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B2B sales strategy digital-first embrace new tech Marketing Sales Tech

How Can B2B Sales Go Digital-First Even After Covid-19?

digital-first b2b sales

Covid-19 has taken growing trends and accelerated them at exhilarating speeds. This has made it difficult for businesses to keep up with new consumer needs and best practices. Juggling social distancing and quarantine periods has been difficult enough; now organizations need to figure out how to thrive in a post-Covid world.

One such trend is that of digital and virtual sales. A study conducted by McKinsey and Co. shows that 90% of B2B decision-makers are confident that virtual sales will continue even after Covid-19 has passed. While remote/digital sales became necessary to prevent the spread of the virus, businesses should prepare to make this a part of their full-time strategy entering 2021.

Changing your B2B sales strategy is easier said than done. To help you make the transition effectively, keep the following tips in mind. They’ll help you get started on the right foot.

Embrace New Technology

Transitioning to digital sales will be a challenge if your business isn’t equipped with the right tools. A carpenter will be much more productive with a table saw than a sheet of sandpaper. Your digital arsenal will need a boost if you hope to find success with virtual sales.

Here are the types of tools you’ll need to succeed with digital-first B2B Sales — especially during and after this pandemic.

  • Videoconferencing tools enable more fluid and personal interaction with customers.
  • Customer relationship software keeps track of customer information and sales leads.
  • Data analytics tools let you know which strategies are working and which aren’t.
  • Email marketing software automatically sends email messages to generate leads and close sales.
  • An online sales navigator organizes the sales you make online over platforms such as LinkedIn.
  • Sales presentation tools broaden the capabilities of your videoconferencing calls, increasing their effectiveness.

While even one of these tools will help, the best strategy implements multiple tools. Start with your digital sales goals and pick out the tools that will help you reach them.

Learn How to Build Relationships Digitally

A huge part of sales is the relationship-building process. How can you develop close ties with customers and partners without seeing them in person? Just like with sales pitches, you’ll need to take a different approach to really reach your clients on a deeper level.

Charles Gaudet, CEO of the business coaching and consulting firm Predictable Profits, offers the following three-step guide for building relationships digitally:

1. Social Selling

Your social media sites can be used for more than just marketing. Interacting with clients’ pages by liking, commenting, and sharing their content helps establish a digital relationship with them.

2. Video

As with sales pitches, video is more effective than text or voice alone. Video calls are more personal than emails or even phone calls. While all three should be used to a degree, great success comes from making sure video is a part of your relationship-building strategy.

3. Steady Communication

As important as the platform you use to contact customers is how you communicate with them. Such is true with any partnership or relationship. Prompt follow-ups, honest inquiries, and genuine care expressed through steady communication will go a long way.

These three simple steps will help you start developing relationships with your customers virtually. As you get used to the process, you can adjust it to meet the needs of your customer base and fit it to your team’s strengths.

Learn How to Sell Virtually

Traditional sales tactics aren’t as effective in the virtual world. Some techniques will translate over nicely, but your general sales approach will need some tinkering to align with virtual interactions. These small adjustments are what set a successful digital sales strategy apart from the rest.

For example, in-person sales meetings often involve reading and expressing body language. Body language helps the sales rep gauge buyer interest and figure out what keeps them engaged during a presentation. Your appearance, expression, gestures, and posture also carry more weight in an in-person meeting.

What methods will you use in your digital sales strategy?

Virtual meetings don’t allow for as much physical expression, so you must learn how to generate interest and attract attention using other methods. For example, a study performed by Gong.io shows that deals close 127% more quickly when video is used. Video allows you to connect with customers more effectively and use visual resources that can be of great benefit to a sales pitch.

Be Aware of Pitfalls

Digital sales isn’t a fairy wonderland of endless cash flow and paying customers. There are still pitfalls and obstacles that stand in the way of success. Recognizing and anticipating these pitfalls will prevent you from getting stuck in a sales rut.

