Scale, Dip, Breakout: How PipeRocket Grew Astra Security's Paid SQLs 48%

The challenge

Astra Security sells penetration testing and VAPT into one of the most competitive, high-CPC corners of B2B — cybersecurity — across four regions at once: North America, APAC, EU, and ANZ.

PipeRocket took over the paid program in June 2025 with a clear mandate: scale. Grow qualified-lead volume through paid search — not squeeze efficiency out of a fixed budget.

That’s harder than it sounds. When you push spend up in paid search, cost per lead usually rises faster than volume, because the cheap, high-intent conversions get exhausted first. Most accounts scale by trading efficiency away — and in a high-CPC security market, that trade gets expensive fast.

The account we inherited had several structural problems working against it:

• No geographic granularity. NA, EU, and UK traffic was funnelled into broad campaigns with shared budgets and no geo-specific messaging — making real optimisation nearly impossible.
• Intent mismatch in the keywords. High-intent buyer terms sat in the same ad groups as low-intent research terms, diluting the signal and dragging up CPA.
• A competitor blind spot. Rival vendors were fielding comparison searches with no Astra presence — bottom-of-funnel demand lost every day.
• Landing-page friction. Forms buried below the fold, a chatbox overlapping CTAs, and one-size-fits-all messaging regardless of whether the visitor came from the US, EU, or APAC.

Our approach

PipeRocket ran the full Google Ads + Microsoft Ads program across all four regions, in six phases over the year.

Phase 1 — Restructure & NA split (Jul–Aug ‘25)

Replaced the broad US campaigns with tightly themed ones — one per core service line — and only paused the old campaigns once the new structure had proven traffic. The UK got dedicated keywords; the US competitor-alternative campaign moved to target-CPA bidding.

Phase 2 — Geographic expansion & competitor launch (Aug–Sep ‘25)

Stood up a dedicated ANZ campaign (excluded from APAC to avoid cannibalisation) and restructured EU/UK with geo-specific landing pages. Launched competitor-conquesting campaigns against the main rival vendors — plus a Bing competitor campaign — and moved several service-line campaigns onto portfolio bidding.

Phase 3 — Budget scaling & peak (Oct–Nov ‘25)

With the structure validated, scaled the weekly budget and pushed into peak performance. Refined ad copy, sitelinks, and negative keywords, and launched a high-intent quote-request keyword paired with a dedicated quote landing page.

Phase 4 — Seasonal defence & CRO triage (Dec ‘25)

As B2B demand softened after mid-December, proactively trimmed budgets by region in proportion to MQL volume — then used the slower period for a Microsoft Clarity audit, which surfaced the chatbox overlapping CTAs, form-rendering issues across screen sizes, and low-converting pages. Each was filed to the dev team as a specific ticket with session recordings.

Phase 5 — Quality drive (Jan–Mar ‘26)

Rebuilt budgets around the top performers, then pivoted the India campaigns to optimise for SQLs rather than MQLs — accepting a short-term dip in raw lead volume for better-qualified pipeline. Reactivated EU/UK service-line campaigns on exact match, expanded the competitor campaigns to more rival vendors, and continued Clarity-guided landing-page A/B tests.

Phase 6 — Aggressive scale (Apr–Jun ‘26)

Set target-CPA at the ad-group level, concentrating the most aggressive targets on the proven high-intent ad groups. Moved the lead form into the first fold, launched Performance Max for incremental volume, and closed the attribution loop by uploading offline conversions from HubSpot back into Google Ads via GCLID — so Smart Bidding optimised toward real qualified leads, not just form fills.

The results

Scaling is rarely a straight line, and Astra’s wasn’t. The four-quarter arc tells the real story: a scale-up, a dip, and a breakout.

Quarter-on-quarter change (Google + Microsoft Ads, all regions):

• Q4 ‘25 — the scale-up. The program launched its scaling push in November, and spend jumped 68% quarter-on-quarter, pulling SQLs up 34%.
• Q1 ‘26 — the dip. A rough patch from December into February pulled volume back (SQLs −23%). Scaling exposed weak spots, and they got fixed.
• Q2 ‘26 — the breakout. SQLs rebounded +42% to the highest-SQL quarter of the entire engagement, at the strongest lead-quality rate since the scale-up began.

Net across the window, SQLs grew +48% and MQLs +51%, while paid spend scaled +126%.

The March → June breakout

The recovery wasn’t a one-quarter blip — it was a sustained, month-over-month climb through the first half of 2026. SQLs increased every single month from March onward:

From March to June, SQLs grew +94% cumulatively, with June the single best month of the engagement across SQLs, MQLs, and total leads.

Why it worked

Seven compounding factors, not one silver bullet:

1. Geo-theme campaign architecture. Splitting NA into tightly themed campaigns let the algorithm learn buyer intent precisely — each sent clean, homogeneous signals instead of muddied mixed-intent data.
2. Ad-group-level target-CPA. Setting aggressive targets on the proven high-intent ad groups and lower ones on untested groups meant budget flowed toward proven converters instead of spreading evenly across unknowns.
3. Competitor conquesting. The main rival vendors were all running unopposed — targeted comparison campaigns captured bottom-of-funnel buyers already in vendor-selection mode.
4. Form in the first fold + chatbox removal. Lifting the lead form above the fold and clearing the chatbox off PPC pages removed the scroll and overlap barriers on the highest-spend campaigns.
5. The offline-conversion loop. Uploading HubSpot MQL/SQL data back to Google Ads via GCLID meant Smart Bidding learned from real qualified leads, not just form fills — sharpening every downstream bid.
6. Region-specific landing pages. UK, EU, APAC, and ANZ visitors each saw pages built for their context. Relevance converts; generic pages don’t.
7. Weekly tracking against goal. A regional MQL/SQL tracker updated weekly surfaced deficits early — giving the team room to correct course mid-month instead of discovering a shortfall at month-end.

Honest notes

• This was a scale mandate, and cost per SQL rose as spend scaled — expected when you more than double investment in a high-CPC market. The story is qualified-lead growth, not cost reduction.
• Pipeline for the most recent quarters is still maturing and is understated at time of writing, so this case study leads on SQL volume rather than booked pipeline value.