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12 authentic ways to receive better online reviews (Infographic) 0

Posted on October 28, 2018 by Rob Petersen

Better online reviews

Better online reviews are now a key consideration for every organization, brand, doctor, lawyer, contractor, caterer, hotelier, restaurant owner and human resource department. And for good reason:

The facts show better online review influence our buying decisions and impact revenue for every kind of business. But any business is not above getting a negative review and figuring out how to deal with it. Some even resort to writing their own positive reviews. Do they work? Hardly.

How does a business get better online review authentically? Jessica Leone, an unapologetic word nerd, bookworm and Florida Gators football fan, let us know in an infographic she created, How to Get More Positive Reviews (and Deal with the Negative).

Here is a brief summary how to get more positive reviews and deal with the negative.

  1. HAVE A CLEAR CALL-TO-ACTION ON YOUR SITE: Make it easy for people to see and go to where they can write a review.
  2. SAY THANK YOU: A simple thank you page to customers with a request they leave a review goes a long way.
  3. SEND A PERSONALIZE TEXT OR EMAIL: Ask if they will leave a review when your business and their experiences are still fresh.
  4. SOCIAL MEDIA IS YOUR FRIEND: Use a display plug-in to share social media reviews.
  5. FACE-TO-FACE: Asking in person for a review is 7X more effective than asking by email.
  6. TALK TO VENDORS: For B2B industries, ask vendors and suppliers. 7 out of 10 people will leave a review if they are asked.
  7. CONSIDER AN INCENTIVE: Zappos Rewards Program gives members 100 points toward products for leaving a review.
  8. TIMING IS EVERYTHING: Ask consumers to leave a review when they are likely to be at their happiest. American Express found a happy customer will tell 9 other people about their experience.
  9. SEND A FOLLOW UP: 20% to 25% of Esty purchases result in a review because they send a follow up email or text.
  10. ALWAYS RESPOND: Whether positive or negative, respond to reviews. Harvard Business Review found hotels that respond receive 12% more reviews and their ratings increase.
  11. REACH OUT TO A NEGATIVE REVIEWER DIRECTLY: 78% of consumers who receive a response believe the business cares about them.
  12. SPREAD POSITIVE REVIEWS: Share and promote reviews on your website and social networks.

Here is the infographic.

Better Online Reviews Infographic

Are these ways useful to you to get better online reviews?

9 artificial intelligence case studies show companies the money 0

Posted on October 14, 2018 by Rob Petersen

artificial intelligence case studies

Artificial intelligence case studies demonstrate the many ways companies are using AI to increase sales, productivity, speed, efficiency, segmentation, targeting, compliance, conversions, create new products and, of course, generate significant business growth.

Artificial intelligence is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

These artificial intelligence case studies show AI’s breadth, innovation and business return.

Here are 9 artificial intelligence case studies that show companies the money.

