We at 140 Proof are thrilled to announce that Kim Stiefel has signed on as Director of Business Development. In her new role, Stiefel will lead the charge of expanding partnerships with app developers and web publishers, further growing the advertising network.
Stiefel is an experienced hand in technology sales with senior account roles at companies like AppNexus, NetApp, and EMC. Prior to 140 Proof, Stiefel was a Top 5 sales performer in EMC’s US Commercial Division, closing the single largest transaction to date in division history.
“We’re thrilled to have Kim onboard,” said CEO and co-founder Jon Elvekrog. “Our mission is making social software more relevant by mapping the Blended Interest Graph. As we expand our technology platform into new areas, Kim’s skills will help ensure that we have the best partnerships and channel relationships possible.”
“Social advertising is about expressing meaningful messages across the social universe, and adding relevance to advertising. This has huge implications for developers and bloggers,” said Stiefel. “140 Proof is transforming digital brand advertising and I’m thrilled to help build out the best social ad offering available.
May 15, 2013 - 4 days ago
The best brand advertisers are typically eager to take advantage of a new marketing medium … but how can they tell which will be powerful engines of ROI and which will disappoint?
Take Pinterest for example. Pinterest is now the third-largest social network, behind Facebook and Twitter, and is home to many of the web’s most passionate curators. The site also attracts desirable demographic segments, like moms, and marketers are finding that it’s great place to reach these audiences.
Chad Stoller, Managing Partner at IPG Media Lab said, “Brands know that a robust social ad strategy means reaching customers on their favorite platforms. But for CPG and Home audiences, that often isn’t Facebook or Twitter — it’s Pinterest.”
At the same time, there has been early criticism about Pinterest being an ecosystem for “cupcakes and quilting,” where people play around but don’t buy. The question is, do “pins” actually translate to sales?
One promising data point comes from eConsultancy, which published a case study last May conducted by the jewelry and accessories retailer Boticca.com. The study showed Pinterest can generate more sales than Facebook.
According to the study: “[Boticca] compared engagement statistics from Facebook and Pinterest visitors to see how their behavior differed. They found that after integrating ‘pinning’ buttons across its website, Pinterest became its number one social referrer, assisting roughly 10% of sales, compared to 7% from Facebook.”
In fact, shoppers referred by Pinterest are 10% more likely to make a purchase than visitors who arrive from other social networks, including Facebook and Twitter (Wayfair, 2012). Turns out they spend more too: Pinterest shoppers spend $170 per session on average, significantly more than Facebook at $95 (Reuters).
So if you’re a brand advertiser and haven’t moved Pinterest from your block list to your to-do list, you may be overdue. The question is how to do it well and drive pinning effectively.
Here are four tips to make driving pins a cake walk:
1. Invite existing fans on other channels to follow you on Pinterest. Your followers on Facebook, Tumblr, and Twitter are likely on Pinterest as well. Create a special post geared toward moms, on each social platform, asking them to follow your brand’s Pinterest profile. For example, you might say: “Hi Mom, check out our new ‘mother board’ created just for you on our Pinterest page, where we’ll post special updates on products and early-bird discounts.” You can also encourage engagement by publishing a “We’re on Pinterest” announcement, as a main story in your customer newsletter.
2. Grow Pinterest fans through paid social advertising. It’s important to grow your base beyond existing followers, so you should work to win new fans by running well-planned ad campaigns in other social networks, sites or apps. In terms of targeting, you can rely on basic demographics, such as “women over 20,” or you can target based on people’s interests – what they like and who they follow – to target more specific segments such as “eco-moms who’ve ‘liked’ an environmentally safe brand of laundry detergent on Facebook.” Also, go wide with your advertising. Be sure to advertise on all social networks and properties relevant to your brand, and always use ad units that include an image — the bigger the better.
3. Pin Pinterest-friendly content. No doubt you’ve heard this advice, but it bears repeating. Photos should be high quality and have a concise and compelling caption, and all content should be linked to a relevant page on your site. Most importantly, stay focused. Make sure all content speaks to what moms care about, and is relevant to your brand, and/or within your vertical.
