Zoer: Transforming Influencer Marketing from a Manual Burden into a Scalable Growth System

1. From a Database Origin: Why Zoer Chose to Build a “Truly Complete AI Application”

Zoer AI did not start with Web Coding. Before entering the AI application generation track, the team’s first product was a tool that directly converts natural language into SQL.

With years of experience in databases, backend architecture, and data security, the team’s understanding of “application integrity” far surpasses most AI coding products. They build truly production-ready applications starting from backend and database capabilities.

This also allowed Zoer to form a clear positioning in the AI coding track:

Not just “writing code,” but “helping users get an application fully running from start to finish, even achieving profitability.”

2. In the Early Stage, Why Influencer Marketing Is the Optimal Choice

Currently, Zoer AI’s team has around a dozen people, with 3–4 people in the growth team, which is very lean.

Under limited resources, the team’s core goal is very clear:

Quickly validate PMF and obtain real market feedback with the lowest time cost.

In terms of channel selection, the team had also tried other methods:

• SEO: effective, but the overall cycle to see results is too long
• Product Hunt: more PR-oriented, not for continuous user acquisition
• Self-operated content matrix: controllable, but growth speed is slow

After weighing these factors, the team focused their cold start efforts on influencer marketing:

“For AI products, time is also a cost. Influencer content is currently the method with the highest ROI and fastest feedback we’ve seen.”

Especially for products that are functionally complex and require explanation of use cases,

influencers themselves are the best “product translators.”

3. Challenges of Working with Agencies vs. Building an In-House Team

Before using AhaCreator, Zoer tried two ways to advance influencer marketing: building an in-house team to contact influencers directly, and cooperating with overseas agencies. They found that both approaches had limitations.

3.1 Pricing and Costs Are Hard to Control

Agencies can provide a large pool of influencers, but the pricing is opaque, making it difficult for the team to judge:

• The influencer’s real price vs. the agency’s markup
• Whether CPM is artificially lowered by inflated metrics

3.2 Low Screening Efficiency and Long Cycles

Whether through agencies or an in-house team, matching and contacting influencers was challenging:

• Agencies would propose 10 influencers per week, but often none of the batch met requirements, requiring the team to wait for the next round and repeatedly confirm
• In-house teams had to spend a lot of time screening, sending emails, communicating, and following up

3.3 Data Feedback Is Not Realistic

In addition, the team encountered a core but common problem in the influencer marketing industry: inflated metrics that obscure real feedback.

“Some agencies only pursue exposure. The numbers look good, but user behavior and conversions don’t follow,” Jing said. “We can’t see real user reactions, which is very detrimental to product improvement and market validation.”

Although in-house teams could ensure real interactions, the volume was small and labor-intensive, making rapid scaling difficult.

The team wanted both transparency and speed in market validation, which traditional methods could not achieve simultaneously.

4. Using AhaCreator: Achieve Full Transparency Without Building In-House

After starting with AhaCreator, the biggest change for Zoer was not “having another tool,” but a complete restructuring of the influencer marketing workflow.

According to Jing, AhaCreator’s workflow aligns with the in-house system in 90% of the process. The real difference is:

The team no longer has to handle labor-intensive tasks—the AI staff take over the execution phase.

4.1 From “Repeated Proposals” to “Algorithm-First Screening”

In Zoer’s growth strategy, the core criterion for judging an influencer is:

Whether the influencer’s audience closely overlaps with the product’s target users.

Previously, whether through an agency or manual in-house contact, problems were concentrated in the early stage:

A lot of time and energy was spent repeatedly reviewing influencer profiles and filtering out mismatched candidates.

AhaCreator changed this by completing this step first.

The platform matches influencers based on content direction, audience profile, previous collaborations with competitors, and other dimensions. It also handles initial communication and price confirmation, then pushes highly matched influencers with confirmed pricing directly to Zoer.

The Zoer team only needs to do one thing:

Click on the influencer’s profile and decide whether to collaborate.

As a result, under the same selection criteria, Zoer’s influencer approval rate on AhaCreator can consistently remain above 30%.

Jing commented:

“This was almost impossible under our previous collaboration models.”

