With no shortage of competitors – Fab.com and RueLaLa among them – Gilt has diversified its reach through a variety of avenues, including paid media in luxury publication Du Jour, to reach high-net worth readers and the development of local daily deals offshoot Gilt City.
Although Gilt had close to 100 layoffs in 2012 and sold off luxury travel deals platform Jetsetter.com to TripAdvisor this April, CEO Michelle Peluso said Gilt will continue to diversify its business and look “at advertising revenue a little more,” in a Q&A with AllThingsD. She acknowledged talk of Gilt’s looming IPO, but said, “we’re not in a rush.”
Tamara Gruzbarg, Gilt Groupe’s senior director of analytics and research, joined in 2010 from her prior post as director of digital analytics for Experian Marketing Services. She spoke with AdExchanger.
AdExchanger: From when you joined Gilt Groupe from Experian until now, what has intrigued you the most from a membership standpoint?
TAMARA GRUZBARG: I joined Gilt a little over three years ago and we have definitely grown in terms of membership. I would say more than three-fold since then. The major difference from when Gilt Groupe started in November 2007, was that for the first year or so [growth] was mostly fueled by referrals.
Since then, we’ve been figuring out how to bring high-quality members not just through referral but through various channels like display, search, SEO, mobile and even TV campaigns we launched over the holidays this year. We’re diversified in terms of our acquisition sources and it has fueled our membership growth.
Where are you concentrating your efforts to drive consumer interest?
We came to understand that it’s really one customer. So if you’re talking about a person who checks her email and then launches her app or she sees an ad on some other site, it’s ultimately the same customer. What’s exciting to us is to be able to get as much information as possible and to get better and better in terms of our customers’ cross-channel behaviors. Mobile channels have been experiencing, what I would say, is amazing growth over the past two years. From the data analytics and customer data perspective, one of the most exciting things for us is we will be able to identify, at the user level, all of the [implications across] possible touch points.
Up until this day, we knew about our mobile trends and mobile behavior of customers at the aggregate level, but we were unable to, at the user level, understand… the same person and their mobile actions. Very soon we’ll be able to do that, which will definitely enable us to build much more sophisticated strategies and much more sophisticated models because we will see the big picture and understand when to talk to the customers when they’re most active on which channel and ultimately provide a better experience.
Can you discuss the mobile growth of Gilt Groupe?
Mobile traffic has definitely grown significantly. Right now, we are getting about half of our [site] traffic through mobile devices. Transaction rates, while slightly lower because people are more likely to browse in mobile [and feel more] comfortable purchasing on-site, are actually changing. Transaction rates on mobile are quite substantial now at almost 30%. But if you’re talking about, for instance, a timeframe of a long weekend, when people are on the go, this percentage is 50%. So we can say that we get probably half of our business from mobile devices.
How does email – under the auspices of mobility – impact conversion measurability?
Email is definitely a very high-traffic area for us and what we realized is that while we still closely monitor specific email-related metrics like click-to-open rates and the transaction rate that’s directly related to email, we realized that with such a huge movement over to mobile devices, we can’t rely solely on these metrics when measuring the success of email, because email really has a halo effect.
Imagine somebody who is on the go with their mobile device. If you got an email from Gilt, you probably will not click through on your mobile device, because it might not make sense. You will probably go and launch the app. This action is not captured by direct, traditional email metrics, but it was definitely influenced by email, so that’s why we are looking at overall transactions of people we know are engaging in emails and attributing this to [specific device usage to determine how this contributed to the] success of the email channel.
How do you look at data to promote, recommend and, ultimately, personalize?
Personalization, really, underlies everything we do. We send out thousands of different emails to our member base because sales and images that are populated within the body of the email are driven by specific behaviors we’ve observed from customers. We’re launching many, many new sales everyday and we have a sophisticated personalization algorithm that helps us to identify, “What are the sales that we need to be promoting based on their individual behavior?” to make sure that we will spark their interest and [they will] ultimately purchase.
At this point, it’s a cornerstone of what we do and we continue to experiment with the algorithm and the way we know “when to recommend this product” and “when are the right times.” Personalizing not just the products, but also the timing of communication and the frequency of communications. We want to make sure the experience we provide is as relevant as possible.
Are you incorporating paid media into your loyalty marketing efforts?
We are definitely thinking about loyalty from various perspectives. I wouldn’t necessarily tie it, currently, to our paid channels. We are thinking about loyalty for members we’ve already acquired and there are several initiatives on the way that kind of address this. It’s a really interesting topic for us, but I can’t really discuss details now.
Are you incorporating predictive modeling into your paid media strategy in order to use your wealth of aggregate data to look at who bought when and what they’re likely to click on, view, etc. in the future?
We recently started testing some capabilities that combine predictive models of segments that we developed internally and are working with our partners in implementing them for external targeting.
What are some of your immediate goals that will help you really gain more insights and put audience data to use?
One of the big goals and big pushes is to become better at fully understanding cross- channel behavior and fully optimizing the customer experience where it’s not only email or site we are looking at, but understanding where people are, when people are the most active with which channel and optimizing their experience based on these behaviors. I’m excited that, very soon, we’ll be able to start solving this problem.
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