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Do you know where your leads, sales & phone calls come from? Try Ruler Analytics for free to discover this and more. www.ruleranalytics.com

28/10/2026

Is Google Analytics adequate for attribution?

GA4 does a great job of measuring what happens on your website. Where it struggles is treating every conversion equally and giving upper-funnel channels the value they deserve. On its own, it rarely provides the complete picture needed to make confident budget decisions.

22/10/2026

CUSTOMER SUCCESS STORY 📈

A fast-growing consumer health brand was running paid media across Google, Meta, connected TV, Amazon, Walmart and QVC at once, and the picture of what was working was getting harder to measure.

Every platform reported its own version of the truth, and Google claimed a huge share of conversions through last-click attribution, including sales that had been influenced weeks earlier by a TV ad.

Upper-funnel activity was effectively invisible, and a large part of their sales through Amazon, Walmart, Costco and QVC sat in a separate data silo from anything digital.

We helped them bring two years of spend and revenue data together in a marketing mix model, combining online and offline performance with multi-touch attribution across digital channels.

Here’s what happened…

📊 $103M+ in revenue modelled, with paid media accounting for 53%.

🔎 Non-brand paid search came out on top for both reported and marginal ROAS, revealing clear headroom to invest further.

🛒 Amazon accounted for 11% of total revenue, giving the team a clearer view of how brand and performance activity translated into retail sales.

📺 85% of DRTV impact carried beyond the week the ad aired, while TV overall accounted for 8% of modelled revenue.

When online, offline and retail performance sit in the same view, teams can see what’s driving growth, where there’s room to invest and how channels work together over time.

Link in the bio on how to build your own unified measurement framework 📌

07/10/2026

Unified marketing measurement brings your marketing activity and outcomes into one view, so you can see what’s working, what isn’t and where to improve next 📈

04/10/2026

Building the best solution 🧱 by 🧱

12/09/2026

Your GA4 Direct traffic may be hiding the impact of other channels, with as much as 20% potentially misattributed.

Someone sees a TV ad or scrolls past a social post with no link, and later types the brand straight into the address bar. There’s nothing for GA4 to connect that back to, so by default, it lands in the Direct bucket.

Based on what we’ve seen across client data, this can make brand and awareness spend look like it’s doing far less than it actually is, because none of that influence gets acknowledged anywhere in the reporting.

It’s not that Direct traffic is a bad sign. Usually the opposite, people know the brand and are coming back intentionally. It’s more about understanding how much of it was earned through awareness work that never got the chance to show up.

A few things worth a look:

→ Does Direct traffic spike near brand or awareness activity, a new campaign, an OOH push, a TV spot?
→ How does branded search volume move alongside it?
→ What do new customers say when you simply ask how they first heard of you?

The goal should be to understand what’s actually creating direct traffic, because that’s where the real value of your marketing activity often sits.

Have you found a reliable way to understand what’s really sitting behind Direct traffic?

04/09/2026

AI agents are everywhere right now, but we built ours with a clear purpose 👇

Our Analyst Agent and Media Planner Agent exist to answer two simple questions:

- what’s working?
- what should we do next to improve?

They bring together your marketing data to surface useful insights, highlight opportunities, and help guide your next move.

The goal is to give customers ongoing, consultant-level insight and practical recommendations, without the extra workload, complexity, or cost of relying on additional support.

01/09/2026

Last click isn’t broken, it’s just being asked a question it was never built to answer.

It tells you through which channel someone found you when they were already ready to buy. What it doesn’t tell you is what made them ready to buy in the first place, and mixing those two things up is usually where the trouble starts.

Most CRMs, revenue systems and ad platforms default to last click because it’s simple to implement and easy to explain. So marketers end up making budget decisions based on a model that is, by design, blind to everything that happened before that final touchpoint.

Brand awareness, upper funnel activity, the channels that built intent over weeks or months, none of it gets credit. What gets credit is the branded search someone did once they were already convinced.

So teams cut awareness spend, double down on bottom of funnel, and then wonder why new demand dries up. Every planning cycle ends up reinforcing the same conclusion, bottom of funnel gets more, top of funnel gets less, and revenue growth slows.

The plateau is fairly recognisable once you know what to look for. Everything looks fine at a channel level, but total revenue flatlines. Acquisition costs creep up because you’re fighting over a shrinking pool of in market buyers. ROAS looks stable but volume is quietly shrinking, because you’re harvesting demand rather than creating it.

What actually helps is a unified view of the full funnel, one that maps everything back to real revenue outcomes. Not because any single model is perfect, but because that fuller picture asks a much better question than who got the last click.

How do you make the case for upper-funnel investment when the last click gets the credit?

26/08/2026

A lot of budget planning still runs mostly on last year’s numbers, gut feel, and platform data that never ‘quite’ lines up.

Our Budget Scenario Planner works from something more accurate, performance and revenue data pulled into one view. From there, you can build a few models side by side, current, growth, efficiency, each showing the projected revenue impact based on what’s actually happened in the business.

→ Need to cut 10%? See where it costs the least.
→ Board wants 30% growth next quarter? See what that actually takes at current efficiency, before anyone commits to a number.

Compare scenarios in real time, then export something that’s ready for the room.

Built on verified, revenue-linked data, not the platform-reported numbers that tend to run a bit optimistic.

21/08/2026

Queries that used to go straight into Google are increasingly going into LLMs like Claude, and the people doing that are often your highest intent prospects.

Google’s answered with AI Overviews, which have pushed organic results further down the page. The search results page marketing teams have spent years optimising for looks fundamentally different now.

For a while, this demand existed somewhere paid ads simply couldn’t reach. That’s already starting to shift, OpenAI’s introduced ads inside ChatGPT, though it’s still early days, and brand authority is still what carries the most weight there.

You earn that authority through visibility, being mentioned, cited and discussed in the right places, press, directories, industry publications, so you’re more likely to surface in AI generated answers.

The good news is this is more measurable than most people assume. When someone clicks through from an LLM, that referral source can be captured in your first party data. And because first party tracking follows the user across their whole journey, you’re not just seeing that AI search sent a visit, you’re seeing how it fits alongside every other channel that contributed to the conversion.

Layer self reported attribution from lead forms on top of that and the picture gets even clearer. Last year, we found 35% of leads were attributing themselves directly to AI tools.

The traffic is there and the signals exist, you just have to know where to look.

Are you currently tracking any traffic coming through from AI tools, or is it still a blind spot?

17/08/2026

One thing keeps coming up when we talk to marketers about measurement → a lot of the week is spent pulling data together.

Checking dashboards, cross-referencing channels, and trying to figure out what’s actually changed and why. Not because anyone’s doing anything wrong, but because that’s simply how the workflow has evolved for most teams.

That gap, between collecting data and actually acting on it, is what led us to build our AI Analyst and AI Media Planner.

AI Analyst → monitors your full marketing mix, surfaces what’s shifted, and explains why, connecting the channels that normally live in separate dashboards.

AI Media Planner → turns those insights into budget decisions and helps see the likely impact on pipeline and revenue before making a move, with the reasoning to back it up in the next budget meeting.

Together, they provide ongoing monitoring, modelled ROAS and marginal ROAS at channel and campaign level, budget scenarios you can stress-test, and a model that keeps refreshing as your marketing mix changes.

That’s less time collecting data and more time planning what to do with it.

👉 How much of your week goes to analysing data vs. acting on it?

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Liverpool
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Opening Hours

Monday	9am - 5pm
Tuesday	9am - 5pm
Wednesday	9am - 5pm
Thursday	9am - 5pm
Friday	9am - 5pm

Website

http://www.ruleranalytics.com/

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