Tag Archives: BLOG WITH BEB

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.

 

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.

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.

The Bureau 2015 Year in Review

THE BUREAU BANNERRON BIO PIC

2015 was a year of tremendous change at BEB. As many of you already know, my father and former President Emeritus Robert “Bob” Royall passed away in November. We are a family owned business.  My brother Ro (Executive Vice President) and I had the pleasure of running the operation alongside my father for over 20 years. His passing has had a profound and lasting impact on all of us, and his legacy remains strong. Thank you to everyone that reached out to us regarding our loss. We are deeply moved by the outpouring of condolences, and appreciated hearing so many stories about how my father touched so many lives. As we sustain the solid foundation of the company he cultivated, we face the coming year with confidence and clear direction. He is deeply missed.

Our business continued to transform during 2015. Existing clients required a deeper, moreBOB WITH THE BOYS BUSINESS EXTENSION BUREAU'S THE BUREAU comprehensive relationship and demanded broader service offerings to meet their needs. Data acquisition and mining increased over the past year, as did our digital fronts including, website design, email marketing and social media services. We saw a steady growth in printing (digital, offset and large format), and direct mail climbed doubled digits as our clients continue to see the value of direct mail marketing.

Based on the current political and economic climate, we anticipate the coming year to be a challenge on many levels. We believe that marketing dollars will be scrutinized, campaigns will be more closely monitored, and higher returns expected. As a result, our goal for 2016 is to continue expansion of our service offerings while strengthening our core competency as a marketing production company. Because we believe that companies will expect more from fewer people, the need for a partnership with our clientele is more valuable than ever. We will continue to be extremely agile and promise to develop stronger connections with you, our valued clients and partners.

This marks our 4th year of the annual “Year in Review” edition of The Bureau. In this issue, we’ll introduce you to our newest Business Development Manager, Kathy N. Hall, formerly with the United Postal Service, we’ll reveal some new service offerings and review highlights from the past year. We included updates on postal rate increases, and changing marketing patterns within the social media world as well as information on our upcoming Marketing for Small Business Seminar Series- The Basics (blogging, social media, email marketing and SEO) that started in February.  In April we offer three new intermediate classes that focus on social media for business on Twitter, LinkedIn and Facebook.

We hope your 2016 is a great year, and thank you for your business and partnership.

Sincerely,    YEAR IN REVIEW COLLAGE

Signature - Ron Royall

 

Ron Royall – CEO