has reason to push conversion; one with their own product line may see a brand as a competitor; one who earns mainly from an engaged community will protect it from unconvincing sponsorships. Haenlein et al. (2020) note that influencer marketing has professionalised quickly, with creators operating as businesses and expecting to be treated as such.

Between brands and creators sit intermediaries: talent agencies that represent larger creators and negotiate their fees and exclusivity; influencer agencies that plan and run programmes for brands; and discovery and management platforms, including the platforms' own creator marketplaces. Intermediaries add speed and scale, but each takes a margin and each has incentives, such as favouring their own roster, that a brand should recognise.

The edges of the economy are expanding. Virtual influencers are computer-generated personas run by companies; they offer control and less risk of off-brand behaviour, but raise questions of authenticity and disclosure. At the other edge, employee advocates and customer advocates are people with small followings whose credibility comes from first-hand experience rather than reach. For a brand whose audience trusts other users' routines, customers who already post about the product may be a creator tier in their own right.

Before choosing creators, a brand must decide what influencers are for. There are four main roles. Awareness: putting the brand in front of people who do not know it, especially through recommendation-led feeds. Credibility: borrowing trust the brand cannot claim for itself, which matters most in categories with high perceived risk. Content production: creators make platform-native content faster, more cheaply and more convincingly than many brands, and that content can be reused. Conversion: driving sales directly through links and codes. Most programmes want more than one, but they should rank them, because the role decides the criteria. A credibility role puts audience fit and expertise first; an awareness role weighs reach and audience overlap with non-customers; a conversion role weighs audience purchase intent and trackability.

The role must follow from the strategy already set. Module 1 gave each platform a role and set objectives that ladder up to business goals; Module 2 turned listening into insight. An influencer strategy that contradicts either is a separate plan, not part of the strategy.

Three partnership models are common. A campaign model buys a burst of content around a moment such as a launch: efficient for reach, but every relationship starts cold and ends abruptly, which can look transactional to followers. An always-on model keeps a rolling roster of creators posting throughout the year, building familiarity and steady content. An ambassador model signs a small number of creators to longer relationships, often with product input or exclusivity; it builds the deepest credibility because repeated, consistent advocacy reads as genuine preference, but it costs more per creator and concentrates risk on a few people. Many brands combine them: a campaign for the moment, ambassadors for continuity.

Finally, a brand should ask whether influencers are the right tool at all. Paid social offers control over targeting, message and frequency and is easier to measure; owned content builds an asset the brand keeps. Influencers earn their place when the job needs someone else's voice, as when the audience discounts brand claims. Creator content can also feed paid social, but that depends on usage rights agreed in the contract, which belongs to Module 5.

For Moorfield, the key insight that people with reactive skin trust other users' routines more than brand claims points to credibility as the first role and TikTok discovery as the second, which is why Amara chooses a launch campaign plus always-on ambassadors for the Barrier Repair Serum.

Discovery and vetting are where most poor influencer decisions are made, often invisibly: a creator is found because someone in the team follows them, and vetted by glancing at a follower count. A disciplined process separates the two steps and records evidence for each.

Discovery should cast a wide net. Routes include searching hashtags and keywords on the target platforms, social listening (the creators already talking about the category or the brand), platform creator marketplaces, agencies and discovery tools, and the brand's own customers and followers. Fans who already use the product are often the most credible micro and nano creators available, and listening is the cheapest way to find them.

Vetting then tests each candidate against the role. Audience fit comes first: who follows the creator, by age, gender and especially location. A UK brand paying for an audience that is mostly overseas is paying for reach it cannot convert. The best evidence is platform audience data supplied by the creator or accessed through an approved tool, ideally first-party exports or live screen-shares rather than static screenshots, which are easy to edit.

Audience authenticity asks how much of the following and engagement is real. Warning signs include sudden follower spikes that do not match a viral post, engagement that is high but generic (emoji strings and "love this!" from accounts with no content of their own), engagement concentrated in the first minutes from the same accounts on every post, which suggests an engagement pod, and follower bases dominated by inactive or irrelevant accounts. Third-party audit tools estimate these patterns, but their methods are proprietary and their estimates differ, so treat them as prompts for judgement rather than verdicts.

Brand safety and values review means reading the creator's back catalogue, not just the last few posts: past controversies, claims they make (in skincare, medical claims are a particular risk), tone, and whether their values align with the brand's. The risk runs both ways; the creator is also judging whether the brand is safe for them.

Past partnerships show how often the creator posts sponsored content, whether they have recently worked with direct competitors, and how their audience responded. A feed dominated by sponsorships signals a creator whose recommendations followers may already discount.

For Moorfield, vetting Jas Kaur meant checking platform audience data (81% UK), reading a year of her content for claims and controversies, and reviewing her skincare partnerships.

Selection turns vetting into a decision. The method this course has used since Module 1 applies here too: choose criteria that follow from the role, weight them, score each candidate on a defined scale, write down why, and test whether the ranking survives a change of weights. A scorecard does not make the decision objective, but it makes the judgements visible, comparable and open to challenge, which is what an auditable process means.

The research gives good reason not to let follower count dominate. De Veirman, Cauberghe and Hudders (2017) found in experiments that Instagram influencers with more followers were seen as more popular and more likeable, but that for divergent products, a large following could reduce the brand's perceived uniqueness and so harm brand attitude. Wies, Bleier and Edeling (2023), using 802 Instagram campaigns with more than 1,700 influencers plus eye-tracking and experiments, found an inverted-U relationship between follower count and engagement with sponsored posts: engagement rises with following and then falls, because larger audiences signal a weaker relationship with each follower. The decline was weaker where creators had more freedom over content and where the brand was less familiar.

Leung et al. (2022), analysing 5,835 sponsored posts by 2,412 influencers on Weibo in October 2018, found that larger followings, more original content and more salient sponsor mentions made posts more effective, while new-product announcements made them less so; influencer activity, follower–brand fit and post positivity all had inverted-U effects, meaning moderate levels outperformed extremes. Two cautions apply. The data come from one platform in one country at one point in time, so generalising to UK TikTok in 2027 is a judgement, not a finding. And the finding on product launches is a warning for any launch campaign: followers are reluctant to vouch for something unknown, which is a further argument for credible creators who use the product before they post.

Taken together, the evidence argues for selecting on fit, authenticity and content rather than size, and for a tier mix rather than a single bet. A tier mix pairs a small number of larger creators, who provide reach and a visible anchor, with many smaller ones, who provide closer relationships, more varied content and spread risk. Budget follows the role: a credibility-led programme should not spend most of its fees on the largest name available.

Moorfield's launch mix is one macro creator, six mid-tier creators and 24 micro creators, a structure Amara justifies in the worked example.