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Actioning Individual Customer Context With Artificial Intelligence

April 21, 2020 No Comments

Today’s customers interact with products or brands at various stages, from brand awareness to comparison to purchase to product support and loyalty. Most marketers are focused on awareness and maybe a little on experience during comparison and loyalty. They rarely get deeper, either because they do not have access to the full customer experience cycle, because there has not been a way to handle all of it, or because they are not incentivized to do so,

In recent years, marketing has started to delve into customer support to standardize customer experience. However, machine learning (ML) and artificial intelligence (AI) have started to provide tools that can offer much deeper insight and actions. So, what are the true and far-reaching opportunities for marketers with AI?

Imagine being able to serve every customer or potential customer at any touch point in the cycle as if there were a live salesperson there who instantly knew that person’s history with the brand — the summary of clickstream, purchase history, loyalty, support encounters and sentiment. Imagine that salesperson’s efficiency if they could instantly have at their disposal a best offer or reward, or information to nudge the customer to engage or repeat engage with the brand.

So far, we have seen data analytics and maybe some ML used to analyze clickstreams and some digital visitor behaviour to make recommendations for cross-selling and up-selling. Much more recently, we have seen chatbots used to scale customer support, as well as do voice-based sentiment analysis with tools based in some form of ML, AI, natural language processing and speech recognition. While these have been steps in the right direction, they are very narrow. They are point solutions based on isolated data pools. They take no steps toward either determining broader context or finding the best opportunities for marketers and sales folks to increase acquisition and retention. Catering to customer segment is old-fashioned. With AI, we can cater to individuals based on extended or immediate history with the brand.

The current capabilities of ML and AI allow not only the complete context of the customer to be gathered instantly, but also to serve the experience most likely to drive customers further down the funnel. The following key elements are required to exploit this phenomenal opportunity that is now available to marketing and sales.

To enable capture of complete customer context: Data from the following different pools needs to be joined and integrated into a single customer 360 view or hub: store and online purchase data, website and mobile clickstream, social behavior, support encounters, sentiment analysis, demographics and loyalty data. Joining data across anonymous and authenticated customer sessions is still not easy, but there are workarounds. Data so integrated provides a complete immediate and extended history of any customer.
To create the right experience for each context: Whether created manually or generated via automated methods, content and experiences that cater to customer intent and context at various points in the customer life cycle have to be developed. Everything from appropriately keyworded variations of product or service descriptions and videos to granular reward schemes for loyalty or for support scenarios to different purchase experiences that surprise and delight must be generated and kept at the ready.
To serve the best experience each time: Previously, data analysis and even ML was used to determine hidden customer segmentation and to predict product or service demand. Marketing and sales then manually arranged experiences to be served, after some A/B and even multivariate testing. Now AI can be used to run acquisition and retention maximization models. AI can run multivariate testing using the data and the experiences developed in the previous steps. Based on training gained from such testing (at scale or in smaller focus areas), AI can instantly determine the most likely experience that would cause new customer acquisition or repeat sale and retention.

All of the above should only be done in stages. Companies have spent years attempting to pull together customer 360 databases. Start by integrating online clickstreams with demographics and purchase and support data. Bring in-store purchase, sentiment analysis and social data at a later stage. With the same objective of leveraging online first, create content and experiences in digital formats before taking on in-store experiences or field sales agent empowerment. Retention models to achieve or increase customer lifetime value are much more lucrative and less infested with stakeholders. Honing and running retention models before new customer acquisition models is a great way to prove out AI capabilities with the fewest unnecessary concerns and the least amount of interference.

Relinquishing manual or even rules-based recommendation is not an easy cultural shift, but already, results with ML and AI outperform anything marketing and sales have otherwise done.

Best Western used AI-based tips and tricks for various destinations to help travelers plan and realized a 48% increase in traffic to Best Western Locations.
The Humane Society used ML messaging and realized an 86% lift in shelter pet adoption by reaching friends and cohabitants in the relationship graphs of those who had been identified visiting a shelter and showing any intentions to adopt.

Marketers reacting in retrospect to segmentation analysis is old-school and far too late. The new tech-savvy marketer wants to wield individual customer context and experiences nimbly, in real time, to catch the most new customers and achieve the greatest customer lifetime value. The race is on. Brands that win this race will set themselves so far ahead of the rest that they will not be caught for years.

Feature Image Credit: Getty

By Pradeep Aradhya

CEO of Novus Laurus. Business and transformation strategist. Digital technology, film, and food investor. Read Pradeep Aradhya’s full executive profile here.

Sourced from Forbes

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The far-reaching impact of AI in education

April 17, 2020 No Comments

By Randhir Kumar

With the rise of AI, the Indian learning and e-learning landscape have seen considerable change. Here’s how the power of AI is being capitalised in the field of education.

