The question keeps being raised about the business value of social media tools. As we work with facebook, twitter, yammer etcetera - what value are we driving? I just got a free book on search engine interfaces, through twitter. If I was not on Twitter, I would not have this interesting book to read months prior to publication. Imagine that these networked tools did not exist. So I can only interact with the people near me, in close physical proximity. I talk to people in Cleveland. I sell to the people in Cleveland and I learn from the schools in Cleveland. I'm doing pretty well for myself. Someone I know tells me - you should go to New York, they have more people, and more opportunities to sell, and more clubs, more museums, more of everything. Is it worth it? What business value will I gain from going to New York?
Until I go to New York, I cannot understand the difference in scale. Once there, I see many different distractions - shows, plays, clubs, museums, what have you. But there is also much more opportunity there. I think social networking tools are like New York - if you are there, you can't understand why anyone would not be there. If you are not there, you really can't see why anyone would want to be there.
Yes, there is a lot of non-work related things that happen on these tools. There is a lot of non-work related things that happen in the office, from the water cooler conversations to the quick coffee run. But if you are not taking part in the conversation, you will miss the serendipitous moments that happen because you are part of the conversation. Like when a water cooler conversation leads to a new idea or a shorter process. Similarly there are things that happen in Twitter or Facebook that will add value.
This is only a half formed analogy, comments are welcome and needed. Anyway, I need to get back to work.
Wednesday, July 1, 2009
Tuesday, May 12, 2009
The burger joint and the mini
So, the burger joint. It is a hotel restaurant done up to be a small hole in the wall place. They got the atmosphere right, and the burgers were great. What made this the best dinner I have ever had in NY though, was the company. Because the place is small, recently reviewed in the New York Times - it was packed. I ended up sharing the table with a couple who had been married for 32 years, but were now divorced, and a girl from Long Island now living in the city. This random meeting of total strangers made the dinner great fun. The burger was good, but the company was better.
The mini surprised me. I have not played with one before, since our local Apple store would have to order one for me. It was fast. It did not bog down playing two movies, one in HD and one in SD. Each application opened quickly, ran smoothly and was very responsive. Even with iTunes playing music and the HD movie running. All on 2 GB of RAM and a 2.0 ghz processor.
Something on this Mac was configured differently, and it had a right click on the mouse. Not sure how, since the whole top moves, but if you push on the left it reads a left click, right reads a right click.
I think I may bite the bullet and finally buy a Mac. Only a couple decisions left to make. I need to decide if I want the wireless Apple keyboard, or if I should go with the Logitech dNovo keyboard with the built in click wheel. And, do I want to put in the 4 GB right away or wait till I need a speed boost? Apple RAM is a rip off, but the thing is hard to open.
The mini surprised me. I have not played with one before, since our local Apple store would have to order one for me. It was fast. It did not bog down playing two movies, one in HD and one in SD. Each application opened quickly, ran smoothly and was very responsive. Even with iTunes playing music and the HD movie running. All on 2 GB of RAM and a 2.0 ghz processor.
Something on this Mac was configured differently, and it had a right click on the mouse. Not sure how, since the whole top moves, but if you push on the left it reads a left click, right reads a right click.
I think I may bite the bullet and finally buy a Mac. Only a couple decisions left to make. I need to decide if I want the wireless Apple keyboard, or if I should go with the Logitech dNovo keyboard with the built in click wheel. And, do I want to put in the 4 GB right away or wait till I need a speed boost? Apple RAM is a rip off, but the thing is hard to open.
Enterprise Search Summit 2009
Attendance is way down, the economy seems to be hitting this event very hard. I am not able to blog from the conference itself as the wireless is very flaky and there are not many places to plug in. This is the first time I have seriously considered the need for a netbook. Something very small, with a very long battery life would be helpful right now.
I'm heading out now to try the Burger Joint at Le Parker Meridian, then maybe off to the Apple store to look at the Mini again.
I'm heading out now to try the Burger Joint at Le Parker Meridian, then maybe off to the Apple store to look at the Mini again.
