Social Media Has 4 Primary Functions

A recent McKinsey social media survey of about 200 companies revealed that social-media-based marketing is driven more by faith than by evidence. While over 70 percent of companies believe that digital marketing holds significant potential, more than half struggle to measure its exact impact on sales and profits. A lack of information clearly isn’t the problem: the amount of data points from ad and page views, click-through rates, and product and service “buzz” from friends and followers—all available daily—has reached flood-stage proportions. Even if companies collect terabytes of digital data every day, however, much of this fails to provide reliable ROI assessments.

The data exists—and marketers have an array of methods to choose from when assessing digital ROI. Marketing mix modeling, for example, is a tried and tested approach to assess the impact of marketing on business results. While it has worked well in paid media (e.g., print campaigns, TV spots, and display advertising), marketers have had difficulty applying it to social media, primarily because “earned media” channels like social networks are a two-way street. Companies send out their messages, but consumers can also voice their opinions about these companies, comment on their products, and discuss their services.

Social media has four primary functions—to monitor, respond to, amplify, and lead consumer behavior—which can be linked to the “decision journey” people take when buying a product or service. Being able to identify exactly how, when, and where social media influences consumers at each stage can enable executives to craft marketing strategies that tap into social media’s unique ability to engage with customers. In their traditional forms, ROI analytics are not up to this level of complexity, but in combination with next-generation tools, they can deliver results.

The fundamentals of ROI marketing analytics remain solid; but to extend them to digital marketing, McKinsey has developed three innovative analytical methods to help marketers better understand the impact that targeted marketing responses have at individual touch points along the consumer decision journey. When employed in combination, they can provide useful new insights into what works in digital marketing, while offering a solid starting point to optimize social media marketing.

No method exists to reduce the multitude of social media KPIs to a common denominator for comparison across different social media platforms like Facebook, Twitter, or blogs. For traditional media, gross rating points (GRPs) fulfill this function by measuring the advertising intensity of a campaign as a whole. McKinsey has created an online analog. Social media GRPs is a metric based on the number and reach of company-related postings across social media. It serves as marketing mix model input to determine the impact of social media on business performance. Various sources provide the information needed: from monitoring of social media panel data to platform-specific tools such as Facebook Insights. Compared with classic GRP data, social media GRPs have a critical added dimension: sentiment. After all, social media postings can also be negative, making it necessary to differentiate between negative, neutral, and positive social media GRPs.

By using social media GRPs, marketers can integrate social media into their marketing mix models to determine its effect on sales and profits. Marketing mix models also enable teams to develop response curves—akin to the ones used for traditional media—to optimize their marketing mix based on expected returns.

Which factors determine company performance in social media? Marketers can answer this question by using an approach that systematically analyzes buzz and identifies its key underlying drivers. The buzz monitoring approach addresses central consumer interaction questions and—since it is central to the “monitor” stage—is the premise for responding to, amplifying, and leading consumer behavior. When in the buying process do users voice their opinions—before acquiring the product or afterwards? What are the dominant themes—the product, service, or the price? And where does the discussion take place—in forums, on Facebook, or in blogs? Buzz monitoring answers these crucial questions. 

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This piece originally appeared on the McKinsey & Company Telecom, Media and High Tech Extranet 

AREND Project aims to ward off poachers with unmanned aerial vehicles

Like many a technology before it, the aerial drone is finding applications far beyond military circles, from burrito delivery to surveying broken bridges. One emerging area with huge potential is wildlife conservation, with drones delivering the ability to patrol and detect illegal poachers from the air. AREND (Aircraft for Rhino and Environmental Defense) is an international team of students currently developing an unmanned aerial system with the ultimate objective of combating poaching in Africa's national parks.

The AREND project is backed by Wildlife Protection Solutions (WPS), an international non-profit group concerned with the conservation of endangered species. The team consists of experts in aerospace, mechanical, electrical and software engineering stationed around the globe, from Helsinki to Colorado.