Artificial intelligence (AI) is one of the major technological innovations in recent times, set to revolutionise industries across verticals. In simple terms, AI is the capacity of a computer/machine to collect, anticipate, analyse information, recognise patterns and, consequently, perform actions as opposed to natural human intelligence.

AI has permeated industries throughout the years, aiding and executing taxing responsibilities such as customer service (voice assistant services), in automobiles, robotics, etc. Its presence has likewise penetrated the education sector, which can be further corroborated by the surge in edtech startups in India.

With the rise of AI, the Indian learning and e-learning landscape have seen considerable change. Here’s how the power of AI is being capitalised in the field of education:

Modernisation of education

AI aids the process of channeling focus on core concepts of all subjects, while embedding interdisciplinary concepts on the same platform. AI has allowed education to be personalised for students to fit their unique needs. It aids the process of designing and developing technology, which facilitates quick resolution of queries with independent support to students as opposed to a teacher teaching a class of 20+ students.

Meeting unique needs

AI also brings value on the table by procuring information on the unique requirements on students, courses, and their syllabi to develop a holistic and robust learning trajectory. Leading and competing players in the e-learning market have harnessed AI’s ability to recognise patterns, and congregate data by mapping online movement/footprints from numerous sources to decipher the finest techniques of learning for students in general and individuals in particular. It has filled the gaps, which a normal classroom lacks, through clever coding, algorithms, and big data, enabling students to choose subjects, concepts that suit them best in accordance with where their interests lie. In this manner, content isn’t imposed on students unlike in schools.

Ultimately, the student excels in their academic goals and paves way for a brighter future. The same ability throws statistics on how quickly or slowly an individual can digest information besides preferences, interests, and degree of involvement to further help e-learning platforms tailor their offerings for them. AI has ensured a personalised learning journey while making education more relevant to students, parents, and teachers.

Feedback that supports growth

AI lends support by monitoring and mapping the learning graph of a student or an individual. Once the data has been acquired on the individual, it’s scrutinised using advanced analytics for insight generation (strengths and weaknesses) to develop tailored plans for an individual to ensure that the person gets the most out of his/her course online.

Learning can be fun

Artificial intelligence can turn learning into an enjoyable experience. One of the newest ways teachers can engage students online or in a classroom is by using simulation. Leading gaming companies have been using simulation to engage their customers for decades. Many medical and flying institutes have started using computer-powered simulations to put candidates/students in a real-life situation wherein students can react and interact, based on which one can be judged.

Breaking geographical barriers

Students can move beyond the geographies of their classroom/room without actually stepping out. AI makes communication with peers on a global scale easier through the Internet. With the help of third-party apps, getting insights on a subject matter of concern to the student is just a click away.

This ability can be further used to enable partnerships on a global scale, similar to an electronic student exchange program, where students or individuals could come together and provide answers to solutions or create a collective craft.

Beyond learning

We have adopted AI in all forms, from chatbots to adtech in our lives, making our life simple and easier. We have embraced a greater scientific approach, which enhances strategy, targeting, insight, creativity, knowledge, and experience. Basic and redundant processes are made easy, like the creation of profiles, which require consolidating information of students, which also, at times requires constant updating. Another understated potential is regular updates to the online alumni community. To that end, a feed framework can be created on a subscription basis, to update students with developments in the field and enable them to take calculated steps to enhance their career curve.

Segmentation framework

Another facet of how AI is used in the edtech industry is in the segmentation framework model. Under this, AI aids the study of different data sources that are available to understand their structures for profiling. The data, which is profiled, addresses different objectives, for instance:

Assessment: Whenever an individual poses a question, with the help of advanced analytics, AI can determine the level of understanding of the student/individual. It helps in assessing whether the analytical intelligence of the student/individual is on par with the level of the concept and whether they have a proper understanding of the subject.

Cross-selling of content: AI identifies the learning patterns of a student or an individual basis, which it provides them with supplementary learning content to ensure that the individual grasps the concept in its entirety.

Dropout: When a student or an individual chooses to opt out of a course or arbitrarily drops out, AI is able to determine the reason by determining how interested the individual was in the subject.

With the baseline data and touch points, educators can then proceed to develop predictive model layers over the data to draw and retrieve inferences, which will form the foundation of all future engagements.

By Randhir Kumar

Sourced from YOURSTORY

In News

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

September 12, 2019 No Comments

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

In News

The Technology That’s Disrupting Social Media Advertising for Mobile Retail

July 30, 2019 No Comments

By Madeleine Streets

Are retailers hearing the call of mobile?

A recent report by Forrester found that smartphones were used in more than one-third of U.S. retail sales in 2018, from product research to checkout. For retailers looking to convert greater mobile sales, they might want to reevaluate their social media advertising.

According to a Think With Google survey, 51% of smartphone users purchased an item from a different company than originally intended, due to messaging appearing exactly when they needed it. That suggests social media advertising campaigns could attract new customers, if deployed strategically. Designed to help retailers capitalize on this opportunity, marketing platform SmarterHQ launched an Ad Personalization program on Tuesday morning.

