Ryds Glas

Streamlining & Structure for Maximum Marketing Profitability

cost

-38%

cost per lead

growth

+13%

leads

clicks

+12%

CTR

The
problem

Siloed Sales Data: Ryds Glas used HubSpot to qualify leads, but data was never fed back into marketing. Google Ads was optimizing completely blind, unaware of which leads were actually producing real business value.

Fragmented Customer Journey: The ad architecture and user experience were fractured, making it impossible to tailor messaging based on where prospects were in the buying process.

Hard-to-Pinpoint Niche: Attempting to isolate the right B2B decision-makers in the glazing and glass industry using standard targeting alone led to massive ad waste and volatile lead quality.

SCALE

—

DISRUPT

—

GROWTH

—

ROI

—

OPTIMIZE

—

STRATEGY

—

DATA

ROAS

—

SCALE

—

DISRUPT

—

GROWTH

—

ROI

—

OPTIMIZE

—

STRATEGY

—

DATA

—

ROAS

—

The solution

01 / Value-Based CRM Integration

We bridged the gap between marketing and sales by connecting HubSpot directly to Google Ads. By feeding closed-loop lead values back through the sales pipeline, we gave the algorithms a precise source of truth to optimize for actual revenue rather than mere clicks.

02 / Funnel-Based Audience Targeting

We overhauled the account architecture and created dynamic audience lists mapped to the exact stage of the buying cycle. This allowed us to surgically align search messaging depending on whether a prospect was identifying a need or requesting a quote.

03 / Dynamic Audience Modeling

By feeding ideal customer profiles (ICPs) into the system, we pointed bidding algorithms toward decision-makers exhibiting identical digital behavior patterns, driving up relevance and depressing costs. Streamlining and structure gave Ryds Glas maximum marketing profitability, with budget aimed at real deals instead of clicks.

import { MMM } from 'zkond-core';
const engine = new OptimizationEngine();
// Analyserar Google Ads Performance...
engine.analyze('ROAS', '7.2x');
if (engine.status === 'ready') {
  engine.applyScale(Math.PI * 2);
}
console.log("CR: +12.5% | Sales: +185%");
function syncPixels(cid) {
  return cid.map(t => t.value);
}
// Running deep-link validation...
let data = MMM.fetchMatrix('Q3_DATA');
const config = { mode: 'aggressive' };
data.process(config);
// Fetching GA4 Realtime API stream...
const ga4Stream = await fetch('/api/ga4/stream');
const metrics = await ga4Stream.json();
if (metrics.bounceRate < 0.25) {
  budget.allocate('Meta Ads', 0.40);
}
/* Executing Machine Learning Attribution Modeling */
const model = new DataDrivenModel();
model.train(metrics.historicalData);
console.log(`Attribution confidence: ${model.score * 100}%`);
const webhookUrl = "https://zkond.se/hooks/v1";
await axios.post(webhookUrl, { status: "OPTIMIZED" });
// Cleaning temporary caching matrices...
Cache.clear(['temp_roas', 'temp_cpa']);
let activeCampaigns = engine.getRunning();
activeCampaigns.forEach(c => c.refreshBid());
console.warn("High CPA detected on TikTok Ads - adjusting.");
engine.throttle('tiktok_pixel_01', 0.85);
// Optimering slutförd. System stabiliserat.
window.dispatchEvent(new Event('ZKOND_SYNC'));
import { MMM } from 'zkond-core';
const engine = new OptimizationEngine();
// Analyserar Google Ads Performance...
engine.analyze('ROAS', '7.2x');
if (engine.status === 'ready') {
  engine.applyScale(Math.PI * 2);
}
console.log("CR: +12.5% | Sales: +185%");
function syncPixels(cid) {
  return cid.map(t => t.value);
}
// Running deep-link validation...
let data = MMM.fetchMatrix('Q3_DATA');
const config = { mode: 'aggressive' };
data.process(config);
// Fetching GA4 Realtime API stream...
const ga4Stream = await fetch('/api/ga4/stream');
const metrics = await ga4Stream.json();
if (metrics.bounceRate < 0.25) {
  budget.allocate('Meta Ads', 0.40);
}
/* Executing Machine Learning Attribution Modeling */
const model = new DataDrivenModel();
model.train(metrics.historicalData);
console.log(`Attribution confidence: ${model.score * 100}%`);
const webhookUrl = "https://zkond.se/hooks/v1";
await axios.post(webhookUrl, { status: "OPTIMIZED" });
// Cleaning temporary caching matrices...
Cache.clear(['temp_roas', 'temp_cpa']);
let activeCampaigns = engine.getRunning();
activeCampaigns.forEach(c => c.refreshBid());
console.warn("High CPA detected on TikTok Ads - adjusting.");
engine.throttle('tiktok_pixel_01', 0.85);
// Optimering slutförd. System stabiliserat.
window.dispatchEvent(new Event('ZKOND_SYNC'));



HubSpot CRM integration



Dynamic CRM audience lists



Value-based bidding



Non-brand keyword architecture

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