Marketing Experiments I Explored This Year (as a product marketer)

Results, tips, what failed, and what worked.

Do you experiment enough?

One of the things I love about being a marketer is that marketing is never boring. When I feel like I’m stuck in my comfort zone, I immediately start looking for new ideas to experiment with.

Sometimes the experiments are successful but sometimes they fail.

I am going to share the lessons I’ve learned from some interesting experiments I carried out this year and how they have made me a better Product Marketer. 

My first experiment: Features over Benefits Website Test

As a product marketer, it is my job to lead positioning and messaging efforts. I created separate landing pages - one of them focused on the product benefits and outcomes while the other focused on what the product does and how it works

Surprisingly, the landing page that got us the most demos and overall interest was the second page focused on how the product works and what it does.

I also added a pop-up on the both landing pages asking users why they were leaving without taking the next step. The pop-up was set to trigger when a user attempts to exit the page and these were the options;

A. I don’t need this solution right now

B. I don’t understand what you do

C. I already use a similar solution

D. Don’t worry, I’ll be back

Out of the 20 people who engaged with this pop-up, 13 of them said “I don’t understand what you do”

So, what did I learn?

We are in 2024 and software products are no longer novel. Bring up an idea, someone has probably thought of it before, so instead of making a lot of promises about how cool a product is and how it can help customers reduce costs, etc… Customers want to clearly understand what exactly your product does and how it does it so that they can decide between your product and similar alternatives.

You say your product can save them money, everyone says the same thing. So how exactly do you do it that’s different from existing alternatives?

The second experiment: Exploring Distribution Channels

I work in B2B SaaS so it can be more challenging to reach our target audience on Social media. I decided to explore Reddit more intentionally as a strategic channel for lead generation which I had not focused a lot on before.

I was surprised to find out how many demo bookings we started getting from this channel.

It turns out that while our target audience hang out on Linkedin, they go to Reddit to look for answers and get opinions from their peers.

What did I learn?

It’s important to understand where your customers are, but beyond that, it is also important to know where they go to seek solutions. Sometimes (like in this case), these are two different places.

The third experiment: Copying big competitors.

Now, I am a big advocate for “don’t copy your competitors” especially when they are much bigger than you but I went ahead to explore what the result could be if we made our GTM similar to how the bigger cats are doing this.

I created an affiliate program, removed pricing from our website, updated our homepage, added some new pages to the website, and focused on enterprise accounts. Well, it mostly failed.

Nobody cared about our affiliate program because we are not as popular as the bigger competitors, the new homepage did worse than the old one, and enterprise visitors did not understand how we are different from the market leader or why they should trust us.

The sales cycle was extremely long and the pool of potential customers was so small.

However, something went well. We started serious conversations with 2 big accounts

Was this enough to continue with this strategy? No, it was not.

This experiment helped me realize the importance of transparency for startups. Your bigger competitors get away with a lot of things that start-ups cannot get away with like being vague about what they really do because they are famous.

The fourth experiment: Discount Codes

Everyone talks about how people love “cheap” things and yes they do prefer not to pay $1000 for a product but cutting down your prices and giving out tons of discounts will not help you sell to B2B buyers (as a startup).

We explored a discounted offer for a limited timeframe but discovered that while hundreds of people visited the page from the campaign, they did not go ahead to claim this discount.

So we paused the discount and offered a free trial instead. We started getting sign-ups.

The discount code experiment failed because while people love discounts, they can only claim it by committing to pay something and they just won’t do it unless they trust the product to deliver on its promise and they NEED it.

In the B2B sales cycle, there are just too many people involved in the decision to purchase software and a 30% discount won’t make all these people/steps disappear.

For a startup, focus more on offering value. A free trial for a limited time makes it easy for a company to explore the value you can offer before committing to a paid tier and works better than discounts. While discounts work for more established companies and for B2C businesses, it is not always as effective for B2B startups.

For some of these experiments, I already knew how they would turn out before I started and for some others, I had no idea what the results would be.

I am only covering these four experiments in this piece but I have been part of a lot more experiments (maybe I’ll do a part 2)

Even though I thought some experiments would not work out, I went ahead to do them because it was important to the rest of the team who wanted to explore these options and because I stand by my “don’t assume when you can test it” policy

As a product marketer, you might wonder why I run so many experiments.

Here's why: experimentation is key to creating a powerful positioning and go-to-market (GTM) strategy. By testing ideas, I can identify what resonates most with the market and refine our GTM approach for maximum impact

Finally, if you’d like to start experimenting, be very open-minded. Sometimes you get amazing results, other times you get bad results. Don't get sucked up by your own biases and try to engineer things to work out in your favor - focus on the objective data.

I hope you learned something today?

See you next time!