Powered by massive leaps in AI, deep learning, and on-device processing, today’s automatic speech recognition (ASR) systems are faster, more accurate, and more context-aware than ever before. Far from simply converting voice to text, speech AI systems can help shorten your workday, secure your home, and even drive your car.

Key takeaways

• Automatic speech recognition (ASR) uses technology to convert speech into text. Speech AI systems use AI and NLP models to extract insights from this data and make decisions.
• Digital assistants like Siri and Alexa use speech recognition to interpret voice commands and act as agents on users’ behalf.
• Speech recognition technology is used in a variety of industries to improve efficiency, safety, and outcomes. For example, virtual meetings are transcribed and summarized instantly. And while driving, people can use voice commands to monitor their navigation.

What is speech recognition technology?

The umbrella term ‘speech AI’ encompasses several distinct, yet interconnected, technologies, all powered by machine learning to analyze audio data.

Automatic speech recognition (ASR) is the technology that converts spoken words or recorded audio into written text. This is also referred to as ‘speech-to-text.’ ASR’s primary goal is accurate transcription.¹

Examples of ASR include:

• Using your smartphone’s dictation feature to record a voice note that is automatically transcribed and sent as a text message.
• A doctor using a dictation system to transcribe patient notes directly into an electronic health record.
• Live captioning on a TV broadcast or online video.

Natural language processing (NLP) is a subset of machine learning in which computers interpret, manipulate, and comprehend human language. Speech recognition is an example of NLP for audio data. There is also text-based NLP that analyzes large corpuses of written information.²

Examples of NLP include:

• A language translation app that converts text from one language to another.
• Automatic grammar and spell-check systems.
• Email filters that automatically detect spam based on the language used and metadata.

Audio intelligence refers to the application of machine learning models to extract insights from audio data and complete tasks like sentiment analysis or content moderation. Audio intelligence relies on automatic speech recognition to convert audio data into digital information and NLP models to complete tasks.³

Examples of audio intelligence include:

• A smart home device detects the sound of a fire alarm or a window breaking to send a security alert to authorities.
• Software that listens to recorded customer service calls and automatically identifies and categorizes the customer’s tone as positive or negative.

What are speech recognition digital assistants?

Digital assistants are designed to help people perform or complete basic tasks and respond to queries. With the ability to access information from vast databases and various digital sources, these robots help to solve problems in real time, enhancing the user experience and human productivity.

Popular digital assistants, include:

• Amazon’s Alexa
• Apple’s Siri
• Google’s Google Assistant
• Microsoft’s Cortana

Five applications of speech recognition technology for 2026

Speech recognition technology and the use of digital assistants quickly moved from mobile phones to homes. Today, its application is apparent across crucial industries, including healthcare, banking, and marketing.

1. Speech recognition in the workplace

Speech recognition technology in the workplace is moving beyond simple voice commands to become a primary engineer for productivity and efficiency. The core goal of this technology in the workplace is the elimination of low-value, repetitive administrative tasks, freeing employees to focus on strategic work.

• Meeting and notetaking automation: AI serves as a virtual meeting scribe for the hybrid work environment. Using ASR technology, platforms can automatically transcribe conversations in real-time, even with multiple speakers or diverse accents. These systems immediately extract insights, generate summaries, and identify next steps or action items to share with participants.⁴

• Customer service: Speech AI and ASR are leveraged in the customer service industry to augment human work. For example, real-time agent assist features can do live sentiment scoring and summary of customer calls, providing immediate, actionable insights for representatives.⁵

• Workplace accessibility: Speech recognition is critical for making in-person and hybrid work environments more accessible for all employees. Real-time transcriptions provide support for people with hearing impairments or language barriers.

2. Speech recognition in banking

For the banking and financial services industry, Speech AI can help achieve two main goals: enhancing security and fraud prevention and creating a frictionless customer experience. The technology moves beyond simple account inquiries to handle complex authentication and compliance requirements.

• Personalized self-service: Speech-based tools can allow users to schedule recurring payments, check available funds, and review past transactions over the phone. For example, some bank mobile apps offer users the ability to use their microphone to send money via Zelle or transfer funds.⁶

• Call routing: Speech AI can interpret live phone calls to immediately route customers to the right bank department or specialist, reducing the need for transfers. This can also lead to shortened resolution times.⁷

3. Speech recognition in marketing

Speech AI has added a new dimension to how marketers interact with consumers, making search and shopping more conversational and immediate. This shift requires marketers to pivot their digital strategies to focus on how people talk, not just how they type.

• Voice commerce: Shopping via voice command is expected to produce $81.8 billion in sales worldwide in 2025.⁸ Consumers use voice assistants to research products, check prices, and make purchases. This move towards V-commerce mandates that brands optimize product listings and checkout experiences to work via voice commands.

• Conversational SEO: Voice queries tend to be longer, more conversational, and more question-based than typed queries. Marketers must optimize content for long-tail keywords and answer-focused content.⁹

4. Speech recognition in healthcare

In healthcare settings — where accuracy, speed, and hands-free operation are matters of patient safety — Speech AI offers transformative potential for clinical efficiency and reducing physician burnout.

