Articles tagged: Omnichannel

When brands cut prospecting to chase ROAS, they stop replenishing future demand – and history illustrates what happens next.

The Haus playbook for measuring tentpole brand campaigns

We analyzed over a hundred incrementality tests before, during, and after BFCM 2025 and uncovered dramatic delayed conversion effects.

Can TikTok scale? How much omnichannel impact does TikTok have? Haus’ analyses of hundreds of TikTok incrementality tests answers these questions and more.

Use A/B testing to optimize and incrementality testing to prove impact. Dive into differences, use cases, and how to pick the right test.

Learn the fundamentals of marketing measurement — from ROAS and MMM to incrementality testing — and discover how to measure true campaign impact.

Our large-scale analysis of real-world, branded search incrementality experiments unpacks when branded search is most effective and how best to leverage it.

Experiments reveal causality and establish the ground truth for cross-channel decision-making — even when it comes to OOH campaigns.

From balancing the funnel to optimizing creative, our new guide has data-backed tips for improving performance on Meta.

We analyzed 640 Meta experiments on the Haus platform, revealing key insights into Meta's incrementality.

Explore geo experiments from all angles — what they are, why they matter, and how you can use them to measure incremental impact.

GeoFences enable you to exclude markets from your test that aren’t relevant to your business — helping you focus more deeply on the ones that are.

An exclusive Haus analysis show Meta is incremental in most cases — but is the platform's move toward automation improving incremental efficiency?

At our Open Haus AMA, a customer asked us: “How do you know when a brand is at the scale where investing in an incrementality tool makes sense?”

In our recent Open Haus AMA, we were asked why incrementality has become such a buzzword in marketing. Let's dive in.

Based on open source mobility data collected from mobile phone GPS data, Haus Commuting Zones minimize spillover and improve test accuracy.

Sometimes used interchangeably, it’s worth clearly distinguishing between these two approaches and what they accomplish.

Dive into the key differences between attribution and incrementality — how each approach works, when they're useful, and key pros and cons.

Building an incrementality practice is vital for any brand that's trying to improve decision making. Let's explore how to get started.

Let’s walk through how to build a marketing measurement plan that puts experimental data at the center.

Our Measurement Strategists explain which tests can make a difference as you prep for Prime Day 2025.

When macroeconomic conditions shift, marketers should proactively partner with finance, understand how budgets may change, and test for efficiency.

Incrementality testing isolates true campaign impact — giving you clarity, confidence, and a case your CFO will love.

Platform creative tests may not meet the definition of a causal experiment, but they can be performance optimization tool within the bounds of the algorithm.

Fuzzy on some of the nuances around incrementality testing? This guide goes deep, unpacking detailed examples and step-by-step processes.

When real-time retail data meets incrementality testing, CPG brands can finally measure what’s working and optimize ad spend with confidence.

5 common signs that indicate it is definitely time to start investing in incrementality.

While incrementality is better than relying on attribution alone, comparing them as-is is challenging. Thankfully, there’s a better way to get an unbiased data point regardless of the channel.

Haus transforms the way businesses make decisions.