  1. ALIBABA GROUP: Is a Chinese multinational conglomerate specializing in e-commerce, retail, Internet, AI and technology. Among companies is our artificial intelligence case studies, Alibaba uses AI to help map the most efficient delivery routes. Works quite well! And Alibaba claims that smart logistics have resulted in a 10% reduction in vehicle use and a 30% reduction in travel distances.
  2. AMAZON: Alexa is one of Amazon’s most popular and most famous AI product. It helps drive the algorithms that are essential to Amazon’s targeted marketing strategy. AI allows Amazon to predict what products will be the most demanded to provide customized recommendations based on customer searches. And according to rejoiner, Amazon’s recommendation engine drives 35 percent of total sales.
  3. COCA-COLA: Coca-Cola Amatil is the largest bottler and distributor of non-alcoholic, bottled beverages in the Asia Pacific. Coca-Cola Amatil was relying on limited and manual measurements of products in store, as well as delayed data sourced from phone conversations. Coca-Cola Amatil sales reps used Trax Retail Execution image-based technology to take pictures of stores shelves with their mobile devices; these images were sent to the Trax Cloud and analyzed, returning actionable reports within minutes to sales reps and providing more detailed online assessments to management. Coca-Cola Amatil gained 1.3% market share in the Asia Pacific region within five months.
  4. COGNIZANT: Is a multinational corporation that provides IT services. Cognizant Digital Business has developed an AI-driven machine learning solution for the compliance function at a leading healthcare services provider that parses doctors’ notes entered into the organization’s electronic medical records (EMR) to identify potential drug-seeking behavior. Opioid dependency is devastating for patients and their families. In our artificial intelligence case studies, Cognizant’s system uses text analytics and an advanced machine-learning algorithm to mine physicians’ notes and electronic medical records. alerts doctors during patients’ visits when a pattern of at-risk behavior is identified. So far, 85,000 at risk patients have been identified through this system with savings to organizations of $60 million.
  5. GLOBAL TECH LED: Is a LED lighting design and supplier to U.S. and international markets, specializing in LED retrofit kits and fixtures for commercial spaces. The company used Google Analytics’ Smart Lists in our artificial intelligence case studies to automatically identify Global Tech LED prospects who were “most likely to engage” and to remarket to those users with more targeted product pages. They used Google’s Conversion Optimizer to automatically adjust potential customer bids for increased conversions. Remarketing campaigns triggered by Smart Lists drove 5 times more clicks than all other display campaigns. Traffic to the company’s website grew by more than 100%, and was able to re-engage users in markets in which it was trying to make a dent, including South Asia, Latin America, and Western Europe.
  6. JD.COM: Beijing-based JD.com partnered up with Siasun Robot & Automation Co Ltd. to use automation technology, such as robots, to improve warehouse operations. The key idea was to improve the speed and efficiency of product sorting and delivery in warehouses, cutting down the costs and increasing revenue.   According to Techemergence, after implementing this new initiative, a number of online orders reached 1.26 billion in 2015 (double the amount of orders in 2014) and approximately 85% of those orders were delivered within two days. Unfortunately, JD.com aims to use Artificial intelligence to reduce the number of employees from approximately 120,000 to 80,000 over a decade to increase efficiency, by reducing manual work and therefore increasing profit margin.
  7. PETER GLENN: has provided outdoor apparel and gear to individual and wholesale customers for over 50 years, with brick-and-mortar locations along the east coast, Alaska, and South Beach. Peter Glenn used AgilOne Analytics for advanced segmentation abilities included data on customer household, their value segment, and proximity to any brick-and-mortar locations. Peter Glenn saw a 30% increase in Average Order Value (AOV) as a result of its automated marketing campaigns.
  8. RAKUTEN: Japan’s largest e-commerce site, Rakuten, continues to invest in AI to better predict customer behaviors as it is critical to the e-commerce success. Right now, with their Rakuten Institute of Technology, they are able to analyze their 200 million products to forecast sales with a high degree of accuracy. Now they are also capable of segmenting buyers more accurately using real-time data.
  9. UNDER ARMOUR: An American manufacturer of sports footwear and apparel,  built a UA Record™ app was built using the IBM Watson Cognitive Computing platform. The “Cognitive Coaching System” was designed to serve as a personal health assistant by providing users with real-time, data-based coaching based on sensor and manually input data for sleep, fitness, activity and nutrition. The app has a rating of 4.5 stars and grew revenue for Connected Fitness accessories by 51% to $80 million.

Do these artificial intelligence show you the money? Are you ready to see how AI can be used at your company?

Should your company have a Wikipedia Page? 8 Pros and Cons 0

Posted on October 07, 2018 by Rob Petersen

wikipedia page

Wikipedia page for a company increases recognition and notability. It adds credibility to any business.

A Wikipedia page is a web page on world’s best known encyclopedia created, edited and updated by volunteers. It contains over 4,500,000 articles in English, but there are many more in 280 languages.

10,000 articles are read each day and 500 million people read it every month. But Wikipedia has no formal editors or formal peer review process. A Wikipedia page is not for every business or organization.

Should your company have a Wikipedia page? Here are 8 Pros and Cons.

