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AI can predict risk of a heart attack in the next year from a routine eye scan

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By Jeanna Vazquez

An artificial intelligence system is capable of spotting whether someone will have a heart attack within the next year — through a routine eye scan.

A team from the University of Leeds believes this AI tool opens the door to a cheap and simple screening program for the world’s No. 1 killer. Their tests find the computer can predict patients at risk of a heart attack in the next 12 months with up to 80% accuracy. The breakthrough adds to evidence that our eyes are not just “windows to the soul,” but windows to overall health as well.

“Cardiovascular diseases, including heart attacks, are the leading cause of early death worldwide and the second-largest killer in the UK. This causes chronic ill-health and misery worldwide,” project supervisor Professor Alex Frangi says in a university release.

“This technique opens-up the possibility of revolutionizing the screening of cardiac disease. Retinal scans are comparatively cheap and routinely used in many optician practices. As a result of automated screening, patients who are at high risk of becoming ill could be referred for specialist cardiac services,” Frangi adds.

Looking at the retina to discover red flags in the heart

The retina is a small membrane at the back of the eye containing light sensitive cells. Doctors have found that changes to the tiny blood vessels can hint at vascular disease, including heart problems.

Study authors used an advanced type of AI, known as deep learning, to teach the machine to automatically read more than 5,000 eye scans. The scans come from routine eye tests during visits to opticians or eye clinics. All of the participants are part of the UK Biobank, which tracks the health of half a million adults.

“The system could also be used to track early signs of heart disease.”

Deep learning is a complex series of algorithms that enable machines to make forecasts based on patterns in data. The technique, described in the journal Nature Machine Intelligence, could revolutionize heart therapy, according to the researchers.

“The AI system has the potential to identify individuals attending routine eye screening who are at higher future risk of cardiovascular disease, whereby preventative treatments could be started earlier to prevent premature cardiovascular disease,” says co-author Professor Chris Gale, a consultant cardiologist at Leeds Teaching Hospitals NHS Trust.

The study identified associations between pathology in the retina and changes in the patient’s heart. Once the system learned each image pattern, the AI could estimate the size and pumping efficiency of the left ventricle from retinal scans alone.

This is one of the heart’s four chambers. An enlarged ventricle can increase the risk of heart disease. The computer combined the estimated size of the left ventricle and its pumping efficiency with data like age and sex.

The eyes are revealing a lot about disease and death

Currently, doctors determine this information using an MRI (magnetic resonance imaging) or echocardiography scans of the heart. The diagnostic tests are expensive and are often only available in a hospital. The tests can be inaccessible for many people in countries with lesser health care systems. They also increase health care costs and waiting times in wealthy nations.

“The AI system is an excellent tool for unravelling the complex patterns that exist in nature, and that is what we have found – the intricate pattern of changes in the retina linked to changes in the heart,” adds co-author Sven Plein of the British Heart Foundation.

A recent study discovered a similar link between biological aging of the retina and mortality. Those with a retina “older” than their actual age were up to 67% more likely to die over the next decade.

Feature Image: Their tests find the computer can predict patients at risk of a heart attack in the next 12 months with up to 80% accuracy. (CREDIT: Getty Images)

By Jeanna Vazquez

Sourced from Brighter Side of News

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How AI Is Transforming The Future Of Digital Marketing

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By Bernard Marr

When people think about artificial intelligence (AI) today, they might think of computers that can speak to us like Alexa or Siri, or grand projects like self-driving cars. These are very exciting and attention-grabbing, but the reality of AI is actually thousands of tools and apps running quietly behind the scenes, making our lives more straightforward by automating simple tasks or making predictions.

This is true across every industry and business function, and particularly true in marketing, where leveraging AI to put products and services in front of potential customers has been standard practice for some time, even though we may not always realize it!

In business today, the term AI is used to describe software that is capable of learning and getting better at doing its job without input from humans. This means that while we’ve become used to using machines to help us with the heavy lifting, now they can start to help us with jobs that require thinking and decision-making, too.

A huge number of questions that would previously have needed human intervention to answer – such as “will this person be interested in my products?” or “what results will I get from this advertising campaign?” can now be answered by machines – if they are given the right data. And because machines can answer questions far more quickly than humans, they can easily chain together complex strings of queries to come up with predictions, such as who is most likely to buy your products and where the best places to advertise might be.

That’s the basic principle behind all business AI today – automating the processes of learning and decision-making in order to create knowledge (usually referred to as “insight”) that helps to improve performance. And marketing is one area where it’s certainly been put to good use!

Targeted marketing

The high-level use case for AI in marketing is that it improves ROI by making your marketing – often one of a company’s biggest expenses – more efficient. In the old days, before online advertising, businesses would pay huge amounts of money for TV, radio, or newspaper adverts, in the full knowledge that only a small number of the people who saw their ads would ever become customers. This was tremendously inefficient, but companies didn’t have any choice if they wanted to position themselves as market leaders.

In the online age, we’ve developed the ability to learn a great deal about who is or isn’t interested in our products and services. The first breakthroughs came thanks to the likes of Amazon with their recommendation engine technology and Google and Facebook with their targeted advertising platforms. Today, each of those platforms has been augmented with machine learning technology that allows them to become increasingly effective as they are fed more data on customers and their buying habits.

AI-driven content marketing

The rise in social media marketing and our growing appetite for online content has made content-based marketing the dominant form of marketing in many industries. AI lends a hand here by helping us work out what type of content our customers and potential customers are interested in and what the most efficient ways are to distribute our content to them. Advertising creatives have always strived to find formulas for creating adverts that will get people talking and sharing the message with their friends. Now, this can be done automatically using any number of AI-powered tools. For example, headline generation algorithms that monitor how successful they are and tweak their output to achieve better metrics, such as the open rate of emails, or the share rate of social media posts.

Taking this a step further, AI is developing the ability to take care of the entire content generation process itself, creating copy and images that it knows are likely to be well-received by its audience. A huge buzzword in this space will be personalization – where individual customers are served content that’s specifically tweaked to them, perhaps using information and reference points that the AI knows are relevant to them, intertwined with the overall marketing messages.

