Marketing Solutions

Buy, in the large majority of cases. Braze, Klaviyo, Customer.io and their competitors solve the general problem well and carry deliverability infrastructure you genuinely do not want to own. Building is justified when your eligibility or decisioning logic is specific to your business in a way no platform expresses — insurance renewals, lending offers, regulated communications — or when volume makes per-message pricing genuinely painful. Most teams asking for custom automation actually need better data underneath the platform they already have.

No, and anyone quoting you a fixed inbox-placement number is describing something they cannot control. Placement depends primarily on your own sending behaviour — list quality, engagement rates, complaint volume and consistency — rather than on the software. What we can do is build the technical foundations correctly: SPF, DKIM and DMARC configured properly, dedicated IP warming where volume justifies it, automatic bounce and complaint handling, engagement-based list hygiene, and monitoring so a reputation problem is visible before it becomes a crisis.

Mostly data modelling rather than charting. Consolidating events from web, app, email, advertising and CRM into a warehouse, resolving identity so one person is not four rows, defining metrics once so "active customer" means the same thing in every report, and then building the views on top. The visualisation layer is the last and easiest part. Teams who start with the dashboard and work backwards usually rebuild it within a year.

Yes, through the WhatsApp Business Platform and equivalent channels. The practical constraints are worth knowing before planning: message templates require approval ahead of use, there are defined windows during which you may message a user after their last interaction, and pricing varies by conversation category and country. These rules shape what campaigns are possible, so we establish them during design rather than after a journey has been built around an assumption.

Consent lives with the customer record and is checked at send time by the decision layer, so it cannot be bypassed by a segment definition or a new journey. Preferences are granular — channel and topic, not one global switch — because a single unsubscribe for everything drives people to opt out entirely rather than reduce. Deletion and export requests propagate to every connected system, which is the part most stacks quietly fail.

Yes, by limiting variation to dimensions that demonstrably change behaviour rather than every attribute you happen to hold. Personalisation multiplies content production and QA effort, so three meaningful variants that get properly reviewed beat forty combinations nobody has actually looked at. We also build fallbacks for missing data, because the classic failure — "Hi {first_name}" reaching thousands of people — is a content-modelling failure, not a bug.

A focused capability on top of existing tools typically reaches usable in three to four months. A full customer data and decisioning layer replacing several systems is realistically eight to fourteen months, and the constraint is usually agreeing the data model across teams rather than engineering throughput. We sequence so something useful ships early rather than everything arriving at the end.

You own the code and the data, and both should be exportable in a standard format without our involvement. Warehouse, repositories and platform accounts belong in your organisation's name from the start. This matters more in marketing than most areas, because several popular platforms make leaving deliberately awkward — we would rather that constraint be a decision you made knowingly than one you discover later.