Comparison is the default
Price and spec comparison is one tab away. Many carts are filled just to see the final price, so a test that lifts add-to-cart can mean nothing.
Technology & Electronics
For online shops from €100k a month
A/B testing for technology and electronics shops
Your buyers compare specs, check the price on three other sites and read the one-star reviews first. We find out what makes them choose you, put odds on every test idea before it's built, and run six to ten tests at once.
A free 30-minute call with the team. That's it.
4.3 millionA/B tests in the genome, from 151,000 shops
50%+of our A/B tests win. The industry: about 1 in 5
€500M+additional revenue for 250+ brands
What's different here
Buyers who want to be sure
Tech buyers don't want to be persuaded. They want to feel they made the objectively right choice, and they'll check before they trust you.
Too many specs, too little clarity
Product pages full of numbers overwhelm. When buyers can't tell which features matter to them, they leave to find someone who explains it.
Fear of the wrong choice
Expensive products bring buyer's remorse. Vague descriptions set wrong expectations, and wrong expectations come back as returns.
Research on mobile, buy later
Much of the browsing happens on a phone, and the order often comes later. The mobile page has to move the decision forward even when it doesn't close it.
What we test here
What a tech backlog looks like
Every idea starts in research into your buyers, then Apex by DRIP, our own testing tool, gives it a Likelihood to Win, based on 4.3 million past tests, before anyone builds it. A few ideas that tend to show up:
Specs translated into use
Short "what this means for you" summaries above the spec table, so buyers see which features matter for how they'll use it.
Comparison on your page
Side-by-side views of your own models, so the comparison happens with you instead of on a price site.
Risk taken off the table
Warranty, returns and support shown where the price is, not in the footer, so an expensive order feels safe.
Accessories that make sense
Bundles and add-ons that actually fit the product, offered at the moment they're useful, to lift order value.
Results from our case studies
We don't have a public electronics case study yet. These are two of our biggest results, run with the same method.
€8.2M+
additional revenue
How SNOCKS scaled from €2M to €90M a year
€12.2M
over 3 years
How Giesswein added €12.2M in revenue after a post-COVID drop
Common questions
Not on price, and we won't pretend to. What testing can change is everything around the price: how clear your specs are, how safe the order feels and how easy it is to choose. That's usually where the research finds the money.
Yes. We test templates, not single products, so a change to the product page or the checkout runs across the whole range and collects enough traffic to give a clean answer.
The statistics are fixed before launch: frequentist method, 80% confidence and 80% power, minimum detectable effect and duration set upfront, and no early stopping. A fake win is worse than a loss, because it ships and keeps costing you.
The first month is research, and the first tests go live by the end of it. By month three, six to ten tests run at once and the first winners are live. The guarantee: at least 10% more revenue in under six months, or month seven onward is free.
We work with online shops from €100k a month. Book a call and we'll tell you straight whether yours is a fit, and if it isn't, we'll say that too.
Spend the same on ads.
Make more from them.
Book a call with the team and tell us about your shop. We'll talk through where it stands, where you want it to go, and how we'd get you there. If working with us isn't the best return on your money, we'd tell you rather than take it.
See if your shop is a fit
30 minutes, and you'll know exactly where your shop stands.
The guarantee, in full
At least 10% more revenue in under six months, or month seven onward is free.
When you can predict what wins, you can promise the outcome. What counts as uplift, how it's measured, and what happens if we miss is written down in plain language.
We can promise it because we know our numbers: more than 50% of our A/B tests win, across 4,000+ documented experiments. That's when a guarantee stops being marketing and becomes underwriting.