Today, the startup, which launched in August 2010, is also announcing the general availability of AdGrok to users. AdGrok’s web-based platform allows small businesses purchase contextual keywords on Google AdWords, without the cost of a SEM agency’s work. The SaaS suggests keyword buys, carries them out, and then collects and displays stats about their performance. AdGrok essentially becomes a business’ interface to AdWords, replacing Google’s platform with a more user-friendly software.
AdGrok’s “GrokBot” will crawl a website looking for product pages. When it finds one, it builds the AdWords campaign structures in order to send traffic to that page, generates keywords for that product, and builds text ads from a template library to accompany the keywords specific to that product.
Grok-O-Matic allows companies to import their entire product catalog on AdWords. And companies can find poor performing keywords or a compelling text ad that everyone likes to click on via Groknoculars.
AdGrok’s platform includes deep analytics, including how much traffic businesses are seeing from a keyword or how a text ad is doing, how much it costs, and how much revenue they’re making. AdGrok’s technology will also evaluate a company’s campaign for ways it can be improved and presents these actionable insights and recommendations to users.
AdGrok also offers an agency-like product called GrokMe, in which a Google Certified Professional will do all the set-up and daily management of a business’ Google AdWords account, and they’ll get a weekly report with their campaign’s performance.
The startup’s founder Antonio Garcia-Martinez says that he wants AdGrok, which faces competition from Clickable, to be the TurboTax of search engine marketing and keyword bidding. AdGrok’s platform has evolved since we its launch, now offering both a self-serve and a agency-like offering and now appeals to both small and large businesses.
MyBuys builds profiles based on individual shoppers’ behavior, and then uses a patented portfolio of algorithms and real-time optimization to deliver the most relevant recommendations to them. The company says over 300 online retailers, brand and agencies currently partner with them to offer personalized recommendations to their shoppers.
The company recently launched predictive display advertising and personalized mobile commerce solutions, enabling clients to optimize the shopping experience for individuals using the iPhone, the iPad, Android or BlackBerry devices.
MyBuys is so certain that it can create a better-performing personalized mobile website for retailers that they let them test the performance of the solution free of charge. The creation of the mobile site comes without implementation fees if MyBuys’ mobile site doesn’t perform better than their current websites.
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.
Google and Microsoft, tech giants embroiled in a competitive battle that has spanned many years and will continue to rage for many years to come, have teamed up to take down a Texas-based patent troll’s geotagging patent that they claim has been used in lawsuits against more than 300 companies, many of which are their customers or partners.
The news was first reported yesterday by The Times Of India as far as I can tell.
The defendant in the case, geo-location technology provider GeoTag, is trying to make coin from its US Patent, No. 5,930,474, entitled “Internet organizer for accessing geographically and topically based information”.
The patent was originally applied for in 1996 and granted in 1999. Microsoft and Google, who fear for their respective online mapping services to get targeted as well, claim there was prior art at the time of filing that the USPTO did not care to take into account.
GeoTag reportedly paid a whopping $119 million to obtain the patent.
The patent has, however, “changed ownership at least five times,” with the current owner headed by one of the patent inventors, according to the complaint. GeoTag, meanwhile, is plotting an IPO and has filed documents with the SEC to sell shares at $6.25 each.
Microsoft and Google seek to invalidate the applicable patent, prove that the technology is not used in Google Maps or Bing Maps, but also pleaded for a judge to order GeoTag to stop suing so many of its customers and partners over their store locator services.
Let’s hope the patent troll loses, big time.
Patents should be used to protect companies that produce actual, innovative products and services, not to make greedy people behind non-practicing entities enormously wealthy without them ever producing anything, let alone selling a product or service to anyone.
Way back in December 2007, Google began to roll out a new centralized Profile feature that allows users to establish their own public online profile, complete with a short bio and links to personal sites. They were mostly useless (you never really saw them), until 2009 when Google began incorporating them into search results (run a query for someone’s name, and their Google Profile has a good chance of popping up). Which is a nice feature, but there’s been one problem: Google profiles are just plain ugly.
Open up a profile with the existing design and you’ll see a poorly-organized smattering of links, a bio, and maybe a map — sort of like a personal homepage someone might have set up in 1998. They’re not difficult to read, but compared to the social networks profiles we’re all used to, they’ve never felt personal or social in the slightest. But now Google is looking to change that.
In a post on the Google Social Web blog, Google has announced that it’s giving Profiles a face lift. And, judging by the photos, it looks like it’s decided to adopt an interface that’s more in line with the social networks we’re all used to — like Facebook. User photos are now more prominently seen in the upper left hand side of the page, and content is presented in a larger right column, broken up by section (employer, education, and so on).
Granted, it’s not an exact clone of Facebook — and countless sites have adopted a similar layout — but the similarity helps make the profiles feel inherently more social. And the timing isn’t a coincidence: the profiles will likely play some role in Google’s +1 social initiative, whatever form that eventually takes.
Y Combinator-backed AdGrok has raised $470,000 in angel funding from Chris Sacca, Russ Siegelman, Ben Narasin, TriplePoint Capital and Y Combinator.
