Spin Valley Post

Twitter has announced some changes to their follower and following pages interface design and functions.

Now, when web users click to see lists of the people they follow or who follow them, they will see more information than just avatars and usernames. The new, improved pages contain full names, locations, most recent tweets, a one-click follow button, and a drop-down menu of possible actions, including @replies, DMs, and blocking.

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Without question, this feature is welcome and even overdue. We would actually have liked to see bios included in the available information. And we aren’t yet seeing any changes to the official Twitter mobile site. But, as the saying goes, you can’t always get what you want.

Here’s what the options look like for users you follow:

And here’s what they look like for users following you:

Also, you can browse through other users’ followers/following pages and exercise about the same list of functions:

Finally, users can toggle back and forth between a simple avatar/username list and the new, expanded list. The drop-down menu and follow buttons remain:

On our wishlist of Twitter improvements, getting more follower information was quite high, and this improvement does a bit to meet that need.

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This is one post/chapter in a serialized book called Startup 101. For the introduction and table of contents, please click here.

“It ain’t over till the fat lady sings” means that nothing happens until you get the signature on the contract. That is when the money gets wired. Deals often get derailed. They drift, and then nothing happens. Or a competitor comes in and snatches the prize from you. That is why a “closer,” someone who can seal the deal, is so prized.

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For enterprise systems, closing is a core competency. For Web ventures, you may need the skill less. But when you do need it (to raise money or win over a big strategic partner), you really need it. And you cannot delegate negotiating and closing. You can get advisors, but as the entrepreneur/CEO, you have to make the big calls. So, in this chapter we aim to distill a few libraries’ worth of books on negotiating and closing into a few points for the busy entrepreneur.

Four Points on Negotiation and Closing

1. Two ears, one mouth,
2. Wait until you hear them scream,
3. Use tension to your advantage,
4. Imagine the press conference.

Deals are deals. The deal could be securing an enterprise-wide contract for your software, raising a Series A VC round, selling your venture, or doing a big partnership deal. We tend to use the language of “buyer” and “seller” when discussing these four points, but they can apply to any kind of deal.

Two Ears, One Mouth

This is the simplest and most important sales lesson: listen. It also means keep quiet. No golden oratory, no gift of the gab, no persuasive speeches. Just listen to what the customer wants and let them reveal their needs and negotiating position. Then work out how to present what you have to meet those needs. Or decide that they are not the ones to focus on and move on to a better a prospect.

Silence is very awkward socially. We are all brought up to fill these awkward moments with some type of conversation. Good negotiators use silence to great advantage.

Let’s say you have just proposed a valuation to your investor. The investor looks at you with a blank stare. Time ticks by and you think your deal has gone south. You start to think, “Oh no, we blew it and started too high.” More time ticks by. You could stammer something about it “all being negotiable, of course” or just keep silent and wait for him to say something. It is, after all, his turn to speak, and he will probably say something.

When someone agrees with you, shut up. When the contract is about to be signed, shut up, or talk about the weather. You can derail a good deal by raising more issues than need to be raised.

It is a simple mantra: you have two ears and only one mouth. Use them accordingly. If in doubt, shut up!

Wait Until You Hear Them Scream

When I managed a six-person sales team selling financial trading systems on Wall Street, there was one guy who was consistently the best performer. He was also, by all other visible metrics, the worst salesperson. His presentations were rambling and verged on incoherent. His writing style would have given my old English teacher apoplexy. He was consistently abrupt, almost rude, to all concerned. He came in late, left early, and took long, expensive lunches.

I was really interested to find out what he was doing right. I do not believe that luck is a consistent reason for success. He must have been doing something really, really well, because everything visible he was doing was being done very badly.

I discovered that the thing he was doing right was qualifying his prospects with great care and discipline. We all know we should do that, but very few salespeople do it well at all. We think sales is all about hard work, persistence, determination, and all those other good Protestant work ethics. So, we drive relentlessly on, calling each prospect for the umpteenth time.

This guy on my team waited until he could see that a customer’s need was real and urgent. He waited till he could hear them scream. He then looked for an indicator that we had an edge in the deal, some unfair advantage.