“The biggest pitfall of a digital-first sales approach is the ability to get and keep your prospects’ attention,� notes Gaudet. “With every enterprise sales organization using a digital-first strategy, inboxes are flooded with messages. To counter this challenge, companies must use an omnichannel approach to prospecting.�

An omnichannel approach means using a variety of sources to contact and connect with customers. Email, social media, and cold calls are all methods that work better together than separately.

Grab Hold of Digital Assets

Prospects will do their research when shopping online for products, services, or business partners. Due to their careful research, you’ll need to have your digital assets lined up and displayed to attract their attention and lure them to your company.

Your first digital sales weapon is your website.

Your website is often the first exposure a customer will have to your brand. Your website should have educational resources, clear pricing and product/service options, as well as a certification of authority in your respective field.

Your online sales and marketing strategies will bring customers over to your website and social pages, where the content they find will influence them just as much as any sales pitch would. Take the time to review your digital assets to look for ways to strengthen them, display them better, or add to them.

Give digital sales a try — and get good at this type of sales.

Ready to give digital sales a try? Remember that your remote sales team is important and will need training for these unprecedented times. Better now than later, because this trend will sweep you in its direction eventually whether you like it or not.

The sooner you start working on your digital sales strategy, the sooner you can optimize it to shatter your sales goals in 2021.

Image Credit: pexels; pixabay

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Grow Hack Tech

Is Technological Progress Slowing Down?

Technology is amazing. And it seems to get even more impressive every year. Every day, there’s some new gadget or breakthrough in the news worth getting excited about. And every year, our collective capabilities as a species seem to be getting broader and further-reaching. 

For decades, we’ve seen a veritable explosion in technological development – an exponential curve of innovation that constantly takes us to new heights. And we’re told that this technological curve is continuing – that we’re still growing exponentially, with massive leaps forward every year. 

But is this really true? 

There’s a compelling case to be made that while technological progress is still moving forward, it’s slowing down. And if that’s true, we need to be prepared for the consequences of such a shift in momentum. 

The Low-Hanging Fruit

Our first clue that tech innovation is slowing down is a change to the traditional model of tech development. In many ways, technology is all about solving problems; every new tech advancement is a solution for some long-standing issue. It makes sense that our current wave of tech advancement resembles an exponential curve because new technologies make it faster and easier to solve other, often unrelated problems. 

For example, the development of the internet was revolutionary for technological development overall. People now can review massive databases of information, communicate with other like-minded professionals, share ideas, and even publish their ideas to a broader audience. These capabilities have led to new ideas and new technologies that otherwise could never have been possible. 

But this trajectory is limited. In the course of tech development, we often explore new territory very quickly – but only for a limited period of time. Think of it this way. As early human beings began exploring new territory, they found themselves surrounded by an abundance of game animals, trees, and fish. But as they hunted, harvested lumber, and fished, many of those resources began to dry up. In other words, they’d taken all the low-hanging fruit, and were forced to come up with new ideas. They had to explore new territory, invent new agricultural methods, and even find new sources of nourishment. 

Our current burst of technological progress could be almost exclusively focused on low-hanging fruit. We’re solving the easiest problems first, and we’re solving them in quick succession. But the hard problems – like general intelligence-level AI, efficient battery storage, and even finding a cure for cancer – show little progress even over the course of decades. 

Any futurist will tell you that all of humanity’s problems can be solved eventually. But we have to understand that our pace of innovation tends to slow down as we master all the “easy� problems and start looking at the “hard� ones. 

Digital Innovation vs. Chemical Innovation 

We also need to understand that most of the tech progress we’ve seen in the past 30 or 40 years has been limited to the digital world. These technologies have been astounding, accelerated by novel high-growth startups, but they’ve almost been exclusively focused on digital communication efficiency. The internet, software engineering, and AI have all taken amazing strides forward. But on the level of chemistry and physics, we’ve advanced very little. 

We’re still incredibly reliant on non-renewable resources to fuel our consumption. We haven’t discovered any groundbreaking new elements, molecules, or chemical processes. And our understanding of the universe at the base level of physics hasn’t changed much, if at all, since the 1980s. We’re still struggling to reconcile major physics ideas that were first introduced nearly 100 years ago. 