AI will also increasingly be useful for identifying what stage of the buying process a customer is at. If it detects that they are “shopping around” – comparing products and services that are available – it can serve content designed to differentiate your product or service from those of competitors. If it detects that they are ready to make a purchase, it can target them with promotions urging them to “act now” to take advantage of a limited-time offer.

A digital marketing agency called 123 Internet has embraced the ongoing industry developments by utilizing various AI-based technologies to improve service delivery. Scott Jones, CEO said:

“We’ve been using AI tools for a while now, in particular automatically checking website designs in hundreds of screen and browser types, this speeds up our design and development process”.

Their team also use an AI generated website audit which can be downloaded from their website and runs without human interaction.

Identifying micro-influencers

Influencers are another huge trend in marketing right now, and AI algorithms are already in use to make sure the personalities that are most likely to appeal to you are appearing in your search results and social feeds.

Increasingly, advertisers will also use AI to identify smaller influencers that are most likely to gel with their brands and audiences. This has led to the emergence of “micro-influencers” – typically everyday people, rather than celebrities, who have a specialist knowledge they’ve used to build a niche audience that cares about their opinion. AI enables companies to find the micro-influencers with the right audiences for them, across a large number of niches and audience segments. AI helps establish when it makes sense to pay 100 people $1,000 each to talk about their product, rather than pay $100,000 to Justin Bieber or a Kardashian. Once again, here it is about creating efficiency by following the data, rather than simply doing what a marketer thinks or feels is the best plan.

AI in CRM

Customer relationship management is an essential function for any marketer to master, as existing customers are often the most important source of a company’s revenue. Here, AI can be used to reduce the risk of customer “churn” – by identifying patterns of behaviour that are likely to lead to customers heading elsewhere. These customers can then be automatically targeted with personalized promotions or incentives to hopefully restore their loyalty. AI-augmented marketers are also increasingly turning to chatbot technology – powered by natural language processing. This can segment incoming customer inquiries, meaning those who require a quick response can be urgently catered to, to minimize dissatisfaction. AI-driven CRM will also allow businesses to more accurately forecast sales across all the markets where a company operates, meaning stock and resources can be more efficiently distributed. Additionally, it can be used to maintain the quality of data in the CRM system, identifying customer records where errors or duplicates are likely to exist.

The future of the marketer

If you work in marketing, you would be forgiven for worrying that we’re heading for a future where humans in your role will be redundant. You can take heart, though, from current predictions that state AI will end up creating more jobs than it destroys. It’s inevitable that your job will change, though. Marketers will spend less time on technical tasks such as forecasting or segmenting customers and more time on creative and strategic tasks. Those who are competent at working with technology, and identifying new technological solutions as they become available, will be hugely valuable to their companies and are likely to have a bright future!

Feature Image Credit: Adobe Stock

By Bernard Marr

Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things. Why don’t you connect with Bernard on Twitter (@bernardmarr), LinkedIn (https://uk.linkedin.com/in/bernardmarr) or instagram (bernard.marr)?

Sourced from Forbes

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7 Tips to Use AI to Acquire and Retain Customers

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By Kevin Payne

Artificial Intelligence (AI) mimics the cognitive functions of the human mind, particularly in learning and problem-solving. Many of the apps that we use today are powered by AI. From voice-activated virtual assistants to e-commerce, AI applications are everywhere.

With the advancements in AI technology and access to big data, companies across different industries are integrating AI into their processes to find solutions to complex business problems.

The application of AI is most noticeable within the retail and e-commerce space. Websites and apps can interact intelligently with customers, creating a personalized approach that enhances the customer experience.

No matter what industry your business operates in, these seven tips can help you acquire and retain customers more efficiently at a fraction of the time it takes to do things manually.

How to Use AI to Get and Keep Customers

1. Identify Gaps in Your Content Marketing Strategy

If you’re just starting with content marketing, you’ll need to know what type of content to create.

By using AI, you can identify the gaps, find fixes, and evaluate the performance of your content marketing campaign.

Take Packlane, a company that specializes in custom package designs, for example. They came up with high-quality content like helpful blog posts that provide valuable information. At the same time, the content they publish makes it easier for their target market to understand their brand and services.

If you’re in the retail or e-commerce space, you can use AI to identify the gaps in your content marketing. Your content may be focused on your products and their features, but through AI, you can determine the relevant content that addresses your audience’s needs and pain points.

2. Pre-Qualify Prospects and Leads

Not every visitor to your site will become a paying customer. If you’re not getting sales despite the massive traffic, it means you’re generating low-quality leads.

Some reasons why this happens includes:

  • Targeting the wrong audience
  • Poor content marketing strategy
  • Using the wrong type of signup form
  • Promoting in the wrong social media platforms
  • Ineffective calls to action

These explain why 80% of new leads never convert into sales. The mistakes can be rectified with the help of artificial intelligence.

AI tools can extract relevant data to help you learn more about your target audience. These tools also provide predictive analytics on your customers’ behaviour. They, in turn, help improve your lead generation strategy because you’ll know which leads to pursue, where to find them, and how to effectively engage them.

3. Provide Personal Recommendations

According to a report by the Harvard Business Review, even though there are privacy concerns when consumers’ personal information changes hands, people still value personalized marketing experiences.

Brands that tailor their recommendations based on consumer data boost their sales by 10% over brands that don’t.

Recommendation systems’ algorithms typically rely on data on browsing history, pages visited, and previous purchases. But AI is so advanced that it can analyse customers’ interactions with the site content and find relevant products that will interest the individual customer. This way, AI makes it easier to target potential customers and effectively puts the best products in front of the site visitors.

Because of AI, recommendation engines are able to filter and customize the product recommendations based on each customer’s preferences. It’s a cycle of collecting, storing, analysing, and filtering the available data until it matches the customers’ preferences.

This is an effective way of acquiring and retaining customers because there’s an element of personalization.

4. Reduce Cart Abandonment

A high cart abandonment rate is the bane of e-commerce business owners. According to a study by the Baymard Institute, online shopping cart abandonment rate is close to 70%.

