Follower Fraud 2.0: Engagement pods, bought comments and brand budgets

For a long time, influencer marketing had a relatively simple currency: followers. A larger audience meant greater visibility, greater visibility translated into higher engagement, and higher engagement often helped creators command better brand deals. But as influencer marketing has moved from an experimental social media activity to a significant part of media planning, the numbers that once made creators attractive are facing closer scrutiny.

Buying followers is no longer the only way to manufacture influence. Engagement pods, purchased comments, coordinated likes and artificial interactions have created a more complicated version of the problem. An account may have a seemingly healthy follower base, regular comments and impressive engagement rates, yet much of that activity may have little connection to genuine audience interest. The appearance of influence is becoming easier to manufacture, even as measuring actual influence becomes more difficult.

This is where follower fraud enters its second phase. The first version was largely about inflating audience size. The newer version is about making artificial popularity look organic. For brands allocating money to creator partnerships, that distinction matters. They are no longer simply paying for access to an audience that may or may not be real. They could also be paying for engagement that has been engineered to look like consumer attention.

From Fake Followers to Manufactured Engagement

The original follower fraud model was relatively straightforward. Creators purchased followers through third-party services to increase their visible audience size. The practice offered an immediate advantage when brands were using follower count as an initial measure of creator value. An account with 200,000 followers could appear more commercially attractive than one with 25,000, even if the smaller creator had a more relevant and active audience.

Platforms and influencer analytics companies gradually developed ways to identify suspicious follower growth, inactive accounts and unusual audience patterns. However, as brands became more familiar with these checks, the incentive to manipulate engagement evolved.

Engagement pods are one example. These are organised groups of creators or social media users who agree to interact with one another’s content. A member publishes a post, shares it within the group, and other members respond with likes, comments or shares. The arrangement creates an initial burst of activity that can make a post appear more popular than it would have been through organic discovery alone.

Such groups can operate through WhatsApp, Telegram and other private communities. Some are informal networks of creators supporting one another, while others operate with explicit engagement requirements. The distinction becomes important when participation is driven by genuine interest in the content rather than an obligation to generate activity.

Research into Instagram engagement pods has previously highlighted how coordinated interactions can influence platform visibility. A 2020 investigation reported by TechCrunch described research identifying hundreds of groups systematically exchanging likes and comments to manipulate engagement signals.

The problem is not necessarily that every person participating in these groups is a fake account. Many may be real users. The issue is that their interaction is not an independent expression of interest. They are responding because an arrangement requires them to do so, not necessarily because the content has something meaningful to offer.

The Comment Section Has Become Part of the Performance

Comments have traditionally offered brands a qualitative view of audience response. Likes can indicate that someone noticed a post, but comments can reveal whether the content generated a reaction, raised a question or influenced an opinion. For marketers, this makes the comment section a useful indicator of audience involvement.

That value is diminished when comments become another purchasable campaign metric.

Purchased comments can range from generic expressions of approval to more elaborate responses designed to appear relevant to the content. A post promoting a skincare product might receive comments praising its results, while a travel creator’s video could attract enthusiastic responses about a destination. When generated at scale, these interactions can create the impression of an active community around a creator.

Some comments are easy to identify. Repeated phrases, unrelated responses, excessive emojis and generic compliments can indicate suspicious activity. Others are more difficult to distinguish because they are written to resemble ordinary conversations.

This creates a measurement challenge. A campaign may report thousands of comments, but the number alone does not establish whether consumers understood the product, remembered the brand or considered making a purchase.

For brands, the distinction between engagement volume and engagement quality is becoming increasingly important. A comment that contributes to a genuine product discussion is not equivalent to an automated response or a pre-arranged compliment. Both may appear in the campaign report, but they do not carry the same marketing value.

Why the Numbers Still Influence Brand Budgets

If the limitations of vanity metrics are widely understood, why do they continue to influence influencer selection and campaign pricing?

Part of the answer lies in how the creator economy has developed commercially. Brands often need to evaluate hundreds of potential creators within limited timelines. Follower counts, engagement rates, average views and previous campaign performance offer convenient ways to shortlist talent. These numbers make comparisons easier and provide a starting point for negotiations.

However, convenience can become a problem when an initial screening metric turns into the primary basis for investment decisions.