His laziness was a bit of an act. In reality, he was a tireless networker. That is what all those long, expensive lunches were about. However, he worked to create a sense of equality among, and respect for, his customers. Salespeople are usually all too ready to get on their knees for that all-powerful buyer or investor with the big budget or fund. The buyer does not respect that salesperson and will ignore five of their calls, assured he will get another one.

Yes, it is a bit of a power game. The game is easy to play if you work for its most powerful player. But it is hardest to play when times are tough and you are behind in your revenue targets, or when your venture is running out of cash.

One way of checking for urgency is to see how much effort the prospect is putting into your relationship. You have to be able to see some equality of effort. Calling five times before the prospect returns your call is not equality. If you send reams of information and give multiple presentations, but the prospect won’t fill in a detailed requirements questionnaire, that is not equality of effort. With every call, you want the prospect to do something. If this does not happen, then they are not screaming loud enough, and you should move on to your next opportunity.

Make sure you have a live one by waiting for them to scream. Make your prospect do some work before you get too excited.

Using Tension to Your Advantage

If you sell big-ticket deals, you don’t need that many to reach your revenue targets. If you are getting venture capital to power your dreams, you may need to close only one deal for your venture to succeed. But these deals take a long time to close, almost never less than three months and often twelve months or more. By the time you enter the “closing zone,” you and your teammates have expended a lot of time and energy, your company is relying on you to close the deal, and you are starting to think about what you will do once the deal closes.

This is an exhilarating, scary, dangerous time. Exhilarating because you are so close to a big “high five” success. Scary because if you lose now when you can almost taste success, the disappointment will be bitter. Dangerous because a smart buyer could easily exploit your intense desire to close the deal and force major concessions out of you.

Donald Trump (the real-estate developer), in his book “The Art of the Deal,” talks about guiding the other side to the point that they really want the deal and think it is in the bag. Then he backs off and demands major concessions. Smart buyers everywhere have learned some variation of this tactic.

This is when you get a knot in your stomach and may witness table-banging and raised voices. All of this unpleasant stuff is good news. Experienced deal closers recognize these as signs that a deal is closing. The absence of these signs is actually a cause for concern!

One thread running through all good negotiations is some sign of real pain from the buyer that leaves you confident you are not leaving too much money on the table. Of course, the buyer knows you will be looking for this and will send signals that you have reached their limit. The skill comes in differentiating between fake pain, as in “This is well above our budget, and my boss will kill me if I agree,” and the real thing. The buyer will also be looking for the same signs from you.

Losing your temper is usually not good. It implies a lack of control and usually signals fear and weakness rather than strength. However, sometimes it can be very effective. Negotiators use many tactics to simulate table-banging without killing the deal. You can use the old good cop/bad cop routine, or the “My intransigent boss will never agree to this” line, or you could use a stalking horse to lay down a negotiating line.

Your tactic will depend on the specifics of the sale, but the one constant is that when your stomach gets in a knot, you have probably entered the closing zone, and that is good. We were engineered for fight or flight for a reason!

Imagine the Press Conference

Early on in a big complex sale, take time for a bit of day-dreaming. Imagine the press conference in which the CEO or partner of the company you are selling to announces the project to the press.

Perhaps you think day-dreaming is rather self-indulgent. Perhaps this is some variant of the old “think positive” stuff.

Actually, this is a very practical strategic selling tool.

Complex sales are… well, complex. As if you were in the middle of a chess game, your brain can hurt and you may not see the forest for the trees. You are probably juggling internal politics, resource constraints, pressure from partners, competitive moves, and customer politics… and that’s before you’ve had lunch!

You need a way to stay focused on what really matters. You need to know the single over-riding motivation of your decision-maker. This is the story your decision-maker will tell at the press conference when the deal is done. He will say why his great initiative will have a big effect on one of his company’s key strategic objectives and why he was smart enough to select the one vendor that was ideal for the project.

Unless you know this story, you will be shooting in the dark.

