LinkedIn's New Corporate Directory
In my view, the future of LinkedIn depends on finding ways to get itself inside of business workflow – the essence of infocommerce – because the history of databases that remained standalone reference products is a sad one.
LinkedIn’s first big push to build ongoing user engagement was to add user-generated content, lots of it, creating a B2B Facebook if you will. This is certainly a valid approach, but with the Internet already groaning under the weight of endless content, much of it free, this is a tough road. I think workflow integration is a lot easier and ultimately much stickier. It is, fundamentally, the difference between logging into LinkedIn to “stay current” or perhaps find a useful morsel of information through sheer serendipity, and logging into LinkedIn because you need it to do your job.
Well, LinkedIn took a small but important move in the direction of workflow this week with the launch of LinkedIn Lookup. Very simply, this new app allows you to turn LinkedIn into an internal company directory.
As you can imagine, if you were to filter all LinkedIn profiles by current employer, you would essentially get an internal company directory. And it would be better than almost any company directory that exists given the depth of its profiles and the high level of data accuracy. But the new LinkedIn app does more than just filter listings, it also prioritizes fellow employee listings over your own connections so you’re really using it as an internal directory. Corporate email addresses are shown as well.
Overall, LinkedIn Lookup is a fairly weak version 1.0 app. But if LinkedIn sticks with it, it could take this product in some very interesting directions. Consider:
· Setting up the product with a corporate administrator could help make listings more accurate (many people don’t update their employer information if they are not immediately going to a new job). In addition, LinkedIn could make this administrator the point person to maintain the company web page as well, helping to insure deeper and more accurate data
· With listings now used for employment purposes, employees will be more diligent in maintaining their listings to the benefit of both the company and LinkedIn
· By letting employees see all the connections of other employees, an extremely powerful networking tool along the lines of those offered by Reachable can be offered.
· Non-public fields could be made available for corporate directory purposes such as reporting relationships, and this could in turn enable real-time organizational charts
· The product could offer links to a company’s payroll system (as many internal company directories already do), to help insure even higher levels of accuracy
And that’s just a starting list. Indeed, an enormously powerful product platform exists for LinkedIn to exploit with only some additional programming effort. And this product, properly evolved, is certainly one LinkedIn could charge for. No company wants to maintain its own internal directory if it can avoid doing so, and LinkedIn would bring to the table features and functionality no company could duplicate on its own because of its connections data.
Best of all, as companies adopt LinkedIn as their internal directory platform, LinkedIn automatically becomes a stronger database as a result. Employees who haven’t yet built a profile will do so; and those with existing profiles will be motivated if not required to keep them current.
Sure, there are some data governance issues that will need to be addressed and doubtless some technological and structural bumps in the road will emerge; as the saying goes, “hierarchies are hell.” But these issues will come to the fore because LinkedIn is simultaneously becoming more important and the end result of that is a more comprehensive and accurate database for LinkedIn, that will give it the basis to chase even more data-driven workflow opportunities.
If LinkedIn wants to offer high quality user-maintained data that gets accessed frequently, there’s no better way than to help it enable daily business activities. LinkedIn Lookup can be an important first start in this direction.
How Do You Rate?
Morningstar, the financial information giant, today announced that it will be licensing a ratings system from Sustainalytics, a Dutch company that assesses and rates public companies along three dimensions: environmental and social responsibility and governance. Morningstar will adapt this methodology and apply it to mutual funds.
Why the rush by Morningstar to add still more ratings to its data platform? And why license a ratings system when Morningstar already has demonstrated expertise in this area? Indeed, Morningstar has been rating mutual funds on their stewardship (akin to governance) for a number of years now.
The answer, in a word, is that ratings systems are hot. While they don’t look like much on the surface, they offer to users what they most want today: fast answers. You could even go so far as to say that the other reason ratings system are so popular is that they do the research – if not the thinking – for you.
Most importantly of all from a data perspective, a ratings system provides a consistent, normalized and sortable data point. This is especially valuable in the investment world, which is in the business of finding needles in haystacks. Ratings systems and other filters significantly streamline this process.