In order for brands to acquire and retain valuable customers, they must have a personalized, cross-channel strategy that spans ad platforms,” said Michael Osborne, president & CEO at SmarterHQ. “But until now, targeting within these platforms hasn’t been comprehensive enough. Syncing first-party data to power highly relevant ads often requires extra manual work and IT resources, which has hindered these efforts.”

The program builds on SmarterHQ’s existing behavioral marketing offering, which centers on collecting omnichannel data to inform brand messaging. Through Ad Personalization, the same omnichannel analysis can be integrated with the user’s Facebook and Google advertising to create individualized and customized campaigns. These can then work in conjunction with email, web and mobile pushes that the user already coordinates through SmarterHQ.

But SmarterHQ isn’t the only company taking advantage of the growing emphasis on social advertising and the new data technology available. At Pattern89, an artificial intelligence (AI) platform for digital marketers, data from all of its customers is anonymized and run through the company’s algorithms. This turns more than 100 billion impressions into 2,900 dimensions of analysis that are available to all users.

Pattern89 Computer screen — The Pattern89 platform is popular with e-commerce brands looking to roll out new campaigns every few days. This made possible by AI, which is able to process data and generate new recommendations daily.

CREDIT: Pattern89

“One footwear retailer wouldn’t see the results of another footwear retailer because the machine doesn’t look at the data in that way,” said RJ Talyor, CEO and founder of Pattern89. “Instead, it looks at all of the red shoes, or all of the ads that are targeting women between the ages of 17 and 23. It anonymizes all this data, runs the analysis and identifies where the biggest opportunities are for you.”

Users of the program are then presented with a daily to-do list to optimize advertising performance, which Talyor estimates can be completed in five minutes. A new feature introduced this week, Gemini, enables users to automate the daily to-do list by clicking a “do it for me” button. Then there is the Creative Planner program, which makes broader advertising strategy recommendations based on AI learnings.

Artificial intelligence is becoming more common in retail; Salesforce projects that the percentage of retail and consumer goods marketers that are leveraging some form of AI will increase to 70%, from 20%, in the next two years. It also found that, during the 2018 holiday season, AI-powered recommendations yielded 14% higher, on average, order value.

Nevertheless, many retailers are still resistant to AI findings. As Pattern89’s algorithm looks at data from across industries, users receive insights collected from unexpected places; the same customer might buy both a pair of shoes and a mattress, revealing trends that work across contexts. But these recommendations can seem counterintuitive or untrustworthy, such as when one woman’s brand was told it should target men in its advertising. The brand chose not to follow the suggestion, but Talyor believes that not trusting AI is a mistake.

“There’s no bias in the machine; it’s looking for the lowest opportunity,” said Talyor. “It requires humans to intervene — and sometimes humans are unwilling to part with their intuition and their experience. But others are and when they do, they find untapped pockets of opportunity.”

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Feature Image: Salesforce found that 87 percent of consumers begin their shopping journey with digital tools, such as smartphones.CREDIT: Glenn Hunt/EPA-EFE/Shutterstock

By Madeleine Streets

Sourced from FN

In News

AI Advertising: 9 Ways To Use Artificial Intelligence in Marketing

July 24, 2019 No Comments

Sourced from Droid Men

61% of marketers declare that Artificial Intelligence (AI) is the most critical element of their data strategy.

Marketing is a fast-paced discipline. If you want to succeed in it, you must stay at the bleeding edge of new breakthroughs.

By 2020, 85% of customer relations will be automated. You, therefore, need to position your brand to stay competitive.

AI is probably the biggest technology push of our time revolutionizing every aspect of marketing. To get the most out of automated customer service, marketers are turning to AI advertising for strategies that can deliver higher value.

Here are some ways in which you can incorporate AI into your marketing to keep up with the times.

1. Chatbots

A Chatbot is an AI software that is capable of simulating a conversation (chat) with a user in natural language.

Brands have taken to using chatbots to interact with their clients on messaging apps like WhatsApp, Slack, and Facebook Messenger.

Through these bots, brands can answer queries customers frequently ask in a speedy fashion.

Since they retain a customer’s data after the interaction, they can build on that information to deliver more personalized experience during the next interaction.

That reinforced learning pattern only makes the experience better for the customer.

2. User Experience (UX)

When you have a website, the user experience will significantly influence whether the customer will return to it or not.

You can use AI to collect information on customers and understand their likes, intent, and desire. Data points to gather here include location, the devices they use to visit the website, demographics among others.

As the user keeps browsing the site, you get to gain more insights about them and deliver appropriate offers and content that resonates with their needs.

AI marketing that helps shape your user experience for the better has the potential to increase your conversion rate.

3. Search Engines

People today take it for granted that they can search for anything on Google and find a relevant result.

Such a scenario is the result of decades of research and analysis on how to create and deliver a more intuitive search experience for customers.

