5 Marketing Experiments We Tried: The Winners, The Losers, and The Useless

One big thing startups do differently from big companies is experimentation. Startups are less like finely tuned money machines and more like laboratories. They have less to lose from a wrong test and everything to gain from one that works.

At Process Street, we have had our share of surprisingly strong marketing experiments, plus a few that went nowhere. The useful part is not copying the exact winner. It is seeing how the test was framed, what changed, and how the result was tracked.

Below are concrete marketing experiment examples we tried across homepage headlines, email subject lines, exit popups, SEO metadata, and experiment tracking. Some were winners, some were losers, and some were useless beyond the lesson they left behind.

Home page headline: +5% conversion rate

A general rule we have at Process Street is that the most time and energy should be put into optimizing material that the most people see. This doesn’t stop us running experiments on everything from subject lines to content upgrade pop-ups, but it does mean we focus most of our time on our main landing page. Out of all your site’s elements, the headline on the landing page is probably the most high-impact test you could run. We’re still testing ours — we’re running an experiment and waiting for the statistical significance to peak — but here’s a test from the past that improved engagement and signups.

The control

This headline had been our main one since the beginning of time.

Variant #1: -9% conversion rate

We found that a lot of our users switched over from Excel, and that they were frustrated with the limitations of spreadsheets.

Variant #2: +5% conversion rate

As it turns out, the focus on automation was the right choice. Since then, we’ve directed a lot of our marketing material to sell the benefits of automation, and even written a free ebook about it.

Email marketing subject line: +30% open rate, +33% click rate

When we first started optimizing our marketing emails, we got amazing results. This isn’t really because of any complex trickery or breakthroughs. It’s mostly because the email marketing we were doing pre-test was terrible. I rip it apart in this post. Here’s an extract: Since then, we’ve started running tests in Intercom instead because it’s linked to everything — our SaaS metrics, our users, and our support conversations. Below are the results of one of the tests since:

The control

It’s straight to the point, but is it too boring?

Variant #1: +30% open rate, +33% clicks

Yes, the control was too boring. The promise of avoiding nuclear war upped the open and click rates by almost a third! Including Ben Mulholland’s trademark playfulness in the subject line paid off.

Exit pop-up for Google-related posts: +196% conversion rate

A big chunk of our ranked posts are for Google-related keywords. We’ve got Gmail tips, Google Drive tips, Gmail vs. Inbox, Gmail extensions — you name it. To make better use of that traffic, we decided to add an exit pop-up. We tested the color, which gave the test an early lift, but the bigger change was the offer itself.

The control

Originally, we wanted to sell the reader on a content upgrade: a list of Google Drive tips. We displayed this on any Google-related post, by setting the show rules as paths that contain google.

Variant #1: +65% conversion rate

All we did here was change the color. As silly as it can seem at first, color has featured in a particularly famous A/B test in the past and makes a proven difference in conversions.

Variant #2: +178% conversion rate

We decided to up the ante and offer a free two year subscription to premium Google Drive. As you might imagine, it sent the FREE STUFF sensors off the charts.

Variant #3: +196% conversion rate

…But a terabyte of data is much more attractive than a two year subscription. This pop-up was the clear winner.

SEO title and description: +212% organic traffic

SEO experiments are useful when the page is already earning impressions but the search result is not doing enough work. The test surface is narrow: the title, the description, and the promise those two lines make before a reader clicks.

For older posts sitting around the middle of page one, we test title and description variants with the same discipline we use for landing pages: one clear hypothesis, a defined comparison window, and traffic checked in Google Search Console before any winner is called.

The control

SEO title: Every Todo List Template You’ll Ever Need

SEO description: Need a to do list template? Check this huge list for Excel to-do list templates and Word documents, too!

Variant #1: +212% organic traffic

SEO title: Every To Do List Template You Need (The 21 Best Templates)

SEO description: Need an awesome to do list template? Check this huge list for 21 Excel to-do list templates and Word documents, too!

The main change was adding the number of templates directly into the title and description. Numbers set expectations before the click, and when the result promises a concrete list, it gives the searcher a stronger reason to choose it over a vague alternative.

How to run your own marketing experiments

A marketing experiment is only useful if it is specific enough to run and structured enough to learn from. The simplest way to keep that discipline is to capture the same information every time, then move the test through a consistent review process.

Start with the question the experiment needs to answer, not the tactic. A homepage headline test, a popup offer test, and an email subject line test can all use the same basic workflow if the hypothesis, owner, metric, and decision rule are clear.