Users abandon their online carts for various reasons:

  • high extra costs
  • complicated checkout process
  • privacy concerns
  • not enough payment methods, or
  • they’re not ready to buy yet.

Using AI-powered chatbots is one way to reduce cart abandonment. AI chatbots can guide the customers through their shopping journey.

AI chatbots can have a conversational approach and give the customer a nudge to prompt them to complete the purchase. These chatbots can also act as a virtual shopping assistant or concierge that can let a customer know about an on-the-spot discount, a time-sensitive deal, a free shipping coupon, or any other incentives that will encourage them to complete the checkout.

With AI, lost orders due to cart abandonment are recoverable and can lead to an increase in conversion rate for e-commerce businesses.

5. Increase Repurchases With Predictive Analytics

Predictive analytics is the process of making predictions based on historical data using data mining, statistical modelling, artificial intelligence, machine learning, and other techniques. It can generate insights, forecast trends, and predict behaviours based on past and current data.

In marketing, predictive analytics can be used to predict customers’ propensity to repurchase products as well as its frequency. When used to optimize marketing campaigns, AI-powered predictive analytics can generate customer response, increase repurchase, and promote cross-selling of relevant products.

It’s all part of the hyper personalized marketing approach, where brands interact and engage with customers and improve their experience by anticipating their needs and exceeding their expectations.

With predictive analytics, you can focus your marketing resources on customer retention and targeting a highly motivated segment of your market that are more than happy to return and repurchase your products. This approach is less expensive than advertising or implementing pay-per-click campaigns.

6. Improve Your Website User Experience

Every business—big or small—knows the importance of having a website, where visitors can interact with the brand, respond to a call to action, or purchase products. But it’s not enough to just have an online presence; it’s important that visitors to the site have a great experience while navigating through your site.

What makes for a great user experience? Users have different expectations. Some of them want faster loading time, while others want a simple and intuitive interface. But most important of all, they want to find what they’re looking for. It could be a product, content, or a solution to a problem. Whatever they may be, it’s up to you to meet their expectations.

With artificial intelligence, you can improve your website user experience tenfold. Here are some of the ways AI can be used to improve user experience.

Search relevance

This pertains to how accurate the search results are in relation to the search query.  The more relevant the results are, the better search experience the users will have. This means they are likely to find relevant content answering their queries or finding products that solve their problems.

Personalized recommendations

Content that is tailor-made for the user tends to have greater engagement which increases the likelihood of conversation. Amazon has perfected the product recommendation system using advanced AI and machine learning. AI gets data from customers and uses it to gain insights and apply predictive analysis to recommend relevant products for cross-selling opportunities.

AI chatbots

The presence of chatbots contributes to a great user experience because they provide 24/7 assistance and support in the absence of human customer service.  Users can get accurate answers to their inquiries quickly and efficiently, compared to scrolling through a text-based FAQs.

7. Social Listening for Potential Customers

Social listening is the process of analysing the conversations, trends, and buzz surrounding your brand across different social media platforms. It’s the next step to monitoring and tracking the social media mentions of your brand and products, hashtags, industry trends, as well as your competitors.

Social listening analyses what’s behind the metrics and the numbers. It determines the social media sentiment about your brand and everything that relates to it. It helps you understand how people feel about your brand. All the data and information you get through social listening can be used to guide you in your strategy to gain new customers.

Social media monitoring and listening can be done much more efficiently with the help of artificial intelligence. It’s an enormous task for a team of human beings to monitor and analyse data, but with AI-powered social media tools, all the tedious tasks can be automated. They can be trained to leverage data to provide valuable insights about your brand with high accuracy.

With AI and machine learning, your social listening can easily determine your audience, brand sentiments, shopping behaviour, and other important insights. By having this information within reach, you’ll know how you can connect with them more effectively and turn them from prospects to paying customers.

Key Takeaways/Conclusion

More companies across different industries are using the power of artificial intelligence and machine learning to significantly increase brand awareness, enhance customer engagement, improve user experience, and meet customer expectations.

  • AI can identify gaps in your content marketing strategy so that you can create content that’s relevant to your target audience.
  • AI can help you generate high-quality leads that are likely to buy your products.
  • With AI, you can personalize and tailor-fit your product recommendations based on your customers’ preferences, increasing repeat purchases.
  • AI can be integrated into your e-commerce site to reduce shopping cart abandonment.
  • AI significantly improves website user experience by making it intuitive, accessible, and easy to navigate.
  • AI-powered social media tools can help you monitor and gain valuable insights about your brand. You can then use this to develop a social media marketing strategy to gain new customers.

Achieve these milestones, and you’ll be sure to acquire new customers and retain existing ones.

Feature Image Credit: iStock/monsitj

By Kevin Payne

Sourced from Black Enterprise

 

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Scientists develop AI to predict the success of start-up companies

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Sourced from Brighter Side of News

A study in which machine-learning models were trained to assess over 1 million companies has shown that artificial intelligence (AI) can accurately determine whether a startup firm will fail or become successful. The outcome is a tool (www.venhound.com) that has the potential to help investors identify the next unicorn.

It is well known that around 90% of startups are unsuccessful: between 10% and 22% fail within their first year, and this presents a significant risk to Venture Capitalists and other investors in early-stage companies. In a bid to identify which companies are more likely to succeed, researchers have developed machine-learning models trained on the historical performance of over 1 million companies. Their results, published in KeAi’s The Journal of Finance and Data Science, show that these models can predict the outcome of a company with up to 90% accuracy. This means that potentially 9 out of 10 companies are correctly assessed.

“This research shows how ensembles of non-linear machine-learning models applied to big data have huge potential to map large feature sets to business outcomes, something that is unachievable with traditional linear regression models,” explains co-author Sanjiv Das, Professor of Finance and Data Science at Santa Clara University’s Leavey School of Business in the US.

The authors developed a novel ensemble of models in which the combined contribution of the models outweighs the predictive potential of each one alone. Each model classifies a company, placing it in one of several success categories or a failure category with a specific probability. For example, a company might be very likely to succeed if the ensemble says it has a 75% probability of being in the IPO (listed on the stock exchange) or ‘acquired by another company’ category, while only 25% of its prediction would fall into the failed category.

