When Excel was originally developed it was 1995. Yes, around 30 years since.
The amount of data processed today in a routine analysis is gazillion time the amount of that time.
Yet, most of the visualization is based on the same software, though updated, and with the same approach. More
The extensive growth of sources and contents, the inexhaustible escalation of fake news producers, the proliferation of social channels with metrics far from being disclosed, the spread of messaging systems. All these factors contribute to make analysts’ life harder day after day.
Today 66% of the organizations do not know how to handle existing data, let forget about collecting new data in a way truly contributing to the business as we know it.
Big data, well data of any size, can be really uneasy to collect and to translate into something
There is a clear need for data ready to use without never ending set up operation, able to answer in seconds to questions.
“Data is an enterprise asset, which cuts across products, services, and organizational units of a company. This makes data hard to manage and data initiatives difficult to organize. The big data mindset is driven by experimentation, discovery, agility, and a “data first” approach, characterized by analytical sandboxes, centers of excellence, and big data labs This mindset often runs counter to, or can complement, traditional hypothesis-driven approaches to data management.”
Randy Bean, Forbes, 2016/11/08
The process of adoption of meaningful big data (or data of any size) can be rather complex then as every process impacting on the corporate culture and workflow.
Looking at this flow and then thinking about each one own organization, it’s easy to spot critical area.
The definition of Stage 1 & 2 is really critical as it is entangled with business priority as it cannot be a first come first serve model, so it is for helping problem owner in choosing the right data to achieve her/his goals.
I would probably add several check-points for process validation so not to get to the end of the entire trip and find out that something has changed in between.
The more accurate is the set up activity in modeling a monitoring system, the best is the experience for the client and the staff working on the platform.
Other than the current filtering modules available in the most performing platforms, we suggest to focus a filtering activity on four indexes with the aim to deliver a content ranking tailored for each client. A website, a Facebook page, a Twitter account could be a threat for a brand and neutral to others or positive…
Ranking the repository of sources is then a strategic activity which requires a periodic revision to keep the info dataset updated.
The index suggested are:
Contributors have each one a posting strategy, if professional authors, or post compulsively if their activity is driven by political or news agenda.
The general rule is that a consistent stream of posting and update keeps the audience more loyal to the author.
If the author does belong to conspiracy or boycott groups, to some political parties, then we do have to consider the filter bubbles he/she belongs. The bubbles support a high level of fidelity no matter how many posts are made each day or week.
While the algorithmic approach to measure sentiment is still rather questionable, on limited amount of text it can be run manually. This task may prove to be vital when introducing a Sentiment by source, better a polarization index. Why polarization? If some sources are 100% negatives by attitude towards some brands or some industries, others can have a mixed approach that depends from a single contributor or a extremely sensitive topic.
The latter being true for news outlets, the former being true for some Facebook pages, blogs and Twitter accounts.
Building a polarization index by source does help in building a knowledge system that can be expanded in a consistent and unique way
How fast a news spreads across the web? Well no one knows a rule for that nor it can be predicted easily though it is possible to build some model based on the previous posts that can help in forecasting a reasonable virality index by source. Within a virality index we do recommend to include the variable of the lifecycle of the news distributed by a source. These information can drive the appropriate reaction by a brand.
Related to each of the index above, the definition of the Audience is no longer a simple quantitative item but a rather qualitative one. While the size of the audience have a impact on the potential reach, it’s its loyalty to the author that impact on virality. Larger audience can work better as far as the goal is awareness, memorability though tend to have a high level of dispersion and a low level of conversion. On social media channels larger audiences are often inefficient.
What to do with these index?
The most important task to be completed is the creation of a unique index to help defining the true relevance of a contribution.
Charting the four indexes is the first step to visualize the impact and to identify at a glance the area of weakness and strength.
There is a long list of task to be completed through the output of the index, setting innovative alert system and multilayer priority definition, just to name a few.
Overall, it’s a matter to deliver rich insights to clients that go over the standard information building a shared knowledge system.
Three weeks after the latest WebSummit in Lisbon, it’s time to write down some thoughts about the event, the model behind it, and the startup ecosystem.
Yes, it’s a crazy place packed with people from all over the world looking for business opportunities. Fair enough.
If you get there you know how it is. Right or wrong is probably not the correct question to ask for. This is the business model of the events dedicated to startups.
It’s a money machine, of course, the one of the kind that has each one of us cry:” Why I haven’t thought about it before him?” as the model is rather simple: you pack in a gigantic space people who want to invest money, people looking for money to nurture their dream, audience looking at the entire show.
It’s cruel, in a way, but no one is there for charity reasons.
An event like this, calls for an equally energetic environment as today’s Lisbon is. Let’s talk about the charm of a decadent city, where you can walk across small streets listening for the music in the language and waiting for your chance to say “Obrigado”.
Then think about one of the poorest countries in Europe, which became a democracy barely 40 years ago and with a glorious past of navigators and conquerors.
Lisbon is exactly the sum of the two: the city is going under massive renovation with old buildings restored, streets repaved and is looking towards a bright future claiming “We are not Silicon Valley, this is Portugal”, “We are not Berlin, this is Portugal”, though very careful about not losing its identity and charm.
The digital economy is the future and the present as well. Not betting on it is like missing a train.
Startups are the huge business of the digital economy. Not betting on them is like missing that same train.
The key is to sell a dream and not a nightmare, an opportunity and not an illusion, a chance and not a lie.
What about our chance?
We learnt a lot because there’s a lot to learn if you walk around listening and watching what others say and do. There were a lot of incredibly smart people to discuss with and to discover: great ideas as well as bizarre ones.
In our opinion the event is the ideal place to benchmark ourselves and the way we present our ideas. Without benchmarking, any idea looks great, unique and we may feel as our own personal Jesus.
Yet, when you present your product in a one to one conversation or you get on the stage for the Pitch, that’s another story. It’s the cruel reality of relevance.
We are proud for having been selected for the Start up Track.
Even more so for having the chance of being among the 200 companies selected out of more than 1.500 applicants to be on stage for the Pitch.
The key learnings we brought home with us:
Listen and talk to everybody around you: learning is in the air
Learn from comments and questions how to introduce yourself and your company better and in a clearer way
Listen for criticism and put it to work for your benefit
Have a clear agenda or you may get lost
The Beta version is everything and does not need to be perfect: it has to work
Any further suggestions from your side?
The first myth to debunk is that online conversations are found only in Social Media.
Since the very beginning of our work in this industry and to this day we insist that a sound monitoring project is a Web and Social Media system. More
The tumultuous rise of the adoption of messaging system is proving to affect the social media-monitoring model as we know it.
While the monitoring platforms are still focused on individuals’ profiles on social media channels, more and more meaningful conversations are taking places outside the radars of the spiders. More