So what? Digital innovation may be so incredibly fast-paced that it can be the conduit through which we solve all other problems, right? 

That may not be the case. For the majority of the digital age, we’ve depended on the momentum of Moore’s law. Moore’s law is an informal observation that the number of transistors that we can fit on a dense integrated circuit tends to double every two years. In other words, our computing power can double every two years, leading to major breakthroughs in a number of different technologies. 

However, it appears that the age of Moore’s law may be nearing its end. There’s an absolute physical limit to the amount of space on a transistor chip. With exponential growth since the 1960s, we’ve gone from integrated circuits with 10 transistors to ICs with something like 10 billion transistors. How much further can we really go without breaking the laws of physics? 

We may be able to push things even further, but to do so, we’ll need to invest in high-end chipmaking equipment and innovate entirely new manufacturing methods. Doing so will sharply increase the cost of chip production, ultimately negating the cost-effectiveness benefits. 

Of course, there’s a solid counterargument here. It holds that digital innovation may continue at the same rate of exponential growth even if we’re unable to maintain the consistency of Moore’s law; even if the number of transistors on a chip remains more or less stagnant, we can find new ways to use the chips we already have. 

Consumer Products and Perceptions 

We see an endless conveyor belt of new gadgets and new consumer-facing technologies emerging on a constant basis. But how innovative are all these products, really? 

Apple introduced the iPhone, a game-changing new type of technology, back in 2007. It combined several existing technologies into one, comprehensive unit, and changed the way we think about mobile tech forever. In the past 14 years, how much innovation have we truly seen in this space? We’ve seen a flock of competitors coming out with smartphone options of their own. And of course, we’ve seen Apple unveil a new model of iPhone nearly every year. 

But these new, “innovative� smartphones only make marginal improvements to the original formula. Their cameras are sharper. Their processing power is beefier. Their storage capacity and battery life are more robust. But they can hardly be considered new technology, at least not at the same groundbreaking level of their predecessor. 

As consumers, we’re getting used to a slower pace of technological breakthroughs. We’re content to see new smartphones, new video game consoles, and new TVs that offer merely slight improvements over their counterparts, rather than completely changing the game – and this is enough for us to continue thinking that we’re living in an age of exponential technology growth. 

What Does a Tech Slowdown Mean? 

So what does all this mean? Is it really a big deal that there’s a major tech slowdown? 

Much of our economic growth depends on technological innovation. Countless retirement plans like 401(k) depend on the growth of the stock market, which in turn depends on baseline economic growth; a slowdown in tech innovation leads to a slowdown in GDP, resulting in a cascade of economic effects that could cripple the economy at large. 

The larger danger is that we don’t realize the tech slowdown is occurring until it’s too late. Tech stocks are being traded and inflated as if they’re inventing fundamentally new technologies; as a general trend, they multiply in price in response to even the most meager announcements. If carried out for years to come, this could result in a massive tech bubble, or a broader investment bubble, that pops once investors begin realizing just how slow our growth has crawled. 

Of course, this slowdown may be merely a temporary lull. Just as the digital era sparked the launch of a million new problem-solving technologies, we may be on the cusp of another, equally paradigm-shifting breakthrough. To get there, we’ll need to refocus our research efforts and accept the limitations of the digital space. 

Our half-century long honeymoon with explosive tech growth in the digital era has been incredible, but it’s nearing its end. If we want to keep moving forward (as we should), we need to reset our expectations, redouble our research efforts, and start looking into new territory for technological expansion. 

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Branding

Dear Robinhood CEO: Here’s What You Should Have Done Instead

Robinhood

It takes years to build a reputation and only moments to destroy it. Amidst an unprecedented (ugh – not that word again!) trading surge, the Robinhood CEO had an impossible tension to navigate. How to address big-picture business concerns, while appeasing the interests of investors and company employees.

I’m sorry to say that employees got picked last.

Robinhood Employes Not Happy

Robinhood CEO experiences employee backlash.