 
Credit must be given to the creator. Only noncommercial uses of the work are permitted. No derivatives or adaptations of the work are permitted. (CREDIT: Greg Ross)

The researchers trained the models on data sourced from Crunchbase, a crowd-sourced platform containing detailed information on many companies. They married the Crunchbase observations with patent data from the USPTO (United States Patent and Trademark Office). Given the crowd-sourced nature of Crunchbase, it was no surprise to learn that some companies’ entries miss information. This observation inspired the authors to measure the amount of information missing for each company and use this value as an input to the model. This observation turned out to be one of the most critical features in determining whether a company would be acquired or otherwise fail.

Lead author Greg Ross of Venhound Inc. notes that the ensemble of models, along with novel data features, “generates a level of accuracy, precision and recall that exceeds other similar studies. Investors can use this to quickly evaluate prospects, raise potential red flags and make more informed decisions on the composition of their portfolios.”

Feature Image Credit: Creative Commons

Sourced from Brighter Side of News

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From Insta captions to blog posts, AI is now crunching copy for brands

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By Ryan Barwick

Chris Lu, cofounder and chief technology officer of Copy.ai, told us these tools give copywriters a “first draft” to work with.

“Marketing Brew is the home of provocative ideas, fresh thinking, provocative insights, and interesting perspectives on what they think about marketing, media and advertising. This publication gives you a way to digest their news, quick takes and new offerings in the field.”

This description of our newsletter was written by artificial intelligence. Pretty close, right?

Given only our name and a brief description—“a newsletter about marketing, media and advertising”—a tool called Copy.ai was able to spit out that paragraph.

The tool is part of a wave of smart content-churning machines that use the power of artificial intelligence to steal writing jobs make life easier for whomever’s crunching copy.

HAL meets Stan Freberg

Copy.ai and other AI-enabled copywriting companies like Jarvis and Copysmith are built upon OpenAI’s GPT-3.

According to the smart folks over at Emerging Tech Brew, GPT-3 is kind of a big deal. Trained on roughly a trillion words to predict—but not understand—text, it’s widely considered to be among the most advanced language models in existence.

“Large language models are powerful machine learning algorithms with one key job description: identifying large-scale patterns in text. The models use those patterns to ‘parrot’ human-like language. And they quietly underpin services like Google Search—used by billions of people worldwide—and predictive text software, such as Grammarly,” writes Emerging Tech Brew’s Hayden Field.

Of course, if you’re a marketer, who cares? You just need content. And lots of it. That’s where these tools come in handy. They can help write everything from Instagram captions to product descriptions to blog posts.

“We want to humanize AI. We want to help you start from something, and not a blank slate,” Copysmith CEO Shegun Otulana told Marketing Brew.

There’s an assumption that machines could take jobs away from writers, but Otulana doesn’t see it quite that way. “There’s an aspect of writing that isn’t easily replaced. A computer can’t tap into the human interactions you express in a story, the emotional aspects of a story you tease out. A computer can’t live the life of a human.”

But if you’re a writer who specializes in, say, product descriptions for e-commerce sites—or other types of copy that aren’t exactly trying to forge a human connection—these tools might pose more of a threat, he said.

For copywriters who need to bang out posts on multiple platforms like Instagram, Facebook, and LinkedIn, there’s a volume benefit to these tools, since the AI provides various options for each post. Sure, you might not actually need dozens of call-to-action phrases, but any professional could whittle those down to five good ones and tweak them if needed.

“We try to give you the first draft,” Chris Lu, cofounder and chief technology officer of Copy.ai, told us. “Content creation is a treadmill. You’ve got to make a lot of it, it has to be relevant, and it has to be on brand.”

Andrew Race, a strategist at the digital agency Juice, called Copy.ai a time saver. “In five minutes, I’ve got 25 different variations [of a headline]. Before, I would have had to write every single headline or idea out myself,” he said. He estimates it cuts his actual copywriting time in half.

  • So far Copy.ai, which debuted in October 2020, has 4,100 paying subscribers made up mostly of marketers.

Ryan’s artificial copy

We asked Copy.ai to make a couple of Facebook headlines and posts for a made-up brand called Ryan’s Lemonade, giving only the keywords “lemonade, sweet, tart, fresh.”

Here are three versions it came up with:

  • It’s So Good You’ll Want Seconds: With a history of providing quality fruit drinks, Ryan’s continues on with their new line of lemonades. From sweet and tart to a hint of fresh, Ryan’s is bound to quench any thirst.
  • Cool, Refreshing: Pure and natural lemonade sweetened only with real sugar, not high fructose corn syrup.
  • Nothing is as refreshing as Ryan’s: Have you ever felt like you were in paradise? Everyday life is a bit harder than we wish it to be. Lemon Ryan’s is the perfect amount of all things good, made by real people in the sun-drenched hills of California. $5 for a gallon? No… lets make that two!

As you can see, it isn’t perfect. But it’s pretty good, and each took less than 10 seconds. Copy.ai assumes a lot—we’re not sure where “$5” or “California” came from. “These are natural language models. All it’s trying to do is write text. It’s just trying to predict the next word,” Lu told us.

If only a few keywords are plugged in, the content produced by these tools can have a generic feel to it. Lu said he doesn’t expect plagiarism to be an issue, but did say the company is planning on adding a plagiarism detector. “The AI helps with how to say, not what to say,” he added.

Copywriter –> AI editor

Similar to Copy.ai, Jarvis also lists templates for platforms like Facebook and LinkedIn, but its bread and butter is longer-form content, like a blog post.

According to Dave Rogenmoser, founder of Jarvis, it has nearly 30,000 paying subscribers. At least 60–70% of its clients, which include Airbnb, Zillow, and CVS, are using it for projects “around 500 words,” Rogenmoser told Marketing Brew.

By inputting a few key words, Jarvis can spit out entire paragraphs, turning your average copywriter into an editor, who can guide the machine in a specific direction. If it veers off and becomes illegible, a user has to delete what isn’t working and try again. It doesn’t eliminate work entirely, as someone still has to pick and choose what works.

