Democrats Avert Disaster in Crucial Calif. Primaries

With their solid showing in this week’s California primaries, Democrats cleared a major hurdle in their bid to take control of the House of Representatives in November.

 The party avoided its worst-case scenario: Being shut out of several potentially competitive races because of California’s unusual primary system, which advances the top two vote-getters, regardless of party, to the general election. On occasion, this leads to races in which two candidates from the same party face off on Election Day.

Democratic leaders fretted about this possibility more and more as primary day drew nearer, envisioning a scenario in which their abundant candidate pool cannibalized itself to Republicans’ advantage. California Democratic Party Chairman Eric Bauman said he expected Democrats to be shut out of “at least a couple” of what should be competitive races in the fall.

Elevated Democratic turnout and machinations by party leaders to steer voters toward candidates they think had the best shot of winning, in some cases by badgering others to drop out of the race, allowed the party to avoid disaster.

The outcome ensures several vulnerable Republican-held seats are still in play, including seven that 2016 Democratic presidential nominee Hillary Clinton won. Democrats need to gain at least 23 seats to win control of the House, which Republicans wrested from Democratic control after the 2010 midterms. They can’t flip the House without California.

But it was far from a victory for the party. Democrats burned through a lot of cash just guaranteeing their candidates slots on November’s ballot. The Democratic Congressional Campaign Committee (DCCC) has spent at least $5.6 million in the Golden State this election cycle, at one point even giving money to Republican candidates in the hopes of splitting the GOP vote.

There was a silver lining for Republicans, who are not accustomed to good news in the state leading the “resistance” to Donald Trump’s presidency.

GOP candidates received a majority of the vote in all but one of the state’s key battleground districts. Granted, they underperformed compared to previous election years. Meanwhile, Democrats will likely do much better in the general election, when their voters are more likely to show up.

But Democrats have only proven they will be able to compete come November. They are targeting 10 seats, which Republicans will not give up easily. One vulnerable Republican, Rep. David Valadao, who represents an increasingly liberal district that voted for Clinton in 2016 and President Obama twice, already looks like a strong bet for re-election.

Furthermore, Republicans were not locked out of all major statewide races, which would have depressed their turnout in the general election. Republican John Cox stands little chance of becoming California’s next governor, but he will square off against Lt. Gov. Gavin Newsom Nov. 6. Democratic Sen. Dianne Feinstein, by contrast, will have no GOP challenger since fellow Democrat Kevin De Leon came in second on Tuesday.

Democrats and Republicans are both spinning the results. In reality, the status quo won. Neither party gained a clear advantage, and the fundamentals of this midterm election did not shift: The House of Representatives is up for grabs; Democrats will gain seats but are not guaranteed enough for a majority; and Republicans will vigorously defend their turf.

Pay attention to the generic ballot, which is starting to swing back in the Democrats’ favor after months of improving numbers for Republicans. With Trump in the White House, the GOP is running on one of the strongest economies in years. If that doesn’t help vulnerable Republican incumbents win re-election, nothing will.

What Businesses Should Do With Artificial Intelligence

Artificial intelligence (AI) improves prediction. AI is computer software that learns, finding complex patterns in massive amounts of data. Improving predictions is obviously very useful for most businesses, with a wide range of applications. For example, AI is helping industries from manufacturing to air travel predict when key equipment or airplane parts will fail, reducing downtime. A servicer of printers and copiers can determine when they will run out of toner, based on how many and what types of print jobs are done. The machines will automatically order more just-in-time toner, preventing waste from replacing toner cartridges too early. Google Translator AI “predicts” (recognizes) equivalent speech in different languages. In all of these examples, the AI gets better as it takes in more data, or “learns.”

But businesses can throw a lot of money at AI simply because it’s the “in” thing. So, owners must improve the odds of success.

First, figure out what problem you want AI to solve. What mission critical information are you dying to know? The problem may not require a solution as complex as AI. Basic snags could simply require statistical analysis, such as linear regression. Another key question to ask yourself: Has AI ever been used before for that application? If not, then being the first may be a tad costly. Run small experiments to determine usefulness before committing to a massive project.