After Google deployed RankBrain, its machine-learning based algorithm, many businesses saw the value of such an application.

Nowadays consumer companies like Amazon take advantage of artificial intelligence marketing tactics that can help them deliver relevant results to you.

Innovations like natural language processing and semantic search determine the relationships between products.

When you run a search, they help recommend similar items and auto-correct mistakes so that you can find the right products.

4. Predictive Analysis

Predictive analysis is the use of data, machine learning techniques, and statistical algorithms to draw conclusions on future actions based on the data.

Using predictive analysis you can determine the probability of a prospect becoming a client.

Thus, depending on the conclusion your draw you can determine how much resources you will dedicate to converting the prospect.

Another area predictive analysis is useful in is pricing. Using this tool, you can more accurately determine which price point will deliver more sales for you.

That information can then contribute towards your value proposition marketing.

5. Email Marketing

Email marketing is a crucial part of any brand’s marketing mix as it is one of the few digital assets they fully control.

But with the rise in sources of data from 10 in 2017 to 15 in 2019, marketers may struggle to personalize these emails.

AI can help you unify the piles of information on a subscriber and learn how to reach more effectively.

For example, it can help you determine how many times to send the email per user and what time of the day is best to send it.

6. Digital Marketing

Pay-per-click (PPC) advertising is a cornerstone for any digital campaign. Typically, PPC ad campaigns are usually managed by an in-house team or a large agency.

AI can help you discover new channels your competition may be unaware of.

Machine learning techniques can help you optimize the layout, bids, targeting, and copy for your campaign.

You will be able to realize a higher return on advertising per campaign by using AI in marketing online.

7. Social Listening

Every brand needs to have a presence on social media to extend its customer service to where its customers are.

Consequently, it is essential that brands have their finger on the pulse of what users are saying about them.

Natural language processing innovation has made it possible for brands to hear what users and the public at large like or dislike about them.

Therefore, they can get ahead of any potential issues before they blow up.

You can also use AI in social listening to identify potential purchasers and nudge them towards a sale.

8. Audience Targeting

Customers today have come to expect a certain level of personalization, and as a marketer, you can’t fail on this expectation.

To help you create more accurately personalized campaigns, you will need to segment your customers as finely as possible.

AI can draw on the data you have on your customers and identify a common variable that can help shape your communication with a specific audience.

For example, if your data shows you that a significant number of your customers are into destiny power leveling, you can set up banner ads to effectively reach them.

9. Voice-Based Services

In the past few years, voice-based services have gained quite some traction.

Voice assistants such as Alexa, Siri, and Cortana have made it infinitely easier for consumers to search and place an order by speaking at their devices.

Natural language processing technology helps improve speech recognition so that customers can successfully issue commands.

AI can help you deploy voice-based services to provide your customers with an avenue for easier sales and interaction.

Beef up Your AI Advertising Strategies or Get Left Behind

Artificial Intelligence is making a big impact on marketing. High automation levels in what once used to be human job roles call for precise AI advertising strategies by brands.

Are you concerned with the impact technology will have on your business? Thumb through our content to learn more about how you can use innovative breakthroughs to power your business forward.

Sourced from Droid Men

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This Tech Guru Used Artificial Intelligence to Make Shopping More Human

June 12, 2019 No Comments

By Gabrielle Olya

A 20-year tech veteran, Christian Selchau-Hansen started his career doing data-driven work at companies like Square and Zynga. Eventually, he wanted to see how data could be used to improve the most human aspect of business — the customer relationship. That’s exactly what he’s doing as the CEO and co-founder of Formation, an enterprise software company that optimizes the customer journey through personalized marketing experiences. Formation counts Starbucks as both a client and investor and has raised $30 million in funding, according to CrunchBase. It was also named one of the 50 most sought-after startups in the U.S. by LinkedIn.

Each week, GOBankingRates sets out to discover what makes the people behind top companies tick. We like to call this series “Best in Business” — and Selchau-Hansen really is one of the best. He told us why it’s important to not get caught up in the short term, his three-pronged approach to success and ways that you can find (or build) your own dream job, too. Below, find our favorite moments from the story of how Selchau-Hansen launched his business.

Motivation: 12 Inspiring Leaders Who Didn’t Strike It Rich ‘Til After 30

His Company Vision Came to Life With a Cup of Coffee

Our origins trace back to my time as an entrepreneur-in-residence at BCG Digital Ventures. I was there after stints at Square and Zynga, and [was] interested in developing some machine learning-enabled concepts. Early on, I met one of my co-founders. We envisioned a world where customer experiences and offers were personal, relevant and helpful — effectively, good for both the customer and the brand. We also saw a gap in the market, and so began working on a concept for an AI platform that could leverage data to truly engage the customer and deliver on our vision. Shortly thereafter, lightning struck.

