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Outcome Tracking

Measure every change. Prove every result.

Did that SEO change actually work? Korvex measures every recommendation’s real impact — automatically. No more guessing, no more hoping. Proof that your SEO is working.

Recommendation #247Success

Add entity-rich FAQ section to /services/compliance

BeforeAfterChange
Monthly traffic120340+183%
Avg position#12#5+7 spots
Koray score4271+29 pts
Click-through rate1.8%4.2%+133%
Outcome measured 28 days after deployment

Most SEO work is a black box.

You make changes, hope for the best, and never really know what drove the results.

Fire and forget

You implement an SEO change and move on. Three months later, nobody can tell you whether it actually helped or just looked good on a to-do list.

Repeating mistakes

Without outcome data, you keep recommending the same types of changes even when they consistently underperform. Wasted effort compounds quietly.

No proof of ROI

When the CEO asks what SEO is actually delivering, you have rankings and traffic charts but no direct link between the work you did and the results you got.

A closed loop. Not a to-do list.

Every recommendation flows through a six-stage cycle. Nothing is fire-and-forget.

Closed-loop cycleContinuous
1

Recommend

SCIS generates action

2

Baseline

Capture current metrics

3

Deploy

Push change to CMS

4

Wait

Impact period elapses

5

Measure

Compare to baseline

6

Learn

Calibrate ML models

Outcomes improve future recommendations

How outcome tracking works.

1

Baseline captured automatically

The moment a recommendation moves to in-progress, Korvex snapshots the current Koray score, organic traffic, average position, and click-through rate for that page. No manual tagging required.

2

Impact period respected

SEO changes don’t work overnight. Korvex calculates an estimated time-to-impact based on the recommendation type and waits until that window has passed before measuring.

3

Outcome classified

After the impact period, Korvex compares the new metrics to the baseline. Each recommendation is classified as success, partial success, neutral, or failed — with the exact numbers to back it up.

4

Kanban auto-promoted

Successful recommendations are automatically moved to the completed column in your Strategy Actions board. Failed ones stay visible with context on what happened.

Before and after. Side by side.

Every recommendation gets a before-and-after report card. You see the exact metrics at the moment the work started and the exact metrics after the impact period — with percentage changes and a clear success or failure verdict.

No more correlating timelines in spreadsheets. No more “well, traffic went up around the time we changed that.” This is causal measurement, not correlation.

  • Baseline captured automatically at start
  • Four metrics tracked per recommendation
  • Impact period calculated by recommendation type
  • Clear success / partial / failure classification
Recommendation #247Success

Add entity-rich FAQ section to /services/compliance

BeforeAfterChange
Monthly traffic120340+183%
Avg position#12#5+7 spots
Koray score4271+29 pts
Click-through rate1.8%4.2%+133%
Outcome measured 28 days after deployment
Prediction accuracy over timeImproving
Month 1
61%
Month 2
68%
Month 3
74%
Month 6
82%
Month 12
91%

Every measured outcome feeds back into the prediction model. The longer you use Korvex, the more accurate your impact forecasts become.

The system gets smarter over time.

Every outcome — success or failure — becomes a training signal. Korvex feeds real-world results back into its ML models to improve future recommendations.

After month one, prediction accuracy is around 61%. By month twelve, it reaches 91%. The platform learns which types of recommendations work best for your industry, your pages, and your competitive landscape.

Recommendations that consistently underperform are automatically down-weighted. High-performers are prioritised and surfaced more often. Your strategy sharpens with every cycle.

78% of recommendations show positive impact.

Across all Korvex clients, 78% of recommendations measured within 30 days show either full success or partial success. That is not a marketing number — it is an aggregate of every outcome the platform has measured.

And the 22% that do not succeed? They are equally valuable. Failed outcomes teach the system what does not work, making the next batch of recommendations sharper.

Outcome breakdownLast 90 days
Success54%
Partial success24%
Neutral14%
Failed8%
78%

Positive impact rate

Success + partial success within 30 days

0%

Positive impact rate

0

Metrics per recommendation

0%

Prediction accuracy (12 months)

0

Manual tagging required

Frequently asked questions.

Stop guessing. Start proving.

14-day free trial. See your first outcome reports within 30 days.