  • This post by Danny Veiga, a digital marketer in San Antonio, was written by Jarvis. Veiga told Marketing Brew Jarvis did about 80% of the work. The other 20% was mostly fact checking.
  • Veiga uses Jarvis for his email marketing, social posts, and homepage copy.

“Jarvis thrives when you need to write a lot of words, but they don’t need to be the most important words you’ve ever written,” said Rogenmoser. In other words, AI probably won’t win a Pulitzer anytime soon, but if you’re cranking out copy, it’ll give you a template for a flood of usable jumping points.

“It takes the mental load off. Writers are safe,” said Rogenmoser. For now.

By Ryan Barwick

Sourced from Morning Brew

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7 Tips to Use AI to Acquire and Retain Customers

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Artificial Intelligence (AI) mimics the cognitive functions of the human mind, particularly in learning and problem-solving. Many of the apps that we use today are powered by AI. From voice-activated virtual assistants to e-commerce, AI applications are everywhere.

With the advancements in AI technology and access to big data, companies across different industries are integrating AI into their processes to find solutions to complex business problems.

The application of AI is most noticeable within the retail and e-commerce space. Websites and apps can interact intelligently with customers, creating a personalized approach that enhances the customer experience.

No matter what industry your business operates in, these seven tips can help you acquire and retain customers more efficiently at a fraction of the time it takes to do things manually.

How to Use AI to Get and Keep Customers

1. Identify Gaps in Your Content Marketing Strategy

If you’re just starting with content marketing, you’ll need to know what type of content to create.

By using AI, you can identify the gaps, find fixes, and evaluate the performance of your content marketing campaign.

Take Packlane, a company that specializes in custom package designs, for example. They came up with high-quality content like helpful blog posts that provide valuable information. At the same time, the content they publish makes it easier for their target market to understand their brand and services.

If you’re in the retail or e-commerce space, you can use AI to identify the gaps in your content marketing. Your content may be focused on your products and their features, but through AI, you can determine the relevant content that addresses your audience’s needs and pain points.

2. Pre-Qualify Prospects and Leads

Not every visitor to your site will become a paying customer. If you’re not getting sales despite the massive traffic, it means you’re generating low-quality leads.

Some reasons why this happens includes:

  • Targeting the wrong audience
  • Poor content marketing strategy
  • Using the wrong type of signup form
  • Promoting in the wrong social media platforms
  • Ineffective calls to action

These explain why 80% of new leads never convert into sales. The mistakes can be rectified with the help of artificial intelligence.

AI tools can extract relevant data to help you learn more about your target audience. These tools also provide predictive analytics on your customers’ behaviour. They, in turn, help improve your lead generation strategy because you’ll know which leads to pursue, where to find them, and how to effectively engage them.

3. Provide Personal Recommendations

According to a report by the Harvard Business Review, even though there are privacy concerns when consumers’ personal information changes hands, people still value personalized marketing experiences.

Brands that tailor their recommendations based on consumer data boost their sales by 10% over brands that don’t.

Recommendation systems’ algorithms typically rely on data on browsing history, pages visited, and previous purchases. But AI is so advanced that it can analyse customers’ interactions with the site content and find relevant products that will interest the individual customer. This way, AI makes it easier to target potential customers and effectively puts the best products in front of the site visitors.

Because of AI, recommendation engines are able to filter and customize the product recommendations based on each customer’s preferences. It’s a cycle of collecting, storing, analysing, and filtering the available data until it matches the customers’ preferences.

This is an effective way of acquiring and retaining customers because there’s an element of personalization.

4. Reduce Cart Abandonment

A high cart abandonment rate is the bane of e-commerce business owners. According to a study by the Baymard Institute, online shopping cart abandonment rate is close to 70%.

Users abandon their online carts for various reasons:

  • high extra costs
  • complicated checkout process
  • privacy concerns
  • not enough payment methods, or
  • they’re not ready to buy yet.

Using AI-powered chatbots is one way to reduce cart abandonment. AI chatbots can guide the customers through their shopping journey.

AI chatbots can have a conversational approach and give the customer a nudge to prompt them to complete the purchase. These chatbots can also act as a virtual shopping assistant or concierge that can let a customer know about an on-the-spot discount, a time-sensitive deal, a free shipping coupon, or any other incentives that will encourage them to complete the checkout.

With AI, lost orders due to cart abandonment are recoverable and can lead to an increase in conversion rate for e-commerce businesses.

5. Increase Repurchases With Predictive Analytics

Predictive analytics is the process of making predictions based on historical data using data mining, statistical modelling, artificial intelligence, machine learning, and other techniques. It can generate insights, forecast trends, and predict behaviours based on past and current data.

In marketing, predictive analytics can be used to predict customers’ propensity to repurchase products as well as its frequency. When used to optimize marketing campaigns, AI-powered predictive analytics can generate customer response, increase repurchase, and promote cross-selling of relevant products.

It’s all part of the hyper personalized marketing approach, where brands interact and engage with customers and improve their experience by anticipating their needs and exceeding their expectations.

With predictive analytics, you can focus your marketing resources on customer retention and targeting a highly motivated segment of your market that are more than happy to return and repurchase your products. This approach is less expensive than advertising or implementing pay-per-click campaigns.

6. Improve Your Website User Experience

Every business—big or small—knows the importance of having a website, where visitors can interact with the brand, respond to a call to action, or purchase products. But it’s not enough to just have an online presence; it’s important that visitors to the site have a great experience while navigating through your site.

What makes for a great user experience? Users have different expectations. Some of them want faster loading time, while others want a simple and intuitive interface. But most important of all, they want to find what they’re looking for. It could be a product, content, or a solution to a problem. Whatever they may be, it’s up to you to meet their expectations.

With artificial intelligence, you can improve your website user experience tenfold. Here are some of the ways AI can be used to improve user experience.

Search relevance

This pertains to how accurate the search results are in relation to the search query.  The more relevant the results are, the better search experience the users will have. This means they are likely to find relevant content answering their queries or finding products that solve their problems.