4. Optimize owned channels for pinning. If you’re really dedicated to scoring more pins, you can get down and dirty with site optimization and add “Pin it” buttons to owned channels. If you have a page that allows moms to give product reviews and feedback (something studies show moms are keen to do), you can integrate a “Pin it” button into the review form. You may even want to remove “tweet” and “like” buttons to maximize pins. And for the most detail-oriented content manager, make all image filenames as obvious as possible. This will improve Pinterest search rankings for brand-relevant terms.
by Jon Elvekrog, 140 Proof CEO
This article originally appeared on Adotas on May 3, 2013.
May 7, 2013 - 1 week ago
Now that we have discussed the role of the interest graph as the ultimate recommendation engine and the significant analytical power needed to process it. But how do advertisers and ad platforms use the interest graph to increase relevance and performance and make people happier?
Let’s Face It: Targeting Is Hard
Targeting is critical to good advertising. Brand marketers understand that it matters who sees your ad. While many products can have appeal to a wide variety of people, it’s often the case that only a subset of the population is likely to buy any given product.
For many brand marketers, the question is how to reach their brand’s target audience. Ideally, they want to advertise to someone who might have the problem or need that the product solves.
Imagine you’re a marketer at Clinique, selling Clinique’s new “Chubby Stick” makeup. Does Clinique expect a lot of video game enthusiasts will buy Chubby Stick? Probably not. Could Clinique interest fashion bloggers in buying Chubby Stick? Yes; that’s much more likely. Clinique probably wants to show their ads to women in the United States age 15 and over, and Clinique doesn’t want to waste budget on advertising to anyone else.
Finding the right person to show ads to isn’t easy, which is why hundreds of startups and companies have grown in the ad industry to help marketers reach the right people. Before the Internet, media buyers relied on information such as geography (which side of which highway in which city?) and vertical (auto magazines versus fashion magazines) to decide where to place their ads. More and more, the decision is about what online venues are best for certain types of ads. Technology companies have been working this problem for over 20 years, and they haven’t nailed it yet.
“Ad targeting is a difficult artificial intelligence (AI) problem, and…it does require a lot of technical heavy lifting.”
“Microsoft recently announced that it’s taking a huge $6.2 Billion writedown over the failed aQuantive acquisition. This news, and the scrutiny of Facebook’s business model following their IPO drama, show that, in online advertising, it’s all about the targeting.”
The Interest Graph Makes Ads Relevant
The Interest Graph makes ads more relevant to audience members, which increases performance, which makes buying social ads more efficient.
Benjy Weinberger at TechCrunch explains why this is important:
“Google AdWords remains phenomenally successful, generating over $36B in revenue in 2011. The key difference? targeting. Google’s sophisticated ad-targeting algorithms greatly increase the relevance to the user, and therefore the likelihood of the user clicking on an ad. This is what makes AdWords so much more effective than banner ads.”
What Is Relevance?
Think about your mailbox. We intuitively know what relevant mail is: important bills, gifts, thank you notes from friends, wedding announcements, etc. We also know what irrelevant mail is: credit card offers, coupons, and announcements that we don’t care about. There’s value in separating out the irrelevant stuff and just leaving what’s relevant. What if you had a friend who went through your mail before you got to it, throwing away all the junk and presenting you with only the good stuff? That’s what good targeting algorithms try to do with advertising.
On the face of it, people may think that no advertising is relevant to them. However, everyone buys things from time to time and everyone welcomes a great recommendation. Consider the value of having an informed sales person help you choose between expensive electronics, or the value of a music recommendation from someone you trust.
Relevant Ads Means Happier Advertisers and a Happier Audience
Increasing the relevance of advertising messages is just another form of efficient recommendations. If a brand advertiser can present its ad to people who find it relevant, the ad is no longer an ad: it is a welcome recommendation.
Our imaginary user “Andrea” can help here. Assume that, as a San Francisco resident, Andrea is used to seeing the print ads on the sides of Muni buses in the city. One day, Andrea sees a Muni ad for “The Book of Mormon,” a new musical by Trey Parker and Matt Stone, the creators of South Park. Since Andrea is a South Park fan (and she had already heard of the musical’s debut in New York), she’s thrilled to see the ad. The ad was not just a request to buy tickets to “The Book of Mormon”: it’s a message relevant to her.