• Documentation: Digital scribes use ASR to document provider-patient interactions and then summarize the visit, populate diagnostic fields, and create billing codes. In a study of nurses who used speech recognition systems to record and document nursing reports, researchers found that paperwork reduction, performance improvement, and cost reduction were some of the most common benefits.¹⁰

The most significant concern using speech recognition in healthcare is the content the digital assistant or AI platforms can access. Hallucinations, transcription errors, and omissions all pose risks to patient privacy and safety. Proper guardrails and oversight can help mitigate these risks.¹¹

5. Speech recognition and the Internet of Things

Speech recognition is a core component of the Internet of Things (IoT), acting as the interface between interconnected smart devices. This is expanding beyond basic smart home features into complex multimodal systems and large-scale industrial applications.

• Automotive control: In vehicles, Speech AI can help manage navigation, climate control, and infotainment systems. By allowing drivers to interact using natural speech, the technology reduces cognitive load and visual distraction.¹² Researchers are also experimenting with ‘hearing cars’ — vehicles equipped with external microphones and AI to help detect and classify hazards that autonomous cars can’t see. Approaching emergency vehicles are the first hazard being tested, but future capabilities could include sensing pedestrians or failing brakes.¹³

• Multimodal security: The future of IoT is multimodal, combining voice with other inputs like computer vision (for facial recognition) and gesture control. For example, a system can confirm a user’s identity via voice biometrics while simultaneously verifying their face, offering a higher level of security for unlocking doors or authorizing sensitive transactions.

Future applications

The speech and voice recognition market is experiencing an explosion of growth, driven by breakthroughs in AI and the rapid integration of large language models (LLMs). The global conversational AI market alone is projected to reach over $136 billion by 2035.¹⁴

The future of speech recognition could include developments in contextual intelligence and multimodal integration.

• Context-aware AI: Autonomous AI agents are systems that can set goals, plan complex tasks, and act with little human intervention. This could mean that instead of waiting for a command, future voice assistants might be able to anticipate user needs. For example, automatically adjusting the vehicle temperature based on a passenger talking about how warm they are.

• Multimodal integration: When Speech AI is integrated with visuals, gestures, and sensor data, it will become more powerful. For example, visual analysis of speakers’ lip movements could help reduce transcription errors. Another example of a future use case is with large-language model (LLMs) applications, like Gemini Live. Users can speak directly to an LLM and have a conversation with the AI system about uploaded files, photos, or a live feed from the phone camera.¹⁵

Explore online artificial intelligence courses and machine learning courses to explore speech AI and the models that power these platforms.

MIT Sloan School of Management
Artificial Intelligence: Implications for Business Strategy

Saïd Business School, University of Oxford
Oxford Artificial Intelligence Programme

MIT Sloan School of Management
Artificial Intelligence in Health Care

MIT Sloan School of Management
Artificial Intelligence in Pharma and Biotech

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With sound cybersecurity in place, you’re never powerless. It tips the odds back in your favor by shrinking the attack surface and helping you recover quickly before the damage spreads.

What is a cyber attack? 

A cyber attack is a deliberate attempt to disrupt, disable, destroy, or take control of computing systems, or corrupt or steal data.² It can be as simple as a fake invoice email or as advanced as a malicious flaw buried in software.

What makes cyber attacks challenging is their variety and intent. The spectrum ranges from nuisance-level disruptions to nation-state operations. However, the common thread is that they exploit weaknesses, whether that’s in technology, processes, or human behavior.

Why does cybersecurity matter?

At the heart of cybersecurity is the CIA triad of confidentiality, integrity, and availability. Confidentiality keeps information private, integrity ensures data isn’t altered, and availability makes systems accessible when needed.³

Picture these as the three legs of a stool. If one leg breaks, the whole seat collapses, regardless of how sturdy the other two are. A cyber attack in practice is any strike that topples one of these supports; and the fallout is costly.

In the United States, it costs organizations $10.2 million on average to recover from a data breach. In South Africa, recovery costs average about $2.4 million per breach.⁴

How cyber attackers work

The front door to most cyber incidents is people, not code. Attackers lean on human behavior, which is why phishing and social engineering attacks are so common. Once inside, intruders escalate privileges, plant malicious code, or wait until the right time.

Most incidents follow a pattern:

• An attacker picks an entry path, like email
• They deploy a tactic, such as malware-laced attachment
• They chase impact, such as data exposure

Modern attackers even use AI to mimic voices or draft emails that feel authentic. Tools like ChatGPT are misused to generate convincing phishing emails, fake customer service chats, or fraudulent job postings. Attackers use these models to write error-free messages that bypass typical ‘bad grammar’ red flags.

This is what a cyber attack looks like in everyday life. Imagine a phishing scam:

1. An attacker picks the email entry path
2. They send a message that looks like it’s from your bank, warning of ‘suspicious activity’
3. You click the link, which leads to a fake login page
4. Once you enter your details, the attacker has your credentials
5. With access, they move quickly, transferring funds or using the account to launch further scams

What are the types of cyber threats you’re likely to encounter?

