Businesses can now take advantage of Instagram’s advanced advertising game, which was launched globally on 30 September 2015. Instagram has made three major changes to its advertising program which mainly consists of the following:
– New markets for the ads
– Opening up Ad-Buying
– Introducing 30 seconds video ads in Landscape mode

Instagram introduced ads nearly two years ago and since then it has made conscious efforts to ensure protection of its customer experience. Advancing its ad game includes allowing both large and small brands to run campaigns on the service and expansion of this ad viewership in more than 30 new countries including Italy, Spain, Mexico, India, and South Korea.

Along with rolling out ads broadly, Instagram has launched new key tools for marketers. Earlier the video ads were limited to just 15 seconds, but now advertisers publish video ads of up to 30 seconds. It is almost the length of an average television commercial, which allows company’s to adequately tell their story. Instagram is also enabling advertisers to use landscape format in order to give a more cinematic feel to the ads along with new delivery and optimisation tools, which could help, enhance brand campaigns.

Additionally, Instagram introduced a new premium ad tool called Marquee, that helps drive mass awareness and expanded reach in a short time frame. Instagram says it’s a new way to push mass recognition and is a perfect advertising platform for movie premieres and new product launches.

These adverts have definitely benefited Instagram by ramping up its revenue. Instagram’s ad revenue is projected to reach $1.5 billion in 2016, according to eMarketer, a research firm, and nearly double by 2017 to $2.8 billion.

This leads us to a few questions concerning these ads, Would you watch an entire 30 seconds ad while looking through your Instagram? Would it cause any interference in your user experience? How much of an impact do you think these video ads have on companies?

Sources:
http://www.adweek.com/news/technology/instagram-debuts-30-second-video-ads-its-latest-pitch-big-brands-166767

http://www.cnbc.com/2015/09/08/finally-here-comes-instagrams-big-ad-push.html

http://economictimes.indiatimes.com/tech/internet/instagram-steps-up-advertising-effort-adds-30-markets/articleshow/48879569.cms

http://www.ibnlive.com/news/tech/goodbye-ad-free-instagram-hello-sponsored-photos-1088975.html

The article by (Malone, Laubacher, & Dellarocas, 2010) discusses how companies can achieve collective intelligence through the use of building blocks by using four main questions, what is being done, who is doing it, why are they doing it and how is it being done. The answer to one of the key questions is called a gene. This article focuses on the 16 principle genes and the factors involved in selecting them. This article enables companies to get answers for these questions, which can help systematically design their collective intelligence system. A weak point is that companies could have a problem identifying useful genes that are suitable for the situation.

The article by (Pisano & Verganti, 2008) discusses the four ways to collaborate namely; elite circle (closed and hierarchical network), innovation mall (open and hierarchical network), innovation community (open and flat network) and consortium (closed and flat network). This article develops a framework, outlining the advantages, challenges and enablers of the different collaborations, which can be useful for companies to make better decisions. On the negative side, this article does not take into consideration the difference in opinion/working styles of individuals within a group. It also fails to mention limitations related to openness, such as reluctance in sharing unknown information to the person, hoarding etc.

The third article by (Borison and Hamm, 2010), proposes judgment driven techniques based on assessing individual experts opinions (probability encoding), combination of such individual opinions (expert aggregation) and by placing bets on a specific outcome of interest (prediction markets). This article emphasizes on each process and outlines the problems, which decision makers could use to improve their assessment of judgmental uncertainty in decision-making. However, the techniques seem complex for a small size company to incorporate and the problem of undesirability, uncertainty and inaccuracy persists, which can lead to distorting market probabilities.

Additional articles include further research on how these crowdsourcing techniques could help accelerate new product development/innovation and the nascent market for labor crowdsourcing. An article by (Aitamurto, Leiponen, & Tee, 2011) claims that combination of user innovation and crowdsourcing is done by directly engaging individuals in the innovation process to gain fresh, fast and creative ideas, accelerating new product development. Since these inputs are from the end-users, there will be higher market acceptance and lower risk of failure. Starbucks crowdsourcing platform, MyStarbucksIdea is a great example of this.

