You know ad algorithms need more signal. Phone orders, offline sales, real LTV, propensity scores. But building that pipeline means hiring a data engineer you can't afford. So you keep explaining why "performance is flat" while agencies with better infrastructure eat your lunch.
Results from agencies using Pragmatik
Every agency owner knows these moments. The calls you dread. The pitches you lose. The gap between what you know should work and what you can actually deliver.
The client's on a call. ROAS is flat. You know the algorithm is optimising on partial data — it's not seeing phone orders, delayed purchases, or real customer value. But you can't explain that without admitting your tracking is broken. So you talk about "algorithm learning periods" and hope next month is better.
"We've been saying 'give it time' for three months now."
They walked in talking about predictive LTV, value-based bidding, propensity scoring. You talked about your team's experience and creative strategy. The client's eyes lit up for them. You drove home knowing you lost because they have infrastructure you can't match.
"We need to figure out how they're doing that."
A £50 impulse purchase and a £5,000 repeat customer are both "1 conversion" to Google. You're running "value-based bidding" with no actual values. The algorithm chases volume, not profit. Your client's CAC keeps rising and you can't explain why targeting "isn't working."
"We're getting more conversions but the client says revenue is down."
A data engineer who understands ad APIs, conversion tracking, ML pipelines, and can build this from scratch costs £100K+. You'd need 15+ clients on the platform before the ROI works. So you stay stuck — knowing what you need but unable to build it.
"We keep saying 'next year' but it never happens."
The agencies winning right now aren't better at media buying. They have data infrastructure that makes the algorithms smarter. You can keep explaining why performance is "complicated" — or you can close the gap.
What changes when your clients' algorithms get complete data — not just what the pixel catches, but phone orders, offline sales, real revenue values, and predicted lifetime value?
"Performance is complicated — the algorithm needs time to learn. Let's wait another month."
"Here's the dashboard. ROAS is up 30% since we started feeding LTV data into bidding. Let's talk about scaling."
Everything algorithms need to optimise properly. White-labelled as your platform. Sold at your price.
Phone orders, offline sales, CRM-closed deals, repeat purchases — piped back to Google, Meta, and Bing as first-party conversion events. The algorithm finally sees the full picture.
Actual revenue, predicted LTV, and margin data flowing into bidding. Not "conversions" — profit. The algorithm stops chasing £50 orders and starts finding £5,000 customers.
ML-powered propensity scores, LTV predictions, and customer segmentation. Feed high-value signals before the conversion happens. The kind of capability that wins enterprise pitches.
Your logo, colours, domain. Clients see your platform — never ours. Markov chain attribution showing real channel contribution. Proof of value they can't get elsewhere.
Your clients' data in their own warehouse. SQL access on demand. No lock-in, no hidden fees, no surprise cloud bills. You're building an asset, not renting one.
No 6-month implementation. No hiring. First client live in weeks. We handle the infrastructure. You handle the relationship and the margin.
Add £1–3K/month margin per client
You charge your clients £3–6K/month. You keep the difference.
10 clients = £30K+/month in new recurring margin. No data engineers required.
See If It Fits →Real outcomes from agencies that closed the signal gap.
We started feeding real revenue values and LTV predictions into bidding instead of treating every conversion as equal. ROAS jumped 30% for our biggest client — a £100M+ retailer. Same ad spend. Same creative. Just better data going into the algorithm.
PPC Agency — £100M+ retail client
Phone orders, offline sales, delayed B2B closes — none of it was reaching the ad platform. After plugging in the pipeline, smart bidding had 20% more signals to work with. Performance improved because the machine finally saw reality.
Performance Agency — eCommerce portfolio
We white-label the platform and sell it as our own data service. Across 8 clients we've added £12K/month in recurring margin. Clients pay more because they see more value. Retention improved because we can prove what's working.
Agency Director — UK performance agency
Enterprise client, big budget. Previous pitch we lost because we couldn't match the data story another agency told. This time we walked in with value-based bidding, propensity scoring, LTV predictions — all under our brand. We won.
Agency Founder — £500K account win
A clear path to closing the signal gap.
We understand your clients, their tracking gaps, and the revenue opportunity. No pitch deck — just a conversation about whether this fits.
30 minutes
Pick one client. We install tracking, connect their ad platforms, and set up the branded dashboard. You see real data flowing.
Week 1–2
Offline conversions, revenue values, and LTV predictions start feeding into smart bidding. Performance impact becomes visible.
Week 3–4
Expand to more clients. Each one adds margin. Each one strengthens your competitive position. The infrastructure scales with you.
Ongoing
The agencies winning right now have better data infrastructure. You can keep waiting for the right time to build it in-house. Or you can close the gap this month.
Let's Talk →30-minute call. No commitment. Just a conversation about whether this fits your agency.
Not ready for a call? Email me directly — I'm the founder and I read every message.