Employees Feeling Disenfranchised

According to its website, Robinhood’s mission is “democratize finance for all.� But the decision was made this past week to restrict transactions on highly volatile stocks (do I even need to tell you which?). And team members were left wondering if they had been lied to.

“In the knowledge economy, employees espouse the brand values as much as their title or their paycheck,� says leadership expert, Robert Glazer, of Acceleration Partners. “One wrong move is often met with grace. But wrong moves compounded with poor communication can cause a revolt and an employee backlash�

Robinhood apologized to its one thousand employees by issuing a $40 DoorDash credit. This gesture occurred after the company secured an additional billion dollars to cover margins. A necessary operational response? Absolutely. But not the message they were looking to send internally.

“The recipients were patronized,� says John Ruhlin, author of GIFT∙OLOGY, a playbook for B2B gifting. “Everyone on the planet is watching your every move. And the best you can come up with is a $40 gift card? This adds insult to injury.�

Foundations of Employee Gifting

In Robinhood’s defense, most business leaders are horrific gift-givers. One recent study documents how givers and recipients place different value judgments on the same gift. The disconnect can be so massive that, according to another study, the wrong gift does more to hurt than help.

Ruhlin says he’s seen it happen. “Loyalty is fickle because feelings are fickle. We have clients that come to us and say: ‘we tried gifting, we messed it up, can you salvage this?’ Fortunately the answer is almost always yes.�

So what should Robinhood’s CEO have done? And how can you successfully execute strategic gifting in your organization? The following tips will help.

Choose your words carefully 

The most important part of an apology is to mean it. Jonathan Bernstein, founder of Bernstein Crisis Management and author of ‘10 Steps of Crisis Communication,’ suggests leading with empathy. “Your messaging must make it clear you have compassion – stakeholders must understand your message the way it was meant to be understood.� In other words: you must genuinely care.

Proper wordsmithing is crucial even when you’re not apologizing. Would you rather eat something 95% lean or 5% fat? If your goal is sincerity, avoid clichés and corporate platitudes.

Good leaders communicate from the heart. Not through the lens of legal permissibility or marketing spin.

Get them what they want

While this might be blasphemous to some, these five studies make a convincing argument to involve the recipient in gift selection. Monika Kochhar is the co-founder of SmartGift, a platform that enables business leaders to connect with others in a virtual world.

“Modern day technology allows us to re-imagine the traditional gifting experience. Instead of saying, ‘here – I got this for you,’ we can now say ‘I got this for you – which color, what size, and where do you want it shipped?’� SmartGift uses artificial intelligence to help match recipients with the right item at a pre-determined price point.

No more ‘one size fits all.’ Something Robinhood employees (and critics) might have appreciated.

Spend the right amount

So how much should Robinhood have spent on their gift? Both Ruhlin and Kochhar cited similar numbers from their client experiences. “Our biggest successes are practical luxuries, in the $100-$300 range. It’s high enough to afford quality, but not so low to appear stingy.�

Kochhar suggests not obsessing over price-tags. “Employee gifting is an investment. Leaders don’t audit the salaried costs of two hour Zoom calls. Yet we’re going to pinch nickels with appreciation? Double standards do not serve us.�

It’s not about you.

The fastest way to devalue a gift and turn it into an advertisement is by putting your company’s name on it (this StoryBrand podcast explains it nicely). Over the years, I have received a thrift store’s worth of logo-covered tote bags, clothing, and water bottles. All have been donated, trashed, or relegated to the garage.

Robinhood might not have done this explicitly. But the immediacy of their gesture suggests more of a reactionary appeasement than genuine remorse. You wouldn’t give your spouse a gift with your name on it. Don’t do it for your employees or clients. And never make your gifts about the optics.

The right perspective. Always.

Leaders like Gary Vaynerchuk encourage leaders to play the long game – both with gifting and decision-making. While I am empathetic to the chaos surrounding Robinhood’s CEO this past week, this saga feels less like a passing tabloid headline and more like THE BIG SHORT. Or at least an extended 30-for-30 episode.

