by   Ranker
Staff
in Data

Why Ranker Data is Better than Facebook’s and Twitter’s

 By Clark Benson (CEO, Ranker)

It’s unlikely you’ll be pouring freezing water over your head for it, but the marketing world is experiencing its own Peak Oil crisis.

Yes, you read correctly: we don’t have enough data. At least not enough good data.

Pull up to any marketing RSS and you’ll read the same story: the world is awash in golden insights, companies are able to “know” their customers in real time and predict more and better about their own market … blablabla.

Here’s what you won’t read: it’s really, really hard. And it’s getting harder, for the simple reason that we are all positively drenched in … overwhelmingly bad data. Noisy, incomplete, out of context, approximate, downright misleading data. “Big Data” = (Mostly) Bad Data as it tends to draw explicit behavior from implicit and noisy sources like social media or web visits.

Traditional market research methods are getting less reliable due to dropping response rates, especially among young, tech-savvy consumers. To counteract this trend, marketing research firms have hired hundreds of PhDs to refine the math in their models and try to build a better picture of the zeitgeist, leveraging social media and implicit web behavior. This has proven to be a dangerous proposition, as modeling and research firms have fallen prey to statistics’ number one rule: garbage in, garbage out.

No amount of genius mathematical skills can fix Bad Data, and simple statistical models on well measured data will trump extensive algorithms on badly measured data every single time. Sophisticated statistical models might help in political polling, where people are far more predictable based on party and demographics, but they won’t do anything to help traditional marketing research, where people’s tastes and positions are less entrenched and evolve more rapidly.

Parsing the exact sentiment behind a “like”, a follow or a natural language tweet is extremely difficult, as analysts often lack control over the sample population they are covering, as well as any context about why the action occurred, and what behavior or opinion triggered it. Since there is no negative sentiment to use as control, there is no aibility to unconfound good with popular. Natural language processing algorithms can’t sort out sarcasm, which reigns supreme on social media, and even the best algorithms can’t reliably categorize the sentiment of more than 50% of Twitter’s volume of posts. Others have pointed out the issues with developing a more than razor-thin understanding of consumer mindsets and preferences based on social media data. What does a Facebook “Like” mean, exactly? If you “like” Coca-Cola on Facebook, does it mean that you like the product or the company? And does it necessarily mean you don’t like Pepsi? And what is a “like” worth? Nobody knows.

This is where we come in. We at Ranker have developed a very good answer to this issue: the “opinion graph”, which is a more precise version of the “interest graph” that advertisers are currently using.

Ranker is a popular (top 200 website, 18 million unique visitors and 300 million pageviews per month) that crowdsources answers to questions, using the popular list format.  Visitors to Ranker can view, rank and vote items on around 400,000 lists. Unlike more ambiguous data points based on Facebook likes or twitter tweets, Ranker solicits precise and explicit opinions from users about questions like the most annoying celebrities, the best guilty pleasure movies, the most memorable ad slogansthe top dream colleges, or the best men’s watch brands.

It’s very simple: instead of the vaguely positive act of “liking” a popular actor on Facebook, Ranker visitors cast 8 million votes every month and thus directly express whether they think someone is “hot”, “cool”, one of the “best actors of all-time”, or just one of the “best action stars”. Not only that, they also vote on other lists of items seemingly unrelated to their initial interest: best cars, best beers, most annoying TV shows, etc.

As a result, Ranker has been building since 2008 the world’s largest opinion graph, with 50,000 nodes (topics) and 20 million edges (statistically significant connections between 2 items). Thanks to our massive sample and our rich database of correlations, we can tell you that people who like “Modern Family” are 5x more likely to dine at “Chipotle” than non-fans, or people who like the Nissan 370Z also like oddball comedy movies such as “Napoleon Dynamite” and “Big Lebowski”, and TV shows such as “Dexter” and “Weeds”.

Our exclusive Ranker “FanScope” about the show “Mad Men” lays out this capability in more details below:

Mad Men Data

How good is it? Pretty good. Like “ we predicted the outcome of the World Cup better than Nate Silver’s FiveThirtyEight and Betfair” good.

Our opinion data is also much more precise than Facebook’s, since we not only know that someone who likes Coke is very likely to rank “Jaws” as one of his/her top movies of all time, but we’re able to differentiate between those who like to drink Coke, and those who like Coca-Cola as a company:

jaws chart

We’re also able to differentiate between people who always like Pepsi better than Coke overall, and those who like to drink Coke but just at the movie theater:

  • 47% of Pepsi fans on Ranker vote for (vs. against) Coke on Best Sodas of All Time
  • 65% of Pepsi fans on Ranker vote for (vs. against) Coke on Best Movie Snacks

That’s the kind of specific relationship you can’t get using Facebook data or Twitter messages.

By collecting millions of discrete opinions each month on thousands of diverse topics, Ranker is the only company able to combine internet-level scale (hundreds of thousands surveyed on millions of opinions each month) with market research-level precision (e.g. adjective specific opinions about specific objects in a specific context).

We can poll questions that are too specific (e.g. most memorable slogans) or not lucrative enough (most annoying celebrities) for other pollsters. And we use the same types of mathematical models to address sampling challenges that all pollsters (internet or not internet based) currently have, working with some of the world’s leading academics who study crowdsourcing, such as our Chief Data Scientist Ravi Iyer, and UC Irvine Cognitive Sciences professor Michael Lee.

