Category Archives: Blog With BEB

YouTube Demographics

Every year, we marketing geeks anxiously await the data presented by the Pew Research Center on demographics of social media consumption in the US. The Pew Research Center is a nonpartisan American fact tank based in Washington, D.C. It provides information on social issues, public opinion, and demographic trends shaping the United States and the world. It also conducts public opinion polling, demographic research, media content analysis, and other empirical social science research. The Pew Research Center does not take policy positions, and is a subsidiary of The Pew Charitable Trusts.

Join us as we review the latest information surrounding who (in the US) is using social media!

The most used platform to date is YouTube. Based on US Census Bureau data (from July 2018), there are over 253 million adults in the United States. 228 million are online. 73% of adults online use YouTube; that’s over 166 million people. That number represents only 13% of the total, 1.3 billion global YouTube users.

Of the US YouTube adult users, approximately 47% are women and 53% are men.

YouTube receives over 500 million views each day, with 300 hours of video being uploaded each minute. That translates to 432,000 hours of video per 24-hours, representing over 49 years of video time.

Learn more about the latest social media statistic by clicking here.

 

List Your Close Friends of FB

Facebook says that the goal of News Feed is to connect people with the posts they find most relevant. It’s not about the amount of time someone spends on social site, but rather the quality of time spent. That means Facebook must predict what users want to see.

To do this, they study to understand what people are doing on Facebook — what they like, comment on and share. They also use surveys to get more context about the posts people want to see and who they want to see them from. In May, FB announced two ranking updates based on surveys: one gives priority to friends someone might want to hear from most and the other prioritizes links a person might consider most worthwhile.

Historically FB has predicted who people might want to hear from based on signals like how often they interact with a given friend, how many mutual friends they have and whether they mark someone as a close friend.

Now, in addition to tracking these signals, Facebook is asking users to to list the friends they are closest to.  Once patterns emerge from the results they will use them to inform the News Feed algorithm with the goal to better predict which friends people may want to hear from most.

This doesn’t mean News Feed will be limited to posts from only certain people and it doesn’t mean you will necessarily see more friend content.

They also know that individuals that are considered close friends today may not be in a year, or even a few months later. The prediction models will continuously update based on the interactions people have with their friends on the app as well as continue to survey people.

 

Informed Address Where There’s No Address At All!

The Postal Service has put an emphasis on enhancing the customer experience by evolving the marketing in the digital world. The USPS is now piloting a new technology platform called Informed Address (IA).

The concept will enable mail to be sent and delivered without a physical address. Instead, Informed Address allows recipients to use identifiers that include email, social media handles, or a custom name for mail processing and delivery functions.

Informed Address will replace the delivery point with a unique code where the usual IMB (Intelligent Mail Barcode) is substituted with an “Informed Address IMB”, which contains the physical address information. This allows customers the enhanced privacy and identity protection, as marketers will no longer need to obtain or hold a physical address for their mail communications.

During the testing period, the USPS will assess consumer engagement, gauge mailer interest, and determine technical feasibility. This new technology provides the opportunity for marketers to provide additional services, including vanity address development and enhanced targeting for B2B and B2C marketing.

The Urban FF Center

What is larger than 14 football fields, has twice as many robots as human workers, and handles 50% more inventory than traditional warehouses? – Amazon’s first New York City distribution center.

Located in Staten Island, this urban fulfillment center can package more than one million items a day during its busiest period even though the site is 20% smaller than a typical Amazon fulfillment center.

In urban settings, space must be used with military precision combined with automation that allows for building up rather than spreading out. Computerized pickers that are approximately the size of a robotic vacuum, pick up inventory that is stored on shelves and then deliver the items to a human associate at a workstation. This limits the number of steps an individual has to take and allows storage of more goods in a robot-only section of the fulfillment center.

Smaller warehouse and fulfillment sites is a good example of how online sales are reshaping logistics in the US.

USPS Driverless Test Run

The US Postal Service has entered into a contract with self-driving truck startup TuSimple to haul mail between Dallas and Phoenix. Founder, Xiaodi Hou says that this USPS pilot gives them fuel to help validate their system and expedite the technological development and commercialization progress.

TuSimple will complete five round trips between May 28 and June 10 while a safety engineer and licensed driver ride along in the cab. Its Level 4 self-driving system (see below for self-driving categories defined), uses 8 cameras to detect cars, pedestrians, and other obstacles over one-half a mile away, even in inclement weather.

TuSimple’s camera-based system allows it to achieve three centimeter (1.18 inch) precision for truck positioning even in inclement weather and tunnels with real-time decision making. By keeping aware of traffic flow ahead, trucks are able to maintain a given speed more consistently than human drivers which can cut fuel consumption by as much as 15%.

The USPS has been interested in self-driving technology for a long time. In 2017, a report published by the Inspector General detailed plans to add semi-autonomous mail trucks to its fleet as early as 2025. Placed into service on 28,000 rural routes, they would free up about 310,000 postal workers to sort and deliver packages.

