Automotive and Mobility Services

Performance Max Case Study: Reducing CPA Through Cleaner AI Training Data

KINTO reduced online sales CPA by over ¥3,000 within four months by using automated fraud exclusion to feed cleaner data into Google's Performance Max bidding algorithms.

Industry
Automotive and Mobility Services
Company Url
Region
Spider AF Product
-¥3,000+ CPA
-¥3,000+ CPA
ROAS improvement
14 days Time to first insight
The Challenge

Budget disappearing with nothing to show for it

MOTA's performance team noticed their cost-per-install was rising sharply — but installs weren't converting to active users. Something was eating their budget.

  • Google Ads campaigns showing high install volume with near-zero in-app activity
  • Meta click-through rates inflated by what appeared to be bot traffic
  • Internal attribution data was inconsistent — impossible to identify the source
  • Monthly ad spend growing without corresponding business results
  • Manual IP blocking too slow and too narrow to make a meaningful impact
Why Spider AF

The only platform built specifically for ad fraud detection

MOTA needed more than a generic analytics tool. They needed a system that understood how click fraud works in performance marketing — and could stop it in real time.

01

Real-time invalid traffic detection

Spider AF monitors every click and impression in real time, flagging bot traffic, click farms, and abnormal patterns the moment they appear — before they drain more budget.

02

Direct Google & Meta integration

Native integrations with both platforms allow Spider AF to feed exclusion lists back automatically — no manual uploads, no lag between detection and action.

03

Transparent fraud reporting

Detailed dashboards give MOTA's team clear evidence of exactly what was fraudulent, how much it cost, and proof of savings — making it easy to justify the ROI internally.

The Approach

From blind spots to full visibility in four steps

01

Connect & audit

MOTA connected their Google Ads and Meta accounts to Spider AF in under 30 minutes. Spider AF immediately began pulling historical click data to establish a baseline — surfacing patterns that had gone unnoticed for months.

02

Identify fraud sources

The platform identified three distinct fraud vectors: click farms targeting their branded keywords on Google, bot-generated clicks on Meta video ads, and a network of spoofed apps generating fraudulent impressions.

03

Deploy exclusion rules

Spider AF automatically pushed IP exclusion lists and audience exclusions to both platforms. Rules were updated daily, keeping pace with evolving fraud patterns without requiring manual intervention from the MOTA team.

04

Monitor & optimise

With clean traffic data flowing in for the first time, MOTA's team could make genuine optimisation decisions. Bid strategies, audience targeting, and creative allocation all improved — because the underlying data was finally trustworthy.

The Results

Campaign performance before & after Spider AF

Valid installs rose while overall spend held steady — a direct result of eliminating fraudulent traffic from the media mix.

Monthly cost-per-install trend (JPY)

Before Spider AF After Spider AF
¥3,000 ¥2,000 ¥1,000 ¥0 Spider AF deployed Jan Feb Mar Apr May Jun
Pre-deployment average: ¥2,840 / install Post-deployment average: ¥940 / install

"We knew something was wrong, but we had no way to prove it. Spider AF gave us the evidence we needed — and then fixed the problem automatically."

Takeshi Yamamoto
Head of Performance Marketing, MOTA
The Outcome

Clean data. Real results. Confidence restored.

Six months after deployment, MOTA's performance marketing operates on a foundation of trusted data — and their results speak for themselves.

With invalid traffic eliminated, MOTA reallocated ¥2.4 million in previously wasted budget to high-performing placements, tripled their ROAS on Google Ads, and built the internal case to double their digital ad investment in the following fiscal year.

Frequently Asked

Questions about Spider AF for performance marketing

Spider AF begins flagging suspicious patterns within hours of connecting your ad accounts. Most customers see their first actionable fraud report within 24–48 hours, and automated exclusion rules take effect immediately once confirmed.

Yes. Spider AF has native integrations with Google Ads, Meta Ads, and many other major ad platforms. Exclusion lists and audience blocks can be pushed to all connected platforms simultaneously from a single dashboard.

Yes — and that's the point. Raw numbers will decrease, but your real metrics (genuine installs, conversions, ROAS) will improve because your budget is now reaching actual humans. Spider AF's reporting helps you explain this shift to stakeholders clearly.

Absolutely. Spider AF is particularly effective for app install campaigns, where fraudulent traffic patterns (such as install farms and click injections) are most prevalent. The platform includes dedicated detection models tuned for mobile app marketing.

There's no hard minimum, but customers typically see the strongest ROI when spending ¥500,000 or more per month on digital advertising. Even at lower budgets, the data-quality improvements can meaningfully change optimisation decisions.

Is click fraud eating your ad budget right now?

Most companies don't know how much they're losing until they measure it. Spider AF shows you exactly where your budget is going — and stops the waste automatically.

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Performance Max Case Study: Reducing CPA Through Cleaner AI Training Data

KINTO reduced online sales CPA by over ¥3,000 within four months by using automated fraud exclusion to feed cleaner data into Google's Performance Max bidding algorithms.