Imagine if someone asked to you identify the ten best restaurants in Dallas. Without Yelp and Zagat and the other existing restaurant rating services, this would be a nearly impossible task, particularly if you were looking for a comprehensive and objective answer. But these services in effect conduct mass-scale surveys, asking people to condense their opinions of restaurants into a predefined ratings scale. This user-generated approach to ratings has all sorts of imperfections, but most people believe that with enough people participating, the truth will present itself.
A step up from these open surveys are the professionally administered ratings systems. These distinguish themselves by identifying and rating companies against a fixed set of criteria. The goal of the exercise is to be objective as possible. That’s why data are used in place of opinions whenever possible. The more rigorous the system, the more valuable it tends to be. That’s because in addition to being normalized and consistent, these ratings systems allow you to make dependable comparisons. Companies rated “A,” for example, are all rated that way because they met a certain specified set of criteria. That means you can place more trust in the ratings system.
Interestingly, most ratings systems happily publish their underlying criteria and ratings methodologies. While this might seem to be their highly proprietary “secret sauce,” the reality is that nobody wants to undertake the same laborious ratings work if somebody else has done it, and publicizing the underlying methodology builds credibility and trust. In fact, the underlying methodology of most professional rating systems is central to their marketing efforts.
Rating systems reflect the fundamental shift we are seeing from data publishers selling vast piles of raw data to high value, more analytical datasets. The next opportunity is to actually do the analysis for them.
You can learn more about how publishers are using their data to produce a wide range of high value products at this year's Business Information and Media Summit. Hope to see you there!
Taking on LinkedIn
I read a fascinating blog post yesterday by venture capitalist Hunter Walk musing how (or indeed if) there might be some way to compete with LinkedIn. In addition to Walk’s insights, the post attracted a number of comments from other venture capitalists and entrepreneurs. Apparently, taking on LinkedIn is a growing topic of discussion, at least in Silicon Valley.
The post discusses a number of different approaches:
· Vertical Markets – could one create a better version of LinkedIn for specific vertical markets? The post doesn’t dismiss this as a potentially viable approach, but does correctly note that simply imitating LinkedIn isn’t likely to work.
· Project Focus – LinkedIn is designed around the traditional resume and with that comes the expectation of fixed employment at specific companies for fixed periods of time. There are some who are speculating that the growing “gig economy” is creating a need for individuals to showcase what they’ve worked on as opposed to where they have worked. I would argue that Houzz, the wildly successful site for architects and designers to display their projects, is in effect a vertical and project-focused version of LinkedIn, optimized for a specific market and its way of doing business.
· Data Verification – All the information on LinkedIn is user generated. That used to be considered a feature; now some are suggesting it’s a bug. My question here is how many people want/need verified data badly enough to justify ripping up the existing LinkedIn model?
· Public and Private Data Control. There are some who suggest that there is room for a LinkedIn competitor that gives users more control over who sees their personal details, presumably at a fairly granular level. This is an interesting concept, but how much more personal information would people put online if they had more control? This new service would quickly start to bleed into Twitter and Facebook. That might sound like a big opportunity, but to me it sounds like a big mess, raising issues about separation of one’s business and personal life that I don’t think anyone has figured out yet.
· Transactional. I’m a huge fan of B2B marketplaces, but the notion of essentially putting a “buy” button on people’s resumes strikes me as a limited opportunity. There are a very limited number of jobs where the work is project-based and people are hired strictly based on their skillsets. In addition, I think if you opt for this model, you necessarily have to fold in the data verification model as well because trust becomes paramount.
These are all interesting concepts, but they all come with issues. The biggest opportunity (and exposure) for LinkedIn is that it exists outside of workflow. If your job doesn’t involve hiring people, you likely don’t interact with LinkedIn too frequently. But what I’ve realized over time is that LinkedIn has become my Rolodex. If this is true for lots of other people (and I suspect it is), then LinkedIn needs to focus on better email integration and even more importantly, a light contact management capability. Why should I use a separate CRM system (which more likely than not is sucking limited data in from LinkedIn already), when I could keep all my contact notes in one central place in the cloud? This, by the way, is something that LinkedIn could sell as a subscription service.
Right now, all of this is just talk and conjecture, but it’s useful to note that in many respects, LinkedIn is no different from most other commercial data products.
How Zillow Spends Zero on Advertising
Doubtless everyone reading this is familiar with Zillow. We honored them as a Model of Excellence in 2006 .