Unlike certain investment strategies, there’s no benefit to volatile reputations. In today’s media-crazed environment, brands explode (or implode) when the CEO makes the right moves. Our opportunity as leaders is to build reputations out of stone, not plastic. When we execute strategic gifting the right way, we create an environment of stability and confidence. And a brand to match.

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Health Lifestyle Smart Home Tech

How to Live a Holistic Lifestyle While Embracing Smart Technology

How to Live a Holistic Lifestyle While Embracing Smart Technology

When you think of living a holistic lifestyle, do you picture someone being completely off-grid with no computer, no internet, and no smartphone? While some people do live this way, the absence of IoT tech doesn’t define a holistic lifestyle.

Smart technology and a holistic life aren’t mutually exclusive. In fact, plenty of people live a happy, healthy, joyful life filled with smart technology. The key is they don’t allow their tech to control their lives. They’re not glued to their smartphones, and if their smart coffee maker stopped working, they’d happily brew a cup of coffee by hand.

There are countless ways smart technology can improve your life. Here are just a few specific ways.

Smart tech can give you critical food and drug recall alerts

Part of living a healthy, holistic lifestyle involves knowing when your favorite food brands test positive for dangerous contaminants. This goes for your pets’ food, too. Food recalls are far too common, and it’s hard to stay on top of every single situation. The easiest way to stay on top of each situation is to subscribe to alert mailing lists and pipe your emails through your smartphone so you’ll never miss a recall.

Even more common than food recalls are drug recalls. As much as you might try to live without over-the-counter (OTC) drugs, sometimes that’s hard. For instance, you might need to take ibuprofen once in a while to ward off a stress headache. There’s no shame in that. However, some seemingly innocent OTC drugs end up having devastating health consequences.

For example, the popular heartburn drug, Zantac, has been voluntarily recalled by the manufacturer. Zantac is the brand name for the generic drug called ranitidine. Unbeknownst to the public for years, the chemical structure of ranitidine literally becomes a carcinogen during metabolization. That’s pretty scary.

If you’re not taking any OTC drugs, you might be taking a medication that is keeping you alive. If that drug gets recalled or black boxed, your doctor may not know about it for a while. Using a smartphone to receive alerts when drugs are recalled could save your life.

Smart technology and holistic living are compatible

You can live a holistic lifestyle while embracing smart technology; you don’t need to choose one or the other. Technology won’t negatively impact your health unless you’re literally sitting at your computer all day long and you never get up to interact with the world.

In some cases, smart tech can even help you live a healthier life. For example, Fitbit tracks a user’s health data like steps taken, burned calories, and heart rate. Tracking this data can help individuals see the impact of their exercise routines, and it also helps them achieve their goals. Other wearable smart tech can be used to transmit data to a healthcare provider, and some wearable devices deliver pulsed electromagnetic frequency (PEMF) treatments.

Other smart devices are incredibly helpful to people with disabilities. For example, there are smart shoes that provide haptic feedback to guide blind people safely around neighborhoods using a smartphone GPS connection.

Haptic shoes convey directional information in a way that doesn’t distract the wearer or anyone else around them. The shoes are equipped with actuators and vibrators on all sides. After the wearer’s smartphone calculates their route, vibrations in the shoe guide the wearer to their destination. These amazing shoes also detect obstacles like steps and curbs and use the same vibrations to guide the wearer around immediate obstacles.

You can use smart tech to connect with likeminded people

Smartphones and smart tablets are tools that can connect you with likeminded people. No matter what your passion is in life, you’ll find a group of people online who share your interests.

The best way to connect with people is to use video conferencing software. Audio phone calls are okay, but why just use voice when you can connect through video conferencing? If you have an iPhone, iPod, or iPad, you already have video conferencing built into your device via FaceTime.

It’s more fun connecting with people through video chat than voice chat. You can tell so much more about a person when you can see them live. Video is the next best thing to an in-person meeting.

You can also connect with people all around the world and you won’t pay a dime beyond what you would pay for data. If you’re on Wi-Fi, then there’s no extra charge.