Most cyber attacks fall into six familiar categories.

1. Malware

Malware (short for “malicious software”) is any software designed to harm, disrupt, or spy.⁵

• Classic viruses spread from machine to machine
• Trojans disguise themselves as harmless files
• Spyware lurks in the background to log keystrokes or send back sensitive information

Modern malware strains can spread faster than IT teams can contain them, leading to corrupted machines, stolen credentials, and entire departments idled for days.

Preventing malware starts with healthy security habits in the organization. Security teams should patch software regularly and staff must be trained to treat unknown attachments with caution.

2. Ransomware

Ransomware locks your files or entire systems, then demands payment for release. Attackers now also add a cruel twist known as double extortion, where they threaten to leak your data if you refuse to pay.⁶

When ransomware is used against businesses, reputations can suffer and decision-makers face the agonizing choice between paying criminals or rebuilding systems from scratch.

Defense usually comes down to building resilience. Companies can:

• Keep offline backups so attackers can’t touch them
• Divide networks into smaller sections to limit damage
• Use multi-factor authentication (MFA) to make stolen passwords useless
• Run practice scenarios, so staff know their roles when a ransomware attack hits

3. Phishing

Phishing (or ‘smishing’ when done via text message) is the art of digital deception where attackers craft messages that look genuine in an effort to steal sensitive information. This could look like an urgent note from the CEO, a bank alert, or even a QR code promising a delivery update.⁷

In March 2025, the FBI flagged a smishing scam where attackers pose as E-ZPass, texting drivers about ‘overdue tolls.’ The messages include a fake payment link that takes targets to a spoofed site designed to steal banking credentials and personal information.⁸

It’s the most common method: 16% of all cyber attacks against organizations are phishing, according to IBM.⁹

To defend against phishing, companies can:

• Invest in layered email filters
• Adopt passkeys
• Provide role-based training

4. Denial-of-service (DoS)

A denial-of-service attack overwhelms a system with more requests than it can handle, like prank callers tying up every phone line in an office. When scaled across thousands of hijacked machines, it becomes a distributed denial-of-service (DDoS) attack.¹⁰

To customers, the site appears broken, which can erode trust overnight.

Mitigation relies on tools that spread out the heavy traffic so no single system gets overwhelmed. For example, companies might:

•  Use networks of servers around the world to share the load
• Set up filters to block suspicious traffic
• Build clear communication plans to keep customers know what’s happening

5. Zero-day exploits

Zero-day exploits target vulnerabilities unknown or unaddressed security flaws, leaving defenders blind until the first attack is detected. The name “zero-day” comes from the fact that there are zero days to fix the problem because malicious actors are already using it.¹¹

For decision-makers, installing software updates is dangerously insufficient, as attackers can strike before patches even exist. That’s why organizations add extra layers of defense, such as:

•  Tools that watch for unusual activity
• Limits on who can access what
• Teams trained to respond quickly if something suspicious appears

6. Account takeover (ATO)

In an account takeover, criminals obtain or guess login credentials to take control of financial, social media, and email accounts. Once inside, they can drain bank accounts, reroute deliveries, or siphon loyalty points.¹²

The most effective protection against ATO is making stolen passwords worthless. Companies do this by:

•  Adding extra login steps like a code sent to your phone
• Setting up rules that flag suspicious behavior
• Linking accounts to trusted devices
• Scanning the internet for stolen credentials so they can act quickly if customer details are exposed.

What does good cybersecurity look like?

Strong cybersecurity policies are part of a long-term strategy that strengthens over time. Instead of wrapping a business in steel walls, leaders should focus on creating shock absorbers that minimize impact when bad actors slip through.

People: 

Role-based training can help apply practical cybersecurity steps to different teams facing a variety of risks.¹³ For example, finance staff might see fake invoice emails, while IT teams could be tricked with technical-looking requests.

Companies also run short practice drills across departments, like test phishing emails, so spotting scams becomes second nature.

Process:

Clear, lightweight playbooks for common scenarios can be critical. For example, a ransomware response guide should outline who makes the call on shutting down systems, who contacts law enforcement, and who handles press inquiries.¹⁴

Other processes can be integrated into how an organization runs their website. Rate limiting helps defend against denial-of-service attacks by capping the number of requests a single user or system can make.¹⁵

Technology:

Technical controls don’t need to be flashy to be effective. Multi-factor authentication, passkeys, and regular backups can instantly remove the low-hanging fruit that attackers rely on. More advanced tools, like endpoint detection and web application firewalls can act like digital security guards.¹⁶

Culture:

A culture of security means staff feel safe to report mistakes without fear of punishment. It also means leadership treats cybersecurity as part of business continuity, rather than just an IT expense line.

Education is just as critical as technology. Continuous learning helps staff recognize threats and respond effectively. Organizations can consider short, practical online cybersecurity courses to build skills across all levels, from foundational awareness to advanced risk management.

Frequently asked questions

What is ransomware in cybersecurity?