The Interest Graph: a Better Predictor of Brand Affinity
Online advertisers have historically used a couple ways to target their ads:
1. Advertising on sites or apps that fit into verticals: for example, if Chevrolet wanted to advertise on news sites, they might start with Wired Auto before moving on to the Financial Times. Because the site is relevant to the ad, the ads usually perform well, but advertisers sometimes want more scale than this approach provides.
2. Showing ads to people based on browser history: for example, a shoe retailer might target people who have visited a shoe retail site in the last 60 days.
But neither of these approaches fits the new, decentralized, content-driven nature of the internet. People visit social first and branch out from there, based on what their friends and influencers recommend to them.
But a powerful, third form of targeting has emerged that’s perfect for social: Interest Graph targeting.
Interest Graph targeting transcends platform and can be applied everywhere, even on mobile, because it’s not tied to device IDs, browser history, search history, or browser cookies. It means more apps get downloaded, more ads get clicked, more content gets read, etc. Interest graph based advertising has shown higher performance than traditional display. For example, some networks report average click through rates of 0.50%, which significantly outperforms standard the banner ad CTR of 0.01%.
Key Players Are Moving to Bring the Interest Graph to Advertising
As we discussed, the interest graph is extremely useful for making effective recommendations. Companies of all kinds are capitalizing on this: for example, Highlight and Airtime are using interest graph technology to recommend new people to follow.
In the advertising world, four main players are working the problem of using the interest graph to improve advertising recommendations: Facebook, Twitter, Google+, 140 Proof, and Gravity.
Here’s how 140 Proof deploys the interest graph in an advertising context. Imagine that our imaginary user, Andrea, has opened her favorite social app to check her friends’ updates. While loading social data, the app asks 140 Proof’s interest graph algorithm for a relevant ad based on Andrea’s interests. 140 Proof assesses Andrea’s profile, confirms that the profile is marked public, and determines that she follows Ryan Lochte, Dara Torres, Patton Oswalt, and she has mentioned Comedy Central shows like South Park, qualifying her broadly for the “Sports” and “Comedy” categories. 140 Proof then searches its current inventory for ads matching those categories, and returns a relevant ad, in this case a promotion for a major sports media brand. The app displays the ad to Andrea at the top of her social feed, and she decides whether to engage the brand.
Now you should have a sense of what the interest graph is, why it’s important, and how it can help advertisers connect better with users. Do you have questions about the interest graph and all the ways it can be used to improve recommendations and advertising? Get in touch with us at email@example.com.
by: 140 Proof Research Team
Contributors: Jon Elvekrog, John Manoogian III, Vanessa Naylon & Lau Ardelean
April 29, 2013 - 2 weeks ago
Now that we have introduced the concept of the interest graph and why it’s the ultimate recommendation engine for brands and technologists, we’ll explain the basics of what the interest graph is and how it’s mapped and analyzed to offer relevance to businesses.
What Is the Interest Graph?
The interest graph is made of Likes, Follows, and other social relationships between people and things, products, or brands. As Naval Ravikant, founder of AngelList, described in TechCrunch, the interest graph is asymmetrical, organized around interests, public by default, and aspirational.
Relationships in the interest graph are asymmetrical, meaning they’re one-way follow relationships (not two-way friendships). Users can follow or like @Rihanna without Rihanna being required to follow or like the users in return. This means that they’re organized around interests, not friendships. In fact, friendships are described by the social graph, a picture of who knows whom. The social graph has been explored for various purposes, including advertising, but its best use tends to be limited to making recommendations for more friendships. (You may have seen the “People You May Know” sections on LinkedIn that encourage you to connect with more people.) It’s important to make the distinction that knowing each other in real life isn’t required by the interest graph. You can like Tom’s Shoes, Converse, and Puma without having ever visited their retail stores.