Consider two creators competing for the same campaign. The first has 500,000 followers and an engagement rate that appears consistently high. The second has 80,000 followers, a smaller but relevant audience and a comment section where users regularly discuss the category. If the selection process prioritises reach and engagement percentages, the first creator may receive the larger allocation.

But the second creator could offer stronger audience relevance, greater credibility and a better opportunity to influence purchase consideration. Without examining the quality of the audience and its interactions, a brand risks confusing visible popularity with commercial effectiveness.

This becomes particularly significant as influencer marketing budgets grow. According to the India Influencer Marketing Report 2025 by The Goat Agency, part of WPP Media, in collaboration with Kantar, India’s influencer marketing industry was estimated at Rs 3,600 crore in 2024, with projected growth of 25% in 2025. The report also highlighted a shift towards content quality and creator relevance rather than follower count alone.

At this scale, even relatively small inefficiencies in creator selection can translate into substantial budget leakage. When artificial engagement influences the evaluation process, the financial consequences extend beyond an inflated campaign report. Brands may overpay for distribution that does not reach the intended audience or generate the expected response.

The Indian Market: A Larger Creator Economy, a Bigger Verification Challenge

India’s influencer marketing landscape presents a particularly interesting case. The rapid expansion of regional creators, short-form video consumption and platform-led communities has made creator partnerships relevant across categories ranging from beauty and fashion to automobiles, financial services and consumer technology.

This growth has also increased the complexity of identifying credible creators. A brand looking to reach audiences across different languages, locations and interest groups may need to evaluate a large number of profiles. The process becomes more demanding when creator discovery, audience verification and campaign measurement are handled separately.

Data from a 2024 analysis by influencer marketing platform KlugKlug, reported by Moneycontrol, found that 58.5% of Instagram profiles examined in India had more than 60% spurious or fake followers. The analysis covered eight million profiles. While the findings reflect the methodology and dataset used by the platform, they underline the scale of the audience-authenticity question.

There is also a wider issue of trust. Influencers are often selected because audiences perceive them as relatable and credible. Their recommendations can carry a different kind of value from conventional advertising because they are delivered through an established relationship with followers.

When engagement is manufactured, that relationship becomes difficult to evaluate. A creator may appear to have a responsive community without having built the level of audience trust that brands expect to access through a partnership.

The challenge is not limited to large creators. Micro and nano influencers are frequently valued for their focused communities and closer audience relationships. However, smaller follower counts do not automatically guarantee authenticity. Artificial growth and coordinated engagement can occur at different levels of the creator ecosystem.

For marketers, the implication is clear: creator size should not be treated as a substitute for creator credibility.

When Campaign Reporting Rewards the Wrong Behaviour

Follower fraud also exposes a weakness in how influencer campaigns are evaluated. Many campaign reports continue to place considerable emphasis on impressions, reach, likes, comments and engagement rates. These metrics are useful, but they only describe particular aspects of campaign activity.

They do not independently establish whether the campaign achieved its objective.

A brand running an awareness campaign needs to understand how many relevant consumers were exposed to the message and whether the content contributed to brand recall. A campaign designed to generate consideration needs evidence of interest, product exploration and meaningful interaction. A conversion-focused campaign needs to examine attributable traffic, enquiries, leads or sales.

When all these objectives are reduced to engagement volume, the measurement framework can reward behaviour that has little commercial value.

There is also a reporting problem. If a creator’s performance is evaluated primarily through likes and comments, agencies and brands may end up comparing creators on metrics that are not equally reliable. A creator using organic audience development could appear less effective than someone benefiting from coordinated interactions.

Over time, this creates the wrong incentives. Creators are encouraged to optimise for the numbers that attract brand partnerships rather than the relationships that make those partnerships valuable. The result is a market where visible performance can receive more attention than actual influence.

The issue also complicates return-on-investment calculations. If artificial interactions are included in the denominator of an engagement-based efficiency metric, the campaign may appear more successful than it really is. Brands could then use misleading benchmarks to evaluate future investments, creating a cycle in which poor measurement influences subsequent spending decisions.

Detection Needs to Move Beyond a Follower Count Audit

Identifying artificial engagement requires a more detailed examination of creator activity. A single metric rarely provides enough evidence to determine whether an account is authentic. Instead, brands need to look at patterns across audience growth, engagement behaviour, content performance and campaign history.