To cut your way through the complexity of enterprise sales, you need to simplify. Select the person who is the key decision-maker. Understand what is important to him. Find the one big reason why he wants to do this project. Select the one reason why he will announce that your company is the right vendor.

In long sales cycles, take time to imagine the press conference. Use this to get clarity on the key “ones”: one decision-maker, one business driver, and one vendor selection driver.

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Pandora is one of the Internet’s slow and steady success stories.

After years of work and more than $20 million dollars invested, the company is finally looking at the light of the end of the tunnel: Turning a profit. In this exclusive interview with founder Tim Westergren after a town hall meetup in Richmond, Virginia, we discuss the company’s close call with bankruptcy in 2007, their ad-based revenue model, their roadmap for adding new features and an open API, and their incorporation into a variety of hardware devices.

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Westergren told us that in 2003, he was burdened by about $200,000 of personal debt from his efforts with the startup. Most of the employees had gone long periods of time without paychecks. When the company finally got a badly needed round of funding, about $1.5 million went immediately to recifying a payroll backlog.

Now, however, the “unwitting nonprofit” is closer than ever to growing revenues larger than their expenses, news the investors will surely be ecstatic to hear.

In addition to recording this one-on-one talk with Westergren, we also captured about 20 uncut minutes of his talk to Richmond fans and users. Watch for the fuller story of Pandora’s trials, triumphs, and evolution, including an extended discussion of the utterly unscalable but nevertheless fascinating Music Genome Project.

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This guest post is written by Mary Hodder, the founder Dabble. Prior to Dabble, Hodder consulted for a number of startups, did research at Technorati and wrote her masters thesis at Berkeley focusing on live web search looking at blog data.

Real time search is nothing new. It is a problem we’ve been working on for at least ten years, and we likely will still be trying to solve it ten years from now. It’s a really hard problem which we used to call “live web search,” which was coined by Allen Searls (Doc’s son) and refers to the web that is alive, with time as an element, in all factors including search.

The name change to “real time search” seems a way to refocus attention toward the issue of time as an important element of filters. We are still presented with the same set of problems we’ve had at least the past ten years. None of the companies that Erick Schonfeld pointed to the other day seem to be doing anything differently from the live web search / discovery companies that came before. The new ones all seem to be fumbling around at the beginning of the problem, and in fact seem to be doing “recent search,” not really real time search. While I’m sure they’ve worked really hard on their systems, they are no closer than the older live web search systems got with the problem. All the new ones give a reverse chron view, with most mixing Twitter with something: blog data, other microblog data, photos, creating some kind of top list of recent trends. Some have context, like a count of activity over a period of time, or how long a trend has gone on or a histogram (Crowdeye) which both Technorati and Sphere experimented with in the early years. Or they show how many links there are to something or the number of tweets. All seem susceptible to spam and other activities degrading to the user experience and none seem to really provide the context and quality filters that one would like to see if this were to really work. All seem to suffer from needing to learn the lessons we already learned in blog search and topic discovery.

Publicly available publishing systems starting in 1999 took the value of time and incorporated it into what was being published (think Pyra which is now Blogger, Moveable Type, Wordpress and Flickr, among the many) as well as search and discovery systems for those published bits like Technorati, Sphere, Rojo, Blogpulse, Feedster, Pubsub and others, to walk down memory lane . . . (btw, for disclosure purposes I should state that I worked for Technorati in 2004 for 10 months, and consulted or advised most all the others in one form or another).

I started working on this problem in 1999, at UC Berkeley, and eventually did my master’s thesis on live web data search and topic discovery at SIMS (or the iSchool as it’s now known). From 2000 to 2004, people at SIMS would say to me, “What are you doing with blogs and data, it’s just weird. Why does it matter?” But the element of time was the captivating piece that was missing for me from regular search. It’s the element that makes something news, as well as the element that can group items together in a short period to show a focus of attention and activity that often legacy news outlets miss (until more recently when they decided that live web activity was interesting).

