Digital Marketing Services: Analytics, Funnels and Experiments

You want growth you can explain: where customers come from, what each one costs and what makes them stay. Our digital marketing services approach that the way engineers approach any system. We make measurement trustworthy first, then find the constraints in your funnel, then spend and iterate where the evidence points.

We help companies of every size move from offline to online, from desktop-only to mobile, and from a single channel to several that work together. Done well, digital marketing looks less like a string of campaigns and more like a well-instrumented product: every change starts with a hypothesis, every result is measured and what works gets scaled.

Analytics first: a tracking plan you can trust

Many marketing problems are measurement problems in disguise. Numbers disagree between tools, conversions are counted twice, and nobody is sure which campaign drove last month’s sales. Before spending more, we fix that.

We write a tracking plan: a short list of the events that matter, such as sign-up, activation, purchase and renewal, each with a clear name, defined properties and an owner. Then we implement it properly:

• Key conversions are sent from your server as well as the browser, so ad blockers and privacy features do not erase them, and the two sources are deduplicated.
• Consent is enforced in code. Tags fire only when the user has agreed, under the privacy rules that apply to you, such as the GDPR in Europe or KVKK in Turkey. Your legal team sets the policy; we implement it faithfully.
• Tracking is tested in staging like any other feature, and broken events raise alerts instead of disappearing silently.
• Marketing analytics, such as Google Analytics, and product analytics, which follows behavior inside your app, share the same user and event definitions. At larger volumes, raw events flow into a data warehouse where they can be joined with revenue.

Attribution comes next, with some humility. Each ad platform tends to credit itself, so their reported conversions often add up to more than you actually sold, while last-click models undervalue the channels that create awareness. We triangulate: platform data, your own analytics, self-reported attribution at sign-up and, where budgets allow, holdout tests that show what would have happened without the spend.

Funnels and conversion rate optimization

Bringing prospects in is the easy part; converting them is harder. We map your funnel stage by stage, from landing to sign-up, activation, first purchase and repeat purchase, and look for the steps where the most people leave.

The fixes are often unglamorous. Before testing button colors, we look for form validation that rejects valid input, slow pages on mobile networks, payment errors, confusing pricing and landing pages that do not deliver what the ad promised. Session recordings with sensitive fields masked, together with short usability tests, show why people leave, which analytics alone cannot.

Because we are also a product team, these fixes do not wait in another company’s queue. Our designers and engineers change the landing page, checkout or onboarding flow directly, with the same UI/UX design discipline we bring to products. Every improvement lowers your cost per acquisition across all channels at once.

Paid acquisition without the waste

Different channels do different jobs. Search captures demand that already exists. Social and video create demand. Shopping campaigns depend on the quality of your product feed, and app campaigns need a store listing and onboarding that convert. Depending on your audience, the mix can include Google Ads, Meta, Microsoft Advertising, LinkedIn and TikTok, retargeting networks such as Criteo, and regional platforms such as Seznam where your market calls for them.

We often start narrower than you might expect, so each channel gets enough budget to produce a clear signal. A few principles guide the work:

• Feed the algorithms good data. Automated bidding optimizes toward whatever conversions you send it. For lead generation, we send qualified leads and closed deals back to the ad platforms, so they optimize for revenue rather than form fills.
• Separate brand from non-brand. Brand searches convert well and cheaply; mixing them into other campaigns makes weak campaigns look strong.
• Treat creative as the main lever on social platforms, and test it systematically.
• Judge channels on unit economics: cost per acquisition and payback against customer lifetime value, not clicks or impressions.

Once something works, we scale it step by step and watch whether efficiency holds as spend grows.

Lifecycle email and push

Acquiring customers is expensive; keeping them is where growth compounds. Lifecycle messages, meaning email, push notifications and in-app messages, turn product events into timely, useful communication: a welcome sequence, a nudge when someone stalls in onboarding, an abandoned cart reminder, a win-back message for customers who have gone quiet.

The engineering details decide whether these messages arrive and help:

• Email is authenticated with SPF, DKIM and DMARC, marketing mail goes out from its own subdomain, lists are kept clean and unsubscribing takes one click. Major mailbox providers now require authentication and easy unsubscribing from bulk senders.
• Transactional messages, such as receipts and password resets, stay separate from marketing in both infrastructure and consent.
• Both iOS and current Android versions put push notifications behind a permission prompt. We ask when the value is obvious, often after a short screen explaining what users will get, rather than at first launch.
• Every notification deep-links to the right screen, respects frequency limits and is triggered by real behavior rather than a fixed schedule.

Every message spends attention, so we count unsubscribes and push opt-outs as costs and use holdout groups to check that a campaign actually changes behavior. Push and in-app messaging are built together with our mobile app development team.

Experiments that produce answers

An experiment is only useful if it can change a decision. We write each test down before it starts: the hypothesis, the primary metric, guardrail metrics that must not get worse and the sample size needed to detect the smallest effect worth acting on. Then we run it with discipline:

• Tests run for full weekly cycles, so weekday and weekend behavior are both represented.
• We do not stop a test the moment it looks like a winner. Checking repeatedly and stopping early is a classic way to find an effect that is not really there.
• We confirm that traffic was actually split as planned before trusting any result.
• Product experiments run behind feature flags, so a losing variant can be switched off without a release.

Low traffic changes the approach. If you do not have the volume to test a small tweak meaningfully, running the test anyway is theater. We make bolder changes, compare before and after with care and lean on qualitative research. Every experiment, winning or losing, goes into a shared log so the organization learns instead of repeating old tests.

How our digital marketing services work

We start by getting to know your business: margins, sales cycle, customers and what has been tried before. Then we audit your analytics, fix what needs fixing and agree on the few numbers that define success. Only then do we plan, execute and iterate, and when we find the channels and messages that work, we scale them. We can start from zero or take over campaigns that are already running.

The team is shaped around the work: analysts for measurement and reporting, engineers for tracking, integrations and landing pages, and designers for creatives and conversion work. Search and social plug into the same plan and reporting; our SEO services and social media optimization articles cover them in depth. You get regular check-ins and a monthly report that connects spend to outcomes and lists what we learned and what we will test next.

Your ad accounts, analytics properties and customer lists should belong to your company, with us added as users. That keeps you in control and keeps the relationship transparent.

Paid growth is not always the answer. If people who try your product do not stay, more acquisition just fills a leaky bucket, and activation and retention come first. With a small budget, one channel done well beats several done thinly.

Frequently asked questions

How much should we spend on advertising?

Enough to get a clear signal from one channel before adding the next. The right level depends on your margins and how quickly a customer pays back their acquisition cost, which is why we work out your unit economics before recommending a budget.

Can you work alongside our in-house marketing team?

Yes. Some teams need us for the technical layer, such as tracking, integrations and landing pages; others want us to run specific channels. We agree on who owns what at the start and report in one shared format.

Which analytics tools should we use?

It depends on your product and data volume. Many companies end up with a marketing analytics tool, a product analytics tool and, eventually, a data warehouse. The tools matter less than a clear tracking plan that all of them follow.

Can you fix our existing tracking without starting over?

Usually, yes. We audit what is there, keep what is reliable, repair or remove what is broken and document the result, so your historical data stays usable wherever possible.

How quickly will we see results?

Measurement fixes and obvious funnel repairs pay off quickly. Paid campaigns need a learning period before they settle, while SEO and lifecycle programs compound over months. Each monthly report shows where things stand.

If you want marketing you can measure and explain, we would like to hear what you are working with. Tell us about your product, your channels and your goals, and we will suggest where to start.