This is not new, but the above flow chart has worked for me throughout my life. Every January, friends ask about New Year’s resolutions and popular ones are typically about changing themselves (less weight, debt, vices, stress) or about jobs (more pay, better education) which will make them happier. But without habits in place, the success rate is at best the success rate of starting up your own business (<80-90%). As with good habits, resolutions are a continual work in progress.
As long as what I'm doing is aligned with my mission* in life, I feel at ease. For me, happiness is not ignorant bliss, but an understanding of who I am now and where I want to be. And that's something to think about all year, not only in January.
(from Delivering Happiness)
* My mission – “To be a decent and respectable human being, considerate of others and the environment. I want to affect the lives of others in a positive way and I hope very much to be a positive role model for others.”
Great news for Brooklyn tech. I wrote about how NYC is planning to attract science and technology students by creating a science and tech campus on Roosevelt Island and an applied sciences campus at 370 Jay Street in Downtown Brooklyn. According to a press release from Senator Squadron today, Joe Lhota believes, “Jay Street will happen long before 347 Madison,” referring to the MTA’s planned sale of its midtown headquarters. Joe Lhota made the statement at his confirmation hearings by the New York State Senate to be chairman and CEO of the Metropolitan Transportation Authority on Monday.
Senator Squadron and his colleagues have been urging the City and the MTA to move forward with NYU-Poly’s proposal for a Center for Urban Science and Progress in the space. The MTA, which has a long-term lease on the building, and the City, which owns the building, must reach an agreement before it can be transferred to a new owner.
Senator Squadron adds, “Chairman Lhota’s comments today were a welcome sign of the MTA’s commitment to putting 370 Jay to use. Now, the City and the MTA must work to make NYU-Poly’s proposal a reality – which would bring jobs to Brooklyn, fuel New York’s growing tech sector, and move forward Downtown Brooklyn’s continued revival.”
Looks like the endorsement of the MTA’s new CEO brings us closer to a Brooklyn technology hub. More info on NYU’s 2031 Downtown Brooklyn strategy.
(Photo from Brownstoner)
Our friends over at KD Nuggets posed a question about analytics and data mining trends in 2012. As of today, the poll results are broken down as such:
- Analytics in the Cloud and Hadoop (16%)
- Big Data (21%)
- Competition platforms (5%)
- Game analytics (4%)
- Location-aware analytics (9%)
- Social analytics (17%)
- Privacy (4%)
- Sensor data (6%)
- Text analytics (14%)
- Other (3%)
Analytics in the Cloud and Hadoop, big data, social analytics, and text analytics are almost evenly spread out with big data at 21%. You can argue that all of the choices can amount to big data, so it makes sense that it is the leader in the poll by analytics professionals. What I believe will be the biggest area is how big data analysis is used on the other areas, and the combination of several of these can potentially unlock a goldmine of information for any business that collects and uses data. What do you see as the hottest analytics area in 2012?
Studying online behavor starts with my own. At least for me, using my own online activity allows me to get a sliver of understanding of how companies market online. It is by no means a lens into the vast world of online marketing, but for someone who has grown up with digital around me, there must be a few others who can relate. How does behavior translate to effective marketing? That’s something online marketers have been trying to quanitfy since online advertising started in 1994.
Web based advertising started with a 468×90 pixel banner ad from AT&T in 1994 on HotWired.com (a favorite of mine at the time, it was the digital magazine of Wired, which also discussed the original banner). Back then, there were no analytics to track click throughs, no ad server networks, and no marketplace (selling was done manually). This is what the banner ad looked like:
While there are no analytics to back this up, online discussion estimated around 70% click through rates for the initial banner ads. Fast forward 17+ years later. Clickthrough rates of 0.3% (or less) are more the norm (that’s 3 people of 1000 viewers). As a comparison, email marketing has response rates of 2% to 12%. I’m accustomed to ignore any ad on a browser or on an app on my mobile device. However, I do find value when I use a geo specific app such as Foursquare or a hyperlocal blog showing ads from local businesses or a brand that is interacting with customers on social media sites. I’m more inclined to support a brand that personalizes and communicates directly with their customers.
Google Research released a paper last week titled “Measuring Ad Effectiveness Using Geo Experiments”. In these experiments, a region (e.g. country) is partitioned into a set of geographic areas, which are called “geos”. These geos are randomly assigned to either a treatment or control condition and geo-targeting is used to serve ads accordingly. The experiments then measured the impact of advertising on consumer behavior (e.g. clicks, conversions, downloads, etc.). Its conclusion is that measuring effectiveness is a challenge, but geo experiments “can be applied to measure a variety of user behavior” and don’t require the tracking of individual user behavior over time and therefore avoid privacy concerns that may be associated with alternative approaches.
This tells me there are too many variables to quantify advertising effectiveness, which is where we started with in the 1994 AT&T banner ad. So how does a brand or business measure effectiveness when someone like me ignores online ads? Stop obsessing over click throughs and response rates for banners and email, but rather find out what customers are asking for. These values can be used as indicators to compare the success of similar online advertising programs with similar marketing schemes, but rather than using them as a measurement for purely ‘ROI reasons’, it’s more important to build relationships with those who are supporting the business with a mix of tactics. Measuring brand building exercises are difficult to measure, so think of how you build your real life relationships. Reach out via social media, respond to emails and thank them from time to time. How do you connect with others, and share stories relevant to them?
We know that the use of analytics for business is the key to unlocking its data’s value. Getting actionable data translates to positive business outcomes can be used to reduce operational efficiency, meeting compliance requirements, or anticipating market needs. But the complexity of large business data can make it difficult to unlock the value.
Data can exist in various formats in various servers, files, hosting providers, and data warehouses. This also implies that an integrated data warehouse already exists. Even if there is an existing warehouse, shifts in business strategy or the use of technology can create disperate data locations that can’t be used in a data analytics platform. This is something I experienced as a corporate CIO. We knew there was a great amount of information we could use to better serve internal and external customers, but compiling the data into a usable report took too much time and was not on-demand. We did not lack good tools or the talent to generate insight. We had the support from BI vendors such as Oracle, Microsoft, SAS, and others. And our team was one of the best in the business. But the complexity and shifting requirements (either by the business or compliance reasons) added complex variables into the equation. Additionally, unstructured data didn’t necessarily ‘fit’ into our data warehouse for analysis.
In an Internet startup, analytics is essential as well, but is easier in the sense that there are no legacy systems, historical data, and outdated models that need to be pulled together. Jason Goldberg, CEO of Fab.com, posted his thoughts on how their data was used to raise $40million. Data analytics providers such as RJMetrics (customer acquisition metrics and customer lifetime value), SEOmoz (SEO data), Salesforce (CRM data), and Google Analytics (visit data, referrals, and traffic) can provide value for much less implentation costs.
Combining data from these services, they can provide a good view of where the business is now. While easier to build in analytics from the beginning, you still need to know what you’re looking for and how to set goals for your business. Without those, you as the visionary CEO won’t know where you’re paving the road towards so your team can get there.