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Case Study

How Clickbringer Drove Breakout Amazon Growth for Vega Protein and Great Lakes Wellness

A strategic reset across structure, targeting, and budget allocation turned mixed early-year performance into meaningful second-half acceleration.

Engagement focus: H2 2024 optimization and growth pivot

Great Lakes Wellness visual used as cover for the Wellmore case study
Wellmore Portfolio: Vega + Great Lakes Wellness

Featured Brand

Vega Protein logo

Cross-brand execution balanced efficiency discipline with growth acceleration across protein and collagen categories.

The Challenge

  • Vega was down roughly 20% YTD at one point, with soft retail demand and increasing CPC pressure.
  • Budget was spread inefficiently across markets and campaign types, limiting return on incremental spend.
  • Non-branded reach was constrained, reducing new-customer acquisition and top-of-funnel growth.
  • Business priorities shifted from strict efficiency toward revenue and NTB growth under tight timelines.
  • Prime Day, T5, and BFCM windows created high-pressure moments where strategic mistakes would be amplified.

Before pivot

Vega down ~20% YTD

Efficiency pressure, uneven demand, and higher CPCs were weighing on core campaigns.

After stabilization

Efficiency held while scaling

The team protected the efficiency baseline before shifting harder into growth.

Breakout outcome

Stronger H2 momentum

The Wellmore portfolio delivered meaningful full-year growth across Vega and GLW without exposing confidential dollar figures.

Amazon Ads Strategy Reset

  • Re-segmented campaign structures by intent: branded, non-branded, and discovery.
  • Expanded non-branded keyword coverage to create scalable new-demand capture.
  • Adjusted placements and bid controls to manage CPC inflation while preserving visibility.
  • Shifted the operating model from efficiency-first to a hybrid growth framework prioritizing revenue and NTB where performance justified it.

PDP + Conversion Alignment

  • Prioritized ASIN-level execution during tentpole and high-traffic periods.
  • Aligned promotions, traffic, and listing visibility to maximize conversion lift.
  • Directed disproportionate support to top-performing ASINs when demand windows widened.
  • Maintained strategic focus on conversion alignment rather than unnecessary PDP redesign work.

Market Intelligence + Budget Steering

  • Used competitive spend signals in plant protein to exploit temporary efficiency opportunities for Vega.
  • Reacted to collagen category acceleration with tighter positioning for GLW.
  • Continuously reallocated budget by performance, market movement, and search-term quality.

Phase 1 — Stabilization

  • Tightened segmentation and corrected targeting inefficiencies.
  • Reduced spend leakage while protecting volume and baseline momentum.
  • Established a steadier efficiency baseline before increasing growth pressure.

Phase 2 — Scaled Growth

  • Increased non-branded and discovery investment once efficiency floors were stable.
  • Accepted controlled efficiency trade-offs to unlock greater topline expansion.
  • Rebalanced budgets dynamically instead of relying on static monthly allocations.

Second Half (Post–June 26 Start, YoY)

  • Vega gross sales

    +56%

  • GLW gross sales

    +25%

Full-Year Impact

  • GLW YoY growth

    +32%

  • Vega YoY growth

    +16%

Advertising Performance

  • Vega ad sales YoY

    +39%

  • GLW ad sales YoY

    +21%

Key Takeaways

  • Stabilizing structure before scaling prevented high-cost inefficiency during growth phases.
  • Non-branded expansion was the primary engine of incremental revenue.
  • Dynamic budget reallocation consistently outperformed static budget models.
  • Category-level competitive insight created timing advantages that internal metrics alone would miss.

This was a controlled strategic pivot under pressure. Structure, timing, and market awareness turned a pressured portfolio into measurable growth for both brands, while the public story stays limited to percentage and relative performance metrics.

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