Search, Scent and the Happiness of Pursuit
Jared Spool gave a key note on search and e-commerce. There were a number of interesting points he made. In his studies of e-commerce sites, he found that the most successful sites, used search the least. Search is our tool to be used when navigation fails. Improving the "scent" of the links on the main page, or within the navigation hierarchy, will decrease the need to use search.
UIE collects 2000 pieces of data per participant. In their studies they found that the #1 predictor of success was the # of pages the user visited between the home page and the sales cart. Fewer pages led to greater success. The best way to improve scent is to build the trigger words into the link titles, or the description of the tool. To find the trigger words, examine the search logs - those words are the words the users are scanning the pages to find. Referring again to his studies, he found that no one only went to search. Everyone started by scanning the page, looking for categories or links that contained the trigger words. They only went to search when nothing could be found.
An interesting point he made, if you can follow the users click path and know when they leave the page through search, then you can know when the trigger words dried up. Adding a link on that page that takes the user to the search term will increase success for that one trigger word.
Search works well for known item location. So it is easy to find "The Princess Bride" or "Tom Clancy". Search does not work well for less concrete items like "an inexpensive yet high quality SLR" or "Novels written by Nobel Prize for Literature authors". To solve this issue he recommends using editorial capability to improve content finability.
Looking at 77 installed versions of search engines on e-commerce sites, the same vendors that were the best, were also the worst. The difference is the implementation, not the technology. Focus on doing a good job on configuring the installation.
UIE collects 2000 pieces of data per participant. In their studies they found that the #1 predictor of success was the # of pages the user visited between the home page and the sales cart. Fewer pages led to greater success. The best way to improve scent is to build the trigger words into the link titles, or the description of the tool. To find the trigger words, examine the search logs - those words are the words the users are scanning the pages to find. Referring again to his studies, he found that no one only went to search. Everyone started by scanning the page, looking for categories or links that contained the trigger words. They only went to search when nothing could be found.
An interesting point he made, if you can follow the users click path and know when they leave the page through search, then you can know when the trigger words dried up. Adding a link on that page that takes the user to the search term will increase success for that one trigger word.
Search works well for known item location. So it is easy to find "The Princess Bride" or "Tom Clancy". Search does not work well for less concrete items like "an inexpensive yet high quality SLR" or "Novels written by Nobel Prize for Literature authors". To solve this issue he recommends using editorial capability to improve content finability.
Looking at 77 installed versions of search engines on e-commerce sites, the same vendors that were the best, were also the worst. The difference is the implementation, not the technology. Focus on doing a good job on configuring the installation.
Emergent Social Search Experiences
This was a moderated panel discussion around social search. The panel discussed the definition of social search, why to do it and how.
They defined social search as social tagging.
You do it because it enhances the findability of an object.
There is a psychological burden of asking a question within an organization. "Didn't we hire you to know that?" There is also a cognitive load on asking and posting within an organization as people take the time to format the question well. People don't share because they don't want to tip their hand.
The Steve museum project explores leveraging social tagging to help identify and find art. They build the tools internally, but examples are on the web at www.steve.museum.com. They included a statistical analysis tool set to help tell when tags were useful. They found that the tags were useful for 80% of the time.
In a study with ACM, they found that when authors post tags themselves, they are precise but they are not very broad. They recycled the authors tags, added them to a pseudo controlled vocabulary and found more use of the tags that were created, and more tagging on the documents as a whole. Providing the leverage to reuse the tag, increased the usage of the tags. People saw the reuse as a value, giving them a reason them to tag in the first place.
In the Steve museum project, they had a two part study where some users know that they are helping an organization and others did not see a connection to a organization. The users who knew and saw the value they were adding were more than twice as likely to help.
Vendors:
ConnectBeam seems to have closed. They discussed it as a good product, but there does not seem to be any new products, and people have left the firm.
"Knowledge Plaza is interesting." No other data given on the product.
Arrdvark - ask a question, be routed to someone to answer it. Most of the QA is private.
Hunch is a system to find previous questions.
Panel sees these tools as a way to pull tacit knowledge from users.
They defined social search as social tagging.
You do it because it enhances the findability of an object.