Company Overview

Company: KINTO Corporation (Toyota Group)
Industry: Mobility Services
Service: Car Subscription Service “KINTO”
Marketing Structure: Fully In-House Digital Marketing Team

KINTO Corporation, a Toyota Group mobility services company, operates the car subscription service “KINTO”, which provides consumers flexible alternatives to long-term car ownership.  Unlike many companies that outsource advertising operations, KINTO manages strategy and execution entirely in-house through its Digital Marketing Group.

As the company scaled its use of AI-driven campaigns such as Google Performance Max (P-MAX), the team faced a growing challenge: maintaining data quality while expanding aggressively. To address this, KINTO implemented Spider AF to protect campaign performance and brand integrity.

The Challenge

Scaling AI-Driven Campaigns Without Compromising Data Quality

KINTO’s marketing mission extends beyond maximizing contract volume. According to Mr. Nagao from the Digital Marketing Group:

“Our mission goes beyond simply maximizing the number of contracts. ROAS differs by vehicle model, and retention rates vary depending on the subscription plan. We focus on how to reach users who not only contribute more value to the business but are also likely to remain satisfied long term.”

To support this objective, the team leverages first-party data and a CDP (Customer Data Platform) to execute advanced data-driven marketing strategies.

However, as AI-driven campaigns like P-MAX became central to their strategy, concerns emerged.

“Our biggest challenge was balancing aggressive investment in growth with maintaining data quality.”

Low-quality or fraudulent traffic risked contaminating machine learning signals. If invalid clicks were included in optimization data, Google’s algorithms could misinterpret performance signals, reducing overall bidding precision.

Brand safety was also a priority.

“For us, protecting Toyota’s brand safety and maintaining strict data hygiene are issues closely tied to executive-level priorities.”

Initially, the team handled suspicious traffic manually. As Google Ads investment scaled, this approach became unsustainable.

The Solution

Automated Protection Designed for In-House Teams

KINTO evaluated multiple tools before selecting Spider AF. The decision centered on two primary factors: automation and transparency.

“The key factor was its ability to create a clean data environment capable of supporting advanced bidding strategies, combined with seamless integration suited for in-house operations.”

With a lean internal team, operational efficiency was critical. Spider AF’s API integration with Google Ads automatically excludes detected fraudulent IPs from campaigns.

“This level of automated defense enables us to execute sophisticated data strategies without increasing operational burden.”

Visualization also played an important role in the decision.

“Ad fraud often feels like a black box. Spider AF’s dashboard made the situation transparent. We were confident we could clearly demonstrate cost savings and risk mitigation to internal stakeholders.”

The Results

Quantitative and Strategic Gains

Within approximately four months of implementation, KINTO achieved measurable performance improvements.

Key Outcomes:

  • Reduced CPA for online sales by over ¥3,000 (~$20 USD)
  • Improved bidding precision
  • Increased operational efficiency through automation
  • Greater confidence in AI-driven optimization

Mr. Nagao explains:

“Quantitatively, we reduced CPA for online sales by more than ¥3,000.”

Beyond cost reduction, the quality of optimization improved.

“By eliminating fraudulent traffic, Google’s machine learning can now more accurately identify truly valuable users as signals.”

The team also observed improved downstream performance metrics:

“We have also seen improvement in the ratio of applications to actual service activation, indicating that bidding optimization is functioning as intended.”

Organizational Impact

Increased Confidence in Data-Driven Growth

One of the most significant changes was internal confidence in campaign scaling.

“The greatest impact may be the confidence we now have. Knowing that AI is operating on clean data allows us to scale with conviction.”

Previously, the team questioned the reliability of performance data. With data integrity maintained automatically, focus shifted toward strategic initiatives.

“With Spider AF maintaining data integrity, we can focus more on core strategy development and full-funnel initiatives integrated with our CDP.”

Looking Ahead

Data Quality as the Foundation for Advanced Bidding

As the industry moves deeper into a cookieless era, KINTO sees first-party data as increasingly critical.

“In a cookieless era, the importance of first-party data continues to grow. However, collecting data is not enough. The real question is how to refine it and activate it effectively in advertising.”

The team plans to continue developing advanced strategies such as Value-Based Bidding (VBB) while maintaining brand trust.

“The more advanced the technology, the more critical data quality becomes in determining outcomes.”

Spider AF is positioned as foundational infrastructure supporting this direction.

“We see Spider AF as a foundational partner that provides the baseline assurance required to pursue this approach.”

Conclusion

For KINTO, scaling AI-driven advertising required more than budget expansion. It required confidence in the integrity of the data fueling machine learning.

By implementing Spider AF, the company achieved measurable CPA improvement, strengthened brand safety, and enabled its in-house team to scale campaigns with greater precision and assurance.

For organizations leveraging automated bidding tools like P-MAX, KINTO’s approach demonstrates how indispensable clean data hygiene actually is. 

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