Personalized recommendations

Content that is tailor-made for the user tends to have greater engagement which increases the likelihood of conversation. Amazon has perfected the product recommendation system using advanced AI and machine learning. AI gets data from customers and uses it to gain insights and apply predictive analysis to recommend relevant products for cross-selling opportunities.

AI chatbots

The presence of chatbots contributes to a great user experience because they provide 24/7 assistance and support in the absence of human customer service.  Users can get accurate answers to their inquiries quickly and efficiently, compared to scrolling through a text-based FAQs.

7. Social Listening for Potential Customers

Social listening is the process of analysing the conversations, trends, and buzz surrounding your brand across different social media platforms. It’s the next step to monitoring and tracking the social media mentions of your brand and products, hashtags, industry trends, as well as your competitors.

Social listening analyses what’s behind the metrics and the numbers. It determines the social media sentiment about your brand and everything that relates to it. It helps you understand how people feel about your brand. All the data and information you get through social listening can be used to guide you in your strategy to gain new customers.

Social media monitoring and listening can be done much more efficiently with the help of artificial intelligence. It’s an enormous task for a team of human beings to monitor and analyse data, but with AI-powered social media tools, all the tedious tasks can be automated. They can be trained to leverage data to provide valuable insights about your brand with high accuracy.

With AI and machine learning, your social listening can easily determine your audience, brand sentiments, shopping behaviour, and other important insights. By having this information within reach, you’ll know how you can connect with them more effectively and turn them from prospects to paying customers.

Key Takeaways/Conclusion

More companies across different industries are using the power of artificial intelligence and machine learning to significantly increase brand awareness, enhance customer engagement, improve user experience, and meet customer expectations.

  • AI can identify gaps in your content marketing strategy so that you can create content that’s relevant to your target audience.
  • AI can help you generate high-quality leads that are likely to buy your products.
  • With AI, you can personalize and tailor-fit your product recommendations based on your customers’ preferences, increasing repeat purchases.
  • AI can be integrated into your e-commerce site to reduce shopping cart abandonment.
  • AI significantly improves website user experience by making it intuitive, accessible, and easy to navigate.
  • AI-powered social media tools can help you monitor and gain valuable insights about your brand. You can then use this to develop a social media marketing strategy to gain new customers.

Achieve these milestones, and you’ll be sure to acquire new customers and retain existing ones.

Feature Image Credit: iStock/monsitj

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5 Ways To Close More Deals In A Downturn Using AI

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By Louis Columbus

Bottom Line: Understanding which pricing strategies cause buyers to progress through buying processes in a downturn still isn’t completely understood, but AI-based pricing can help remove blind spots in how pricing drives more sales during recessionary times.

The Struggle To Make Quota Is Real

Even in stable, healthy economic conditions, just 42% of sales professionals are making quota based on Salesforce’s State of Sales Report. Only 16% will be over 100% of quota in a given year. In an economic downturn, these numbers shrink, making the struggle very real to make quota in a recession. Here’s what it’s like to compete on pricing during a downturn:

  • Go-to pricing strategies that worked in better economic times fall flat and don’t generate 10% of what they before, with B2B-based selling teams seeing this most often.
  • Sales reps’ email in-boxes are either silent or filling up with requests for lower pricing, price protection, discounts, stock balancing or worse, returns.
  • Many CEOs, senior management teams, and sales reps’ initial goodwill calls to the top 20% of customers offering their complete support are now turning into returned calls asking for price breaks and permanent re-negotiated pricing.
  • Low-priced competitors surviving on single-digit margins continue their price wars, trying to keep production operating with orders while trimming staff.
  • Videoconferences are keeping deals alive in B2B pipelines, but when it comes to pricing, deals often stall as CFOs and their staffs review every new expense, introducing new members of the buying process at the last minute.

CROs say that sales cycles vary by industry, with automotive being the slowest and medical device manufacturing, medical plastics including PPE production, and consumer packaged goods manufacturers being the fastest. Getting pricing right has never been more critical or challenging, according to the CROs I’ve had conference calls with. When asked where AI is making a difference, several said automating special pricing requests, taking the drudgery out of managing co-op reimbursements, or researching sales prospects using automated services. Generating fully-priced quotes faster than competitors is where AI is most paying off according to the CROs I spoke with and is contributing to more won deals.

5 Ways AI Can Help Close More Deals In A Downturn

It’s counterintuitive to consider a downturn as a good time to find new ways to improve margins with more effective pricing. But that’s just what distributors, discrete and process manufacturing CROs are looking to accomplish today.  A 1% price increase can deliver a 22% increase in EBITDA margins and a 25% uplift in stock price according to McKinsey’s recent pricing research provided in the article, Pricing: Distributors’ most powerful value-creation lever. CROs are looking at when, how, and if they will increase prices on the most price-inelastic products they have. The logic behind prioritizing price-inelastic products is that selling on quality, availability, and build-to-order flexibility for customers buying these products is the goal to stabilize and grow margins. The smartest CROs I’ve met realize that engaging in price wars on price-inelastic products cost everyone margin, and no one wins. They’re also benchmarking their recovery efforts using EBITDA. The following graphic illustrates why pricing is so powerful, especially for distribution-centric businesses. Source: Pricing: Distributors’ most powerful value-creation lever. McKinsey & Company,  September 16, 2019

The following are five of the many ways AI can help close more deals in a downturn:

1.    Knowing why specific pricing strategies succeed or fail on a deal-by-deal basis in a downturn often defies easy explanation, which is why commercial analytics are so important now. Combining traditional win/loss deal analysis and AI-based commercial analytics provides new insights into what’s working in a downturn. Commercial Analytics suites that are the most effective combine transactional analysis with product and service mix, price, and volume analysis. Vendavo’s approach to providing commercial analytics is noteworthy for its streamlined, intuitive interface design that supports drag-and-drop report customization, real-time configurable alerts, integration to the price management module, pricing localization, and more. The following is an example of how Vendavo’s PricePoint works:

2.    By using AI’s supervised and unsupervised machine learning algorithms to improve risk scoring, only pursue opportunities that show the greatest margin growth and least downside risk.  CROs see the potential for AI to improve the cognitive functioning of sales, sales operations, and pricing working together to price and win the most profitable deals that have the least risk. The challenge is to take into account entirely new buying groups comprised of personas sales teams haven’t interacted with that much in the past. The pandemic and resulting downturn have completed changed group buying dynamics and introduced new risk factors into sales cycles not seen before. When the data is available, it’s possible to quantify the impact of risk factors on margin, price, and revenue gains.

