Publishing a page does not place it instantly at the top of a search result. Google needs to discover and crawl it, decide what it is about and then compare it with other possible results for a particular search, location and user context.

We can make the foundations sound — crawlability, sitemaps, Search Console, page structure, metadata, useful content, redirects and local signals where relevant — but no credible developer can guarantee an instant organic ranking.

More importantly, we ask whether Google organic results are even the first channel the business should invest in. Being discoverable by the right people matters more than chasing a vanity ranking.

Yes. Large migrations are data projects as much as design projects. Before moving anything, we inspect the shape and quality of the source data and map products, variants, categories or collections, images, attributes, metafields, URLs and integrations into the destination.

We also plan for what sits around the catalogue: redirects, search visibility, customer/account implications, analytics, feeds, shipping and any downstream systems that depend on product identifiers.

The goal is not merely to get thousands of rows imported. It is to arrive with a catalogue that is usable, findable and maintainable after the migration.

Yes. An existing LMS may contain years of courses, learners, reporting rules and integrations. Replacing it because one part is frustrating can create a much larger problem than the one we started with.

We separate the layers: LMS platform, WordPress or surrounding website, LearnDash configuration, SCORM packages, enrolment/access, navigation, reporting and external integrations. Once we know where the friction actually lives, we can decide whether to configure, customise, integrate or replace.

The least disruptive solution that achieves the learning outcome is usually the place to start.

Yes. SCORM is only one ingredient in the learning experience. A valid package can still sit inside a confusing course journey, poor navigation, awkward access flow or LMS template that makes good content feel difficult to use.

We test the package separately from the surrounding platform so we do not blame the wrong layer. Then we can look at launch behaviour, completion, navigation, responsive presentation, course structure and how the learner gets into and out of the content.

That distinction matters because rebuilding the SCORM package will not fix a problem caused by the LMS — and replacing the LMS will not fix a broken package.

Yes. You do not need to arrive knowing what an LMS architecture should look like. Start with who is learning, what they need to complete, how access should work, what the organisation needs to track and what content already exists.

From there we can work through platform choice, course/resource structure, LearnDash or other LMS functionality, SCORM, user roles, reporting, integrations and the surrounding website or portal experience.

The subject-matter expertise belongs with you. Our job is to turn it into a digital learning experience people can actually access, understand and manage.

Because generating code and taking responsibility for a working system are different things. AI can be excellent at explaining concepts, drafting code, finding patterns and accelerating debugging. We use it for exactly those reasons.

Experience provides the context AI does not automatically have: how this particular site is built, what else depends on the change, whether the suggested library is appropriate, what security or data implications exist, how the browser behaves and what needs testing afterwards.

It is a bit like using AI to guide you through servicing a car. The instructions can be useful, but if you misidentify the part or do not recognise a warning sign, the cheap DIY fix can become expensive quickly. AI gives us better tools; years of experience still shape the decisions.

Yes, when it is used where it creates leverage. It can accelerate research, content exploration, prototyping, repetitive coding, debugging and analysis. That can let more of the budget go toward the parts that actually need human judgement.

We do not price a project around pretending every AI-generated output took hours by hand, and we do not ship generated work simply because it appeared quickly. Efficiency is useful only if the result remains accurate, maintainable and fit for purpose.

AI assisted. Experience led. The technology changes quickly; responsibility for the outcome does not.

Yes, where it helps — especially when a client has strong business knowledge but very little written material. AI can help organise interviews and notes, explore structures, identify gaps and produce useful starting points much faster than staring at a blank page.

But generic generated copy is easy to spot and easy to forget. We bring the content back to the client’s real customers, terminology, proof, objections, experience and point of view. The useful material usually comes from what the business actually knows that competitors cannot simply generate.

The aim is not ‘AI content’. It is better content produced efficiently and then reviewed by people who understand what it needs to achieve.