Our data suggests you won’t be dropping gallons of iced water on your face over it. But if you’re a marketer or an advertiser, we predict it’s likely you will want to pay close attention.

by   Ranker
Staff
in Opinion Graph

The Best Possible Answers To Opinion-Based Questions

Ranker, as an openended platform for ranking people/places/things, is a lot of different (awesome) things to different people. But the overarching goal for Ranker has always been to provide the best possible answer to opinion-based questions like “What are the best _____?”

Popular sports and entertainment vote lists often grow into being a great answer within 12-72 hours as they get lots of traffic quickly, but the majority of Ranker lists take 1 – 3 months to build to full credibility as visitors on Ranker and from search engines find them and shape them with votes and re-ranks.

I thought it would be fun to showcase some Ultimate Lists and Vote Lists in other categories that haven’t gone viral, but through the participation of lots of Rankers over a few months have indeed become “the best possible answer” to this question.

Food

You all clearly love to weigh in on the start of the day, and the 5 o’clock hour:

Best Breakfast Cereals

The Best Cocktails

But you also have strong opinions on hydration during the day:

Best Sodas (and for the more calorie-conscious among you The Best Diet Sodas)

And even specific Gatorade flavors (thanks for the list Lucas)

Snacking, whether it be on a particular type of cheese, candy bar, or even as granular as a specific Jelly Belly flavor (thanks for the list Samantha but what’s with all the chocolate pudding haters?)

Dining out, specifically at Italian chain restaurants

A list I am not authorized to vote on, pregnancy cravings

And hundreds more, including perhaps a new category entirely – food nostalgia (I do miss those Crispy M&Ms myself)

Fashion/Beauty

Not categories that I personally check up on much, so I was psyched to see quite a few solid rankings here, some of them high-end but mostly stuff you can find at the mall:

Best women’s shoe brands

Best denim brands

Top handbag designers

Fashion Blogs

Sulfate-free shampoos

And even a men’s facial moisturizers list (have only tried 3 or 4 myself, but agree with their relative positions on the list)

Travel

Rankers, I know from a number of you that as we’ve been adding datasets of “rank-able objects” over the last year, one of the most-requested ones that we don’t yet have is hotels/resorts. Trust me, it’s still on the list. But in the meantime, it’s been heartening to see how many of you have participated in these great resources for travel destinations and attractions, like these:

Best US cities for vacations

Honeymoon destinations

Coolest cities in America

Theme parks for roller coaster addicts

And my personal faves, “bucket lists” of the world’s most beautiful natural wonders and historical landmarks.

Great stuff – these lists and 1000s more like them are true testimonials to the “wisdom of crowds”. Thanks, crowds!

by   Ranker
Staff
in Opinion Graph

The Best Possible Answers To Opinion-Based Questions

Ranker, as an openended platform for ranking people/places/things, is a lot of different (awesome) things to different people. But the overarching goal for Ranker has always been to provide the best possible answer to opinion-based questions like “What are the best _____?”

Popular sports and entertainment vote lists often grow into being a great answer within 12-72 hours as they get lots of traffic quickly, but the majority of Ranker lists take 1 – 3 months to build to full credibility as visitors on Ranker and from search engines find them and shape them with votes and re-ranks.

I thought it would be fun to showcase some Ultimate Lists and Vote Lists in other categories that haven’t gone viral, but through the participation of lots of Rankers over a few months have indeed become “the best possible answer” to this question.

 

Food: you all clearly love to weigh in on the start of the day, and the 5 o’clock hour:

Best Breakfast Cereals

The Best Cocktails

But you also have strong opinions on hydration during the day:

Best Sodas (and for the more calorie-conscious among you The Best Diet Sodas)

And even specific Gatorade flavors (thanks for the list Lucas)

Snacking, whether it be on a particular type of cheese, candy bar, or even as granular as a specific Jelly Belly flavor (thanks for the list Samantha but what’s with all the chocolate pudding haters?)

Dining out, specifically at Italian chain restaurants

A list I am not authorized to vote on, pregnancy cravings

And hundreds more, including perhaps a new category entirely – food nostalgia (I do miss those Crispy M&Ms myself)

 

Fashion/Beauty: not categories that I personally check up on much, so I was psyched to see quite a few solid rankings here, some of them high-end but mostly stuff you can find at the mall:

Best women’s shoe brands

Best denim brands

Top handbag designers

Fashion Blogs

Sulfate-free shampoos

And even a men’s facial moisturizers list (have only tried 3 or 4 myself, but agree with their relative positions on the list)

 

Travel: Rankers, I know from a number of you that as we’ve been adding datasets of “rank-able objects” over the last year, one of the most-requested ones that we don’t yet have is hotels/resorts. Trust me, it’s still on the list. But in the meantime, it’s been heartening to see how many of you have participated in these great resources for travel destinations and attractions, like these:

Best US cities for vacations

Honeymoon destinations

Coolest cities in America

Theme parks for roller coaster addicts

And my personal faves, “bucket lists” of the world’s most beautiful natural wonders and historical landmarks.

Great stuff – these lists and 1000s more like them are true testimonials to the “wisdom of crowds”.  Thanks, crowds!