Incentives Work: Microsoft Seeing Positive Results from Cashback Program; Partners with Shopping Cart Providers

Incentives Work: Microsoft Seeing Positive Results from Cashback Program; Partners with Shopping Cart Providers

It’s easy to pick on Microsoft. It’s practically a national pastime at this point. So when they announced their Cashback program to help grow Live Search, the snears came fast and furious.

“You have to pay people to search?” they said.

Turn your laughter into claps, people. It turns out that Cashback is working. Microsoft is seeing positive results on three goals it said it would report. They are:

• Number of offers in the system
• Advertiser return on investment (ROI)
• Percentage of commercial search queries as measured by comScore

There’s been a 30% increase in the number of products offered via Cashback. 4.5 million unique users per month are generating 68 million commercial queries. eBay has seen an increase of 50% on their ROI.

“We believe this early traction speaks to the differentiated and unique value proposition of Microsoft Live Search cashback for both consumers and advertisers, especially in these tough economic times,” said Brad Goldberg, general manager of Microsoft Live Search.

Is it really any surprise that incentives work? No. Have you ever been listening to the radio and they’re having a $1,000 giveaway? You have to be listening at the right times to call in.

Incentives are nothing new. Microsoft was smart to implement them into Live Search. People don’t necessarily use Google because it’s any better but because it’s familiar. Live Search needs a way to get people searching, and Cashback is working to help accomplish those goals.

That may be why Microsoft is expanding Cashback by partnering with shopping cart providers Miva Merchant, Early Impact Inc. (ProductCart) and 3DCart. Through the agreement, merchants who use the shopping carts are eligible for Cashback.

Google Discusses Search Evaluation Process

Google Discusses Search Evaluation Process

Google had been doing a series of posts about search quality. Today, the latest post in the series discusses how evaluation enters into the the process.

Scott Huffman, Engineering Director, gave four insights into the nuances of difficulty experienced in search evaluation:

• First, understanding what a user really wants when they type a query — the query’s “intent” — can be very difficult. For highly navigational queries like [ebay] or [orbitz], we can guess that most users want to navigate to the respective sites. But how about [olympics]? Does the user want news, medal counts from the recent Beijing games, the IOC’s homepage, historical information about the games, … ? This same exact question, of course, is faced by our ranking and search UI teams. Evaluation is the other side of that coin.
• Second, comparing the quality of search engines (whether Google versus our competitors, Google versus Google a month ago) is never black and white. It’s essentially impossible to make a change that is 100% positive in all situations; with any algorithmic change you make to search, many searches will get better and some will get worse.
• Third, there are several dimensions to “good” results. Traditional search evaluation has focused on the relevance of the results, and of course that is our highest priority as well. But today’s search-engine users expect more than just relevance. Are the results fresh and timely? Are they from authoritative sources? Are they comprehensive? Are they free of spam? Are their titles and snippets descriptive enough? Do they include additional UI elements a user might find helpful for the query (maps, images, query suggestions, etc.)? Our evaluations attempt to cover each of these dimensions where appropriate.
• Fourth, evaluating Google search quality requires covering an enormous breadth. We cover over a hundred locales (country/language pairs) with in-depth evaluation. Beyond locales, we support search quality teams working on many different kinds of queries and features. For example, we explicitly measure the quality of Google’s spelling suggestions, universal search results, image and video searches, related query suggestions, stock oneboxes, and many, many more.

Not sure if I’m buying that Olympics example. Google didn’t do a great job with the Beijing Olympics, and surely their algorithm could handle serving up more relevant search results during the time surrounding the event.

I’m not saying that search query intent evaluation is easy, just that the Olympics query is not quite as problematic as Google is making it out to be.

The rest of the points are things we’ve been hearing from Google for a long time. We know they’re progressing on universal and personalization search efforts, all in their famous intent to create the best user experience.

So, what methods does Google employ to address these evaluations? Huffman offered up the following:

• Human evaluators. Google makes use of evaluators in many countries and languages. These evaluators are carefully trained and are asked to evaluate the quality of search results in several different ways. We sometimes show evaluators whole result sets by themselves or “side by side” with alternatives; in other cases, we show evaluators a single result at a time for a query and ask them to rate its quality along various dimensions.
• Live traffic experiments. We also make use of experiments, in which small fractions of queries are shown results from alternative search approaches. Ben Gomes talked about how we make use of these experiments for testing search UI elements in his previous post. With these experiments, we are able to see real users’ reactions (clicks, etc.) to alternative results.

What do you think of Google’s search evaluation? What evaluations would you like to see them conduct? Discuss in the comments.

Searching Rich Media at TechCrunch50

Searching Rich Media at TechCrunch50

Video search has been a key topic at the TechCrunch50 show in San Francisco. Lots of newly launched companies presented (kind of like DEMO minus the payola). In a “rich media” grouping of companies, the proverbial challenge of making images and video searchable kept coming up.

Presenting companies were
• VideoSurf: video search
• GazoPa: image search
• Fotonauts: image search
• Bojam: online music collaboration (like garage band in the cloud)

On the panel of judges was Bradley Horowitz who was a key part of Yahoo’s acquisition of Flickr back in 2005. Now he in charge of Google Gadgets and recently oversaw the integration of facial recognition software in Picassa.

“For a number of years I worked at MIT on image recognition technology and the first time I saw Flickr, I wanted to rip up my diploma,” he said from the stage. “It turns out humans are very good at this. You don’t need a hyper-technical solution. It can sometimes be the activity around the video, not the content in the video that defines relevance.

This point underscores many of the companies walking different lines between algorithmic solutions and user interaction/tagging in order to solve this longstanding indexing issue.

For the sake brevity, I’ll just talk about the best one I saw — San Mateo, Calif based video search engine VideoSurf. CEO Lior Delgo agrees that users should be brought into the mix but asserts that relying on this alone is flawed.

The company still got Horowitz’ vote for its underlying technology, which includes a great deal of intellectual property around visual recognition. This is paired with some social features that together make it a viable choice for video search over and above existing engines like Truveo and Blinkx.

The technology essentially goes beyond the voice recognition, meta data, and surrounding content that many existing sites rely on, and instead tags each frame with more granular information. This includes character names in popular shows and other things that are more contextually relevant and likely as search terms. Relevancy is weighed on frequency of these keywords, click throughs and a few other factors.

This could also be the right time for this technology, given the expanding corpus of video being brought online. This isn’t just the long tail YouTube ranks but head content that will get more search queries such as network shows on sites like Hulu. Lots more to the nuts and bolts, and it’s clear video search will continue to be a tough nut to crack. But this will be one to watch.

I hope to dive deeper in a column later this month on this and the many other search related companies here — including a social network for bird watchers (seriously).

An Introduction To Advanced SEO Techniques

This website is a hard-hitting guide that gives you the information you need to make the adjustments to your site right away to help improve your search rankings and benefit from the increase in organic search traffic. Read more

An Introduction to Google Search Quality

Posted by Udi Manber, Google VP Engineering, Search Quality

Search Quality is the name of the team responsible for the ranking of Google search results. Our job is clear: A few hundreds of millions of times a day people will ask Google questions, and within a fraction of a second Google needs to decide which Read more

Search Engines and How They Work

Search Engines are special sites on the Web that are designed to help people find information stored on other sites. Read more