Sudden and unexplained increases in followers can be an early warning sign. A creator who gains a large number of followers without a corresponding change in content visibility or public exposure may require closer scrutiny. Similarly, engagement that rises sharply on selected posts but does not follow the account’s usual performance pattern deserves investigation.

Comment analysis is equally important. Brands can examine whether responses are relevant to the content, whether the same accounts repeatedly interact with the creator and whether conversations demonstrate actual interest in the category.

Audience geography and demographics also matter. A creator targeting Indian consumers may not deliver meaningful value if a substantial portion of the audience is concentrated in markets outside the brand’s distribution network. The location of followers, their interests and their activity patterns should be assessed against campaign objectives.

Technology can support this process. Influencer analytics platforms increasingly use automated tools to identify suspicious follower growth, engagement anomalies and potentially inauthentic interactions. However, such tools should be treated as decision-support systems rather than definitive judgements. An unusual engagement pattern may warrant investigation, but it does not automatically establish deliberate fraud.

Brands also need to assess performance across multiple campaigns instead of relying exclusively on a creator’s most successful post. Consistency, audience response and the quality of interactions over time can provide a more useful picture of influence than a single impressive report.

What Brands and Agencies Need to Change

The first change needs to happen during creator selection. Follower count can remain a discovery filter, but it should not determine the final investment decision. Brands and agencies need to evaluate audience authenticity, content relevance, engagement quality and historical performance before agreeing to a partnership.

The second is to make verification a standard part of campaign planning. Audience audits should take place before contracts are finalised, not after a campaign has delivered questionable results. This also requires agencies to maintain transparent documentation of creator selection criteria and the checks used to validate performance.

Contracts can play a larger role. Creator agreements should clearly define deliverables, reporting requirements, disclosure obligations and expectations around authentic engagement. Where appropriate, brands can include provisions addressing purchased followers, artificial interactions and misrepresentation of audience metrics.

Payment structures also deserve reconsideration. Paying entirely on the basis of follower count or a promised volume of engagement can create incentives that are not aligned with campaign outcomes. A more balanced arrangement can combine fixed creator fees with clearly defined deliverables and performance-linked components, depending on the nature of the campaign.

However, performance-linked payments need to be designed carefully. Not every campaign is intended to generate immediate sales, and creators should not be penalised for outcomes that depend on factors outside their control. The objective is not to make every partnership conversion-led. It is to ensure that the metrics used to evaluate performance reflect the reason the partnership was commissioned.

Finally, brands need to recognise that authentic creator marketing is not simply about finding accounts that pass a fraud check. It is about finding people whose content, expertise and relationship with their audience make them relevant to a particular brand or category.

Authenticity Is Becoming a Commercial Requirement

The next phase of influencer marketing will be shaped by a more demanding approach to accountability. As creator partnerships receive larger allocations and become integrated into broader media plans, brands will increasingly need evidence that the audiences they are paying to reach are real, relevant and responsive.

This does not mean that every high-engagement account is suspicious or that every creator participating in an engagement community is manipulating the system. Genuine creator communities often support one another, and meaningful engagement can take different forms across categories and platforms. The distinction lies in whether interactions reflect actual interest or are being generated primarily to create an artificial impression of popularity.

It also means that the industry needs to move away from treating authenticity as a subjective quality that can be established through a creator’s personal brand. A polished profile, consistent posting schedule and large comment section are not sufficient evidence of influence. Credibility needs to be supported by observable audience behaviour and transparent campaign reporting.

For agencies, this creates an opportunity to offer more than creator discovery and campaign execution. Their role can extend to audience intelligence, verification, measurement and accountability. For creators, it places greater value on building communities that engage because they find the content useful, entertaining or relevant.

For brands, the question is ultimately one of budget discipline. Every rupee allocated to influencer marketing should have a clear purpose, whether that is awareness, consideration, community building or conversion. Artificial engagement may help a post look successful, but it cannot guarantee any of these outcomes.

Follower Fraud 2.0 is therefore not just a problem of fake accounts or purchased comments. It is a problem of how the industry defines and rewards influence. When the numbers become easier to manufacture, the value of those numbers begins to decline. The brands that recognise this shift will be better positioned to distinguish between popularity that exists on a dashboard and influence that makes a difference in the market.

Because in an industry built around attention, the real question is no longer how many people appear to be watching. It is how many are actually listening.