6 min read
Thank you to everyone who joined our recent webinar! The conversation turned out to be very engaging and open, with sharp questions from the chat, real disagreements, and genuinely useful experience shared by our guests.
If you missed the live session or want to rewatch it, the full recording is available here: https://drive.google.com/file/d/1HcGCJn5tSmWSVvyzw0PEykUOM7vf-AAe/view?usp=sharing
And if you would rather read through the key takeaways, we have put together a full summary below.
Key Takeaways
- Influencer marketing is a multiplier, not just an acquisition channel.
- Most teams fail due to lack of experiments and structured processes.
- Scaling breaks on operations, not creator discovery.
- The best results come from combining in-house and agencies.
- Automation enables scale, but key decisions must stay human.
1. The real role of influencer marketing
Influencer marketing is more than a user acquisition channel. It builds trust, shapes brand perception, and amplifies the effectiveness of everything else you run.
Its impact is often indirect: many users don't click a link in a description but instead Google the brand, visit the App Store, or find it through other means. This makes performance-only measurement misleading and promo codes one of the more reliable ways to track results.
Think of it as a multiplier: when the same audience sees your brand across paid and influencer channels, conversions across all channels tend to improve.
2. Core mistakes teams make
The most common mistake is over-focusing on a single KPI, usually user acquisition, while neglecting brand awareness, sentiment, and share of voice.
A related pattern is running only five or six tests, seeing no clear impact, and concluding the channel does not work. This typically reflects a lack of expertise in running experiments rather than a real channel failure.
Poor experiment design compounds the problem: when different briefs are sent to different creators simultaneously, it becomes impossible to separate what caused the result. To get clean insights, one brief should be tested across multiple creators.
Another costly assumption is believing the brand is well-known enough that creators will work for free or purely on a revenue-share basis. Outside of a brand's existing community, this rarely holds.
3. In-house vs agencies
In-house teams bring deep product knowledge and tighter control over strategy and messaging, but they are often stretched thin operationally. Agencies, particularly local ones, bring market expertise, established creator relationships, and the ability to scale execution faster, especially in regions where language and cultural context matter.
That said, agencies sometimes overpromise: claiming relationships with creators they do not have, or underestimating timelines. They also serve multiple clients, which means attention is naturally divided, and smaller accounts tend to receive less focus. The most effective model is hybrid: in-house teams own strategy and final decisions, while agencies extend execution capacity.
4. What breaks at scale
The real bottleneck at scale is not finding creators. It is managing the process across dozens or hundreds of them at once. Communication, approvals, follow-ups, and logistics grow exponentially and quickly overwhelm in-house teams that are also responsible for strategy.
Budget constraints add another layer: to justify increased spend, teams need to demonstrate results, which is harder when processes are not yet solid. Headcount is a third constraint, since hiring enough people to manage large creator volumes is rarely feasible without automation or agency support.
5. What actually scales
Results come from volume and systems: running many experiments, building repeatable processes, and combining mass outreach with smart filtering. Defining clear goals before execution is essential to avoid wasted effort. The difference in output can be dramatic: one Creally client, Spiry, went from reaching 200 creators per month to over 5,000 in 30 days, freeing their team from manual outreach entirely.
6. Most expensive mistakes
The costliest failures come from a lack of structured processes, which causes the same mistakes to repeat across campaigns. Poor measurement leads to wrong conclusions. Working with creators who are a poor fit wastes both budget and time. Full upfront payments without content approval create unnecessary risk.
A safer and widely used approach is to pay once the video is complete and approved but before it is published, which protects both the brand and the creator. Agencies can also serve as a useful intermediary in this process, holding payment until all conditions are met.
7. Automation: what works and what doesn't
Automation is well-suited to outreach at scale, analytics, number-crunching, and generating briefs or scripts. These are repeatable, rules-based tasks where AI tools can save significant time.
What should not be automated is final decision-making. An algorithm can surface a creator with strong stats and apparent relevance, but if the creator would never genuinely use the product, or if something about the fit feels off, no tool can replace that judgment.
Creative concepts, brand fit evaluation, and relationship-building remain fundamentally human. AI is a tool that empowers experienced marketers; it does not replace them.
8. Key principle of working with creators
At scale, mass outreach to a filtered and relevant pool consistently outperforms exhaustive manual selection. Rather than spending hours reviewing thousands of profiles before sending a single message, it is more efficient to reach out broadly to a qualified set and focus effort on those who reply.
The time savings are real: Moonly — Moon Calendar's influencer marketing manager reduced daily creator search from five hours to under one, recovering over 80 hours per month (all by switching to Creally). For smaller campaigns where volume is limited, manual selection still delivers better results, as careful curation pays off at that scope.
9. How to build the right strategy
Start with a clearly defined goal, then select the right model (CPA, gifting, or paid), decide on execution structure, and only then scale. Skipping this sequence is one of the most consistent sources of wasted spend.
When the foundation is in place, scaling becomes operational rather than chaotic. Using Creally, Peech doubled their ambassador base in the first month, with campaign setup taking 15 to 20 minutes per launch.
Final conclusion
Building an effective influencer marketing strategy starts with clarity on the goal, but the key is understanding how that goal shapes every downstream decision. A performance-driven goal requires different creators, formats, and measurement approaches than a brand-focused one, and mixing the two too early often leads to weak results on both sides.
The choice of model should follow naturally from that goal. CPA models tend to work only when demand and conversion are already validated, while gifting works best for content-native products, and paid collaborations are needed when control and predictability matter.
Choosing the wrong model too early can slow down testing or limit creator interest.
Execution structure comes next, and this is where most teams underestimate complexity. In-house teams bring product understanding and control, while agencies bring local expertise and speed. Without a clear division of roles, this often leads to misalignment rather than scale.
Only once the foundation is in place should scaling begin. Trying to scale before validating the model, process, and messaging typically results in wasted budget and operational overload rather than growth.