How Klover Proved Influencer Marketing Actually Drives Incremental Growth

Fast Facts

Industry: Fintech / Consumer Mobile App (Cash Advance Service)

Challenge: Influencer marketing spend was scaling fast via Agentio, but the team had no way to prove whether YouTube sponsorships drove incremental conversions or just captured users who would have converted anyway.

Solution: BlueAlpha integrated Agentio spend and view data directly into always-on MMMs, establishing causal contribution across iOS and Android while building a custom measurability tool for evaluating future creator partnerships.

Timeline: Full integration in 2 weeks; first confident contribution reads within 4 weeks; measurability tool delivered within 6 weeks.

Results:

• ~10% modeled contribution to iOS conversions from Agentio

• ~7.5% modeled contribution to Android conversions

• Incremental cost per conversion better than expected vs. other channels

• 38+ YouTube channels tracked at granular level (scaling to 100+)

• Custom measurability calculator to evaluate any influencer deal before signing

• Confidence to scale influencer spend aggressively

The Situation

Klover, a cash-advance app with millions of users, had already proven they could optimize programmatic channels with BlueAlpha. Meta iOS spend was cut 50% without losing conversions. Apple Search Ads scaled 10x while remaining incremental. The action system was working.

Now they faced a different challenge: influencer marketing.

Klover was partnering with YouTube influencers through Agentio, an AI-native platform for buying, managing and maximizing influencer investments. They measured conversions with AppsFlyer through a last-touch attribution logic. The channel showed promise based on AppsFlyer’s last-touch attribution, but this attribution logic is fundamentally the wrong framework for measuring influencer impact: it fails capture non-click, cross-device, and delayed conversion behaviors typical of creator-driven journeys.

The Challenge

YouTube influencer marketing breaks every rule of performance measurement.

Traditional programmatic ads generate continuous signals: impressions, clicks, and conversions flow steadily, giving models plenty of data to learn from. YouTube influencer spend, by contrast, is deployed upfront, while impact compounds over time as creator content continues to generate views, engagement, and conversions long after the initial post.

The Klover team articulated the problem clearly:

"A lot of people want to experiment with influencers. They want to pay $10,000 and have someone post a video or an Instagram story. But it's just very hard to measure the incrementality when you're relying on last-touch attribution - which is what most teams default to. And that's not good enough."

The questions stacking up were familiar to any growth team scaling creator partnerships:

• Is Agentio actually driving new users, or just capturing people who would have found us anyway?

• Which YouTube channels are performing better than others?

• How do we evaluate a new creator deal before signing? What's the minimum audience size that would even register in our data?

• Should we scale this aggressively, hold steady, or pull back?

Without answers, Klover faced the risk of leaving money on the table.

The challenge of influencer marketing measurement: lumpy spend vs. continuous signals.

BlueAlpha's Approach

BlueAlpha deployed a three-phase methodology designed specifically for lumpy, hard-to-measure channels like influencer marketing.

Phase 1: Deep Data Integration (Weeks 1-2)

Unlike programmatic platforms with API connections, Agentio data required custom integration. BlueAlpha built a pipeline capturing:

• Weekly spend by campaign - When money went out the door

• Views over time - Not just total views, but the daily/weekly trajectory as videos gained traction

• YouTube channel granularity (via Agentio's reporting) - Which creator posted what, enabling channel-level performance analysis

The key insight: treating influencer spend like programmatic spend (attribution at point of click) would never work. Instead, BlueAlpha modeled the relationship between accumulated views and downstream conversions, capturing the delayed, distributed impact of creator content.

To properly observe incrementality, Agentio spend was initially counted in both iOS and Android models at 100% each - a temporary approach to see actual contribution before establishing the optimal allocation split.

Phase 2: Contribution Measurement (Weeks 3-4)

With data flowing, BlueAlpha's MMM revealed what last-touch attribution metrics never could: the actual causal contribution of Agentio to conversions.

Observed Performance:

• iOS Model: ~10% contribution to weekly conversions

• Android Model: ~7.5% contribution to weekly conversions

• Consistent ratio between platforms, enabling proper spend allocation

The team's reaction: "This is better than we expected."

The model also established a critical baseline metric: boost per 1,000 views.

Across the initial observation period, Agentio delivered approximately 2 conversions for every 1,000 video views, with natural fluctuation between 1 and 3 depending on content and audience.

Phase 3: The Measurability System (Weeks 5-6)

Proving Agentio worked was step one. The growth team needed something more: a system to evaluate any influencer deal before spending a dollar.

