Adding a personalized signature to your emails is not only aesthetically pleasing, it’s also useful for advertising and gaining followers. Email signatures allow you to passively offer your contact information, website and social profiles to anyone you communicate with via email.
A Canadian-based startup has developed a Twitter tool called TwitFooter that displays tweets in the footer of your email signatures.
Users can setup TwitFooter to post either random tweets, the latest tweets, or just the Twitter bio. It works by copying a code from TwitFooter into the place you normally edit your email signature. It works without having to install any software, all you need to do is authorize it on Twitter.
If you’re a blogger or content creator this tool could be useful because TwitFooter will post your latest articles (through tweets) within every email you create. It also features statistics that track inbound clicks from emails.
TwitFooter is a free tool that supports Hotmail, Gmail, Yahoo, Outlook Express, Windows Mail and Outlook 2003 & 2007.
This post is made possible by Microsoft BizSpark as a new part of the Spark of Genius series that focuses on a new and innovative startup each day. Every Thursday, the program focuses on startups within the BizSpark program and what they’re doing to grow.
Your credit score carries significant weight in your financial life. Want to rent an apartment or buy a car? Good luck doing so with a bad credit score. The same logic applies to landing a job if you have a negative online reputation.
So says MyWebCareer, an early stage startup that has developed algorithms to run your “Career Score,” a credit check for your professional web persona. The service analyzes your Facebook profile, LinkedIn network, Twitter account and Google juice — evaluating more than 200 different variables in the process — and spits out a score between 350 to 850.
Where you fall could be an indicator of how employable you are and indicate your overall professional attractiveness.
Credit Check
Once you grant MyWebCareer access to Facebook and/or LinkedIn, the service works to retrieve employment history and searches Google for references to you in any of the positions you’ve claimed to have held. The startup is also running semantic analysis on your Facebook updates, checking out your Stack Overflow profile, if you have one, and factoring in your Klout score, among other things.
The resulting score — which remains private until you opt to share it publicly — is evaluated against your peers in three areas: your connectedness, professional online brand and internet search footprint. The service will highlight potentially offending status updates and make specific recommendations for how you can improve your score.
If a search query doesn’t bring up results, for instance, relating to past jobs, MyWebCareer will call your attention to these eyebrow-raising issues.
The public beta service, only having launched in February, is far from complete. Co-founders Greg Coyle and Nip Zalavadia say they want to make the Career Score as reflective of your online reputation as possible. This means they’ll continue to add data sources — like Quora once there’s a publicly accessible API — in the future.
The Credit Bureau of the Web?
If MyWebCareer’s calculation is meant to be a credit score for your digital life, then the startup aims to be like an Experian or Equifax.
This presents it with the challenge of convincing consumers, and eventually business users, that its score means something significant, beyond the novelty of the site itself. Because other startups also traffic in reputation management (Brand-Yourself) and online influence scoring (Klout), this will not be an easy sell.
In a month’s time, the startup has acquired more than 4,000 users, according to Coyle and Zavaladia. Not overly impressive numbers, and more interesting, perhaps, is that a significant subset of users are openly sharing their scores via Facebook or Twitter and helping to bring in new members — 20% of new users sign-up through this network effect.
In the product pipeline are new features that could better drive home the utility of the service. A premium version is slated for early April release and should offer the full breadth of everything that MyWebCareer evaluates for a small monthly or yearly fee.
Also in the works is an enterprise version that will allow employers to evaluate content without giving them direct access to a candidate’s Facebook or LinkedIn profile, says Coyle and Zalavadia. This will eventually be positioned as a recruitment tool that employers can use to discover potential talent with high Career Scores in certain industries.
So long as MyWebCareer can figure out what their score really means, it could have bright future. Employers are socially screening candidates and employees are more likely than ever to have blemished online records, so there is an audience for the product.
The Spark of Genius Series highlights a unique feature of startups and is made possible by Microsoft BizSpark, a startup program that gives you three-year access to the latest Microsoft development tools, as well as connecting you to a nationwide network of investors and incubators. There are no upfront costs, so if your business is privately owned, less than three years old, and generates less than U.S.$1 million in annual revenue, you can sign up today.