Ransomware is a type of malicious software that locks your files or systems and demands payment, often in cryptocurrency, to release them. Beyond locking data, some ransomware gangs also threaten to leak sensitive information if businesses refuse.

What are the most common types of cyber threats?

The most common cyber threats fall into six main groups: malware, ransomware, phishing, denial of service, zero-day exploits, and account takeover attacks. Each works differently but targets the same goals: disrupting operations, stealing data, or hijacking accounts.

What are the differences between malware and ransomware?

Malware is a broad term for any harmful software, like viruses, spyware, or trojans. It’s the umbrella under which ransomware sits. Ransomware is a specific type of malware with a clear objective of locking or stealing data to demand payment.

How do cyber threats impact businesses?

Cyber threats hit businesses in multiple ways. They can cause outages and halt sales, leak customer data to damage trust, or trigger regulatory fines. A single breach can also force costly system rebuilds or ransom payments. Beyond money, the reputational damage lingers as clients may hesitate to return if they doubt your security. For smaller companies, the impact can be difficult to recover from without a strong security baseline.

How can individuals protect themselves against cyber threats?

Individuals can reduce risk with a few simple habits:

• Use strong, unique passwords paired with multi-factor authentication so stolen logins are useless.
• Keep software updated to close security gaps.
• Treat unexpected links or attachments with caution, especially in emails or texts.
• Back up important files so ransomware can’t trap you.
• Stay alert. Pausing for a moment before clicking can be the best defense against attackers’ tricks.

University of Cape Town (UCT)
Fundamentals of Cybersecurity online short course

HARVARD'S VPAL
Cybersecurity: Managing Risk in the Information Age online short course

The post What are the types of cyber threats? An easy-to-understand guide appeared first on GetSmarter Blog.

The accelerated use and integration of applications, algorithms, software, and smartphones is revolutionising how brands reach and engage with hyper-connected audiences. However, L’Oréal Professor of Marketing and Associate Dean of Research at Saïd Business School, University of Oxford, Andrew Stephen, cautions brands against letting the technology drive the solutions. 

Transcript

What are we talking about when we, when we refer to this thing called marketing technology? So really, it encompasses pretty much anything, from technology being used in marketing. So software, applications, algorithms, overall programs and platforms, the hardware, fast computer processes, increased resolution, you know, smartphones themselves, things like interactive billboards even could be considered within marketing technology. And then all the services wrapped around that. So not just sort of software as a service type concepts, but also consulting, implementation, project management, systems integration, you name it, sort of all the IT world type services being brought into particular marketing applications.

So how do we bring this into the context of, of marketing practice?

So, really the world these days is governed by algorithms and we can automate a lot. And then in marketing, we see tons of marketing automation driven by algorithms. There’s a lot of automation that happens now in marketing, and that’s really one of the big things that marketing technology has provided.

And it’s really, actually, at the end of the day, there to help better serve hyper-connected customers. So if we think about algorithms in marketing and automation in marketing, which are powered by algorithms, from a customer perspective, they’re really there to help marketers better reach and engage with customers, find the right customers in a complex landscape where, let’s say on Facebook, an individual user on Facebook might be defined by literally thousands of characteristics. There’s no way in the world a marketer could manually decide how to target ads at a person on the basis of that many variables. So of course we need algorithms.

Of course, we need some, some level of automation to help marketers actually effectively and efficiently reach and engage with customers. 

Just because there is a solution, just because, you know, there is a tech service you could buy or lease does not mean that there’s a problem that needs to be solved. So I think putting the cart before the horse, or sort of the tech solution before the problem, is obviously not the way we should do it, but it happens all the time.

And of course marketing technology companies are going to tell you they’ve got the best solution to whatever problem or set of problems. But don’t let them drive your solution-finding. Think about what your problems are, and then go out and find the solutions from marketing technology to help you.

But it’s a really exciting space. And I think it’s one that professional marketers nowadays, and into the future, really need to be up on because there’s a lot of innovation happening in marketing technology. 

The post Marketing Technology Strategy: What Is MarTech? appeared first on GetSmarter Blog.

Algorithms and AI play an increasingly influential role in how we experience the world, the decisions we make, and our perception of reality. So how can marketers ensure that they’re using this technology responsibly?

Transcript

I think it’s actually quite difficult to go through the day, any day, without having a machine curate what you see and mediate your experience with the world around you. We’re already at a point where what we choose to eat, who we choose to date, how we drive, and what directions we take are being affected and mediated by technology.

I think what’s important about that though, is that that increase in spread is also being accompanied by a decrease in the consciousness around the fact that this is happening. So it’s become so natural for us to have algorithms and artificial intelligence curating our world. And for us to seek information through these means that we kind of can go on autopilot – it’s so comfortable. So I think as we look to the future, the question becomes not just spread, it becomes whether we even notice it at all.

This filtering and this ability to see the world through the eyes of what the machine has decided is best for you to see is, is the way in which we’re kind of experiencing reality right now. We know from behavioral science that humans, although brilliant, tend to be cognitively miserly.