They’re now a real estate listing behemoth that sports a market capitalization of $5 billion. We all know what Zillow does and how successful it’s been. But did you know that Zillow launched with virtually no advertising budget?
In a fascinating interview, Zillow’s Chief Marketing Officer, Amy Bohutinsky, explains Zillow launched with the classic “sell data with data” strategy. Using data to promote your data is – unsurprisingly – a marketing tactic available only to data publishers. And it’s a tactic well worth exploiting to the maximum.
Zillow launched itself with press releases aimed at the consumer mass market. It offered free access to data that was catnip to almost every consumer: instantly find the estimated value or your home, or anyone else’s for that matter. Zillow, after collecting and normalizing property assessment records from all 50 states, had developed an algorithm that looked at recent sales and area demographic data to calculate a home price valuation. Sure, it was necessarily imperfect, but the data was credible if not authoritative, comparable (all homes were evaluated the same way) and of course free. This quickly drove millions of page views, allowing Zillow to execute on its business model of selling listing enhancement to real estate agents.
But Zillow didn’t stop with this single gambit. Instead, it allowed consumers to sign up to receive email updates to their home valuation – every time the estimate changed, Zillow would send an email. This created critical ongoing engagement (important because the average person doesn’t buy or sell a home all that frequently), brand enhancement, and an important advertising vehicle (the email also presented information on nearby homes for sale).
Beyond this, Zillow regularly mines its own data to find newsworthy statistics that keep its brand front-of-mind and implicitly credential it as an authoritative and central industry player. It issues press releases on everything from the standard reports on where homes are selling most quickly and slowly, to offbeat data on the “10 biggest homes” or “10 most expensive homes,” and the like. Obviously there’s no shortage of material.
As we noted earlier, you’re most likely to get media coverage if you can provide facts and statistics. That’s hard news as opposed to opinions or transparent gimmicks to try to attract attention. More importantly, every piece of data you release reinforces your central market position, your authority, your knowledge and your expertise. You become generally understood to be the “go to” place for data in your market. There’s no better positioning than that, and best of all if you do it right, it’s practically free.
You can hear how another Model of Excellence winner, Capterra, pulls of this trick when its CEO Mike Ortner joins us for our infamous “Excellence Revisited” panel at this year’s Business Information and Media Summit. Hope to see you there.
The Macro Problems with Micropayments
Micropayments companies – companies that make it somewhat faster and easier to purchase small units of content such as a company profile or an article – have existed since the early days of the Internet. You may remember names such as First Virtual, Cybercoin, Digicash, Millicent, Payword, Micromint … and that’s just a partial list. And despite a raft of failures in this space, new players keep coming. For example, a start-up called CoinTent just raised $1 million to pursue its vision for micropayments.
Why are micropayments so hard? I see two primary issues. The first is in establishing market traction. A successful micropayments play needs to not only get a lot of users, its needs to get a lot of publishers, and it needs to grow both sides simultaneously. Moreover, there needs to be a big overlap in terms of interests. I’ve always thought a B2B micropayments start-up might succeed more easily than a broad-based B2C micropayments venture. But then I look at my own web research habits: I’m all over the web, and the content I am most willing to pay for is typically the most obscure. Even if a micropayments company could sign up 10% of online content providers, an unimaginable percentage, it wouldn’t much simplify my life.
More subtly, and more significantly, is the natural hesitation about buying something that the seller won’t show you in advance. Content is an experience good – you can’t assign a value to it until you’ve seen it. And of course, content providers can’t really show their content in a meaningful way prior to the sale. Over the years, I have purchased “articles” that turned out to be 24 words long. I have bought “books” that were 14 pages. Of particular concern to data publishers, I have purchased company profiles that contained little more than the company name and address. It turns out this data publisher had a lot of detailed, high value company information, but on only some of the companies in its database. And it’s not just an issue of length or depth. I have purchased journal articles that were quite lengthy and detailed, but that touched only fleetingly on the topic I wanted to learn about, something that’s very difficult to discern in advance.
In short, micropayments for content is hard, because there’s so much content out there, and the inherent need to say “trust me” to potential buyers. At least at this stage of development, micropayments don’t look like a big opportunity for content publishers, data publishers in particular.