4.2 Hand Over Execution Entirely to AhaCreator

Zoer clearly positions AhaCreator as:

Not just a slight efficiency improvement on the existing workflow, but taking over the entire execution chain.

In daily use, AhaCreator covers nearly all high-frequency, repetitive, and labor-intensive tasks:

• Precisely selecting candidates from a large influencer pool
• Providing market-based cooperation quotes according to CPM, region, historical performance, etc.
• Automatically handling email outreach, collaboration confirmation, and price negotiation
• Sending reminders to influencers, following up on content submission, and monitoring content launch
• Continuously monitoring data performance after content release
• Automatically handling contracts and payment processes

Jing’s impression was very direct:

“Previously, one person’s daily work was just sending and receiving emails. Now, these tasks basically no longer require human intervention.”

This allowed Zoer to free up execution manpower for influencer marketing and enabled newcomers to quickly start producing content without being slowed down by the process itself.

4.3 Real Feedback, No Longer Obscured by Inflated Metrics

For Zoer, the goal of influencer marketing has never been “looking good in exposure numbers,”

but real user feedback and directly convertible users.

They had previously cooperated with agencies and received “guaranteed” exposure,

but inflated metrics, low conversion, and uncontrollable ROI gradually made the data lose reference value.

On AhaCreator, Zoer values whether the data is real and trustworthy.

The platform uses multiple mechanisms to continuously monitor content performance after release:

• Track video play curves for naturalness
• Monitor the ratio of likes, comments, and views for reasonableness
• Use semantic understanding to identify repetitive or potentially fake comments

Influencer marketing is no longer just “shiny exposure numbers,”

but a growth tool that listens to real market feedback and continuously brings genuine users.

5. From One-Time Collaboration to a Scalable, Sustainable Growth System

For Zoer, the real importance of this collaboration was not the performance of a single piece of content, but a key validation:

Whether influencer marketing can now scale like ad campaigns.

5.1 Not relying on viral hits, but “usable in bulk”

Looking at the overall results, the campaign’s traffic was not concentrated in just a few pieces of content.

In the performance distribution of all content:

• Top content contributed a clear amplification effect (video views above 200k)
• Mid-tier content output was stable
• A large number of long-tail content pieces continuously generated effective clicks in different markets

This structure indicates that conversion results do not come from “hitting one influencer,”

but from the collaborative effect of a batch of highly matched, precise-audience creators.

5.2 Multi-language, multi-market, leaving room for growth

This campaign covered multiple non-single-language markets, and in different languages:

• CPC remained low at $0.59
• User feedback structure was consistent, with no obvious “empty markets”

This allowed Zoer to confirm:

Influencer marketing is not limited to the English market and has global scaling potential.

When the budget increases from a few thousand dollars to tens of thousands per month,

the ability to run campaigns simultaneously in multiple markets is a prerequisite.

5.3 Influencer marketing achieves “ad-like” controllability for the first time

More importantly, the entire process is highly controllable:

• Creator sources, data, and audience analysis are clear
• Cost structure is transparent
• Content release schedule is stable and controllable
• Data feedback is timely

This makes influencer marketing no longer a series of “one-off collaborations,”

but closer to a system that can:

• Continuously onboard creators
• Produce content in bulk
• Review, eliminate, and scale based on results

Conclusion ｜When Influencer Marketing Shifts from Execution Burden Back to Growth

In Zoer’s view, the change AhaCreator brings is not just improved efficiency,

but for the first time makes influencer marketing controllable, reusable, and scalable.

When repetitive tasks like screening, outreach, execution, and monitoring are reliably handled,

influencer marketing no longer relies on labor accumulation,

but becomes a growth system that can run continuously.

On this basis, the team’s role also changes.

The growth team is no longer tied down by tedious execution details, but can focus on:

• Judging what content truly resonates with users
• Building a long-term effective influencer and UGC ecosystem
• Continuously optimizing reusable selection and content strategies

Jing, the head of marketing, exclaimed:

“Previously, every day was sending emails and waiting for replies. Now, we can finally focus on ‘what content to create,’ instead of ‘how to contact influencers.’”

When execution is no longer a burden,

creativity can be continuously amplified on top of a clear mechanism.