That lightning came in the form of a delicious cup of coffee. We had the opportunity to pitch our idea to one of the world’s largest restaurant brands. It was an awesome meeting. Their aspirations for their customer relationship matched many elements of our vision. With our concept and vision validated, we set out to develop the concept further, and quickly test whether or not it would drive the kind of impact we believed it would.

Delivering highly engaging, individual experiences at enterprise scale is really complicated. Customers are not static creatures — they’re always in a state of flux. Machine learning seemed particularly suited to the challenge, being able to both conduct the deep analysis needed to surface customer motivations and adapt as the customer changes and grows. And that really was the genesis of Formation and our mission — to use artificial intelligence to build and deepen customer relationships.

Check Out: Learn About These Businesses That Are Changing the World

He Figured Out How To Use Games To Engage Customers

Working in mobile gaming was a crash course in customer engagement. After all, that’s what the gaming industry is ultimately selling — engaging customer experiences. Engaging games must be challenging without being frustrating; they must be tailored to the player’s abilities; they must be fun. Formation’s experiences reflect those lessons. Our intelligent multistep offers are specifically calibrated to the individual customer, with the right level of challenge and incentive. And by employing these lessons, our marketing experiences have a level of repeat engagement that’s on par with the best customer experiences.

There’s a trap that data-driven companies can fall into, where they focus on the short term, where data is more accurate and more granular, over the long term, where data is often less certain and less precise. That was definitely something we wanted to avoid — and for that matter, want to help our clients avoid. Data remains central to our decision-making, but we want to be sure we’re always broadening our investigative horizon and putting equal emphasis on our short- and long-term needs.

Tips: This Founder Thought Failure Might Be Inevitable — Until He Got Advice From Mark Cuban

He’s a Team Player

Recruiting top talent is important for any startup, but the technical sophistication of our product gave our recruiting efforts an extra layer of complexity. We really needed to attract the best and the brightest in cutting-edge, in-demand specialties across engineering and machine learning. Initially, this seemed daunting. But as we started to tell our story, we found that people want to be challenged, to have an impact, to have fun.

Click HERE to read the remainder of the article.

By Gabrielle Olya

Sourced from Yahoo Finance

In News

Three tech trends set to impact digital advertising beyond 2019

May 21, 2019 No Comments

By Nikki Gilliland

Global digital advertising revenues are on the up, growing 17% in 2018 to reach $251 billion (or 45% of global advertising revenues).

This rise is expected to continue, with digital advertising predicted to represent 50% of total advertising spend across the world this year.

While immediate investment is something of a certainty, what trends are set to impact the digital ad industry as we head further into the year and beyond?

Subscribers can read more on the topic in Econsultancy’s Getting to Grips with Digital Advertising: Best Practice Guide. In the meantime, let’s take a look at some of the most notable innovations that advertisers should be aware of.

Artificial intelligence

We have only just scratched the surface of what artificial intelligence can do for the advertising industry. So far, this has largely extended to improving ad relevancy, optimising spend, or enhancing personalisation.

One good example of AI being utilised in this way is Toyota’s 2017 ad campaign for its Mirai vehicle. The campaign made use of natural language processing in order to create advertising copy tailored to thousands of potential buyers and their specific needs.

According to AdWeek, Saatchi LA did this by training IBM’s Watson AI marketing engine with fifty scripts of relevant copy based on location, behavioural insights, and occupation data. Watson was then able to deliver thousands of pieces of copy (explaining the car’s features and how they are relevant to the user), with each one sounding as if they were written by a human. The campaign ran solely on Facebook, allowing Toyota to make use of the platform’s complex behavioural data and targeting capabilities.

This intersection of creativity and data (whereby the AI is used to enhance human input) is where many experts see the technology’s big potential. It is far removed from stereotypical assumptions about AI.

In Econsultancy’s report, Marek Wrobel, Head of Media Futures at Havas, notes: “The best results happen when AI works with human insight, and in our industry, this will mean we’ll have more time to spend on creativity rather than, for example, reporting or optimisation.”

Conversational technology

It is the norm for brands to target users with advertising on social media platforms like Facebook and Instagram. However, chatbots have also enabled brands to talk to users in text-based conversations, and to create an informal and less disruptive style of communication.

Could the next step be a big shift to messaging services like WhatsApp?

In 2018, Facebook’s WhatsApp messaging service introduced a business version of its app. This means that businesses can now share their company details within a profile, as well as handle customer service enquiries and interactions. This is a different proposition to WhatsApp allowing intrusive ads onto its platform. However, the social messaging platform hasn’t been quite so firm in its stance against this either. In late 2018, it was reported that WhatsApp was to launch ads in its Status feature, marking its first real foray into monetisation.

Whether or not WhatsApp expands on ads, experts predict that we will see brands of all kinds start to seriously consider the app from a marketing perspective. Peter Buckley, Communications Planner at Facebook, explains: “If you think about how you communicate with your friends and family, it’s most often messaging. Yet businesses are a little bit slow on the uptake with messaging – communications are most often via call centres or email.”