Connecting with people all around the world is inspiring and can be beneficial for your business. People from different cultures often have different ways of viewing situations and can come up with ideas and solutions you would have never thought about.

You can use smart tech to discover potential business partners

If you’re running a business, there’s no better way to find potential business partners than by assessing the people you’re already connecting with online.

If you’re discussing business with people over the internet, you might get a feeling that someone is a potential business partner. Smart tech will facilitate video conversations so you can get a better idea of who those people are.

Most people can sense who a person is just by being in their presence. Video conferencing is the next best thing if you’re working with people across the world.

Smart technology allows you to bring your workouts anywhere

Perhaps one of the coolest ways smart tech supports a holistic lifestyle is facilitating the ability to take your workouts anywhere. Some online workout programs are hosted in the cloud, like Apple Fitness Plus, which makes them available anywhere you have an internet connection.

You can also upload your workout programs to your private cloud hosting account if they’re not already available online. Last, if uploading is too much work, you can simply load your smart device with your workout programs and use your device to play the programs. If you happen to be in a hotel with a smart TV, you can connect your device to the TV to play your workout video on a larger screen.

Smart tech will help you track progress and goals

As long as you aren’t tediously tracking data that doesn’t matter, using smart tech to track your progress and goals in any area of life will prove beneficial. For instance, you can use your smartphone to track your reps while you’re at the gym instead of lugging around a notepad. You can also download an app to track what you eat. There are also apps that will tell you what to eat and when to eat depending on your body type and specific goals.

Technology has always been great for tracking progress. You can also track your business goals, sales, and just about anything else from a smartphone app.

Embrace smart technology as a way to enhance your holistic lifestyle

Living a holistic lifestyle is central to wellbeing. A holistic lifestyle involves taking care of your entire self – your mind, body, and soul. Smart technology can help you take better care of yourself by providing you with tools to stay on track.

Regardless of what you’ve read online, living a holistic lifestyle isn’t about giving up gluten, eating a plant-based diet, and living in a converted shipping container tiny home. Living a holistic lifestyle is about unifying your mental self with your physical self to promote overall wellness. It’s a lifestyle that keeps you in touch with the way your thoughts and attitude impact your physical health and keeps you in tune with nature, whether you eat gluten, fish, beef, or potatoes. It’s not about what you eat – it’s about who you are.

Technology has the power to facilitate your growth both in your personal life and in business. There’s no reason you can’t use a little smart technology to sustain a joyful, healthy life.

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AI data analysis data capture firm election results and data capture Georgia runoff spending ReadWrite using AI for data capture

Data Capture Firm Uses AI to Dissect Georgia Runoff Spending

georgia runoff spending

With majority control of the Senate at stake, it’s no surprise that the recent Georgia runoff elections were the most expensive political race in American history. Wherever campaign dollars flow freely, as they did in Georgia, accountability questions proliferate. Where did that money come from, where did it go, and what influence (if any) did those spending choices have on results?

Election law requires that campaign expenditures be made public. Even so, it often takes weeks or even months for analysts to sift through a dense forest of information and build usable datasets. Important decisions have to wait; only after a dataset has been given the green light can anyone even begin to search for associated outcomes and trends.

Many have wondered whether there is a legitimate place for artificial intelligence in harvesting public data repositories. Can machine-generated data really be trusted? And even if it can be, can it replace human analysts?

When Data is Public but Nearly Useless

Each TV and radio station is required to carbon-copy invoices for political advertisements to the Federal Communications Commission, which makes them public record. This sounds great on paper, but the FCC mandate is to merely publish the invoice documents — and each election comes with tens of thousands of invoices.

The invoices are important because of the dates, callsigns, and amounts listed on them page by page. The data allows analysts to build spending maps and scrutinize campaign behaviors, but the data needs to be aggregated in a spreadsheet first. A spreadsheet analysis would ordinarily mean going through this massive amount of invoices by hand.

A Better Use of Data

Of course, it’s not just the FCC receiving invoices — all businesses receive invoices when they trade with each other. Any company of size faces the same problem as the data analysts who would like to use the FCC data.

