Real Clients.
Real Results.

The Challenge

Aoife & Co had been trading online for two years but their Shopify store was slow, cluttered, and not converting. Their average session duration was under 45 seconds. On mobile which accounted for 72% of their traffic the experience was borderline unusable. They were spending €1,200/month on Instagram ads with a ROAS of barely 0.9. Every euro in was a euro lost.

The founder had tried two freelancers before coming to us. Both delivered a redesign that looked good in Figma but performed poorly in the real world. She needed a partner who understood both the technical and commercial sides of e-commerce growth.

Our Approach

We started with a full conversion audit heat maps, session recordings, checkout flow analysis, and a full mobile UX review. Within the first week we identified seven critical friction points killing conversions: slow load times (6.2s on mobile), a confusing navigation structure, no trust signals at checkout, and poor product photography presentation.

We rebuilt the store on a performance-first architecture. New mobile-native UI with large imagery, streamlined navigation, trust badges, size guide integration, and a one-page checkout. Page load dropped to 1.8 seconds. Simultaneously, we restructured the Meta ad campaigns rebuilt the audience targeting from scratch, introduced a three-stage funnel (awareness → retargeting → conversion), and created new UGC-style ad creatives that matched the brand's authentic voice.

The Outcome

By day 30, conversion rate had climbed from 0.8% to 2.1%. By day 60, the ad campaigns hit a 3.1× ROAS. By the end of month three, monthly revenue had more than doubled compared to the same period the previous year with the same ad budget. The bounce rate on mobile dropped from 74% to 31%. The client reinvested her first month's gains into a new product line.

The Challenge

Arjun's startup was building an AI-powered HR automation tool for mid-size Indian companies a market with clear demand and a fragmented competitive landscape. He had an angel investor ready to commit ₹40 lakhs, but the term sheet required a working demo with real users within 45 days. Two previous development agencies had quoted 4–6 months and ₹25L+ just to begin. He had 45 days and a seed budget.

Our Approach

We ran a 3-day product scoping sprint to define the minimum loveable product stripping the feature set to the core value proposition: automated payroll computation, leave management, and an AI assistant for policy queries. We chose a modern tech stack (Next.js, Node.js, PostgreSQL, OpenAI API) optimised for speed without sacrificing scalability.

Week 1 delivered the database schema, authentication, and core payroll engine. Week 2 shipped the leave management module and admin dashboard. Week 3 integrated the AI chatbot and built the onboarding flow. Week 4 was QA, load testing, and deployment on AWS. We documented every component for future handover. On day 28, the product was live with a beta invite list of 340 early sign-ups from Arjun's waitlist campaign which we also helped structure.

The Outcome

The investor demo went ahead on day 30. The product performed flawlessly under live conditions. The seed round closed within two weeks. The day-7 retention rate of 62% well above the industry benchmark of ~40% for B2B SaaS tools gave the investor confidence in product-market fit. Quorae Tech continued as the technical partner for the next three months of growth-phase development.

The Challenge

Michael's company sold industrial workflow software to mid-market manufacturing firms across Germany and Austria. Their Google Ads account had been running on autopilot for three years broad keywords, generic ad copy, and a landing page that hadn't been updated since 2021. They were spending €8,500/month on paid search and generating roughly 40 leads per month, of which the sales team considered fewer than 8 genuinely qualified.

Their SEO presence was non-existent. A competitor ranking for their core product keywords was generating an estimated 1,200 monthly visits organically traffic they were paying for with ads.

Our Approach

We began with a full PPC audit keyword intent mapping, search term reports, quality score analysis, and competitor intelligence using SEMrush and SpyFu. Immediately apparent: 60% of spend was going on top-of-funnel informational queries from people who were not buyers. We restructured the campaigns into three tiers product-aware, competitor comparison, and demo-intent with tailored landing pages for each.

In parallel, we built an SEO content strategy targeting 22 high-intent German-language keywords across blog, feature pages, and a new comparison hub. We also implemented LinkedIn retargeting crucial for B2B in the DACH region and introduced a lead scoring model so the sales team could prioritise outreach effectively. The €8,500 budget was cut to €5,200 with spend reallocated to the highest-performing intent signals.

The Outcome

Within 90 days: ad spend was down 38%, qualified leads per month went from 8 to 27, and the SEO content had begun ranking on page one for 7 of the 22 target keywords. The sales team's close rate improved from 12% to 21% a direct result of better-qualified pipeline. Michael's marketing team, now working with Quorae Tech on a retained basis, has since expanded the strategy to the Austrian and Swiss markets.