There is a psychological burden of asking a question within an organization. "Didn't we hire you to know that?" There is also a cognitive load on asking and posting within an organization as people take the time to format the question well. People don't share because they don't want to tip their hand.
The Steve museum project explores leveraging social tagging to help identify and find art. They build the tools internally, but examples are on the web at www.steve.museum.com. They included a statistical analysis tool set to help tell when tags were useful. They found that the tags were useful for 80% of the time.
In a study with ACM, they found that when authors post tags themselves, they are precise but they are not very broad. They recycled the authors tags, added them to a pseudo controlled vocabulary and found more use of the tags that were created, and more tagging on the documents as a whole. Providing the leverage to reuse the tag, increased the usage of the tags. People saw the reuse as a value, giving them a reason them to tag in the first place.
In the Steve museum project, they had a two part study where some users know that they are helping an organization and others did not see a connection to a organization. The users who knew and saw the value they were adding were more than twice as likely to help.
Vendors:
ConnectBeam seems to have closed. They discussed it as a good product, but there does not seem to be any new products, and people have left the firm.
"Knowledge Plaza is interesting." No other data given on the product.
Arrdvark - ask a question, be routed to someone to answer it. Most of the QA is private.
Hunch is a system to find previous questions.
Panel sees these tools as a way to pull tacit knowledge from users.
Search Analytics
This presentation was an interesting overview of leveraging your metrics to help improve search and the overall web site. Lou spoke to working with metrics from the bottom up and from the top down.
Bottom up, he suggests, is working with the information and asking questions. Do not get caught up in specific statistical analysis methods, instead just look at the metrics and see what questions you have. Examples of these are:
- What are the most frequent search queries?
- What are the most frequent results clicked on?
- Which pages are referring the most queries?
- Which pages are launching the most 0 hit queries?
He suggested that you should look at your search results to create better metadata. This involves looking at your top 50 to 100 queries, developing a set of categories that these queries might fall into, then seeing what percentage of your queries fall into each category. Once you have the values for the categories, you can also look at the attributes.
You can also scan your data for content types that people are searching for. If you track this data over time, you begin to see the seasonally of the queries and the adaptations that the enterprise makes to its environment.
He suggests digging deeply into the failure states, specifically for the pages within the site that are not working. Look for where the *content* is failing as well as where the search is failing.
His last suggestion was to leverage your best bets to become a A-Z listing for the site. He showed an example from the University of Michigan where the list was of the terms the best bets were created, paired with the best bets. Seems a simple, quick win.
Top Down is the process of thinking about the larger business issues and seeing what the metrics can tell us about them. So if the bottom up is thinking about the most common queries, top down would be the question "can users find the items they are looking for, with these top queries?" His actual example was e-commerce conversion for the top queries.
The slide deck will be available at SlideShare.net, but here is a similar one from a few years ago
Bottom up, he suggests, is working with the information and asking questions. Do not get caught up in specific statistical analysis methods, instead just look at the metrics and see what questions you have. Examples of these are:
- What are the most frequent search queries?
- What are the most frequent results clicked on?
- Which pages are referring the most queries?
- Which pages are launching the most 0 hit queries?
He suggested that you should look at your search results to create better metadata. This involves looking at your top 50 to 100 queries, developing a set of categories that these queries might fall into, then seeing what percentage of your queries fall into each category. Once you have the values for the categories, you can also look at the attributes.
You can also scan your data for content types that people are searching for. If you track this data over time, you begin to see the seasonally of the queries and the adaptations that the enterprise makes to its environment.
He suggests digging deeply into the failure states, specifically for the pages within the site that are not working. Look for where the *content* is failing as well as where the search is failing.
His last suggestion was to leverage your best bets to become a A-Z listing for the site. He showed an example from the University of Michigan where the list was of the terms the best bets were created, paired with the best bets. Seems a simple, quick win.
Top Down is the process of thinking about the larger business issues and seeing what the metrics can tell us about them. So if the bottom up is thinking about the most common queries, top down would be the question "can users find the items they are looking for, with these top queries?" His actual example was e-commerce conversion for the top queries.
The slide deck will be available at SlideShare.net, but here is a similar one from a few years ago
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