TuSimple has R&D labs in San Diego and test facilities in Tuscon. It expects to close out 2019 with a 200-truck fleet in the US and a 300-truck fleet in China, making it the largest self-driving truck solutions company in the world.

Later this year, TuSimple will operate several self-driving trucks for 22 hours each along the I-10, I-20, and I-30 corridors through Arizona, New Mexico, and Texas. It says freight along the I-10 corridor accounts for 60% of the US’s total economic activity. It expects its semi-autonomous trucks to be a frequent sight along that route in the months ahead.

Self-Driving Systems are categorized by five-levels:

Level 1- Driver Assistance-Under specific conditions, the car controls either the steering or the vehicle speed, but not both simultaneously. The driver performs all other aspects of driving and has full responsibility for monitoring the road and taking over if the assistance system fails to act appropriately. Cruise control is Level 1

Level 2- Partial Automation- The car can steer, accelerate, and brake only in certain circumstances. Maneuvers such as responding to traffic signals or changing lanes largely fall to the driver, as well as scanning for hazards.

Level 3- Conditional Automation-The car is able to manage most aspects of driving, including monitoring the environment. The system prompts the driver to intervene when it encounters a scenario it can’t navigate. The driver must be available to take over at any time.

Level 4 -High Automation-The vehicle can operate without human input or oversight but only under select conditions defined by factors such as road type or geographic area. In a shared car restricted to a defined area, there may not be any. But in a privately owned Level 4 car, the driver might manage all driving duties on surface streets then become a passenger as the car enters a highway.

Level 5- Full Automation-The vehicle can operate on any road and in any conditions a human driver could negotiate.

Prescriptive Analytics

Prescriptive analytics is the third and final phase of business analytics, which also includes descriptive and predictive analytics.

Prescriptive analytics goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the implications of each decision option.

Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen. Further, prescriptive analytics suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option. Prescriptive analytics can continually take in new data to re-predict and re-prescribe, thus automatically improving prediction accuracy and prescribing better decision options. Prescriptive analytics ingests hybrid data, a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts), and business rules to predict what lies ahead and to prescribe how to take advantage of this predicted future without compromising other priorities.

Predictive Analytics

Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.

Predictive models identify patterns found in historical or transactional data to identify risks and opportunities. Models capture relationships among multiple factors to allow assessment of risk or potential associated with a particular set of conditions. The defining functional effect is a predictive or probability score for each.

One of the best-known applications is credit scoring, which is used throughout financial services. Scoring models process a customer’s credit history, loan application, customer data, etc., in order to rank-order individuals by their likelihood of making future credit payments on time.

Descriptive Analytics

Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and prepare the data for further analysis. Descriptive analytics is sometimes said to provide information about the past or what happened.

The vast majority of the statistics used today fall into this category. (Like sums, averages, or percentages).  For all practical purposes, there are an infinite number of these statistics. Descriptive statistics are useful to show things like, total stock in inventory, average dollars spent per customer and Year over year change in sales. Common examples of descriptive analytics are reports that provide historical insights regarding the company’s production, financials, operations, sales, finance, inventory and customers.

Descriptive, Predictive & RX


Companies are studying historical information, forecasting the future, and even getting  recommendations for a next move by using data and analytics. Data driven organizations have an edge over their competitors and enjoy returns on their investment which include optimizing supply chains, lowered operating costs, and increased revenues.

Reviewing all of the available analytic options can be daunting. However, analytics can be categorized at a high level into three distinct types. No one type of technique is better than another. Actually, they work best when used together. The three types are:

  1. Descriptive Analytics-What has happened
  2. Predictive Analytics-What might happen
  3. Prescriptive Analytics-Recommendations of what to do

Join us as we define the meaning of each of these three types of analytics.

Social Media Marketing

In 2018, artificial intelligence (AI) and augmented reality (AR) began to take off and major catastrophes caused online hesitation such as data breaches, interference in elections, and world leader arguments on Twitter.

From small businesses to major corporations, every business needs to have a social media marketing plan. It’s not necessary to have photography staff or a video production studio in order to keep up with the latest social trends. Keeping your finger on the pulse concerning where your clients are and what they are responding to is necessary.

Brand professionalism, voice, authenticity, and trustworthiness matter more than ever.

There have been more than 3,500,000,000 live videos on Facebook since “going live” was first introduced to the platform. Over 2 billion people have watched live videos. This trend is just getting started.

“Stories” are potentially the next stage of social media as we know it.  Mark Zuckerberg stated in January that views to stories will surpass newsfeed views this year.   FOMO (fear of missing out) is a marketing buzzword that is gaining credibility.   200 million Instagram users use Instagram Stories each month.

Facebook, YouTube, and Instagram have emerged as the top platforms for video marketing, and audiences are responding more than ever. With the launch of long-form, vertical videos on IGTV from Instagram and continued new options for YouTube Creators, video is evolving fast.