And because mutual following is not required, people can follow based on what they want versus who they already know. This means following is aspirational. You can follow @BillGates on Twitter because you admire his philanthropic work and want to learn more about it, without Bill Gates needing to decide you’re worth following in return. Asymmetrical following emphasizes interests because it helps people reach for their wishes and hopes.
Due to the nature of social platforms, interests (and the interest graph) are public by default. Information about who and what people follow is standard public information in user profiles, which means that it’s not only revealing, it’s noninvasive too. (However, users can make their profiles private, and some ad platforms use this as an automatic opt-out feature.)
The Blended Interest Graph (BIG)
Every platform has its own interest graph. Facebook data helps us create a picture of user interests via the Like button. You can do something similar with Twitter data by analyzing interests expressed via the Follow button. Every social platform has its own version of the one-way follow relationship (on most platforms, it’s called “Follow”).
Because all social platforms also have implemented APIs and/or data streams, each proprietary interest graph is available to be analyzed in aggregate. For the purposes of this article, we’re talking about all of these secondary interest graphs taken as one — the Interest Graph. Think of it as:
- The Facebook Individual Interest Graph
- and Twitter’s Individual Interest Graph
- and Google+’s Individual Interest Graph
- and Foursquare’s Individual Interest Graph
- and Pinterest’s Individual Interest Graph
- and Instagram’s Individual Interest Graph
…and on and on. The sum of all individual interest graphs is the Blended Interest Graph (BIG) for online social platforms.
BIG = Big Data
The interest graph is made up of basic social building blocks like Facebook Likes and Twitter Follows. 140 Proof CEO Jon</h>s Elvekrog likes Domino’s Pizza on Facebook. That’s one data point for the interest graph. For example, 140 Proof CTO John Manoogian III (@jm3) follows creative agency @Mekanism and Forbes journalist @a_greenberg on Twitter. That’s two data points for the interest graph.
These individual data points add up to a huge set of information. And the interest graph is growing at an accelerated pace. Every relationship in social is represented by the interest graph.
As new users join and follow influencers, the data set grows by 2 billion Likes every day — six Likes for every person in the United States, every day. Put another way: the current world population is estimated at 7 billion, and the interest graph is about 40 times larger — currently sitting at around about 266 billion Likes and Follows.
The interest graph is a picture of the present moment. To analyze the interest graph is to understand what’s happening right now. Unfollows are discarded and new follows are included and folded into the analysis.
How Do Social Companies Analyze the Interest Graph?
Understanding and mapping the interest graph requires a dedicated team steeped in information theory, big data architecture, and lightning fast calculation. The biggest challenge in harnessing the power of the interest graph is making millions of decisions in real time. With over 2 billion new interest signals every day, any delay in processing means relevance could be compromised. At 140 Proof, an elastic architecture composed of hundreds of cloud servers grinds public social data, collects interest signals from social platforms, analyzes the data, and makes rapid decisions about people and personas. Dedicated data scientists, engineers, and statisticians ensure that computation happens not just instantly but accurately.
by: 140 Proof Research Team
Contributors: Jon Elvekrog, John Manoogian III, Vanessa Naylon & Lau Ardelean
Read Part Three: How the Interest Graph Makes Ads Relevant
April 15, 2013 - 1 month ago
140 Proof expands its social ad technology offering today with the addition of Pinterest sharing to its native social ad offering.
The integration allows brands to increase social sharing and re-pins of their branded visual messages on Pinterest.
Read coverage on The Next Web
Pinterest is now the third-largest social network behind Facebook and Twitter and is home to some of the Internet’smost passionate curators and online shoppers. Pinterest has also become a major driver of e-commerce revenue: according to eConsultancy, Pinterest has been shown to drive more sales than Facebook and more referral traffic than Twitter, as well as more revenue per click than either Facebook or Twitter.
Says Chad Stoller, Managing Partner at IPG Media Lab:
“Brands know that a robust social ad strategy means reaching customers on their favorite platforms. For CPG and Home audiences, that often isn’t Facebook or Twitter — it’s Pinterest.”
Now that social is a daily destination for people online, brands want get their content out everywhere that people share. For many brands Pinterest feels tailor-made for sharing great visual content.