Second, do you have good data to work with? Remember the GIGO principle: If the data are old, unstructured or disjointed, then you’re not going to get good results, period. And you need a lot of data—AI is only useful when it has much to work with because its whole purpose is identifying complex patterns in large data sets. Thousands of data points are a minimum, and millions are best. Also, your data needs to be labelled so a machine can understand what it is. Provide the context that is creating the data from the start so that the AI doesn’t make a boneheaded mistake, such as treating Christmas-time sales as the normal monthly level.

Third, AI learns or evolves with experience in real world operations. It will be wrong at first. So, does the application allow room for growth, or is it so important that it has to be right the first time? AI cannot be perfected solely based on in-house training data.

Fourth, AI requires development—there is no AI “plug and play.” It is unlikely that a company has the expertise to do this in-house. So, finding the right contractor that has the specific knowledge for a particular problem is important. Trusting the contractor is key: AI programs are not very good at explaining how they got their results, so you’ll have to take the contractor’s word for it. Have your experts examine vendors’ results and evaluate both their accuracy and usefulness. Today’s main AI platforms are IBM’s Watson, Amazon Machine Learning (part of Amazon Web Services), Microsoft’s Cortana Intelligence Suite, and Google Cloud Platform. (A website listing a plethora of specialized AI vendors follows below.)

Finally, don’t relegate AI to the IT department. AI will boost worker productivity, but it can also shed light on what lines of business strategy to choose, so CEOs should be fully informed.

Some AI vendors worth a look:

https://appliedai.com/vendors/1

Applications:

Health care: https://www.techemergence.com/machine-learning-healthcare-applications/

Finance: https://www.techemergence.com/machine-learning-in-finance/

Advertising and marketing: https://www.techemergence.com/artificial-intelligence-in-marketing-and-advertising-5-examples-of-real-traction/

Justice Dept. Trumps Blockbuster AT&T, Time-Warner Deal on Antitrust Grounds

The Justice Department moved this week to block AT&T’s proposed merger with Time Warner Cable. Now, the courts must decide the fate of the blockbuster deal that, if approved, would give America’s largest telecom company control over a media empire that includes CNN, HBO and other cable staples.

Will the merger go through? Flip a coin. This isn’t how antitrust cases of this kind normally proceed. The Justice Department regularly blocks transactions it deems “anti-competitive,” among them AT&T’s 2011 bid to acquire rival T-Mobile. But so-called “vertical mergers,” which involve firms operating at two different levels of an industry, have a better record of success.

Continue reading “Justice Dept. Trumps Blockbuster AT&T, Time-Warner Deal on Antitrust Grounds”

Trump’s Travel Ban: Third Time Not a Charm

It’s deja vu all over again for President Trump’s travel ban. This week, a federal court in Hawaii blocked the latest version of the president’s controversial executive order from going into effect, only seven months after the same court put a similar hold on Trump’s second travel ban.

Much has happened in those seven months. After multiple unfavorable lower level rulings, the second ban finally reached the Supreme Court this summer. But the justices ultimately declined to hear the case during the court’s fall session, arguing that the issue was moot since the order had already expired.

Continue reading “Trump’s Travel Ban: Third Time Not a Charm”

Advertising in the Digital World

Advertising on the internet is now bigger than on TV and is growing fast. Many businesses are jumping on the internet and social media bandwagon to hawk their wares, or just to build brand awareness. Some advice for businesses:

Stick your toe in the water by building brand awareness on social media.  Advertising on Facebook is cheaper than on Google, and is best for expanding your business’s online visibility. Ads appear in Facebook’s news feed and can be targeted by location, language, age, gender, workplace, college, interests, relationship status, education level, college major or your own email lists. Eighty percent of the time, Facebook is viewed on smartphones, where simple branding-type ads work best. However, product-selling ads are also used. Ads that require the customer to input lots of information, such as financial services ads, should be targeted only at desktop computers.