At Burning Man in 2005, under a shade structure during a hot, quiet afternoon, I remember having a four or five hour conversation with Barney Pell (who would later found Powerset) about the Live Web and Live Web Search, how to do it, what it meant, how to understand and present time to the user, how much was discovery and how much was search, how structured was the data you could get and how reliant on the time could you be with the data, what meaning you could make from that data, etc. Sergey Brin was sitting and listening, and finally, after a couple of hours, he asked me, “What is the live web and what is live web search?” Since Barney and I had already been doing a deep dive, I assumed Sergey knew what we were talking about, so it surprised me, but I explained why I thought time was a huge missing element of regular search, and that this was the type of search I worked on. Barney and I continued for a couple more hours. And it got cooler so it was time to go admire the art and that was the end of that. But I have wondered over the years where Google is with the live web and when they might do something with time. Twitter seems to be prodding them.

In 2006, “The Living Web” Newsweek cover story by Steven Levy and Brad Stone poked at this issue for the first time in a national forum.

When I look at the latest crop of search startups, I think: Why are we doing it all the same way again? Reinventing the wheel? Is anyone doing anything original either with data or interface? Is anyone building on what we’ve learned before about the backend or UI’s?

Frankly, our filters suck.. and I suppose that if a name change gets us to think anew about better filters, well, I should rejoice. I’m partly to blame for the bad filters we have to date because in having worked on this problem, I’ve contributed to some of the various live web or real time or whatever the word of the moment is to describe trying to solve this problem. We are very good at publishing our thoughts and visions, with time stamps, but not very good at the filtering side of things. The old method of information search and discovery was to open the paper or magazine, turn the pages with editorially filtered and placed information, and when you were finished, you said, “Okay, I’m informed” (whether you really were or not). But the media got complacent, missed stories and with the ease of blog publishing and sites like Flickr for photos, we could replace paper and supplement our information needs with the whole web. The only problem is, it’s the whole freaking web. An avalanche. We feel anxiety on the web from the lack of filter and editorial grace that one or two printed news sources used to give us.

I did a study in 2002, which I repeated in 2004 and again last year in 2008. I asked users to track their online information intake for one week. There were only 30 people in each study, chosen randomly from Craiglist ads, but what I found across each group of 30 was that the average time spent online with news and information sites was 1.25 hours in 2002, 1.85 hours in 2004 and 2.45 hours in 2008. These people are not in Silicon Valley, but they do all have broadband at home and live in the US. Every one of them reported some level anxiety over the amount of data they felt they needed to take in in order to feel informed. They often dealt with it by increasing the time they took to stay informed. They didn’t know that better filters might actually reduce their anxiety.

As Erick noted, the tension to solve this problem is between memory and consciousness; or as Bob Wyman and Salim Ismail called it at Pubsub: retrospective verses prospective search. And it is part of the issue. But there is more.

Discovery does mean you have to introduce time as an element. The user cannot be expected to know what is bubbling up, or the specific phrases that will name the latest thing.

Some people will say “michael jackson” and some will say “MJ” and some will say “king of pop.” And Michael Jackson as a topic is actually pretty easy. I remember once doing usability tests for a live web search and discovery system in 2003, where we asked users to search on Google News and various live web systems for an incident in Australia where a “giant sea creature” was found. But since all the media covering it originated in Australia, and they’d all called it a “massive squid,” and all the follow-on American sources including bloggers had copied the Aussie language, there were no recent hits for “massive sea creature.” Testers had to think creatively about how to get to the info they knew was there, and yet it was a semantic leap. One search tester actually cried as she refused to give up, she was so determined to find the result in any of the live web systems we were testing. We begged her to stop; it was painful. Good discovery could have helped.

Another key element of discovery and live web search is getting structured data, because spidering, which Google uses to get data from the web for it’s regular retrospective web search, makes understanding time with a published work more difficult. It’s hard to work with time if you only know for sure when you spidered the page. Twitter on the other hand has structured data because everything is published in their silo so the sites they provide their complete stream to get it in a structured format. They know the time of each tweet. Not to mention the data is available through API’s. This is the most efficient way to draw out meaning for search because you know for sure about the context of each piece of data, with time as one of the pivots, for search and discovery.