Editor’s note: This is a guest post submitted by Mahendra Palsule, who has worked as an Editor at Techmeme since 2009. Apart from curating tech news, he likes analyzing trends in startups and the social web. He is based in Pune, India, and you can follow him on Twitter.
What’s the Next Big Thing after social networking?
This has been a favorite topic of much speculation among tech enthusiasts for many years. I think we are already witnessing a paradigm shift – a move away from simple social sharing towards personalized, relevant content.
The key element of the next big thing is the increasing significance of the Interest Graph to complement the Social Graph. While Facebook, Twitter, and Google are already working on delivering relevant content, a slew of startups are focusing exclusively on it.
Relevance is the only solution to the problem of information overload.
The above matrix is a representation of how the process of online information discovery has evolved over time.
Phase I: The Search Dominated Web
This is how Google began its dominance over the web two decades ago, using PageRank to surface the most popular web pages as identified by other web pages that linked to them.
Phase II: Web 2.0 With Social Bookmarking
In the Web 2.0 era, social bookmarking services gained significant traction, surfacing popular content. Sites like Reddit and StumbleUpon are hugely popular even today, driving millions of page views.
Phase III: Personalized Recommendations
Services like Hunch, GetGlue, etc. have focused on building an Interest Graph for users, to deliver personalized recommendations using a ‘taste engine’.
Phase IV: Personalized Serendipity
The latest crop of startups is focusing on personalization using a combination of Interest and Social Graphs. Personalized Serendipity is what Jeff Jarvis calls ‘Unexpected Relevance’. Examples include Gravity, my6sense, Genieo, and TrapIt.
What Exactly Is Relevance?
The battle against information overload is sometimes presented as a choice between Relevance and Popularity, where ‘relevant’ is equated to ‘personalized’ as against popular.
However, Relevance does not always mean Personalized. Relevance is very dynamic – it depends on the needs of a person at a specific point in time. There are times when users want to know about the most popular stories, and other times when they seek personalized content.
There are multiple approaches to filtering information for Relevant Content. Google, Paper.li, and PostRank are examples of algorithmic filtering, while Reddit, Hacker News use a crowdsourcing approach. Klout can be used to filter Twitter streams by influence, while Facebook uses social affinity as a filter for its newsfeed and social signals for its new Comments Plugin. Location is another high-impact signal for delivering relevant content, gaining importance in a mobile world.
In other words, Relevance spans across all the quadrants of the Discovery Matrix above, and none of the above approaches to filtering for relevance is the ‘best approach’. There is no killer approach to Relevance. Henry Nothhaft, Jr., CMO of TrapIt, described it as “the myth of the sweet spot”. The competitive edge will be with services that support multiple discovery methods, multiple filtering approaches, have flexibility, and support multiple mobile platforms.
Quora: A Showcase Of The Interest Graph
Quora has pioneered the use of the Interest Graph as a dominant signal for its newsfeed. Quora asks new users to select Topics to follow, as part of its onboarding process, which is the first revelation that Topics are as important as Users to follow.
Quora’s newsfeed is an interesting showcase of what happens when you mix an Interest Graph with a Social Graph – and the result is the mysterious addictiveness so many have experienced, but found difficult to explain. An item pops up in your newsfeed not because you were following a user, but because you were following a related topic.
This often leads to Personalized Serendipity – or Unexpected Relevance – which is why Quora gets many people hooked.
The war over the Interest Graph began between Twitter and Facebook last year, as Erick described so eloquently. So how did Quora beat them to this game?
For starters, Quora is built from the ground-up with the Interest Graph being a backbone of the framework. Twitter’s ‘Browse Interests’ is too broad and primitive to be of use, even at present. And while Facebook has a mechanism for allowing publishers to push new items to your feed, most publishers have been unaware of this functionality.
The implications of a Relevance-driven web are wide-ranging and broad in scope. Better utilization of the Interest Graph by services will lead to better ad targeting, and a potential decrease in reliance on CPM/CPC-based advertising. Monetization focus will be on higher yields through transactions and subscriptions as Dave McClure once described. Online media publishers will focus on Relevance Metrics revealing engagement and time-spent on site, than primitive metrics like page views and traffic.
Social media may lose its obsession with follower numbers and traffic, evolving to context-driven reputation systems and algorithms.