Says Karen Renner, Associate Director of Social Media at digital marketing agency VML:
“Pinterest is an ideal platform for consumer brands to express their essence visually while attracting a primarily female audience that is already in the purchasing mindset.”
Read more on The Next Web: 140 Proof adds Pinterest sharing to its social advertising service
To learn more about accelerating sharing on Pinterest, email us at firstname.lastname@example.org.
March 27, 2013 - 1 month ago
Why are tech industry titans so bullish on the concept of the interest graph? And why are CEOs, venture capitalists, and industry experts predicting big things for the company that can capture it?
The fact that you follow Snoop Lion on Twitter and like Starbucks on Facebook means something. It’s important to a lot of people. One person likes nonagenarian actress Betty White and another likes hipster musician La Roux; one person likes Method soap and another likes PUBLIC Bikes; that’s worth a few cents to NBC, Arista Records, Tide, and Specialized.
Why is that? Because knowing what you love helps businesses understand what new things you might like. Relevance is the magic ingredient. Brands, bands, games, and teams you like are highly relevant to you. And for businesses who want to find people who might like what they’ve got, relevance is king. Advertisers have always been interested in what you like, and the fastest, simplest, most transparent tool for knowing what people like is something called the interest graph.
The Interest Graph Is the Ultimate Recommendation Engine
The interest graph could ultimately prove to be the best indicator of brand affinity. In this report, we’ll explain how that’s possible by walking through what the interest graph is and how it’s analyzed.
“Interest Graph” = “Virtual Diagram of Connections to What We Love”
The terminology is easier than it looks: A graph is a picture of the connections between objects. The picture can be real or imagined; what we care about is the data, not necessarily producing a physical graph. Objects, in this case, are people and things. In the interest graph, we understand what things every person on the graph is interested in. Imagine a young woman named Andrea living in San Francisco. Andrea loves swimming, but you wouldn’t know it by looking at who her Facebook friends are. Her Facebook friends include cousins, high school friends, college roommates, and co-workers. But if you knew that Andrea follows swim blogger @speed_endurance and Olympic swimmers @RyanLochte and @DaraTorres on Twitter and that I liked my local pool and Michael Phelps’s nonprofit for kids on Facebook, you could figure out she was an aquaphile.
The Interest Graph is growing in importance for social companies as they build out their future business plans. Because advertising is the main source of revenue for online businesses (see: Google), knowing which ads to show to whom is key to sustained happiness for both users and advertisers.
Technology Leaders Put Their Weight Behind the Interest Graph
The interest graph has attracted attention from technologists for its potential to deliver relevance for advertisers. Dick Costolo, CEO of Twitter, has said that the interest graph will offer “powerful value to advertisers.” And Naval Ravikant, founder of AngelList and investor in Twitter, wrote in TechCrunch that “the interest graph lends itself brilliantly to commerce.”
The interest graph holds big value for app developers too. Airtime, for example, launched a much-touted video chat app that analyzes Facebook’s interest graph to help match like- minded participants. Sean Parker, founder of Napster and investor in Facebook, describes the interest graph as a powerful tool for creating “a very nuanced view of people.”
And Benchmark venture capitalist Bill Gurley, in conversation with Goldman Sachs, explains why he values the interest graph, especially over a concept like the social graph (a concept we’ll explain more later):
Social graph signals have not been helpful in optimizing advertising. It seems intuitive to everyone that your friends’ recommendations would be powerful motivators…but when you look a little deeper, you hang out with people who have very different tastes than you. And you may have a special affinity through a hobby or something that they don’t share. One of the mythical high grounds that everyone’s thinking about…is this notion of an interest graph. Facebook connects you with people you know. But what connects you, if you’re into road biking, with the top 15 road bikers that are within 15 miles of where I live?
