Technology, Data & AI
We build the data and software layer a strategy depends on, then test it against the orders, invoices and records it claims to describe.
Discuss this with usTechnology, data and AI work at THEFOCUS covers the systems that record, move and report a business's activity: commerce platforms, analytics and tracking, data pipelines, business intelligence, integrations, custom software and AI features. We design them around the decisions they must support, build and test them on real inputs, and check what they report against the system of record.
Relevant industries
Associated solutions
Business challenges
01
Two analytics tools, two answers
Duplicate tags count every page view twice, two analytics properties disagree with each other, and a redirect app rewrites traffic sources, so the dashboard cannot say which channel produced a sale.
02
Ad platforms that claim more revenue than the business took
Two conversion actions both count every order, or several platforms credit themselves with the same sale. Reported return looks healthy, and budget moves toward the campaigns that are best at claiming credit.
03
Integrations that look connected and deliver nothing
A pixel loads but never records a purchase, an email platform stops sending once a plan quota is reached, a connected sales-channel app starts campaigns nobody created. Each one looks healthy on its settings page.
04
AI features nobody has tested on real questions
A chat assistant passes its own test suite and still gives wrong answers to the questions customers actually ask, because the tests checked which route a question took and never read the reply.
05
Migrations that quietly lose history
A store or system is moved to a new platform without checking that every product, customer and historical order arrived, and reports built on the new platform start from an incomplete record.
What this covers
- Technology strategy and platform selection
- Choosing commerce, CRM, analytics and hosting platforms against the processes and reports they must support, with migration effort and running cost stated for each option.
- Digital transformation and replatforming
- Moving products, customers and order history between platforms, with record-by-record count checks against the source before the old system is switched off.
- Enterprise and custom software
- Web applications, internal tools and multilingual sites built on modern frameworks and managed hosting, with test suites written against real use.
- Data architecture and business intelligence
- Event design, server-side tracking, consent handling and reporting models that reconcile to the order book or the ledger.
- AI integration and AI-search readiness
- Assistants that answer only from the business's own content, with regression tests built from real customer questions, and sites prepared for AI search through structured data and machine-readable files such as llms.txt.
- Workflow automation and systems integration
- Connections between the store, CRM, accounting, email and advertising systems, with logging so a failed run raises an alert instead of passing unnoticed.
How we approach it
01
Map the system of record
For each figure the business relies on, we identify which system holds the authoritative record and which systems copy it. Every report we build is later checked against that source.
02
Prove collection, then prove delivery
A tag on the page shows that data is collected. We confirm delivery from what happens downstream: purchases arriving in the ad platform with the right value, sessions credited to the right channel, emails that were actually sent.
03
Change live systems with a way back
Bulk edits run only after a full snapshot of the prior state. Anything that spends money is staged paused for review. Migrations are checked by count and by sample before the old platform is retired.
04
Test on real inputs
Software and AI features are tested against realistic inputs, and every case that fails becomes a permanent regression test before the feature ships.
What you keep
- A measurement plan and event specification tied to named business decisions
- Working tracking, consent and server-side event setup, checked against recorded orders
- Migrated platform data with a written count and sample check
- Source code, configuration and test suites held in the client's own accounts
- Integration and automation documentation, including failure alerts and owners
How outcomes are evaluated
- Gap between reported conversions or revenue and orders recorded by the business
- Share of key events firing with correct values across tracked pages and devices
- Field Core Web Vitals results for tracked URLs
- Migration completeness by record count and sampled field accuracy
- Regression test results on real-world inputs for each AI feature
Scope boundaries
- Platforms, hosting and software subscriptions are recommended for the client's own accounts, so the client owns the systems, code and data when the work ends.
- AI features are scoped to defined tasks with written limits. We do not present them as autonomous decision-makers or claim capabilities they have not been tested for.
Questions executives ask
Do you build software yourselves or only advise on it?
We do both. The core team builds websites, web applications, integrations, tracking and automation, and brings in developers from the partner network for larger or specialist builds. Code and configuration end up in your own repositories and accounts.
Which platforms do you work with?
Recent engagements have used Shopify, GA4, Google Ads, Google Merchant Center, Meta advertising, Klaviyo, Next.js and Netlify, alongside accounting and CRM systems. We assess other platforms on the same terms and say so when a specialist partner is better placed.
How do you handle access to our systems and data?
We start read-only and list the permission level needed on each platform before work begins. Write access is requested only for changes you have approved, and bulk changes start from a backup of the prior state.
Can you work alongside our developers or IT supplier?
Yes. We can write the specification and acceptance tests for your in-house team or existing supplier and review their work against them, or take on specific workstreams such as tracking, integrations or migration ourselves.
Where do you use AI, and where not?
We add AI where a defined task has the data to support it, for example an assistant that answers product and service questions from your own site content. Each feature is tested against real questions before release and its limits are written down for your team.
What happens after launch?
You receive the documentation, credentials and test suites. We can run scheduled checks that compare reported figures with recorded orders and flag drift, or hand the systems over fully to your team.
Related capabilities
Discuss this with us
A few details help us route your enquiry to the right partner. Fields marked optional can be left blank.