3.    Help sales teams be more effective by improving Deal Price Guidance with AI, reducing the heavy cognitive load many are dealing with as pricing changes happen several times a week, along with new bundles and promotions. No one is talking about how sales teams are struggling to make sense of the many pricing, promotional, and bundling offers that are increasing today. Chances are your sales teams are overwhelmed with pricing reports, new pricing updates, promotional programs, rebates and bundles as many are. In good economic times, sales reps are sending, on average, 27%, nearly a third of their week, on internal administrative activities according to a recent Forrester/SiriusDecisions study.

4.    Tailoring up-sell and cross-sell recommendations for each customer using AI to define the optimal series of options and alternatives increases the average deal size and only presents the most buildable, profitable products to them. AI-based product recommendation engines integrated with CRM, e-Commerce, ERP, and pricing systems recommend the products and services that have the highest propensity of being purchased. The most advanced AI recommendation engines take into account previous buying behavior and buying patterns in making their recommendations.

5.    Knowing how price, volume, and mix decisions over time impact sales across product lines, sales teams, and business units is another area where AI is helping to improve sales in this downturn. It’s common to find groups of Sales Analysts crunching this data using Excel, which is a time-consuming, iterative process that’s a perfect candidate for AI-based automation. Imagine if the many Sales Analysts crunching data had more time to analyze it and see why pricing decisions by product, region, business unit, and geography are outperforming median sales and profit levels? Finding the reasons why pricing decisions are working in a downturn is how every CRO I’ve known defines a recovery plan. Vendavo’s recently-announced Margin Bridge Analyzer is an example of how AI can be used to understand better what’s hidden in the thousands of Excel spreadsheets organizations use for tracking pricing effectiveness.

Conclusion

Achieving commercial excellence in a down economy needs to start by improving pricing effectiveness that delivers solid gains to EBITDA margins over time. Of the many ways AI is improving selling, pricing, and margin performance, the five key areas helping distributors, discrete and process manufacturers the most are discussed in this post. McKinsey finds that the best short-term/high-impact an organization can make is concentrating on pricing and promotions shown in the graphic below. Improving sales in a downturn is possible when AI is used to decipher the data this recent downturn is producing and find new margin opportunities fast.

Source: Rapid Revenue Recovery: A road map for postCOVID-19 growth, McKinsey & Company, May 7, 2020

Feature Image Credit: ISTOCK

By Louis Columbus

I am currently serving as Principal, IQMS, part of Dassault Systèmes. Previous positions include product management at Ingram Cloud, product marketing at iBASEt, Plex

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Watch out, AI is coming for your playlist next

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The London-based startup Auxuman plans to release a new AI-generated album a month, in a quest to see if robots can be creative geniuses.

What: AI musicians are a growing trend.

Who: Auxuman, an artificial intelligence startup up based in London

Why we care: Robots are coming for your playlist! AI personalities like Yona, Mony, Gemini, Haxe, and Zoya have the ability to put out a new full-length album via Auxuman every month. On average, most human musicians release one or two studio albums in a year, while rappers can put out up to three or four mixtapes in the same period, according to Digital Trends.

Auxuman dropped its debut album on September 27 and plans to continue releasing AI-generated albums every month on YouTube, SoundCloud, and elsewhere. The music is generated through engines that create the words, melodies, and a digital singing voice.

Does this mean that AI could be the death of human musicians? No. It’s not doomsday for the music industry just yet. The AI personalities sound like robots, which is certainly not everyone’s taste. There’s also the cult of personality. The average fan would probably prefer to imagine an actual human being behind the vocals and synths, no matter how autotuned they are. Nothing beats actually meeting idols in the flesh. However, AI could be another supplementary creative component used in music.

“There is always [a shortage of people] giving birth to a new genre,” Ash Koosha, Auxuman founder, told Digital Trends. “Due to the economic nature of the act of making music for humans, we are naturally submissive to forms that have been successful. We believe machines [can] blend and merge forms and styles [and in the process], find the next exciting sound.”

But then where does that leave the concept of creativity? The dictionary definition of creativity is the use of imagination or original ideas, especially with regard to artistic work. A computer can’t be imaginative; it’s interacting with algorithms and data. So the human mind wins this round, but who’s to say there isn’t a genius tune to be made by interweaving AI-generated sounds into notes arranged by human beings? So, musicians and producers, keep your instruments and Magix Music Maker locked and loaded.

Featured Image Credit: [Photos: Icons8 team/Unsplash; Franck V./Unsplash]

By Starr Rhett Rocque

Sourced from Fast Company

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Surveillance at the Heart of Smart Cities

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By Jessica Burton

Today’s cities are living entities. They develop, grow and become more complex over time. Yet, many of their most pressing issues, such as the need for utility improvements and monitoring crime, remain the same. Like never before, city officials have the capabilities to implement analytics technology. But surveillance will be at the heart of smart cities.

These technologies will help with a myriad of everyday city demands, in addition to more intricate challenges pertaining to security, healthcare, mobility, energy and economic development.

We need accurate insights into cities like never before.

With more than half of the world’s population residing in cities, this need for smarter and more accurate insights into their everyday workings is monumental. City management officials could learn much from leaders like Cisco, Amazon and Google. These companies have made it their business to not just collect data, but  utilize it to improve livelihoods and communities.  As we look to their successes, it becomes increasingly evident that the answer to creating smarter cities lies largely in surveillance technology that captures data analytics.

With the rise in surveillance technology and predictive analytics, we can make smart cities smarter and effectively, increase their efficiency. The reality is, however, that connectivity is never a guarantee. Therefore, necessary data must be present, regardless of connectedness, to ensure real-time decisions can be made. Satisfactory amounts of local storage must exist to position the most perceptive data nearest to the point of compute. This speaks to the increasing importance of the edge, as well as embedded storage.