In future then, we can expect to see a shift to messaging platforms, in order for businesses to enhance both customer service as well as marketing.

Connected technology

Advertisers must think differently in the context of a connected world. This is one of the biggest takeaways from Econsultancy’s report.

This is because technology such as smartwatches, cars, and household appliances (like fridges or thermostats) have opened up a wealth of valuable new data and potential insight for advertisers to draw upon. Of course, some brands are already making use of this data. Take Siemens, for example, which has partnered with Finish dishwasher tablets. Siemens’ ‘Home Connect’ technology updates the owner’s Amazon shopping basket when their supply of dishwasher tablets is running low.

In a more simplistic sense, the connected world also just means the opportunity for a larger amount of screens – i.e. on our car dashboard or freezer door. This means that advertisers will need to think beyond connected TV’s and smartphones (and standard 16:9 ads).

That being said, advertisers must also think differently in terms of how they approach advertising on connected devices. Providing something of value for consumers is key, and a necessity if brands want to ensure real results (rather than apathy towards an ad-saturated world).

By Nikki Gilliland

Sourced from Econsultancy

In News

A new customer experience: How AI is changing marketing

May 17, 2019 No Comments

Sourced from AdAge

In the summer of 1956, 10 scientists and mathematicians gathered at New Hampshire’s Dartmouth College to brainstorm a new concept Assistant Professor John McCarthy called “artificial intelligence.” According to the original proposal for the research project, McCarthy—along with fellow organizers from Harvard, Bell Labs and IBM—wanted to explore the idea of programming machines to use language and solve problems for humans while improving over time.

It would be years before these lofty objectives were met, but the summer workshop is credited with launching the field of artificial intelligence (AI). Sixty years later, cognitive scientists, data analysts, UX designers and countless others are doing everything those pioneering scientists hoped for—and more. With deep learning, companies can make extraordinary progress in industries ranging from cybersecurity to marketing. It’s just a matter of knowing where to start.

Think of AI as a machine-powered version of mankind’s cognitive skills. These machines have the ability to interact with humans in a way that feels natural, and just like humans they can grasp complex concepts and extract insights from the information they’re given. Artificial intelligence can understand, learn, interpret, and reason. The difference is that AI can do all of these things faster and on a much bigger scale.

“In the era of big data, we have the need to mine all of that information, and humans can no longer do it alone,” says Mark Simpson, VP of offering management at IBM Watson Marketing. “AI has the capacity to create richer, more personalized digital experiences for consumers, and meet customers’ increasingly high brand expectations.”

The knowledge companies stand to gain by using AI seems to have no bounds. In healthcare, medical professionals are applying it to analyze patient data, explain lab results and support busy physicians. In the security industry, AI helps firms detect potential threats like malicious software in real time. Marketers, meanwhile, can use AI to synthesize data and identify key audience and performance insights, thus freeing them up to be more strategic and creative with their campaigns.

There’s something else AI is very good at, and that’s improving the relationship between companies and consumers. “Even in its earliest iteration, AI helped companies better understand how to be human,” says Brian Solis, author and principal analyst at Altimeter, the digital analyst group at brand and marketing consultancy Prophet. “The irony is that it took this very advanced technology to make them think differently about how they should communicate with their customers.”

Over the past 50 years, Solis says, advances like speech technology, automated attendants, virtual assistants and websites have opened a chasm between companies and customer engagement while also multiplying consumer touchpoints. But AI has the potential to close that gap.

By helping marketers collect data, identify new customer segments and create a more unified marketing and analytics system, AI can scale customer personalization and precision in ways that didn’t exist before. Connecting customer data from sources like websites and social media enables companies to craft marketing messages that are more relevant to consumers’ current needs. AI can deliver an ad experience that is more personalized for each user, shapes the customer journey, influences purchasing decisions and builds brand loyalty.

IBM’s Watson Marketing is leading the charge with a platform that capitalizes on all that AI has to offer. Products like Customer Experience Analytics lets marketers visualize the customer journey and identify areas where consumers might be experiencing friction. Companies get a more complete view of the customer journey, which they can then optimize to improve customer engagement and conversion rates. Since it’s delivered through a single, unified interface, IBM Watson Customer Experience Analytics makes gaining actionable intelligence a seamless process for brands.

According to market research firm TechNavio, the AI market in the U.S. is expected to grow at a compound actual growth rate of about 50 percent through 2021. In its 2017 report “Artificial Intelligence: The Next Digital Frontier?” the McKinsey Global Institute urges companies not to delay “advancing their digital journeys”—especially when it comes to leveraging AI. “It’s those who understand how to use AI in new ways, to create new mindsets and paradigms, that will instill a competitive advantage that wasn’t there before,” Solis says.

