8 ways to get marketing and product teams experimenting together

There are many good reasons why marketing and product departments should work together on A/B testing, from driving efficiencies to creating better experiences. However, achieving harmonious cross-team collaboration is difficult, and most businesses want more than “good reasons.”

So here’s the TLDR: A study by Kameleoon found that companies are 81% more likely to grow when product and marketing strategies are aligned. The same study showed that less than 50% of managers felt confident their product and marketing-led growth programs were aligned.

The picture is clear: collaborative testing efforts make good business sense, but companies struggle to make it happen. It doesn’t help that terms like collaboration, culture, and alignment are difficult to action. So, in this article, I share practical ways to get your product and marketing teams working on experimentation together.

No matter how far into your journey of working with colleagues from other departments, it’s good to take a step back and ensure you have all the groundwork in place. You’ll need strong foundations to build on. Here’s what you need to do first.

1. Define roles and responsibilities

There are many moving parts and different tasks involved in good experimentation. To avoid finger-pointing, identify who is responsible for specific tasks, who makes decisions, and who needs to be kept in the loop. The bigger the business, the more complex this becomes, but it should still be agreed upon with representatives from all teams present.

Make it formal and add structure with a RACI chart. The completed RACI chart will look different for every business depending on the structure of your testing team (centralized, COE, or decentralized), maturity, resources, and department complexity.

Doing the RACI exercise will help managers ensure they have enough resources to support experimentation as things ramp up.

2. Choose a unifying testing tool

It’s hard to work together if you’re using separate testing tools and statistical engines. Teams stay in their silos, finger point, and fail to see how their experimentation work is affecting others.

Different teams have different needs. Marketing teams tend to build more frontend tests using WYSIWYG editors, whereas product teams typically run server-side tests that need a developer. Everyone wants AI.

If your experimentation tool only supports one way of building tests, it will cause unnecessary bottlenecks for developer resources or restrict teams in where and how they test. Neither are good outcomes.

The best way to encourage collaboration is to choose a tool that supports both testing approaches, offers AI features, and provides dashboards that show how each test affects the other team’s metrics. Kameleoon’s research found that organizations that used a single platform for experimentation were 70% more likely to grow significantly than those that didn’t.

“An enterprise experimentation platform that combines strong web and feature experimentation capabilities is critical for bringing all teams together around a unified experimentation approach.”

Peter Ernst, Director of Digital Experiments, Providence Health & Services

3. Standardize with templates and processes

This feels like an easy one to skip over. However, consistent documents and templates mean people from different teams can pick up and understand any test document immediately. This consistency allows you to store all your data in a test repository, and teams can easily view previous experiments. Not only this, but consistent reporting means meta-analysis is possible, leading to great insights into your program.

This consistency is even more important when it comes to prioritization. All teams must use the same method to judge test ideas. Without this, testing becomes a battleground, and tests will be prioritized not in the business’s interest but in the individual’s.

4. Work with the same data and KPIs

It’s rare to find teams using the same tech stack even when doing the same thing. This causes the dreaded data silo where each department holds its own stash of user data and separate KPIs. This leads to situations, for example, where marketers focused on acquisition drive more leads, but those leads may turn out to churn or provide low value. Great companies insist their teams understand how acquisition affects adoption and vice versa.

Collaborating teams need access to reliable data across the user journey that is consistently calculated with visibility of each other’s metrics. Sharing segments, audiences, and KPIs is easy when all teams use the same unified A/B testing platform. And when things are easy, teams do it more often. So make sure your testing tool has these features natively available. In the Kameleoon research, we saw that teams who share data, KPIs, and segments increase test velocity by 3-4x.

Good companies test. Great companies work together to test flywheels

Given that companies have overall goals, you’d expect everyone to pull in the same direction. However, approaches to reaching those goals vary by team. Not to mention, department-specific goals and priorities creep in. This leads to teams fighting over resources to get their work done. No one wins, including the business, in these situations.

That’s why showing teams how experimentation outcomes impact other team goals is imperative. For the greatest business success, teams must work together to test their flywheel. Answering questions like;

• How does our acquisition strategy affect adoption/retention?
• What levers can we pull to improve customer lifetime value?
• What new channels or strategies can be used once we maximize paid acquisition?

The level and willingness to align on goals will depend on organizational structure and how experimentation is perceived internally. As a starting point, teams must have visibility of all team metrics and KPIs.

Here are some additional action points to help product and marketing teams work together.

5. Get input from AI & different teams before running user research

There’s a lost opportunity when user research is done without other teams’ involvement. For example, marketing-led research might not ask users how product features impact their perception of the brand as it’s not something marketing can impact. Still, the insights are valuable for both teams and help improve the business flywheel. After all, the same customer sees your marketing and then experiences the product. Both aspects impact their overall experience. Collaborative user research, with input from AI, creates better insights, a holistic business view, and can draw teams together around shared problems.

6. Build test roadmaps together

Your team’s priorities and goals decide what goes onto your roadmap. But there is only so much test bandwidth and resources. If teams don’t prioritize and build testing roadmaps together, it can lead to chaos. Not to mention wasting effort and potential test conflict if teams aren’t aware of what the other is doing.

Working on a short and longer-term roadmap with swimlanes is a good approach. But in the real world, things change, so regular standups and monthly meetings can help keep individuals on the same page.

7. Invite AI and people from different departments to ideation sessions

There are hundreds, if not thousands, of ways to solve user problems. While common UX patterns offer some advantages for users (reducing the mental load needed to understand how something works), they can leave your experience looking and feeling like everyone else’s.

Divergent thinking can create novel solutions to problems, and involving multiple individuals from different backgrounds and disciplines and AI can boost idea creation. Involving various teams in ideation sessions means individuals are more “bought-in” to a test process than if they weren’t involved at this stage.

8. Celebrate improving the company flywheel

A lot of work goes into cross-team collaboration. It doesn’t happen overnight and won’t always be plain sailing, but the advantages for individuals, teams, and the company make it worthwhile. So, when the wins come, celebrate them.

If individuals are incentivized, using outcomes based on collective testing efforts can help motivate them, too. Rewards that can be enjoyed by all teams together will also strengthen work bonds and foster shared understanding.

Here are eight practical ways to support the marketing and product team in working collaboratively and testing together.

1. Define roles and responsibilities
2. Choose a unifying testing tool
3. Standardize with templates and processes
4. Work with the same data and KPIs
5. Get input from AI & different teams before running user research
6. Build test roadmaps together
7. Invite AI and people from different departments to ideation sessions
8. Celebrate improving the company flywheel

Feature image by Christina @ wocintechchat.com on Unsplash