PROS

  1. INCREASES CUSTOMER CONSIDERATION:  Because Wikipedia is a third-party, public website, information on your Wikipedia page may be more valuable to a potential customer than some of the information on your website.
  2. RAISES SEARCH ENGINE PRESENCE AND RANK: A Wikipedia page has high authority and usually a top rank for a brand or business name. A link from Wikipedia to your website is a valuable link.
  3. ESTABLISHES OWNERSHIP: If you think someone might create a Wikipedia page about your company that reflect a bias, then don’t let that happen and be the one to create it, first. Although you can’t control what other might say on it, at least it is yours to direct and attempt to keep correct.
  4. CONTROLS INFORMATION: Each edit or update of wiki information is recorded in the wiki software. If wrong information is edited, the software can easily revert the changes to the previous version.
  5. IS TIMELY: Information is updated online so you don’t have to wait for a particular publisher to update the information.
  6. PROVIDES REFERENCES: Wikipedia page contains references for all documents linked to the wiki information. This increases recognition and notability.
  7. IS FREE: There are no cost to create a Wikipedia page and no licensing or subscription costs required for installing institutional wiki.
  8. HAS FLEXIBILITY: The program has no any predetermined structure, it can be used for a variety of applications.

CONS

  1. ANYONE CAN EDITS: Anyone can add and edit Wikipedia entries, so information could be incorrect or deliberately false.
  2. LACK OF CONFIDENTIALITY: It is difficult to access user rights. Confidential information can get to the wrong persons since anybody can edit the information in Wikipedia.
  3. MONITOR FOR ACCURACY: Because of the first couple of cons, you’re going to have to regularly be examining your Wikipedia page for accuracy.
  4. NEGATIVE TESTIMONY: People who had bad experiences may come and talk about the negative sides of your business, and the editing staff is going to take a long, hard look at what’s going on if they see you deleting every bad thing someone else says
  5. MAY NOT GET A UNIQUE COMPANY PAGE: An editor may decide that your content would be better if merged into an article on similar businesses, rather than giving you a unique place on the web. This is a risk especially if you are a small business or start-up.
  6. NOT ALL ACHIEVEMENTS ARE NOTEWORTHY: A Wikipedia page cannot be promotional. If your company has just achieved a million dollars in sales, that’s not especially noteworthy for Wikipedia. If your company is a medical device that has saved a million lives, that’s a more relevant achievement.
  7. CITATIONS MATTER: Generally speaking, topics with multiple independent citations are considered worth having a unique page. Try for a minimum of four. The more you have, the better. The quality of the citations also matters. A small mention in your local newspaper is not a noteworthy citation. Exposure in a major national magazine might be.
  8. PAYMENTS MUST BE DISCLOSED: If you paid someone to create a company Wikipedia page, this has to be disclosed.

Is your company considering a Wikipedia page? Do these Pros and Cons help?

6 essential steps to the data mining process 0

Posted on October 01, 2018 by Rob Petersen

Data Mining Process Illustration

Data mining process is the discovery through large data sets of patterns, relationships and insights that guide enterprises measuring and managing where they are and predicting where they will be in the future.

Large amount of data and databases can come from various data sources and may be stored in different data warehousess. And, data mining techniques such as machine learning, artificial intelligence (AI)  and predictive modeling can be involved.

The data mining process requires commitment. But experts agree, across all industries, the data mining process is the same. And should follow a prescribed path.

Here are the 6 essential steps of the data mining process.

1. Business understanding

In the business understanding phase:

  • First, it is required to understand business objectives clearly and find out what are the business’s needs.
  • Next, assess the current situation by finding the resources, assumptions, constraints and other important factors which should be considered.
  • Then, from the business objectives and current situations, create data mining goals to achieve the business objectives within the current situation.
  • Finally, a good data mining plan has to be established to achieve both business and data mining goals. The plan should be as detailed as possible.

2. Data understanding

  • The data understanding phase starts with initial data collection, which is collected from available data sources,  to help get familiar with the data. Some important activities must be performed including data load and data integration in order to make the data collection successfully.
  • Next, the “gross” or “surface” properties of acquired data need to be examined carefully and reported.
  • Then, the data needs to be explored by tackling the data mining questions, which can be addressed using querying, reporting, and visualization.
  • Finally, the data quality must be examined by answering some important questions such as “Is the acquired data complete?”, “Is there any missing values in the acquired data?”

3. Data preparation

The data preparation typically consumes about 90% of the time of the project. The outcome of the data preparation phase is the final data set. Once available data sources are identified, they need to be selected, cleaned, constructed and formatted into the desired form. The data exploration task at a greater depth may be carried during this phase to notice the patterns based on business understanding.

4. Modeling

  • First, modeling techniques have to be selected to be used for the prepared data set.
  • Next, the test scenario must be generated to validate the quality and validity of the model.
  • Then, one or more models are created on the prepared data set.
  • Finally, models need to be assessed carefully involving stakeholders to make sure that created models are met business initiatives.

