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# Components of a Good Test Plan, or Hypothesis Prioritization & Gantt Charting Does Not a Test Plan Make

**Publisher:** Organization Further  
**Author:** Catherine Crim  
**Published:** May 28, 2025

---

[Our Thinking](/our-thinking/blog) > [Blog](/our-thinking/blog) > Data | Solutions

# Components of a Good Test Plan, or Hypothesis Prioritization & Gantt Charting Does Not a Test Plan Make

**Catherine Crim**, Senior Optimization Manager  
**Aug 25, 2021**

*There are plenty of articles on prioritization, but few on what happens after a test has become “the chosen one.” This post focuses on the step after prioritization but before test development starts. By the end of this article you’ll understand the components of a good test plan and why it’s critical to building and scaling a test-and-learn culture across your organization.*

## Optimization test plans: Why you need them

When searching for “conversion rate optimization test plan templates,” the results aren’t surprising. You’ll find screenshots of prioritization framework spreadsheets and gantt charts.

While roadmap planning is understandably a big part of getting a test launched on your site, it’s far from the only part. Often, roadmap planning is straightforward and already has established processes for [getting work into the test queue](https://www.gofurther.com/resource/the-complete-guide-to-structured-ideation).

But time and time again, the challenges our clients face most after a hypothesis has been selected is the cross-functional, multi-stakeholder test planning—that is, our clients need help **planning the scope, design, measurement, development, and implementation of a test**.

Without a good test plan and a strategy to create proper documentation, not only is there lost time in “handoffs” between stakeholders, but processes also get dropped, and everyone has to scramble to pick up the work and move it forward. The purpose of a good test plan document is to create smooth transitions that save time and keep teams in their own lanes while working together to move tests full speed ahead!

## A note on test plan documentation

It’s critical! Without proper documentation of test design, rationale, and decision planning, even if you do increase conversion rate, you will not be fostering a test and learn culture within your organization.  

It’s this culture that turns the relatively small impact of a single test into a long-term organization benefit and digital transformation. How? As insights and recommendations derived from experimentation begin to impact the business, these are shared and scaled across the organization. These learnings can be applied across every customer touchpoint from the website to digital media to even traditional marketing or product development.

## Ten components of an optimal test plan

1.  **A hypothesis statement**
2.  **Logistical information**
3.  **Change log** (this may be able to be put at the end if approvals “stick“ within your organization)
4.  **Business case** detailing the problem and why this hypothesis was prioritized
5.  **Experimental design & integration specifications**
6.  **Visuals** of both the original version and the competitor variation(s)
7.  **A data dictionary** for all metrics and segments
8.  **Duration and statistical standards**
9.  **Decision matrix**
10. **Test setup & metrics tracking QA checklist**

### 1. Hypothesis
It’s a good idea to have this be the FIRST component within your plan. I have learned that intentionally putting this first, big and highlighted, anchors the reader to the objective—testing a new treatment on their visitors to see if their behavior changes in a way that we expect (and hypothesize it would).

### 2. Logistics
Logistical information should include key stakeholder contact info, must-go-live date, related documents, potential blockers or interferences, and expectations.

### 3. Change log
This section is beneficial for two reasons. First, by having a section dedicated to changes that have been made since approval of the original document, you make sure everyone is aware of the change. Think of it as supplemental to the version history of a document. Secondly, having and using the change log brings some finality to the original document. You shouldn’t be continuing to adjust components after approval because those components should be part of the approval process!

### 4. Business case
This explains *why* we’re running this experiment. Not only can it detail business context, like whether the hypothesis relates to a company goal, but it also denotes if there is any previous research or testing that has influenced the hypothesis.

### 5. Experimental design & integration specifications
This test plan section is for the four other W’s:
*   **Who** will see the experiment? Only Desktop? PPC traffic?
*   **What** type of test is this? A/B/n? MVT?
*   **Where** on the site (pages, site elements like header) will this experiment run?
*   **When** in the user journey? After a certain amount of time?

### 6. Visuals
Having screenshots, by device, side-by-side of the control experience and the variation experience makes post-hoc behavioral analysis easy. For extra credit: This section can also house dev. specs, making the handoff between design and development seamless.

### 7. Data dictionary
This details what is being tracked. Ideally, it contains screenshots for tracking that is supplemental to conventional funnel steps. The data dictionary also denotes WHERE KPIs will be tracked and whether this tracking exists today or needs a developer to write code before launch.

### 8. Duration estimate
In this section, you’ll estimate the cost of a test in terms of traffic and time, and you’ll weigh that cost against the potential value the change could yield. You will need:
*   Estimated amount of traffic qualifying for the test
*   Number of primary KPI conversions for those who qualify
*   A runtime calculator (see our [free calculators](https://www.searchdiscovery.com/engage/tools/))

### 9. Decision Matrix
This is where you plan for action, regardless of test result. It answers the question, “What happens if the challenger beats control?” But what happens if it doesn’t?

| | No change in rate of quote starts | Quote rate declines | Increase in rate of quote starts |
| :--- | :--- | :--- | :--- |
| **What it means** | Changes to pre-quote form have not been found to impact performance | Changes to pre-quote form may increase quote starts but discourages higher qualified traffic | Changes to pre-quote form encourage more people to start quoting |
| **What will we do** | Look for other ways to improve pre-quote form | Test reverting to old pre-quote form on homepage and elsewhere to increase quote rate | Rollout new pre-quote form as widely as possible on site & determine next step for iteration |

### 10. QA Checklist
This is where you write out how to qualify for the experiment, what the experiment should do, and what data should be sent to the testing tool and/or the analytics platform.

---

### Common concerns about test plan documentation

**"Do I really need ALL this just to test one hypothesis?"**  
Yes, you really do. The time you spend increasing transparency and gaining alignment on the test plan will save you time and reduce the risk of issues that arise when data is cherry-picked to support a desired outcome. Documentation limits the back-and-forth between departments and ensures that as people flow in and out of the organization, they can get up to speed quickly.

**"This is going to take too much time!"**  
Creating a test plan is a lot less effort than you might imagine, especially when you use a template. Once you’ve got a template, many of these sections are ten-second copy and paste activities from previous experiments. The time saved on the backend more than makes up for the initial effort.

### Coming up next
In our next post, we’ll be covering in-depth the most strategic component of a test plan—the data dictionary. We’ll discuss the different types of metrics, how to leverage them to craft rich data stories, and how those stories can truly ignite a test & learn culture within your organization.

### [*Reach out today to foster your test and learn culture!*](https://www.gofurther.com/contact)  
*We can help you craft a test plan template perfect for your organization.*

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**Catherine Crim**  
Senior Optimization Manager

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