One automation software company that solves the problem of translating business documents to data for enterprises decided to unleash its automatic data capture on the FCC invoices for the Georgia runoff elections. The vendor Rossum, in partnership with analysts from the e.ventures fund, just published the resulting data set.

AI-Powered Reporting Follows the Money

Ever since the 1976 film “All the President’s Men,â€� many of us have internalized the admonition to “follow the money.â€� The practice remains a tried-and-true method for discovering unseen relationships and shedding light on patterns of activity and motivations that we might otherwise miss.

Data capture technology cannot read the minds of campaign managers — something for which we can all be thankful. But the new breed of automation based on artificial intelligence might at least enhance our ability to better see the tracks they’ve left.

Accelerating Data Collection

In addition to eliminating the time-consuming tedium of keystrokes and accelerating data collection, policy analyst Jordan Shapiro found that Rossum’s processing of the Georgia spending data produced a greater degree of granularity. This granularity, in turn, enabled her to better grasp the thinking that lay behind decisions made by the various campaigns.

Following the Spend

“As a political analyst, Rossum’s data about 2020 Georgia runoff election spending gave me the opportunity to get inside the heads of the campaigns to see which areas they thought were more or less competitive based on how much each candidate spent in that region,� says Shapiro. “Particularly helpful for my work was the ability to compare county-level spending patterns with a shift in vote share between November and January.�

Data Suggests a Shift from Red to Blue

Southern states have historically been fertile territory for Republicans seeking election, but that appears to be changing.

An NPR report from January 2020 found more Black Americans are moving south, and as they relocate, they are contributing to a shake-up in election results. In 2000, Rockdale County (southeast of Atlanta), for example, was a predominantly white area with a Black population of approximately 18%. Today, that same area has a 55% Black occupancy.

Changing Demographics

Shapiro notes that Georgia’s changing demography, heavy campaign spending by Democrats, increased voter mobilization at the grassroots level, and a tumultuous national political stage all played a hand in what many saw as upset victories. Political turmoil and civic unrest on the national scene rocked Republicans and set the stage for Democratic wins. Both races were reasonably close, with Ossoff winning his race by about 55,000 votes and Warnock winning his with around 93,000 votes.

Regardless, Rossum’s analysis found something even more important than spending-outcome correlations: reasons to default to AI-driven analysis.

Why AI-Enhanced Reporting Will Be Big

The mandatory availability of campaign spending records affords skeptics and naysayers an opportunity to fact-check any reporting that emerges after an election. Reports that have been compiled using AI-powered scanning techniques can be fact-checked just as easily as traditional reports constructed by workers furiously pounding away on keyboards.

As AI-powered processes continue to improve, confidence in this newer methodology is certain to grow as well. As that happens, voters can expect to see more accurate, useful information in the run-up to Election Day.

AI-driven reporting benefits democracy in at least four ways:

1. Enhanced Transparency of Public Data

Much data is the subject of public record, but too often, it is not readily available for analysis and therefore carries only a fraction of its potential. The problem with campaign spending records is that key dates and amounts are scattered through scanned documents instead of being aggregated in a spreadsheet that can be readily analyzed for new insights. This problem is common for many registries, FoIA data releases, and internal government operations.

2. Rapid Data Analysis

The speed advantage of AI-enabled reporting systems over traditional methods of computation will make relevant data available much earlier than in past election cycles. Earlier delivery of results could, in turn, open up new options for campaign managers to consider as constituents respond favorably or negatively to various messages.

3. Added Depth and Surfacing of Less-Obvious Correlations

As noted above, Shapiro was able to take Rossum reporting on election data and cross-reference it with migration data. In doing so, she discovered a trend in specific Georgia counties shifting from presumed Republican strongholds to surprise Democratic wins.

4. More Informed Policymaking and Decisions

Tightening the link between election results and policymaking can serve as a check on any politician’s temptation to drift away from the will of the people they serve. A democratically elected official can only disregard his or her mandate for so long. Faster access to accurate information allows voters more time to assess a politician’s voting record.

