District-based LivingSocial largely halted its efforts to attract new customers last year as waning interest in daily deals and a series of financial hits forced the company to retrench. Now, it wants you back. Chief Marketing Officer Barry Judge said the deals company has begun to unfurl fresh ways to entice new customers, win back old ones and turn those customers into repeat buyers. Many of those initiatives, including some slated to launch this summer, crunch data about customers’ shopping preferences and habits to tailor LivingSocial’s e-mails to each individual, and to predict when the company is at risk of losing a customer for good.
■ LivingSocial has always been very focused on, even before I got here, spend a dollar [on acquiring a customer], get a dollar [from that customer] within a certain period of time. Up until the past few months, what that means is spend a dollar through Google on search, get your e-mail address, and then some percentage of those people actually buy a deal. That would be our payback.
As we’ve evolved our thinking about new purchasers and new subscribers, there’s more ways to acquire purchasers than e-mail. A lot of people like e-mail and respond to e-mail, but not everybody does. The initial thinking is [to] still do what LivingSocial always did, but supplement it with other ways for people to buy.
■ One of them is spending money in search [to advertise] a deal and trying to get people to buy that deal directly. Certain deals lend themselves to that. A bigger way we do it is by grabbing the products that we think will sell well off of our site and then typically we’ll use Facebook to get people interested.
We had these Dotzila Bluetooth Shower Speakers go live on the site on May 2, and we’ve already sold 46,000. Essentially, what we do is we figure out from our own users who’s buying, then we find similar audiences on Facebook and sell it to them. That’s a new way of doing things. A large percentage of people who have bought that deal are new to LivingSocial in this particular example.
■ There are all kinds of affiliates, but the ones you might have heard of are Ebates.com or MyPoints.com. It’s taking our good deals and allowing those sites to market them. We give them a small fee to market them, but we’re essentially getting their subscribers to buy our deals.
And what often works well are big national deals. Our Neiman Marcus Last Call deal, which is $25 off $50 [worth of purchases], did very well marketing that deal off of our site because it’s a well-recognized brand and people want access to that. That sold 39,000 deals. Basically, we’re finding other distribution platforms.
■ We have a dollar-out, dollar-in target. We want that dollar back in a certain amount of time. That’s how we adjust how aggressive or unaggressive we want to be. If we give ourselves a longer payback time, maybe over a year, we would [spend more money and] be in the more aggressive mode. And if we gave ourselves less time to make that dollar back, we would [spend less money and] be in less aggressive mode. We toggle that up and down.
We are being more aggressive now than we were last year. We’re getting back to focusing on growing the top line and I think [improving the customer] experience gives us the ability to monetize those users in a faster way than we have in the past.
■ In the July time frame, we’re going to be rolling out personal-level personalization. We’ve been basing personalization [to date] on big groups like gender, men get certain things and women get certain things. But in the past couple of months, we’ve been testing personal-level personalization based on preferences you’ve told us, things you’ve clicked on, things you’ve purchased, etc. If I get you the right deals, I’ve got a better chance of you finding something you like.
Having lots of deals makes this relevancy thing more important. When I have just one deal, I don’t have to spend a lot of time personalizing that. When I have 14,000 deals or something to that degree, the relevancy premium goes up because people aren’t going to wade through all those deals to find the right one. That’s when we started working on these things in earnest.
■ We’ve gotten smarter. It’s building algorithms and models. We’ve invested in a data science team. We’ve probably doubled the size of that team in the last 12 months and they’ve been testing the algorithms. Probably about 20 percent of people on the marketing team are dedicated to data science.
■ Once we acquire a subscriber, we know if you haven’t bought within 30 days the likelihood of you buying ongoing isn’t very high. So we’re trying to figure out in that 30-day period, what are the inflection points when we should be sending out targeted promo codes based upon some drop-off rate? For example, after seven days, should we send you a promo code?
We can build attrition models predicting if you haven’t done something by X, Y, Z day, you’re probably a lapsed customer. Obviously we don’t want you to get to X, Y, Z day, so what are some treatments we can do in terms of deals or offers to get you to buy before you reach that attrition date?
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