BlueAlpha built a custom measurability calculator that answers the question every media buyer asks: "If I sign this creator, will we even be able to detect the impact?"

The tool takes two inputs:

1. Expected views from the media package

2. Cost of the deal

It outputs:

• Expected conversions (based on Agentio's proven boost-per-view rate)

• Cost per conversion (with confidence ranges)

• Measurability Score - a signal-to-noise ratio indicating whether the expected lift would stand out from natural fluctuation

How to interpret the score:

• Score > 2: Effect clearly above noise, will stand out in the data

• Score 1-2: Detectable over a few weeks of monitoring

• Score < 0.5: Effect smaller than normal weekly fluctuation - effectively unmeasurable

This transforms influencer buying into calculated decision-making. Before signing a deal, the team can input the creator's expected reach and immediately see whether the partnership is worth pursuing from a measurement standpoint.

The Results

Influencer Marketing Validated

Agentio wasn't just working - it was working well. The channel earned its place in the marketing mix with measurable, causal contribution to both platforms.

Channel-Level Intelligence Unlocked

With 38 YouTube channels running (scaling to 100+), Klover now has visibility into relative performance by creator. While full incrementality testing per channel would create too much noise, the data provides heuristic guidance: which channels consistently drive higher boost-per-view rates, informing renewal and expansion decisions.

A Reusable Decision Framework

The measurability calculator isn't a one-time analysis. It's a permanent addition to the growth team's toolkit:

• Evaluate any new influencer partnership before signing

• Set minimum audience thresholds for one-off sponsorships

• Compare expected ROI across different creator packages

• Make data-driven renewal decisions

Confidence to Scale

Most importantly, Klover now scales influencer spend with conviction. Every dollar into creator partnerships can be tied to expected outcomes, monitored in the MMM, and validated against the measurability framework.

Key Takeaways

Influencer marketing can be measured - if you build for it. The secret, rather than just "better attribution", is integrating views-over-time with spend data and modeling the delayed conversion impact through a properly calibrated MMM.

Last-touch attribution is the wrong framework for influencer. Measuring creator partnerships via AppsFlyer or any last-touch model will either over-credit (if someone clicks a link) or under-credit (if they search directly after seeing a video). Only incrementality-aligned measurement reveals what's actually incremental.

A measurability system beats one-off tests. Proving a channel works is valuable. Building a reusable framework that evaluates every future deal is transformational.

Lumpy spend requires different statistical thinking. You can't apply continuous-signal logic to lumpy-spend channels. BlueAlpha's approach accounts for natural KPI fluctuation (Klover's weekly conversions fluctuate by ~10% naturally), enabling proper signal-vs-noise assessment.

Every ad platform needs external validation. As Klover's team put it: "Every upcoming ad platform is under pressure to prove their stuff actually works." Third-party measurement isn't just nice-to-have - it's becoming table stakes for credibility.

Contribution chart showing Agentio alongside other channels, demonstrating its relative contribution. This positions influencer marketing as a legitimate, measurable channel within the broader mix.

What's Next

Klover's influencer measurement system continues to evolve:

Scaling Agentio with confidence - With incrementality proven and a measurability framework in place, the team is expanding creator partnerships while monitoring contribution in real-time.

Channel-level optimization - As data accumulates across 100+ YouTube channels, BlueAlpha will provide guidance on which creator relationships deliver strongest relative performance.

Extending the framework beyond Agentio - The BlueAlpha measurability calculator was built on Agentio data, but its methodology applies to any influencer spend. One-off Instagram posts, podcast sponsorships, TikTok creator deals - all can be evaluated using the same signal-to-noise framework.

Productizing for broader use - The BlueAlpha team is exploring how to make influencer measurability assessment a standard feature in the BlueAlpha platform, enabling any marketer to evaluate creator partnerships before committing budget.

About BlueAlpha

Founded by former Tesla leaders, BlueAlpha transforms marketing measurement into an action system. We don't just report what happened - we tell you what to do next, at the campaign level, refreshed weekly.

For hard-to-measure channels like influencer marketing, we specialize in building the data architecture, measurement frameworks, and decision tools that turn "we hope this works" into "we know this works."

Ready to Prove Your Influencer Marketing Works?

Stop guessing whether creator partnerships drive real results. BlueAlpha's incrementality-aligned measurement reveals the truth behind platform metrics - and builds the systems to optimize every future deal.

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View more case studies:
Klover Meta iOS Optimization | Proper Cloth YouTube Validation | Pettable Action System

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