💡 How aiden came to light

If you know Aiden a little bit, you know that we have 1 or 2 opinions about e-commerce. But what you may not know is how our vision for e-commerce has shaped itself. And what Humberto Tan has to do with that.

The online advice light comes on

In 2012/13, I worked - Marja - at Philips Lighting in Eindhoven. Our job: sell as many lights as possible online. Philips had around 3,000 lights at the time. Three thousand unique products, or SKUs, that were sold to a greater or lesser extent around the world. It was my job to make sure that this also happened online.

Complication: buying (re) lights online is quite difficult. Give someone a light and you can be 90% sure they have no idea what kind of lamp it is exactly. That is why many people with lamps (or fixtures) and everything go to the hardware store to find a suitable new lamp there.

In the online product catalog, this was a lot more difficult:

With only these filters for shape and fit, as a user, you just had to know what a B22 looks like. Or what a 'special version' is.

Couldn't we create something that would stop our users from having to search through a huge list of 3,000 lights on their own? Answer 5 questions and this is your lamp, that idea.

Time for a new approach, so I hit the barricades for online advice for the first time.

About 1.5 years later (seriously), he was there: the Philips Bulb Advisor. And as it turned out, the thing worked. We saw that in the reactions, but especially in the conversion figures. People who used the decision aid bought a lamp twice as often.

People who used the decision aid bought a lamp twice as often.

Hack your gift problem

I had a taste for it, so online advice was key again when we participated in the Dutch Open Hackathon with a team of colleagues in 2014. Our hack that weekend won an award and became a hobby project that got out of hand.

In 2015, we launched her: Feli — your personal gift assistant. An app that helped you find the perfect gift.

As a user, you provided some hard specs (gender, date of birth) and soft specs (type of person: is it a party animal or couch hanger?) about the recipient. You then received gift suggestions, which you could “like” or “skip” in a Tinder-like interface. The algorithm learned from your feedback and the gift suggestions kept getting better. So until you found the perfect gift.

Brilliant idea, of course (seriously, we still have the code — you can bid). And that's what the editors of RTL Late Night thought, too.

With Humberto's endorsement, it was not surprising that Feli caught on. We quickly reached 10,000 users in about 2 months. Without any marketing budget.

The common denominator

But secretly, of course, it was the common denominator between lights and gifts that made Feli a success. Taking people by the hand. They help make decisions. By providing them with expert knowledge and input at the right time. So that they dare to press the buy button with confidence.

And that's how Feli became Aiden. We decided that the content doesn't matter much to us. Because whether you're looking for a lamp, insurance or a gift for your mother... Buying things online is sometimes quite difficult.

So let's put our technology now in for all types of content at all kinds of web shops big and small. With Aiden, we offer their customers a helping hand. Say, the advisor from the store — but scalable.

The result? Double conversion rates. A positive impact on NPS. And fewer returns. Because that's the future of e-commerce: buy better instead of just buying (and returning) more.