If it’s too hard to think about, we’ll go with something easier. And that becomes the area in which this influence is really changing the way in which we view our worlds. For me, when I think about social media, I think about the fact that I have family members all over the Earth. And the news that they’re reading about what’s going on in one country, uh, colors their view, not only of that country, but of what my experience is, the kinds of conversations we have, what they think is important to me. And so there’s a path dependency that happens due to this intervention that wouldn’t have happened before. At the same time, I’ve been able to, to plan a family reunion via social media, right? So we have this, we have this, uh, dynamic that is tremendously powerful in positive ways, but also is changing the way in which we interact with each other and not always in good ways.

I think, systematically, we need to think about the processes. So these algorithms ostensibly, are meant to improve our decision making, right? To help us be our better selves. And so I think as organizations create these processes that are algorithmically mediated, the first systematic question is: a) Should we do it? Should we? Should we have an algorithm or machine learning making the decisions with us at this point?

The second question, I think we should ask, is to what degree is this being designed with humans in mind? 

And that’s really important because humans are fallible, have biases, and may rely on algorithms to rationalize decisions that otherwise they’d have to explain themselves.

In other words, if we have biases in algorithms and machine learning, and that supports our own biases, we may feel more robust in the flawed conclusions that we make. And so, I think a really important question is how does this interact with the tendencies of human beings to be cognitively miserly, but also to want to be shown that the way they think is right, to not want to be challenged?

The post The Power of Algorithms appeared first on GetSmarter Blog.

Transcript

As mobile has become more integrated into our lives, consumer expectations have changed significantly. Consumers now expect firms to anticipate their needs and satisfy them in a personalized and context-specific way when they want, where they want. Every time the customer pulls out a mobile phone to solve a problem along their customer journey, there is a mobile moment, and they expect some firm to help them solve that problem. The competition for customers now increasingly occurs in these mobile moments. Whichever firm helps the customers to move along their journey, with the least friction, wins. This means that firms must design consumer experiences around mobile moments and mobile journeys.

With mobile, marketers can now easily offer targeted messages to customers based on their location. The two most common practices are: one, geo-fencing, where a firm sends targeted messages to customers near its location in order to defend the people close to you; and two, geo-conquesting, where the firm sends targeted messages to a customer who’s near a competitor with the intent of poaching that competitor’s customer. For example, when a coffee chain sends you a discount when you’re right next to it, that is geo-fencing. But when it sends you a coupon when you’re next to a competitor, that would be geo-conquesting.

Of course, marketers know more than location. They also know the time, which can improve targeting. For example, suppose you’re near a cafe and a pub on a Friday afternoon at 2p.m. A message from a cafe for coffee would be more effective at this time. But when it is 8p.m., a message from the pub would be more effective.

Let’s consider a banking example. Using location data, some banks are now able to offer loans to customers who have installed their app on their cell phone. As soon as they notice that the customer has spent a lot of time in a car dealership or around a home that is for sale, the bank knows that anyone who spends time in a car dealership or near a home for sale for an extended period is probably looking for a car loan or a home mortgage.

The bank then integrates this information with data from the cloud about the person’s credit history, and is able to assess whether the person is a good credit risk. It’s then able to make a loan offer automatically in real time. The bank completely eliminated the loan application process, the time for underwriting, etc., and significantly reduced any of the unnecessary frictions in the customer journey.

Because, after all, consumers only want a loan, nobody wants to go to a bank or fill a form, etc. Those are purely frictions in the journey. You can imagine that this bank would easily win against the competition in the mobile moment against any bank that requires you to visit it. This kind of digital, mobile-driven innovation is completely disrupting traditional banking as branches are now being seen more as a friction than as a source of customer value in the customer’s journey. 

Mobile has two distinguishing characteristics that differentiate it from desktops: it’s location aware and it is portable. These two characteristics, combined with time, weather, and other data that you could partner with other firms, have significantly enhanced the ability of firms to perform contextual targeting that reduce frictions in the customer journey.

The post Marketing in Mobile Moments appeared first on GetSmarter Blog.

We live in an era of disruption in which innovation and technology have transformed the way we live and work at an unprecedented rate. In order to remain relevant, marketers need to leverage emerging technologies to meet changing consumer behaviours, improve engagement, and achieve data-driven impact. One of these technologies is precision targeting. L’Oréal Professor of Marketing and Associate Dean of Research at Saïd Business School, University of Oxford, Andrew Stephen, explains how a brand can use precision targeting to navigate social media algorithms effectively and deliver its message to the right audience.

Transcript

The purpose of precision targeting is to get the right content seen by the right people. You want to get your content messages, ads, and so on in front of the right people, those likely to want to engage with it, and hopefully, who are the most likely to purchase or do something else that’s commercially valuable to your business in response to that advertisement. This is why precision targeting is important.

So let’s use the analogy of a dartboard – placing ads on a social media site with two and a half million users is likely to be as accurate as playing darts blindfolded. Where your ads end up and who they’re seen by is really going to be out of your control, determined by algorithms, and is not very likely to reach the audiences who would be interested in your ad.

