To Qubit, a London-based company founded by four former Googlers, proper optimization of Web technology deployments plays a critical role in the effectiveness of commerce experiences and online advertising. A range of publishers like the BBC and retail brands like Pandora rely on Qubit’s enterprise tag management product Opentag for digital marketing and other forms of optimization using a single line of code.
Raising $7.5 million in Series A funding from Balderton Capital last winter, Qubit has 1,000-plus customers using the platform, is expanding to New York and is growing revenues 150% year-over-year, according to one of its founders. It has partnerships with Criteo, Rakuten LinkShare, Affiliate Window and Audience Science.
Ian McCaig, cofounder and director of strategy and marketing, spoke with AdExchanger.
AdExchanger: What does Qubit do?
IAN MCCAIG: The four founders have known each other for eight or nine years now [and met] way back when Google was seeing this tremendous growth. We worked across Mountain View and New York and we came together in 2009. The big thing we were seeing with ecommerce businesses was around conversion rates, [which] have remained flat, even though cost-per-click advertising is continuing to rise.
When I was there, it was getting a lot more expensive to acquire customers. The reality was, conversion rates were being flattened. [With] AdWords, you knew what you could do. If you changed your bid on your keyword strategy, you knew you could optimize your marketing. But conversions were a bit of a black box for marketers. They didn’t really know what they could do to make an impact. There were tools in the market for A/B testing and multi-analytics to help identify malfunctioning product pages. But they were static,, almost bureaucratic, heavyweight systems that weren’t very agile -- which doesn’t really align with the state at which marketers ought to move.
What are you focused on now?
Over the last few years, we’ve built a technology stack that’s focused on driving incremental revenue by improving metrics like driving conversion rates on websites. Effectively, we’ve built a platform that combines traditional web analytics, with A/B testing functionality and personalization. So, the ability to serve relevant content to the right user at the right time. These were in [separate siloes] traditionally and you had your Web analytics over here, maybe your A/B testing over here, or maybe your tag management solution over here. What we’ve done is consolidate it all in to a single platform
We work with hundreds of enterprise retail and channel clients and they’re using this to optimize their websites to conversion.
Can you give a use case?
Our client Superdry is an international clothing brand in New York and they have a huge presence across Europe as well. We tend to look at very specific behavioral segments and things. A really simple one is, you know when a US citizen comes to a website and is presented with a site that doesn’t really look [like it’s optimized for them?] There’s no free delivery to the US or post codes and doesn’t really have a US look and feel. They were looking in certain markets where conversion rates were much, much lower than other markets. And we can connect that in to Voice-of-the-Customer feedback and we found that people didn’t know what shipping charges were for. Based on IP and based on knowing where the user comes from, they basically created a much more friendly US website that allowed them to create a better experience for the customer and drive double-digit growth in conversion rates just by understanding that there’s a problem and be able to provide a more personalized experience. A segment like a country is a very big segment.
Obviously, paid placements are a part of the site mix, too. What are you noticing about the blending of owned, earned and paid media?
It may sound simplistic to look at the world in this way, but we fit some retailers into ‘utility’ work -- like Amazon and the typical catalog retailer that stocks millions of products. You go on the site, you know what you’re looking for, and you buy.
The other side, is the ‘experiential’ and this is brands like Fab.com and Etsy and Net-a-Porter and these kinds of retailers are trying to build much more of an experience and loyalty with consumers. That’s where we see the market for improvement [with regard to] conversion rate. It’s about using rich media and great, editorial content, video merchandising tools and trying to bring the shop to the website and for us. This experience is going to become almost self-curation, where you go to the website and you want to see those products, get reviews from your friends and you want to use the tools and applications that you like using to bring the products to life. I might like video, but you might like 360s and zooms, so it’s trying to figure out what works for different users and then engaging with them.
With utility, it’s going to be about price, immediate delivery and the instant gratification and speed. On the experiential side, you want a brand you can really engage with.
That’s interesting – this convergence of content and commerce.
A lot of publishers are moving in to the ecommerce space because they want to get more transactional. With [client] Telegraph, people who read editorial content – their conversion rates were five times higher than people who did not read editorial content. We find if experts give advice, and show their views, it had a massive, massive impact on conversions. Net-A-Porter announced a few months ago that they were launching a new magazine to compete with Vogue because they see the value of having world-class editorial content alongside luxury products and brands and I think we’re going to continue to see the convergence of content and commerce over the coming years.
You talked a little about attribution. Coming from Google, and being that Google Analytics is a Qubit partner to this day, any thoughts on Google and its data-driven attribution activity of late?
It’s funny, because tag management and attribution have become quite synonymous with one another. If you get the data right at the start, all you can do is present data in terms of attribution data or analytics data. I always thought tag management was named wrong. It should have been data management, because what it’s helping you do is effectively structure your data in a logical so that every technology can collect that data. It’s almost like translating everything into one language.
Obviously Google has been doing attribution for a long time, with their standard GA products and obviously, this new GA Premium just demonstrates how important it is for Google to measure the effectiveness of media. People are starting to question, ‘Am I getting a good return on investment from these millions of generic keywords I’m bidding on?’
Their new product – as far as attribution is concerned – is another byproduct of what we do. A lot of clients want to see, holistically, what’s going on on their website and what’s happening in their marketing channels and have this single view. And I think Google Analytics Premium – it’s a great step. Until they bring in non-Google data, it will be looked at as [a biased] data source. So the big step will be when they bring in more DoubleClick data, data from other DSPs and other ad data to enrich their model -- otherwise it becomes just a Google attribution model, which, although it’s useful because Google is such a large percentage of spend, the ‘advertising cynics’ out there would say it’s Google markets at work.
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