5. Evaluation

In the evaluation phase, the model results must be evaluated in the context of business objectives in the first phase. In this phase, new business requirements may be raised due to the new patterns that have been discovered in the model results or from other factors. Gaining business understanding is an iterative process in data mining. The go or no-go decision must be made in this step to move to the deployment phase.

6. Deployment

The knowledge or information, which is gained through data mining process, needs to be presented in such a way that stakeholders can use it when they want it. Based on the business requirements, the deployment phase could be as simple as creating a report or as complex as a repeatable data mining process across the organization. In the deployment phase, the plans for deployment, maintenance, and monitoring have to be created for implementation and also future supports. From the project point of view, the final report of the project needs to summary the project experiences and review the project to see what need to improved created learned lessons.

These 6 steps describe the Cross-industry standard process for data mining, known as CRISP-DM. It is an open standard process model that describes common approaches used by data mining experts. It is the most widely-used analytics model.

Do these 6 steps help you understand the data mining process? What is your organization’s readiness for date mining?

30 astonishing facts about Amazon customer loyalty 0

Posted on September 17, 2018 by Rob Petersen

amazon customer loyalty

The purpose of a business is to create and keep a customer. – Peter Drucker

Based on Peter Drucker’s wisdom, customer loyalty is one of a company’s most important assets. That goes for any company. Even, or especially, Amazon.

How loyal are Amazon’s customers? Here are 30 astonishing facts about Amazon customer loyalty.

  1. 95% of Prime members say they would “definitely” or “probably” renew their memberships.
  2. 94% of Survey Monkey’s audience say they’ve heard of Amazon Prime and 70% have used Amazon Prime.
  3. 95% of Amazon users always or sometimes read full product descriptions before purchasing.
  4. Almost 90% of Amazon customers say they would not consider purchasing a product with less than 3 stars.
  5. 85% of Prime shoppers visit Amazon at least once a week or more, that number drops to 56 percent for non-Prime members going to Amazon at least once a week.
  6. Nearly 80% of Amazon customers say they trust Amazon’s shipping more than packages shipped by a third-party seller to show Amazon customer loyalty.
  7. 75% of people who shop on Amazon use the Amazon search box.
  8. 69% of Whole Foods shoppers are Prime members to show Amazon customer loyalty with this acquistion.
  9. 65% of Amazon shoppers rank price as the most important factor, above faster shipping, free shipping and better product assortment.
  10. 63% of Amazon customers are Prime members to prove Amazon customer loyalty.
  11. 60% of Amazon customers say they wouldn’t consider purchasing items with less than a 4 ½ star rating.
  12. 59% of shoppers across 27 countries bought items on Amazon.com last year.
  13. 54% of people who buy on Amazon always read the full product description.
  14. 51% of Amazon customers come to the site to compare prices.
  15. 46% of Prime members say they buy on Amazon at least once a week.
  16. 44% of Amazon customers say they will always check prices on Amazon before purchasing on another site as a demonstration of their Amazon customer loyalty.
  17. 43% of all online sales come from Amazon.
  18. 43% say they would pay $10 or more for delivery within an hour while 32% would pay $10 or more for same-day shipping.
  19. 33% of Amazon users come to the site ready to buy
  20. 31% of Prime members go to amazon.com daily.
  21. 30% of Prime members said they ordered products weekly on Amazon in 2016, which grew to 46% in 2017.
  22. 24% of Amazon’s North American retail revenues can be attributed to consumers who first tried to buy an item at stores but found their local stores out-of-stock.
  23. 22% of Amazon users are now more likely to purchase their groceries via the giant marketplace, because of the Whole Foods acquisition, and 37% will consider it.
  24. 7.5% of Seattle’s working age population are Amazon employees.
  25. 13% of people who are not Prime member buy from Amazon weekly.
  26. 1.6 million packages are shipped every day from Amazon.
  27. 45,000 robots roam Amazon’s floors.
  28. #8 most reputable firm in U.S. and #18 in the world.
  29. Amazon is more valuable than all brick and mortar retailers combined.
  30. Amazon Prime offer discounts to everyone on government assistance.

Do these facts convince you of Amazon customer loyalty? Does your business need to improve its customer loyalty?

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