Labor crowdsourcing platforms, such as Amazon Mechanical Turk and Crowdflower, pay intelligent workers to perform simple macro tasks such as image recognition, sentiment analysis etc. These platforms have created a shift from full time employment to part-time employment (Shaughnessy, 2012).

Mini-case study on crowdsourcing and new product develop include P&G’s Connect + Develop program which lists the problems P&G is trying to solve as well as an open submission where innovators can suggest original ideas for review. P&G also partnered with InnoCentive by rewarding innovative ideas with prizes. This helped P&G introduce more than 100 new lines across various markets, resulting in 60% increase in productivity (Confino, 2012). The strength of this case is definitely P&G’s external collaboration with partners through which the company was able to achieve successful crowdsourcing. The efficient use of the innovative ideas and solutions has also contributed to its success.

Second case study is on Threadless, an online community, which consists of more than 500,000 members, who actively participate in creating and selecting t-shirt designs. The company produces and ships over 1.5 million t-shirts per year, which accounts for an excess of $23 million in revenue (Lakhani & Kanji, 2008). Crowdsourcing has been a success for Threadless mainly due to the relationship established with the community members who feel a sense of ownership towards the company due to their contributions, which is the case in many crowdsourcing projects.

Sources:

Aitamurto, T., Leiponen, A., & Tee, R. (2011). The Promise of Idea Crowdsourcing – Benefits, Contexts,Limitations. Nokia Ideasproject White Paper .
Borison, A., & Hamm, G. (2010). Prediction markets: A new tool for strategic decision making. California Management Review , 52 (4), 125-141.
Confino, J. (2012, September 26). Procter & Gamble CEO on solving the world’s sustainability challenges. Retrieved from TheGuardian.com: http://www.theguardian.com/sustainable-business/procter-gamble-ceo-solving-worlds-sustainability-challenges
Lakhani, R. K., & Kanji, Z. (2008, June 30). Threadless: The Business of Community.
Malone, T., Laubacher, R., & Dellarocas, C. (2010). The collective intelligence genome. MIT Sloan Management Review , 51 (3), 21-31.
Pisano, G., & Verganti, R. (2008). Which kind of collaboration is right for you? Harvard Business Review , 86 (12), 78-86.
Shaughnessy, H. (2012, March 10). Work Without Jobs: A Trend For The Educated Elite. Retrieved from Forbes.com: http://www.forbes.com/sites/haydnshaughnessy/2012/03/10/a-little-more-on-work-without-jobs-for-the-educated-elite/

I was keen to write this blog was after attending Ting Li’s lecture on how Twitter has an impact the stock market of a company. The fact that a major company like The Associated Press faced a huge loss in a matter of four minutes due to its twitter account being hacked is truly amusing!

According to a new study, social media sites such as twitter could be used to predict major, potentially world-shaking events. Nathan Kallus, a PhD from Massachusetts Institute of Technology, believed that crowd behavior could be predicted by mining tweets for any future events and then analyzing the trends associated with them. He reviewed the tweets associated with the 2013 social unrest in Egypt and claimed the protests were clearly visible in the Twitter feed days in advance. He added that the social media content even predicted that the protests would go on for weeks beyond the anniversary. He came up with the rationale behind this through natural language processing, which helps in extracting event information from content. This includes; type of event, what entities are involved and in what role, sentiment and tone, and the occurrence time range of the event discussed. Another predictive indicator included the statements mentioned on Twitter about a future date from the time of posting.

The idea of twitter predicting the future has been controversial. Kallus made this prediction about a historical event using historical data. However, do you think its possible to pick out these kinds of evidences before the event actually occurred? It could also be very time-consuming and difficult to accurately analyse the event from various social media platforms. There is also the question of reliability of the information posted in social media. Social media trends tend to vary and might lead to incorrect data. Additionally, I don’t believe that tweets truly represent the intentions of the entire population. Thus, I personally don’t think social media could help in accurately predicting major events.

What is your opinion in this matter? Do you think that sometimes social media could be useful in predicting certain events like box office revenues for movies?

http://www.fastcompany.com/3026593/fast-feed/can-twitter-predict-major-events-a-new-study-says-yes

http://www.technologyreview.com/view/524871/can-twitter-predict-major-events-such-as-mass-protests/

http://www.technologyreview.com/view/427807/twitter-cannot-predict-elections-either/