Interest Graphs will be used to build Better Social Graphs. Today’s monolithic Interest Graph will get further specialized into Taste Graphs, Financial Graphs, Local Network Graphs, etc., yielding higher relevance for different needs.
Chris Boorman is the chief marketing officer and senior vice president of education & enablement at Informatica. He is responsible for Informatica’s global voice to the market, which includes corporate, partner and field marketing.
The thinking about social media in corporate marketing departments is rapidly evolving. Initially, social media was seen as yet another broadcast opportunity for pushing messages out into the world, and for many companies that view persists. A social media consultant recently said that even today, when he approaches potential clients for the first time, they typically refer him to their PR agency, because “they handle Facebook for us.”
There’s nothing wrong with using social media as a tool for disseminating marketing messages or trying to establish deeper relationships with current or potential customers. However, there is another use of social media which may prove to be more powerful over the long term: listening to the voice of the customer by data mining social networks.
Currently, CRM systems create customer profiles to help with marketing decisions using a combination of demographics and prior behavior, primarily historical buying patterns. These systems essentially enable companies to see their customers in the rearview mirror.
The customer data available via online communities like Facebook is both richer and more forward looking. A financial organization with access to such data would not only know that a customer had a checking account, savings account, two CDs and a mortgage, but also that the same customer was interested in golf or gourmet cooking — information that could be useful in planning future marketing initiatives. Every minute of every day, Facebook, Twitter and other online communities generate enormous amounts of this data. If it could be tapped, it could function like a real-time CRM system, continually revealing new trends and opportunities. Here’s how.
Tapping Social Media Data
The good news is that with today’s technology, this data can be tapped. But the process is not without its challenges. The data stream is a prime example of “Big Data.” Dealing with data sets measured in petabytes is a challenge in itself, and there is a serious problem with the signal-to-noise ratio. At my company, we estimate that at best, only 20% of the social media data stream contains relevant information. But before this problem even arises, companies face the issue of identifying their customers among the millions of participants in any given online community.
The Problem of Customer Identity
Most companies approach the problem of finding customers on social sites through the slow, arduous and expensive process of participating themselves. On Facebook, for example, businesses can gain access to the profiles of anyone who clicks the “Like” button on the company’s business site (depending on each customer’s privacy settings). With the right pitch, offer or game, companies can gradually gain an enhanced understanding of a subset of their social customer base.
With new matching technology that’s now available, the process is faster and more comprehensive. For example, matching technology uses artificial intelligence to figure out whether a given “John Smith” in a company’s customer database is the same individual as a particular John Smith on Facebook. The algorithms that accomplish this are extremely sophisticated, and they work. In fact, matching technology has been successfully used by law enforcement agencies to locate criminals.
If a company has one or two key pieces of information about its customers — e-mail address is often the most important — that company can accurately identify them on a social site and extract a substantial amount of data, including both profile data and transactional data that can reveal relationships important for marketing purposes. (Again, the amount of data available for any given customer depends on that customer’s personal privacy settings.)
Putting Data to Work
The second problem with social media is transforming data that is potentially useful into data that is actually useful. Social media data is generated by an entirely different technology stack than the transactional data that typically feeds CRM systems. Accordingly, it is stored in entirely different formats. That data can be transformed into a useful format with Master Data Management (MDM) technology.
MDM is the process of managing business-critical data, also known as master data (about customers, products, employees, suppliers, etc.) on an ongoing basis, creating and maintaining it as the system of record for the enterprise. MDM is implemented in order to ensure that the master data is validated as correct, consistent, and complete.
MDM has been used for more than a decade by companies that want to integrate disparate databases for a 360 degree view of their customers (or product portfolios, for that matter). It is equally effective in integrating social media data into existing CRM systems, and filtering that data for relevance.
What this all means is that companies can achieve important process improvements with bottom-line significance. For example, they can:
Obtain behavioral data that will allow them to more appropriately target segments for better marketing results.
Obtain data on personal preferences and interests to move closer to a true one-to-one relationship with their customers.
The disciplined use of demographic and historical customer data has enabled large numbers of companies to substantially increase the effectiveness of their marketing campaigns. Social media data will enable marketers to take targeting to the next level. It’s Big Data, but today’s technology can handle it.
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