You also need to get the data model right for the backend search data base, in order to get meaning and link metrics. And you need to understand the different corpuses of data to know what things mean to users (not engineers), and figure out the spam and bad actor problems. There is the original context the data had and there is the UI which is so difficult when trying to make time understandable for many users. In fact some think that communicating the time element to regular users is so hard that making time focused search is really an “advanced search” problem.

If designed poorly, the system can contribute to the unnatural production of skewed data by users. If the system involves some sort of filter for authority or popularity, they are subject to power law effects (Technorati calls their metric “authority” but inbound link counts from blogs are not authority, they’re just a measure of popularity). What’s a power law effect? It’s when a system drives activity to reinforce unnaturally the behavior that caused something to be there in the first place. For example, if one of the metrics of a filter counts the number of people clicking on a top search, then the more clicks, the longer the item will stay at the top of the list of searches, even if naturally it would have fallen off the list earlier. Conversely if a metric for a filter involves a spontaneous act, driven by imagination, like writing a tweet, then exposing those items at the top of the filter might be less likely to drive up activity. However, if you show the results to the users, upon seeing a popular topic, they might begin tweeting about that topic without having thought of it before seeing the popular topic. In other words, by revealing the metrics you focus on, you can push users to change their behavior. By driving behavior, power-law distributions keep things with some power at the top because they are at the top or can drive them higher. It becomes a loop. And because no distinction is made between the quality or strength of a unit or what that unit might mean to a group of users in a topic area, straight number counts just aren’t very smart.

For example, if we made a system that counted Om Malik’s inbound links and called it authority, no matter the topic, I think Om would agree that even he wouldn’t have great authority and insight on the subjects of say, modern dance or metal working, if he happened to mention those words in a blog post. But on broadband issues, he is most definitely an authority. But Technorati, OneRiot, and other services that take a metric count and apply it for all topics, all circumstances, all search result matches, without context, randomize the quality of the information the user sees. They may provide a filter across the whole web, but they don’t give us any real help in judging what is useful or not. It’s why topic communities are helpful, and once you find a good editorial filter, driven by the human touch, you glom onto it for dear life because it’s such a time and energy saver.

I’m under no illusions that we’re remotely close to solving Live Web or Real Time search or even recent search. We are not. Nor are we near solving discovery. But I hope we will. Sooner rather than later. Because I need it now. The opportunity is huge. It means really building algorithmically the editorial filters we have today in the form of people, while balancing the mobs’ activities. Solve that and the prize will be big.

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Bet you didn’t see this one coming. Back in 2007 we wrote about a service called Dial Directions which lets you call a special phone number and verbally ask for directions, which are immediately sent to you via SMS. Today comes news that the company has been acquired by Sakhr Software, a development house specializing in Arabic natural language processing (NLP). And with their powers combined, they’re building a real-time voice translation service that will allow users to translate phrases from their mobile phones on the fly.

It’s a better fit than it sounds. Dial Directions has spent the last few years building mobile applications (it has an app for the iPhone on the App Store), and has also built out the technology required to efficently transfer voice input to servers, where it can then be processed (this server-side processing is also used by Google Voice Search and a number of other apps). Once it makes it to the cloud, this speech will be routed through Sakhr’s software, which is capable of translating English to Arabic and vice-versa. Translated audio and text are then sent back to the mobile phone, all within a matter of seconds.

The companies have jointly produced a beta version of the application for the iPhone and BlackBerry, which you can see in the video below. The application is currently in testing with select enterprise customers, with plans to release a consumer version around the end of the summer.

Sakhr’s customers include the Department of Defense, Department of Homeland Security, and the Department of Justice, so it wouldn’t be surprising if the technology makes its way out to defense personnel. A Dial Directions spokesperson says that most translation devices in the field abroad rely on a set library of phrases, and says that the new Sakhr translation software should be more flexible. That said, it sounds like this will come with one significant drawback — if your phone can’t reach the network, the software won’t work.

Terms of the deal were not disclosed. Dial Directions intends to keep its service running for now, though it may not be indefinitely.

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