Social media is failing, now what?

Is social media not the panacea people make it out to be? Or is it a case of “you’re doing it wrong”?

TechCrunch published an article[1] recently describing the results of a survey a German market research firm conducted. The survey found that by and large, social media projects (think Twitter campaigns, Facebook pages, attempts at viral videos on YouTube) fail. Now it’s not clear from the survey what “fail” is meant and which metrics were used to gauge success or failure, but I’m sure those in the industry can judge by their gut that for the most part, enterprise forays into social media have been busts.There are some great comments on the TechCrunch site by some astute readers who in some form or another, hit the nail on the head. Here’s a sampling of my favourites:Martin Edic: “Most of this ‘marketing’ is a knee-jerk reaction to the question ‘why aren’t we in social media?’”

Jenni: “Reputation management is just one small branch of social media.”

Hazel Nieves: “Worst of all is the many ‘professionals’ in the roles of marketing and PR who have no clue on how to create and execute 21st century marketing. They are simply playing the role to keep their jobs.”

Alvin Tan: “Using social media as a broadcaster/megaphone is sub-optimal.”

Matthew: “I have yet to meet a social media whizz who can speak in depth about measurement, nor have I yet to meet a social media expert who has come from an engineering background, or who has been involved in any sort of actual architecting, delivery and running of platforms, or applications.”

Each of these comments sums up why Repustate started and why its doing things differently than others in the field. Here are the biggest problems from our point of view:

1) There is too much douche-baggery in the social media business. Everybody is a guru, yet nobody can produce quantifiable results to justify the promotion they granted upon themselves.

2) The tools needed to measure social media effectiveness don’t exist yet (we’re working on it!). Imagine trying to analyze the effectiveness of your landing pages back in 1997 before Google Analytics. That’s where we are right now with social media measurement. Some companies are changing that [2], but we have a ways to go.

3) The current offerings to solve the above problems are so woeful it’s embarrassing. Basic sentiment analysis is being touted as the be-all-end-all. Being able to tell a brand that person X on Twitter just wrote something negative about them is useless. I’d want to know why it was negative. I’d want to know what I can do about it. In short, I want an actionable strategy. Imagine hiring an SEO consultant who after a couple thousand dollars came back and said, “OK, I’ve done the analysis, and your site is not optimized. Here’s my invoice.” You’d want to know *why* it wasn’t optimal. Are the title tags not relevant? Is the keyword density for your desired search terms too low? Is the markup poor?

It seems just like eCommerce was in the bad old days prior to proper SEO tools, A/B testing and the like, social media is still waiting to grow from its infancy. Repustate is aiming to give it the growth spurt it needs, but in the meantime, we all have to realize that social media is here to stay and an inability to extract value from it is a case of “you’re doing it wrong”.

[1] http://eu.techcrunch.com/2010/08/23/why-social-media-projects-fail-%E2%80%93-a-european-perspective/
[2] http://www.syncapse.com

Surprises in API usage

How a last minute, indifferent decision lead to our most popular API call.

Repustate’s mission statement is to become the world’s largest collection of natural language processing tools. To meet this challenge, we started out with a small set of API calls and are constantly adding and improving with each passing week. Internally, we developed a tool that extracted out the most important text from any web page. If you visit any site today, there’s usually some menu at the top, footer links on the bottom, maybe some ads on one side, perhaps links to other articles on the other side, and the main article down the middle. Often when data mining, you want what’s just right down the middle, the heart of the article.So we wrote a python script to do this. On a whim, we decided to expose this through our API as well. Wouldn’t you know it, clean-html is our most popular API call – by far. In fact, about 60% of all of our API calls are to clean-html, which suits us just fine, but it’s kinda funny. A throwaway decision ended up being our most popular feature.Just goes to show that what one man’s simple, utilitarian API call is another man’s invaluable data processing tool. We’re trademarking that last sentence.

How I almost got to skip my exam and get an A+ (and maybe $1 million)

I coulda been famous, I coulda been a contender.

A PDF came across our Twitter feed today (http://www.scribd.com/doc/35539144/pnp12pt – courtesy of @arnaudsj) and it reminded me of my favourite moment in undergrad. For those who think the PDF is tl;dr – I’ll summarize quickly. The researched who authored the paper believes he has found a proof to a very difficult problem in computer science for which there is a $1 million prize. For 30-40 years, the best minds in computer science and math have tried to solve this problem. Keep that in mind as I tell you my story.In my 3rd year of computer science at York University in Toronto, my algorithms professor, Eric Ruppert, was teaching us about P and NP. He then told us about the $1 million dollar prize for anyone who could either prove or disprove P == NP. He then threw this carrot out there: “And if anyone can solve it, they get an automatic A+ and get to skip the exam.” I was getting about a C+ at the time and did not look forward to the exam (with good reason, only 3 people passed it!)So I went home that night and tried to solve the problem. I don’t remember the details, but I came up with an algorithm that wasn’t polynomial in computation time and could minimize the time needed to traverse a graph (Travelling Salesman’s problem). I was so excited, I emailed my professor telling him I’ll be in his office the next day with good news.

The next day, I strode into his office, like Caesar returning from a victorious battle, expecting to accept my reward and for the crowds of computer science groupies to throw their bras at me. My professor laughed when I told him what I thought I had come up with. So he began to find a hole in my algorithm. A few minutes went by, and he still couldn’t find a hole. I saw that he began to get a little nervous. After what seemed like an hour, but was probably only 5 minutes, he *finally* came up with a scenario where my algorithm failed to find the correct solution and my dreams were dashed. No A+, no automatic deferral of the final exam, and no $1 million prize. But I almost reached the summit of algorithm proficiency. Alas, like George Costanza, I flew too close to the sun on wings of pastrami.