Technologies we build on
Fixed-scope data engineering for D2C and SaaS scale-ups. We reconcile your Shopify, Klaviyo, Meta and Stripe data into a warehouse your team owns — in 3–4 weeks, not 4 months.
Months of discovery. Bloated proposals. £40k quotes for a warehouse your CMO needs in time for next quarter’s board.
Productized packages built from 50+ engagements. Scoped in days. Delivered in 3–4 weeks. Your team owns it after.
Meta says one ROAS. GA4 says another. Shopify says something else. You can't defend any of them when the CMO asks why blended CAC went up 40%.
The last warehouse quote came back at £40k and four months. You don't have that time, and the budget isn't there for the wrong stack.
You couldn’t compete on salary. So you have a junior data analyst drowning in Sheets while your CMO waits on attribution numbers for the next board.
Mixpanel claims it. Amplitude claims it. Hightouch claims it. None of them reconcile to revenue. Customer LTV changes depending on who pulls the report.
From raw sources to business intelligence — a unified, production-grade pipeline.
Each one ships in weeks, fixed-price, owned by your team after handover. Each one can be extended into an optional managed service to keep it reconciled, monitored, and evolving.
Unified Shopify, ad platforms, email and GA4 in your warehouse — with clean dbt models for blended CAC, LTV, contribution margin, and channel attribution.
Managed service to keep it reconciled, monitored, and evolving — from £3k/month.
A unified customer profile across Shopify, Klaviyo, Meta and your CS tools — segmentation-ready, with reverse ETL back into your marketing stack.
Managed service to keep it reconciled, monitored, and evolving — from £3k/month.
A productized BI layer with the dashboards a D2C founder actually uses — cohort retention, channel P&L, LTV curves, and inventory velocity.
Managed service to keep it reconciled, monitored, and evolving — from £3k/month.
For D2C brands, that means customer data privacy that holds under ICO scrutiny. For SaaS, it means infrastructure that passes enterprise security reviews. Both mean: pipelines, warehouses, and access layers your team can defend.
Every Neo Analytica engagement is structured around the seven UK GDPR principles — lawfulness, fairness and transparency; purpose limitation; data minimisation; accuracy; storage limitation; integrity and confidentiality; and accountability. We don’t bolt compliance on at the end. We design for it.
Ingestion pipelines tag every personal data field with its lawful basis under UK GDPR Article 6 — so downstream use is auditable, not assumed.
We scope collection to what the business actually needs. Fewer columns, shorter retention, clearer purpose — aligned with DPA 2018 principles.
Warehouses and lakehouses are modelled so subject access and deletion requests resolve in hours, not sprints — with full audit trail.
Default to UK/EU regions for storage and compute. Cross-border flows are documented with SCCs, transfer risk assessments, and ICO guidance.
UK regulator guidance on governance, records of processing activities, and DPIAs — baked into how we document every pipeline we deliver.
Information security management controls inform our access, logging, and key-management defaults — so your platform passes vendor security reviews without rework.
Identify → Protect → Detect → Respond → Recover. We map observability, alerting, and incident runbooks against NIST CSF functions.
Application-layer threats don’t stop at the API. Our data APIs, reverse-ETL endpoints, and portal surfaces are built against OWASP standards.
Neo Analytica is a UK-registered data engineering consultancy. We are the data controller for this site and act as a data processor for client engagements under signed Data Processing Agreements. See how we applied this in our ETL modernisation case study, or read our Privacy Policy and Terms for the full legal basis.
30-minute call to diagnose your challenges and recommend the right package.
We audit your stack and send a fixed-price proposal within 48 hours.
Weekly demos using proven templates. You see working results early.
Full handover with docs, training, and 30 days of post-launch support.
Founders should not be buried in data pipelines or attribution modelling. Their attention belongs on the work that moves the company forward — launching products, improving retention, and opening new markets.
Too often, though, the infrastructure underneath gets in the way. Time disappears into schema changes. Teams stall over tool decisions. Dashboards lose credibility. Spreadsheets become the fallback. CAC numbers change depending on who runs the report.
Jeff Bezos once asked whether a task “makes the beer taste better.” The idea is simple: if you run a brewery, your job is to make great beer. Everything else still matters, but it should be handled with enough precision that it never distracts from the core business.
That is the role we play. Attribution infrastructure does not retain customers. CAC models do not improve the product. But when they are built properly, they give founders the clarity to move faster, decide with confidence, and stay focused on what matters most.
Does this make the beer taste better?
We built Neo Analytica on a single conviction: the best D2C brands and SaaS companies win because they focus on what they do brilliantly — not because they became expert data engineers along the way.
Fixed scope. Real handover. Your team owns the result. Because infrastructure you depend on shouldn’t depend on us.
Built from 200+ client audits — including D2C brands, SaaS scale-ups, and e-commerce operators — where we consistently find 35–60% of data infrastructure spend is wasted. Covers real cost benchmarks, fillable scoring matrices, and battle-tested stack patterns.
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What’s inside
That’s the whole point. We reconcile Shopify, Klaviyo, Meta, GA4, and Stripe into a single warehouse with one definition per metric — so blended CAC, ROAS, and LTV match across every dashboard. You walk into the next board meeting with one number you can defend, not three you have to choose between.
Yes — D2C and e-commerce scale-ups (£5M–£50M revenue) are our primary ICP, and B2B SaaS (Series A–B) is a close second. Our packages are designed around the Shopify + Klaviyo + Meta + Stripe stack, plus the Mixpanel/Amplitude reconciliation pain SaaS teams hit at Series A scale.
Yes — it’s most of what we do. We build the modelling layer that makes blended CAC, channel ROAS, and customer LTV match across every reporting tool. Reverse ETL into Klaviyo, Meta CAPI, or your ops tooling included.
We model usage events alongside billing events in your warehouse, with shared customer/account dimensions — so product analytics and revenue tie out. Same approach for customer success: usage data joins to subscription state without manual exports.
AWS, GCP, and Azure. Templates are cloud-agnostic at the logic layer, optimised per platform. Default warehouse is BigQuery or Snowflake — we’ll recommend based on your data volume and cost profile.
30 days post-launch support, full documentation, and training. Your team owns the dbt models and pipelines outright — no vendor lock-in. Optional managed retainers available if you’d rather not run it in-house.
Agencies pretend to do data work; freelancers are a single point of failure. We use battle-tested templates from 50+ projects, ship in 3–4 weeks fixed-price, and your team owns every line of code afterwards.
£8,000 to £30,000. Every penny scoped upfront — no surprises. Most D2C engagements land £8–25k; SaaS engagements typically £10–30k.
Every engagement is built around the seven UK GDPR principles and the Data Protection Act 2018 — lawful basis tagging, data minimisation, right-to-erasure-ready models, UK/EU residency by default, and audit-ready documentation. We sign DPAs as standard and align our security baseline with ISO/IEC 27001, NIST CSF, and OWASP — so we pass enterprise vendor reviews without rework.
A 30-minute conversation to understand your stack, your attribution gaps, and whether our approach makes sense. No pitch deck. No commitment.