Now consider the data available on consumers, such as age, location, gender, relationship, languages, education, work, their hobbies, and interests, and so on, and so on, and so on. The opportunity that precision targeting presents, being able to target audiences who would find your ads most appealing and relevant, therefore can be built off this technology that, that knows something about people. Targeting can therefore be really broad, as something like potential customers who live in a certain country or state. Or, if you desire, you can get as specific as potential customers who live in a certain country, currently university students, have shown interest in your brand on another platform, and so on. So let’s have an example. Consider the potential that this all presents for a company that offers live acoustic bands for weddings.

So, using precision targeting, what would this company be able to do? Well, they’d be able to narrow down potential consumers who live in the city – where they’re based – who currently identify as being in a relationship on social media, uh, and who have liked or followed groups associated with that type of music, so live acoustic music. And so that when someone’s relationship status changes to engaged, that’s the trigger. Um, they could use precision targeting to really show a targeted advertisement at people who are therefore most likely to want the services offered by this company. So they can really get on the radar of the consumer who’s planning a wedding. 

The only thing to be mindful of with precision targeting though, is it can get too far. So you can, you can go too far and veer into what I call creepy territory, where you’re even risking the perception that you’re invading the privacy of potential customers. So the best practice is to narrow down your targeting, but not to be so narrow that it could feel invasive or creepy in any way that feels like a breach of privacy. The other practical reason for not going too narrow is, at the end of the day, you do need some volume in your business. So, so narrowing it down to target just one person is probably, most of the time, not going to be enough customers to sustain the business. So you do need some mass reach in there, but it doesn’t have to be the whole universe.

I hope these visual analogies made the concepts of precision targeting and programmatic advertising more real and relatable.

The post The Value of Precision Targeting appeared first on GetSmarter Blog.

How and when brands interact with their customers has changed significantly in recent years. Frank Dudley, a lecturer at Medill School of Journalism, Media, Integrated Marketing Communications at Northwestern University, explains how a dynamic marketing approach drives engagement at every touchpoint, using various channels, and at every stage in the consumer journey.

Transcript

During most of the first decade of the 21st century, we have seen the evolution of digital marketing in terms of channels, including social media, mobile apps, et cetera. However, up until about 2015, almost all digital marketing was still primarily direct marketing over the internet, and was added to marketing services, as it was perceived as one of the many ‘below the line’ marketing functions.

Since 2015, we have been in the era of dynamic marketing, in which digital is no longer a functional below the line area in marketing. In the era of dynamic marketing, all marketing is digital, or digitally enabled, and is driven by customer data and technology. Brands are no longer primarily built through TV advertising alone, but through ongoing customer engagement that can be viewed, shared, reviewed, tracked, and optimized in real time.

We have entered a new age of marketing, whereby customer engagement is driven across multiple channels and various stages of a customer journey for specific segments of customers. There are sometimes multiple customer touch points within several media channels for just one stage of the customer journey.

For example, when in the consideration stage of the journey, you might search on Google, read recommendations on Amazon, Yelp or the company’s website; and seek input from others through social media, such as Facebook or Instagram. Dynamic marketing is a truly new and exciting form of marketing that leverages customer data, both structured and unstructured, to respond to, or anticipate, customer needs within a particular circumstance and with the most relevant content and via the most preferred channel  to fulfill those needs. This enables real-time interaction with customers on a more personalized basis. Unlike the traditional static approaches to marketing that primarily rely upon stimuli to elicit a response from a prospect or customer, a dynamic approach to marketing is much more interactive and fluid. It’s always on.

It’s important for marketing customer experience leaders to understand where a customer is in their journey with the brand and how to trigger the next best action to drive the customer to the next stage in the journey. Today, companies such as Salesforce, Adobe and Microsoft are enabling dynamic interaction with customers and prospects in new and innovative ways.

The post What Is Dynamic Marketing? appeared first on GetSmarter Blog.

“How do you regulate something that’s never existed?” This is the challenge governments face in its efforts to regulate the FinTech industry.  

In this video, Lauren Cohen and Christopher Malloy, Course Conveners in the Harvard VPAL FinTech online short course, discuss the battle between incumbents and start-ups, and consider which companies may be at a disadvantage when further industry regulation comes into effect.

With this in mind, they also reflect on who will lead the future growth of the FinTech industry – will start-ups continue to drive innovation in this sector, or will traditional financial institutions be at the forefront?

Transcript

How do you regulate something that’s never existed? That’s a classic question that technology industries have faced for many years, and now this war between government regulators, incumbents, and start-ups is forefront in the future of FinTech. What’s the right path for government regulation, and how should these FinTech start-ups and incumbents respond to this situation?

So, on this issue of government regulation, the question is, “When is the government going to crack down and when is it not?” And obviously in China, there’s been lots of crackdowns recently. Another case that’s been quite interesting here in the US, is this Madden versus Midland case. Where the government is coming in and potentially regulating FinTech lenders, and saying that they can’t charge above a certain interest rate.

The stated goal of that is, of course, to get rid of what’s called predatory lending, and help consumers from getting ripped off. And the question is, is FinTech ripping off these consumers or not? I mean you could make an argument that FinTech is coming in and helping the exact consumers that the government claims to be worried about.