For us, the pattern is simple: define the test, prioritize it, run it, check the data, document the result, and decide what changes in production. That turns experimentation from a collection of isolated ideas into a repeatable operating rhythm.

Use this quick structure to easily record your experiments

One helpful structure is PILLARS: priority, idea, labor, location, audience, results, and status. It is light enough for a quick backlog, but detailed enough to stop half-formed experiments from becoming ambiguous work.

• Priority: how important the test is compared with other opportunities.
• Idea: the exact change being tested.
• Labor: the effort required from marketing, design, engineering, or operations.
• Location: the page, email, popup, workflow, or channel where the test runs.
• Audience: who will see the test and whether the sample is meaningful.
• Results: the metric, lift, loss, or inconclusive outcome.
• Status: where the experiment sits in the workflow.

Fill in every detail of the highest priority test

The highest-priority tests deserve more detail before anyone starts changing copy, design, or automation. Record the hypothesis, the control, the variant, the primary metric, the expected run window, and the person responsible for calling the result.

This is the point where a lightweight idea becomes accountable work. If the test needs design support, engineering time, or legal review, those dependencies should be visible before the experiment starts. If the metric is unclear, fix that first.

Get the test underway to start boosting conversion rate

Once the test is live, avoid changing the goalposts. The owner should check that the control and variant are running as intended, confirm the sample is building, and watch for obvious implementation problems before treating the data as useful.

The best experiments are boring in the middle. They run long enough to collect a meaningful signal, then the team reviews the result against the original hypothesis instead of chasing every early fluctuation in the data.

Here’s how you properly track the success of your marketing experiments

Good tracking separates the result from the story you want the result to tell. Before launch, define the primary metric, the comparison period, the minimum sample size or run window, and what counts as a win, loss, or inconclusive test.

After the test, record the decision as clearly as the number. Ship the variant, keep the control, run another test, or archive the idea. The decision is what turns experiment data into operational knowledge.

How you can track your own marketing experiments

You can track marketing experiments in several tools, and the right choice depends on how much governance you need. A simple backlog is enough for a small team, while regulated or cross-functional work needs ownership, approvals, evidence, and audit history.

For a broader comparison of operational marketing systems, see our guide to marketing project management tools. For experiment tracking specifically, the three practical options are Trello, Process Street, and Google Sheets.

Tracking marketing experiments with Trello

Trello was made to handle different tasks being pushed through the funnel as part of a larger project, which means it lends itself to tracking tests: As you can see, each test is its own card. As they move through the funnel, more details are filled out. I’ll explain the list names:

• Brainstorm: for pasting in links for experiments you feel could be useful for the future. Anything goes.
• Backlog: once you decide to move forward with a test, you prioritize it (screenshot below)
• Designing: getting the material ready to launch
• Running: the test is in progress! It needs checking, and you need to be recording the data of experiments in this list
• Analyzed: after the run period is up, move the card here and analyze the results. What’s the outcome? Which variable won?

Prioritization and analysis looks like this inside the card: Trello is an easy way to track experiments as they happen, and you also end up with a list of completed tests that you can write up longer analyses on if you need.

Tracking marketing experiments with Process Street

Process Street is a Compliance Operations Platform for turning recurring work into governed, auditable workflows. For marketing experiments, that means every test can start from the same process: capture the hypothesis, assign the owner, define the metric, set the run window, require a spot check, and record the final decision.

The Docs capability area gives teams a controlled home for the experiment procedure and supporting context. The Ops capability area turns that procedure into repeatable workflow runs with assignments, approvals, conditional logic, form fields, and activity history. Built-in AI helps teams draft, standardize, and improve recurring workflows without turning the process into a separate side project.

That structure is useful when the experiment touches multiple people or needs a reliable record. Instead of a loose note that says a test happened, the team gets a completed workflow showing what was tested, who approved it, what changed, and what decision followed.

Tracking marketing experiments with Google Sheets

Google Sheets is still useful for a simple experiment backlog. You can sort by priority, filter by audience, track ownership, and keep result notes in a shared place without introducing a new system.

The tradeoff is execution. A spreadsheet can describe the process, but it does not naturally enforce it. Owners still need to remember when to check the test, where to attach evidence, who signs off, and when the result becomes a production change.

If the team only needs visibility, a spreadsheet can work. If experiments need assignments, approvals, evidence, and an audit trail, move the tracking into a workflow system.

What are your top A/B testing tips? How do you track your experiments? Let me know in the comments.