Following a successful Kickstarter campaign earlier this year, the team at AREND has proceeded to ramp up development of the system. The aircraft has a pusher configuration, which refers to the location of the propeller at the tail end of the fuselage, with communications antennas built into the wings and a gimbaled camera into the nose. The team says it will be capable of silently performing autonomous searches, capturing quality images throughout and then returning safely to a landing area.

The finished product will perform surveillance while distinguishing between people, large animals and other objects such as aircraft wreckage. The team envisions that squadrons of the craft will eventually be permanently ready for fast deployment, working in conjunction with a larger network of sensors to narrow the search area and record and alert authorities to the presence of poachers. This should help build pressure on poacher networks, who AREND says are only becoming more sophisticated and contend with an arrest rate of only 5 percent.

The team behind AREND isn't alone in floating aerial drones as a solution to illegal poaching. Back in January we looked an initiative from Californian company Airware which saw the testing of UAVs at the Oj Pejeta Conservancy in Kenya. Other drone-led conservation efforts to get off the ground this year include curtailing illegal fishing on Belize's barrier reef and hunting down invasive weeds from the air in Australia.

There's no word yet as to exactly when AREND's drones will take to the skies, but with demand for rhino horn on the rise in China and South East Asia, it won't be a moment too soon when they do.

Source: AREND

Motion Imagery Software and How It Fits Within the UAV Framework

Beyond the Aircraft and the Sensor
When you start a discussion about unmanned aerial vehicles (UAV), the typical focus is on the aircraft and its sensors. Sure, the primary goal of any mission, in one form or another, is data collection, and the vehicle and capture device are undoubtedly integral elements in this effort. But what do you do with that raw data after it has been collected? It needs to be mined, processed, and analyzed. This undertaking seems straightforward enough, but more often than not, the task of analyzing the data is fraught with complications such as noisy, unstable imagery and imprecise or missing metadata.

From Imagery to Insight
Motion imagery software enhances, manages, and analyzes the raw data sourced from UAVs so that analysts can extract information and transform it into actionable insights. Identifying the geospatial location of an object within a scene, for example, is a key factor in imagery analysis. But what if that object and its surrounding reference points are undecipherable due to the nature of capturing video from a constantly moving aircraft?
Motion imagery expertise and computer vision based technology is used to enhance the raw input by adjusting the resolution, minimizing distortions, and correcting inaccurate metadata so that reference points are recognizable, and the task of georegistration is facilitated. The software developed by companies like 2d3 includes a technology called Reticle™, which improves geospatial metadata and enhances imagery in order to attain better accuracy in georegistration without the need for improvements at the sensor level.
This capability, along with a host of other features including – image mosaicking, 3D modeling, and visualization – work in tandem to produce relevant and actionable results.

Geared Up for the Commercial Market
The use cases for this type of technology are extensive. Foremost is defense, but industries such as precision agriculture, asset management, and law enforcement are all candidates. Some companies already have commercial market synergies in the sense that their technology has high adaptability for emerging non-government UAV applications.
Commercial off-the-shelf (COTS) business models exist where the company can meet market demand as it happens, without the long lead times associated with custom-built applications. Yet, the software is still extensible, and incremental features can be added quickly to accommodate custom specifications. This plug-n-play technology is priced according to commercial market demands and conforms to a modular product structure where customers can build up or scale down according to their needs. Moreover, some software is platform agnostic, which means it can parse data sourced from any vehicle or sensor and generate actionable insights. This is key since data from UAVs are usually asynchronous and come in a multitude of varying data types.

Bridging the Gap
As commercial UAS applications gain traction – evidenced by the recent US Department of Transportation’s Federal Aviation Administration (FAA) issuance of a Certification of Authorization to multinational energy giant, BP – many companies anticipate the opportunities in this market. It will continue to leverage its core competencies of motion imagery expertise, COTS model efficiencies, and computer vision based technology to focus on the key element of UAV missions beyond the aircraft and the sensor: the software that bridges the gap between imagery and insight.