Whenever you get into this government regulation issue too, then FinTech, are they going to be able to find a way around this? And if they can’t find a way around this, then do you have, Tech on FinTech, like FinTech squared, that’s going to come in, and be able to figure out a way to do it? However much the government wants to regulate these things, it seems like there’s always ways around these.

And so, it’s going to be tough for the government to regulate things like bilateral transactions. If you and I agree that: Okay, I’m going to lend you ten dollars at the beginning of the week, and you want to pay twenty at the end of the week, then of course that’s a massive interest rate. And yet, we might be happy to do that, right? One of us may really need the money until the other is happy to do that, and we’re both better off by making that transaction. So to the extent that the government comes in and tries to tamp down on these – could be not so great for their citizens.

Exactly, and one argument that FinTech companies will make is that these markets don’t exist, but they could exist at some price, and we’re making consumers better off, and – by creating this enormous market – society’s better off.

And so, then the question becomes, “Okay, who is most hurt by this regulation?”

Exactly. So are they going to come after the big established players? Or are they going to crack down the new incumbents?

If history has told us anything, it’s that these government regulators – they have jobs too, and so they want to prove that they’re really doing a great job, and it’s much more newsworthy to take down the big fish. It’s much more newsworthy, if you can take down that firm that everyone’s heard of. And so, in that sense, incumbents almost have more innovative risk in this space, than a new small innovator.

They have large established brands and client bases, and to the extent that they don’t want to put that at risk, they may be less willing to dive into some of these markets, and perhaps that’s why some of these FinTech companies have gotten market share in certain areas where the incumbents have been slow to enter, particularly in developed countries like the US.

But, then, you have this double-edged sword – if I’m late to enter into this market, there’s some kind of brand equity that can be built up from a LendingClub, or a Prosper, or one of these other people, then by the time I want to get into it, it’s too late.

There’s a big first-mover advantage. I can either try, and then compete late, or I try to partner with them. So this partnership angle is something that we’ve seen growing of late. The extent to which FinTech companies always want to build their own brand, and go public, and build a huge business, but now, realizing that maybe it’s in their best interest to partner, and of course, on the incumbent side, perhaps the same way. Like, building all this expertise in-house is quite costly and difficult. It might just be easier to establish a partnership.

You’ve seen this in other industries too, right? We’ve seen this in the biotech-farmer relationship, and how that’s evolved over time. And that, now, much of the innovation in that – in drugs, is been pushed down to biotech, and now large pharma companies – like a Merck or AstraZeneca – simply buy the biotechs later.

And have a marketing role.

Yeah, you can imagine something similar being true here. So, in that sense, what does government regulation do? And what do we need to worry most about in the FinTech space with government regulation? Well, it might not be that it’s going to massively impact the rate of innovation, and the technology that’s developed, but it impacts who does the innovation.

So the most valuable capital that you have, it turns out, is your human capital. So we want you to answer that big question: Where do you want to bet your career? Do you bet your career on that innovative new FinTech start-up that’s going to change the world, or with the incumbent firm that’s trying to get into this Fintech space?

The post How Regulation Works in FinTech appeared first on GetSmarter Blog.

Expensive infrastructure, employee training, and creating a culture of innovation are some of the challenges organizations face when implementing cybersecurity measures. In this video, Heather Adkins, Director of Information Security and Privacy at Google, discusses the critical role leaders play in driving cybersecurity awareness and developing risk mitigation strategies. 

The Harvard VPAL Cybersecurity: Managing Risk in the Information Age online short course equips you with the skills to protect the integrity of digital assets and lead your team through the complexities of risk management.

Transcript

Cybersecurity is going to be one of the biggest obstacles for organizations today and in the future.

The organizations that are succeeding at it are ones where their leaders are setting the tone and the cadence for the organization around cybersecurity. Especially a culture, where at every opportunity they’re taking the time to lay out how important it is to the organization.

I think the leader’s role in this is to educate themselves, of course, but also to inspire their organizations to focus on cybersecurity. It is a permanent function in their organizations, and only then will everyone feel like they can participate in that conversation. It is important that in security, we think of it not being just the role of experts, but the role of everyone. Everyone has a part to play.

C-suite leaders have a very particular role in the organization, with regard to cybersecurity. And I often tell my friends who are going into a CSO role, or a chief security officer role, to only pick the companies where you’re not going to have to push your agenda, but someone’s going to be asking for your agenda. Whether it be the board or whether it be the CEO. And to pick a role where you’re going to have that relationship and a bidirectional dialogue.

Cybersecurity is one of the hardest things the organization’s going to have to do. It’s expensive to continuously modernize your IT infrastructure, and it’s difficult to educate large workforces of people. And those things require a culture that supports change, and sometimes difficult change. And so, that relationship needs to be absolutely solid. And the CEO, the CIO, the CTO, and especially the CSO, need to all be on the same page about where you’re going.

If we are going to suppose that the C-suite leadership and middle management leadership own a part of the conversation and the dialogue, setting the tone and values for the culture, then I think that when you hire, you have to hire for your culture.