We’ve entered the age of deep learning, and with human guidance AI is finally reaching its true potential. Today, the technology McCarthy and his colleagues dreamed about in 1956 takes the form of AI platforms like Watson Marketing. And now is the right time to truly harness the power of AI and put it to work for business success.

Find out more about how Watson Marketing can uncover insights to help you better understand your customers. Read the Guide.

Sourced from AdAge

Content Provided by IBM with Insider Studios. Insider Studios is the branded content studio for Insider Inc., the parent company of INSIDER and Business Insider.

In News

The AI Breakthrough in Service Industries

December 14, 2018 No Comments

By Rilind Elezaj

Among the service industries to benefit the most from the AI breakthrough are the Banking, Insurance, Telecom, and Utility Industries.

It is now no secret that Artificial Intelligence is the next big thing. It is set to transform our entire way of life, from how we live to how we work and how we interact with one another.

In fact, we are already seeing some of the effects of Artificial Intelligence in most industries today.

Artificial Intelligence is currently being utilized in a wide variety of businesses and is widely used in many award-winning apps and software in the market, particularly in service industries, the AI role will only continue to rise.

The service industry landscape has shifted to acknowledge the importance of Artificial Intelligence.

Among the service industries to benefit the most from the AI breakthrough are the Banking, Insurance, Telecom, and Utility Industries.

AI in the Banking Industry

3D illustration of a robot hand holding for a generic credit card with NFC technology. Credit card is fictitious. PixOne / Shutterstock.com

The banking industry has benefited massively from the introduction of AI systems, and will only continue to do so.

Some of the areas that have been impacted include:

– Customer Experience

AI chatbots are all over the place in the banking industry. Almost every major bank has one. These bots have streamlined customer interactions and improved customer experience and satisfaction. App development companies have made it possible for clients to be able to ask for banking assistance and receive it without having to visit a bank at a physical location. This adds a level of convenience that customers appreciate. This is only achievable with AI.

– Management of Customer Data

The breakthroughs of AI in the management of customer data is outstanding. For example, when JPMorgan Chase’s Contract Intelligence AI was given the task to review their 12000 commercial credit agreements, it managed the task in a few seconds. This compared to the estimated 360,000 hours manual evaluation normally took. The AI has now officially replaced humans in performing this task, freeing up more human resources for other sectors. Today, similar AI can be used to manage emails, articles, phone calls and other legal documents.

– Banking Security

AI is changing the way banks secure themselves. Cases of money laundering have previously plagued the industry, but this will all soon change. Banks have started seeking tailored AI solutions to help them combat the vice.

AI in Insurance Industry

AI, artificial intelligence, in modern medical technology. IOT and automation. Wright Studio / Shutterstock.com

AI is literally shaking up the insurance industry. Today, traditional insurance and underwriting are being updated to become more efficient and more consumer-friendly through the utilization of AI technologies. Some of the changes we are bound to see more of include:

– Micro changes

AI is slowly making it possible for insurance companies to access user data and tweak their offers to suit user behaviour. This is only going to be more prevalent in the future. For example, your car sensor may show that you have a history of reckless driving, and consequently, your car insurance rate may increase by 1%. If you are a very good driver, your car insurance rate may drop by 1%. This tweaking not only rewards good drivers but also results in more revenue for insurance companies.

– Customer interactions

The insurance industry stands to benefit greatly from the advances being made in AI for customer interactions. Soon, we may see app development companies develop insurance apps with assistants that warn you if you engage in activities that could lower your insurance rate, or alert you when you are doing something that could boost your rates.

– AI May Make Some Insurance Sectors Obsolete

By 2020, driverless cars will be common on our roads. This shift will bring with it many changes to the insurance industry. The much safer cars will lead to a much lower accident rate for example.

Auto insurance may stop being as lucrative, and insurance companies may have to adapt and switch to ensuring car manufacturers as opposed to individual drivers who will see no need for auto insurance.

AI in the Telecom Industry

Chat bot and future marketing concept . Customer hand holding tablet look for ticket and popup out smart phone screen with automatic chatbot message screen , airport background (Photo Credit: www.shutterstock.com)

The Telecom Industry benefits from the advantages of using AI on three fronts:

– Customer Service and Retention

AI has enhanced customer service in the Telecom industry. The rise in customer service solutions such as chatbots has eased communication between customers and their Telecom companies. This leads to better user experience and satisfaction. AI can also be used as customer service agents, where they interact directly with clients, making the customer service process more cost-efficient.

– Sales and Personalized User Experience

AI has also helped companies in the Telecom Industry to improve customer retention and boost the amount of revenue earned per user. The immense power of AI can be harnessed to offer personalized product recommendations to clients, assessing the type of call or data packages that suite a potential client pre-sale to increase sale success rates, and analyzing social media, brand image, and customer feedback and offering recommendations to help make the company better.