Growth in real-time data is causing a shift in digital storage needs.

The growth of real-time data though edge analytics is causing a shift in the type of digital storage cities need. Fast, uncompromised access to data is becoming ever more critical. With a recent study, Data Age 2025: The Digitization of the World from Edge to Core, estimating that 175 zettabytes of data will be generated by 2025, there has never been a greater volume of insights at our fingertips and cities must step up to develop ways to use this data for good. In many ways, cities are already doing this – from intelligent street lights optimizing routes based on traffic patterns to reduce emergency response time by 20 to 30 percent, to advanced surveillance cameras with analytics deployed to enhance security operations, leading to a reduction in crime by 30 to 40 percent. However, we can do so much more.

To be a true smart city today, cities will need an “edge tier” approach to store, filter and manage data closer to the sensors. To gain deeper insights, the data is then stored and analyzed for longer periods of time in the edge domain as well as in the cloud or backend. Edge analytics that capture and collect data on network video recorders (NVRs) make it possible to act in real-time. With this technology, cities can find missing persons, notify residents of nearby emergencies and send out traffic congestion warnings.

Data insights will provide many wide-ranging benefits to cities.

The opportunities data analysis and data-driven urban improvement present are both hugely exciting and impossible to ignore. Behavioral analytics, thermal cameras and AI engines in edge devices like NVRs are just a sampling of the technologies that have given us the ability to remain constantly connected on a vast network. By horizontally interrelating individual systems, we can now develop insights into various mechanisms. This includes patterns in electricity, water, sanitation, transportation, environmental monitoring and weather intelligence.

West Hollywood’s Innovation Division is an excellent example to look to.

Take for instance, West Hollywood’s Innovation Division, which recently received the American Planning Association (APA) Technology Division’s Smart Cities Award for the “WeHo Smart City” Strategic Plan. Its three-part plan consisted of strategies including:

  • Data-driven decision-making rolling out to departments citywide
  • Collaboration and experimentation designed to enable City Hall staff to work better together.
  • Automation of processes to improve public safety and manage the built environment through smart city sensors and smart building programs.

With data collected from predictive analytics based on Deep Learning activities in the back-end, in some cases for over a year, we can pre-identify trends to manage incidents in one sector that directly impact another.

Access to real-time data and surveillance tech is key.

Cities need data in the moment and on the go. This places  a larger demand on the edge to produce the predictive and reliable information required, often in real-time. In fact, reports (Seagate) predict that due to the infusion of data into our city workflows and personal streams of life, nearly 30 percent of the “Global Datasphere” — meaning the amount of data created, captured or replicated across the globe – will be in real-time by 2025.

That’s a lot of real-time data. So, how can a city implement surveillance technology to better secure a city and enable smarter analyses? The first step is identifying video storage solutions positioned at the center of a smart city’s surveillance application. These solutions enable recordings, data retention, predictive analytics and real-time alerts. The next step is to position data at the edge and provide ample time for cities to make sense of patterns. More than ever before, cities will need to come together to integrate their technologies and ultimately make their networks smarter. This is a challenge that will require broad cooperation across its systems. Surveillance storage technology is the foundation to this strategy, ensuring timely data access and availability from edge to cloud.

By Jessica Burton

Global Product Marketing Manager at Seagate Technology. Jessica Burton has over 10 years of experience in IT storage and is the Global Product Marketing Manager at Seagate Technology. Her previous experience includes expertise in enterprise storage at Hewlett Packard Enterprise.

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A new kind of cybercrime uses AI and your voice against you

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By Ephrat Livni

It’s easy enough to forge a signature for fraudulent purposes. However, until recently, some things—like our voices—have been distinctive and difficult to mimic. Not so in our brave new world.

A new kind of cybercrime that uses artificial intelligence and voice technology is one of the unfortunate developments of postmodernity. You can’t trust what you see, as deep fake videos have shown, or what you hear, it seems. A $243,000 voice fraud case, reported by the Wall Street Journal, proves it.

In March, fraudsters used AI-based software to impersonate a chief executive from the German parent company of an unnamed UK-based energy firm, tricking his underling, the energy CEO, into making an allegedly urgent large monetary transfer by calling him on the phone. The CEO made the requested transfer to a Hungarian supplier and was contacted again with assurances that the transfer was being reimbursed immediately. That too seemed believable.

However, when the reimbursement funds had yet to appear in accounts and a third call came from Austria, with the caller again alleging to be the parent company’s chief executive requesting another urgent transfer, the CEO became suspicious. Despite recognizing what seemed to be his boss’s voice, the CEO declined to make the transfer, realizing something was amiss.

Although the CEO recognized the familiar accent and intonations of the chief executive, it turns out that the boss wasn’t making the call. The funds he transferred to Hungary were subsequently moved to Mexico and other locations and authorities have yet to pinpoint any suspects.

Rüdiger Kirsch, a fraud expert at insurer Euler Hermes, which covered the victim company’s claim, tells the Journal that the insurance company has never previously dealt with claims stemming from losses due to AI-related crimes. He says the police investigation into the affair is over and indicates that hackers used commercial voice-generating software to carry out the attack, noting that he tested one such product and found the reproduced version of his voice sounded real to him.

Certainly, law enforcement authorities and AI experts are aware of voice technology’s burgeoning capabilities, and the high likelihood that AI is poised to be the new frontier for fraud. Last year, Pindrop, a company that creates security software and protocols for call centers, reported a 350% rise in voice fraud between 2013 and 2017, primarily to credit unions, banks, insurers, brokerages, and card issuers.

By pretending to be someone else on the phone, a voice fraudster can access private information that wouldn’t otherwise be available and can be used for nefarious purposes. The ability to feign another’s identity with voice is easier than ever with new audio tools and increased reliance on call centers that offer services (as opposed to going to the bank and talking to a teller face-to-face, say). As the tools to create fakes improve, the chances of criminals using AI-based voice tech to mimic our voices and use them against us are heightened.

By Ephrat Livni

Sourced from QUARTZ

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