That means asking different kinds of questions. How do leaders, especially in the technology space, how do they see the role of technology and the human? I had a mentor who said, “For every new security thing we were going to put in place we were going to take away two.” And the idea there is to set a culture that says, “We’re going to be innovative about security, rather than traditional.” And, I think, it’s important that if you are trying to set that culture in your organization, that you have people thinking in these new and radical ways to make security a little bit easier for everyone in the company.

Make sure that your IT infrastructure is modernized, and that you’re keeping on top of that. We’re no longer in a time where we can buy something, and it’ll still be relevant ten years later. Technology turns over so quickly now and security improvements happen with each iteration.

Be modern in your fleet, as we call it, the machine fleet. And be modern in your thinking about how your employees interact with that technology. You’re going to need things like two-factor authentication and good cryptography. Let your roadmap really guide you, but don’t be afraid to push the boundaries of technology.

The post What Is a Leader’s Role in Cybersecurity? appeared first on GetSmarter Blog.

The overwhelming number of financial products on the market has given rise to two innovative FinTech firms. Wealthfront and OpenInvest provide a service that automatically selects the most suitable investment option based on the client’s preferences, goals, and social and ethical values.

In this video, Christopher Malloy, a Course Convener in the Harvard VPAL FinTech online short course, discusses how robo-advising has made it easier and more affordable for clients to invest and manage their portfolios.

But with a product that’s easy to replicate, how will these companies remain competitive in the long run? And how does this service impact the future of financial advisers?

Transcript

In this video, we will talk about the emergence of a new phenomenon in asset management, which is the idea of robo-advising. And we’ll focus in on two particular companies, Wealthfront and OpenInvest, who are pioneers in this space.

The simple reality of why this industry became into existence is because the wealth management industry is too complicated, it’s too opaque, and it’s too expensive. And those facts paved the way for the emergence of these firms. So now, on the expensive piece, a company called Vanguard, has been a pioneer in wealth management and making products that are very, very inexpensive. And so, Vanguard is now one of the largest wealth management firms in the entire world. But the problem with Vanguard is if you go to their website, you still have to decide which products to choose. And so, that search problem is actually quite hard, and I would encourage you to go onto their website and look at the thousands of products that they have on offer, and try to figure out what you would want to invest in.

And so, because of that problem, which we call the search problem, these robo-advising firms came into being. Wealthfront and OpenInvest basically grew right after the financial crisis, and the idea is quite simple, which is: Could you offer a product totally online, where someone could come onto the site and type in their risk preferences, things that they’re interested in, and goals, and could you then, as a firm, design a very automated product that would go and invest in cheap securities, like exchange-traded funds, and then automatically rebalance that portfolio such that the investor wouldn’t have to keep going and logging in, and they would in one click basically have their entire investment policy set by an automated firm?

So Wealthfront took that idea and designed a very appealing interface, targeted some younger investors, and grew dramatically since 2014, and became a big player in this robo-advising space. And then, seeing the success that Wealthfront had had, other firms began to enter. And one such firm was OpenInvest, which had a refinement of the idea of robo-advising based on this notion that, perhaps, investors had more preferences other than just risk and timeline, but maybe they cared something about, the environment, or maybe they cared about gun control, maybe they cared about some other social issues. So, they design an interface where people could screen out particular types of companies and particular types of investment, and that’s sort of capitalizing on this, the idea of socially responsible investing.

Now, the challenge of socially responsible investing, of course, is how do you define it? Because, for example, say you wanted to invest in environmentally friendly companies, well, then of course, naturally you’d think you would screen out Exxon and BP and these large oil stocks. And the problem with that is those are the very companies that are spending the most amount of resources and doing the most amount of R&D in the area of sustainable energy.

And so, the problem of how to measure social preferences and how to measure firms and investments that are socially responsible is actually quite difficult. And if there’s one thing we know from finance is that if you take a universe and you constrain it and make it smaller, and try to then pick the best investments within that, you are ultimately going to be sacrificing returns. And so, that’s this trade-off that OpenInvest is always having to think about, which is: Can I offer a product that delivers good returns while still screening out the things that people might not want to invest in?

Now, the other big challenges that both OpenInvest and Wealthfront face going forward is, because their products are so easy and transparent, they’re actually quite easy to replicate. You put in a couple parameters, and then they put you into some exchange-traded funds, and then there’s a machine that will automatically invest and automatically rebalance. And you can imagine this would be quite easy to replicate by larger, big financial firms, and so that’s an issue that they’re quite worried about.

A second issue is if we get to the point where all investment is done in a robotic way, what happens to all the financial advisers who are out there, and is it a good thing to get rid of all these financial advisers? So you might say it is, because they’re quite expensive, but at the same time, if you have machines trading with machines by machines, there’s almost no one at the end of the day who’s looking at the actual stocks, and pricing them, and doing the correct research to make sure that the prices are right. And so, you worry about a scenario where all humans are removed from the investment process. Will the prices be right, and what will happen to the returns on your investments going forward?

The post Approaches to Automated Investment appeared first on GetSmarter Blog.