– Network Analysis

AI plays a huge role in the network maintenance of Telecom companies. Optimized networks are a necessity today, especially due to increased data consumption. Telecom companies need to adapt and cater to their users’ needs. In the Telecom Industry, AI is being used as a network maintenance solution with a focus on the creation of self-healing, self-learning, and self-optimizing networks. This approach has proven to be future proof and sustainable.

AI in the Utility Industry

Unrecognizable corporate water utility executive managing meter data via advanced metering infrastructure solution. Industry concept for AMI, SaaS, managed services, MDM, IoT, network as a service. LeoWolfert / Shutterstock.com

The Utility Industry is already gaining a lot from the application of AI technologies. For example, AI is being used in:

– Yield Optimization

In the utility industry, total yield equals total revenue. An increase in total yield usually means an increase in revenue. The application of AI technologies has led to optimized yields. For example, in the power production sector, power generation efficiency can be optimized by using real-time adjustments across their assets to maximize output while minimizing resource use.

– Predictive Maintenance

Maintenance is a huge deal when it comes to the utility space. With the help of AI, drones equipped with deep learning algorithms can be deployed to help automatically identify defects and potential failure points, predicting when maintenance will be needed. This does away with costly and inaccurate manual inspections.

– Customer Insights

AI can be used to help utilities maximize margins and minimize consumption. They can also help craft individual customer offers or deals on their services that will allow utility companies to gain new customers, create a larger user base and boost customer loyalty.

By Rilind Elezaj

Rilind Elezaj is an experienced Digital Marketing Specialist with a demonstrated history of working in the marketing and advertising industry. Rilind possesses a strong entrepreneurial mindset and has devoted his career to enhancing the sphere of digital marketing. In his methodological approach, Rilind integrates web development and other digital marketing solutions to create hybrid strategies that bring the best results.

Sourced from TALK IoT

In News

Technology’s the new passport to better travel

October 31, 2018 No Comments

Sourced from IOL

KEYNOTE speakers provided insight into how technology was transforming travel, at the TravelPort LIVE Africa conference in Hermanus last week.

Mike Croucher, Travelport’s chief architecture, spoke about digitally reimagining travel.He pointed out:

What today’s hyperconnected travellers want and what they value have changed. While cost, choice and convenience are still significant, booking decisions are now based on the experience.

From the moment a traveller thinks about a trip to planning it, booking it and living it we, in the travel industry, must deliver a convenient, personal, all-encompassing experience.

Competition is fierce. Disruptive businesses like Airbnb and Uber, adept at delivering new inspirational experiences, have torn down long-standing monopolies and eroded brand loyalty.

What makes it more than just a trip?

The Internet of Things:

The IoT relates to the interconnection, via the internet, of computing devices that are embedded in everyday objects required to send and receive data at speed. Human beings, however, do not interact directly with the IoT. Instead, we have a mobile device, through which we can digitally exchange information and personalise experiences. This could be adjusting the temperature in a hotel room or pre-ordering room service before arrival.

Mobile:

According to the GSMA, more than two-thirds of the world’s population, 5billion people, are connected to a mobile service. South Africa’s research conducted with 11000 respondents from 19 countries revealed just how vital cellphones are for travellers.

Not only do 33% of travellers book their trips on a mobile device, but 62% also say digital boarding passes and e-tickets make travelling easier and 46% say a good digital experience is important when choosing an airline. The mobile acts as a travel companion. From searching to returning, it determines the traveller’s experience of and the overall journey. It offers a means of continuous, one-on-one engagement, enabling different offers and the availability of services to be tailored to an individual’s preferences. To do this, a mobile device needs intelligence.

Artificial Intelligence (AI):

AI can unlock insights to create the personalised experience. It allows businesses to become more proactive and strategic through predictive capabilities – that is recommendation engines that suggest the best time to buy a flight, book a hotel and so on. By informing a travel AI, training it and providing it with access to extensive real-time data sets, opportunities to deliver frictionless experiences become seamless.

Big Data:

The way we share, analyse and absorb information through technology has exploded to the point where big data’s usage is commonplace. Aside from the benefits of shaping individual travellers’ experiences, businesses can leverage data to better understand what is/isn’t working. Data is the fuel that powers 21st-century commercial intelligence.

In the travel industry, by analysing a complex set of data points like travel history and demographics, predictive analytics can plot travellers’ next moves before they know what they are themselves. To use the data, we need access to significant quantities of computing power. Some of this can be provided by cloud-based infrastructure.

Cloud computing:

Cloud computing technology provides the infrastructure to compute vast amounts of data quickly, affordably and on demand. It is the glue that holds the travel industry together by enabling data and content to be moved with relative ease, as well as computed and delivered as close to the point of consumption geographically as possible.

What does the future hold?

“We should be excited about what the future of the travel industry holds,” Croucher says. “In the Fourth Industrial Revolution, delivering the right kind of travel experience is going to rely on practically applying the technologies described here. The onus falls on us to be enterprising enough to grasp the opportunities.”

Sourced from IOL