[For a platform to] capture the interest graph, they’d be closer to the Google search paradigm, because they’d be right in line with demand generation, and with discovery that relates to product purchases. Context, for the history of the Internet, has been a big deal. The websites that do verticals, while they may not have abundant traffic, have always had huge CPMs, relative to the “Yahoo! Mail”s of the world. That may be this middle ground, between search and the social graph, to bring together people with like interests.
by: 140 Proof Research Team
Contributors: Jon Elvekrog, John Manoogian III, Vanessa Naylon & Lau Ardelean
Read Part Two: Defining the Interest Graph
March 25, 2013 - 1 month ago
At 140 Proof, we’re so excited about our new Pinterest-Enabled Social Ads that our team was inspired to jump on the bandwagon and create new boards for the occasion. Our developer, ad ops, marketing, and sales teams all joined the fun.
Our resident Pinterest experts will pick one board to be awarded an Amazon Kindle in 140 Proof’s company-wide “Go Pin Yourself” contest. Which ones do you love most?
That last board belongs to the official 140 Proof Pinterest page. Come pin with us, won’t you?
March 24, 2013 - 1 month ago
Anonymous hater “Retail Exec D” told Digiday this week that Pinterest is “just people playing around.” Is that what you believe? If you’re a marketer, is Pinterest on your to-do list or your block list?
Anecdotally, my acquaintances have sometimes joked about Pinterest as if it’s all cupcakes and weddings. They imply that a platform that’s home to such mundane conversation couldn’t be important to anyone important. But haters often find themselves on the wrong side of history.
Haters Gonna Hate, Pinners Gonna Pin
The vaguely sexist “no one cares about cupcakes” prejudice against Pinterest brings another social platform to mind. The chart below will roughly illustrate my thinking:
Twitter, now considered by some a $10 billion company, was dogged by perception problems as it grew. Five years ago, many pundits couldn’t look beyond their MySpace-shaped world to see the potential in lightweight and fast-traveling tweets, dismissing them as insignificant chatter about what people ate for breakfast.
2012 happened for Pinterest, too. On an Internet-wide scale, Pinterest now has almost as many users as Twitter. 15% of people on the internet use Pinterest, compared to 16% who use Twitter (Pew, 2012).
It’s tempting to dismiss Pinterest as trivial and leave these cupcake enthusiasts in peace. But we’d be missing something.
Could the U.S. Economy Be Built on Cupcake Enthusiasts?
A big chunk of those Pinterest users, the ones pinning cupcakes and weddings, are women in their 20s and 30s. These Cupcake Enthusiasts…could they actually be…Moms??
(Brand marketers everywhere instinctively freeze and perk up their ears)
Moms wield financial power — and not just when it comes to the grocery list. Moms are the reason automotive designers and marketers consider the “wife acceptance factor.” Moms account for more than half of household consumer electronics purchases (Consumer Electronics Association, 2010). Moms are more likely to shop online for clothes, toys, and music than the average Internet user (Nielsen, 2012).
But maybe you don’t believe me. Maybe jumping from “women” to “Moms” is too big of an assumption when it comes to the purchasing power of Pinterest users. Hmm, but then there’s this:
Pinterest Users Spend More Money Online Than Other Social Users
Those cupcake-and-wedding people like buying things. Shoppers referred by Pinterest are 10% more likely to make a purchase than visitors who arrive from other social networks, including Facebook and Twitter (Wayfair, 2012). Turns out they spend more too: Pinterest shoppers spend $170 per session on average, significantly more than Facebook at $95 (Reuters).
$170 per e-commerce purchase surely isn’t “just playing around.”
Excellent. Now What to Do?
Crack your knuckles. Many savvy brand managers for fashion, home, consumer packaged, goods, travel, and retail have already created owned brand presences on Pinterest. And there’s something all of them want from Pinterest users:
Brands want re-pins of their content.
Fortunately, according to RJ Metrics, 80% of Pinterest pins are re-pins. This means the user base is already sharing and engaging with content on a high level.
Make Pinning Brand Content a Cakewalk
140 Proof is going to be announcing some exciting new Pinterest capabilities next week – stay tuned for more.
P.S. to be fair to the Moms and all Pinterest users, Pinterest actually ISN’T all cupcakes and weddings. Pinerly reports that Weddings and Cupcakes (Food category) comprise no more than 15% of pins. Gotcha.
By John Manoogian III (@jm3), 140 Proof Co-Founder and CTO
March 19, 2013 - 2 months ago