A trial ad campaign can be set up for as little as $1 per day, though $5 to $30 per day is better to gauge effectiveness. If you’re going to go to the trouble of producing decent ads, then you’ll want to give them a good test. Facebook will generate metrics for you, such as number of clicks, likes and shares. The average cost-per-click for Facebook ads is 28 cents in the U.S. Test multiple versions of ads to see which generates the most response. A company like AdEspresso will help you design effective Facebook ads, if you need help.

Google AdWords is a little more expensive, but also gets lots of attention. Ads can be assigned to certain search words, or products can be advertised in Google’s Shopping Ads (Product Listing Ads or PLA). Amazon also has a large reach. Other social media platforms include Instagram, Snapchat, Pinterest and Twitter, but the limitations of each of these needs to be considered.

To save time, consider using an advertising management platform like Hootsuite, Salesforce or Nanigans, which allow you to automate a lot of the ad process. Other companies will help you design ads or both design and manage the entire marketing effort. For larger campaigns, third-party ad management can drive the cost-per-click below 1 cent. The trick is to spend enough on an ad in order to have it appear with reasonable frequency, but not to overspend.

A search engine optimization (SEO) expert can help drive your company up the search rankings in Google, ensuring that users see your website.

Native advertising is growing as a share of ad spend, as opposed to banner ads, which can suffer from “banner blindness.” Native advertising contains content that is related to the same topics as the regular content on a website. It often consists of a product testimonial or description written by the advertiser. The idea is to provide an informational service as well as advertising, which may garner more attention from viewers.

Progressive web apps are gaining ground at the expense of regular apps. It is becoming apparent that, on average, consumers use only seven apps on their mobile phones and ignore the rest. Apps can be a hassle because consumers must download updates and revalidate their accounts. But apps are still valuable because they result in a lot of online orders, if you can get customers to use them. Because of this, Google has developed progressive web apps. These are versionless apps that work just like accessing the web via a browser and never have to be updated. Apple has been reluctant to compromise its revenue selling traditional apps, but is likely to come around, eventually.

Retail outlets and restaurants will especially want to pay attention to their Google Maps listing, which also has star ratings. Currently, these have a small number of reviewers leaving comments, so just a few can have a large effect on the overall rating, for better or for worse.

Use closed captioning on video ads. Many people don’t turn on the sound on their computer and so don’t pay attention to muted videos that play automatically.

In electronic gaming, rewards advertising is rapidly gaining ground. This is advertising that promises an in-game reward, such as game “money,” abilities or lives in return for a willingness to view the ad first: A good way to get the attention of an increasingly video game-addled population.

 

Hurricane-Proofing a City: How Houston Should Prepare for the Next Big Storm

Houston is still reeling from Hurricane Harvey, a record-breaking tropical storm that has drenched the Texas coast with an estimated 21 trillion gallons of water since Aug. 25 and inflicted untold damage on both lives and property.

As with previous hurricanes, many people are asking: What could have been done differently this time to mitigate the damage? And what can be done to prepare for the next storm?

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How Small Merchants Can Fend Off Costly Cyberattacks

Cyber crooks are increasingly launching attacks at the cash register. The payment terminals and company computer systems used by small businesses are a window into customer credit card data and other sensitive info.

“The bad guys are moving to an easy target: The small- and medium-sized business community,” says Stephen Orfei, the general manager of the Payment Card Industry (PCI) Security Standards Council, a group formed in 2006 by the major credit card companies to create payment security standards. A digital attack can be devastating for a small business that lacks the deep pockets and technical prowess of a big company. Continue reading “How Small Merchants Can Fend Off Costly Cyberattacks”

Who Profits from the Next Billion Internet Users?

Tech companies are eyeing a huge new market: The next billion customers coming online for the first time by 2022, mainly in India, China, Indonesia, parts of Africa and other developing regions.

Falling costs and improving technology are making it possible. Low-cost smartphones, running $100 or less, make mobile broadband far more accessible to consumers with little income. Chinese manufacturers such as Huawei, Xiaomi and ZTE are flooding the market with cheap but capable handsets, almost all of them running Google’s Android operating system. Plus, steady advances in wireless radio antennas and other telecom equipment make it cheaper and easier to build mobile networks with faster speeds, more coverage and lower data prices. Continue reading “Who Profits from the Next Billion Internet Users?”