What’s Coming in 2022

With another election cycle coming entirely too soon, keep an eye out for new applications of AI. Both parties will use the technology to unearth patterns, analyze results, and suggest new political strategies. Policymakers will check proposals against their constituents’ latest voting trends.

Will 2022’s political environment be any less fraught than the 2020s? Maybe not — but it will be more data-driven.

Image credit: edgar colomba; pexels

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Data Integration: How Connecting Business Apps Boosts AI Capabilities

data integration apps

Artificial intelligence (AI) and machine learning (ML) have become omnipresent in our personal lives. The same is true in the business world. Data integration can help businesses take their AI applications to the next level.

In many respects, AI is now a mature business technology. Consequently, it’s no longer the sole province of pioneering companies. Not only have advanced analytics powered by ML become popular. Chatbots responding to customer requests through a Natural Language Processing (NLP) AI are also on the rise.

However, many are leaving AI’s full potential untapped.

More than anything, AI needs data. ML algorithms ingest large data sets for training. AI is at its best when it extracts actionable information from a myriad of data points that no human could conceivably make sense of.

Businesses collect ever-larger amounts of data. Yet, most fail to harness all the data they have for their AI applications.

In 2021, a massive section of business operations happens in apps. These are now usually cloud services by Software as a Service (SaaS) companies. There are accounting platforms like FreshBooks. Customer Relationship Management (CRM) systems like Salesforce. Marketing powerhouses like HubSpot.

According to recent statistics, the average business uses 73 different apps. Furthermore, employees conduct over 80% of their work in the cloud. In 2020, the pandemic additionally magnified these trends.

Enormous amounts of data live on each of these platforms. With integrations, these services can take advantage of each other’s data. This enables countless business processes to take place in the cloud, from marketing to financial reporting.

Yet few businesses take advantage of all the possible integrations to unify their data and put it at the disposal of AI and ML.

Having a data integration strategy matters. Here’s why, what the challenges are, and how your business can benefit.

Why Strive for Data Integration? To Create and Harness Synergy.

In business, AI has three central tasks: process automation, generating-depth analyses, and engaging customers and team members.

For all this, data from connected business platforms is invaluable.

Let’s take a core office technology as an example: business phone services. Modern business telephony is cloud-based, thanks to Voice over Internet Protocol (VoIP) technology. For businesses, this has countless advantages, some more obvious than others. VoIP has enabled multiple communication channels, from video conferencing to live chat.

But VoIP business telephony also enables AI applications.

For example, NLP AIs can transcribe voice interactions in real-time. This can be applied to every single conversation between company representatives and customers. Then, ML algorithms can run advanced analytics such as sentiment analysis on the transcripts. The result? Company representatives can receive an instant evaluation of their performance. They can go over the conversation and learn.

But by integrating with other platforms, this kind of AI-generated data becomes even more useful. Connect your cloud business phone system with a CRM, and you can add every transcript to a customer profile. This immediately boosts possibilities for personalization. In turn, this can increase your chances of conversion or retention.

You can also integrate the data into a personnel management platform. For instance, sentiment analyses of a company representative’s conversations might be frequently negative. You’ll see this in their performance evaluation. Then, you can tackle the problem. Targeted training could, for example, showcase positive examples from other transcripts.

Or imagine you’re using sentiment analysis algorithms to sift through online reviews. By itself, this will give you valuable insights into customer attitudes and expectations. But integrating it with data from your digital marketing platform, and you can go much further. AI can then correlate email campaigns or social media strategies with sentiment trends in online reviews.

Getting Crucial Information in Real-Time

Speed is another core advantage of integrating data to boost AI performance. Integration increases the amount of information you can access. What’s more, access becomes easier and much faster.

Let’s go back to the business telephony example. The transcripts from customer calls are in your CRM. Imagine someone calling with a problem they were having with one of your products. A few days later, the same customer calls again. Now, the AI assistant in your business phone service pulls the relevant CRM records. Before your representative even picks up, they get a full run-down of this customer’s case: How they’ve described their problem. Personal information from demographics to billing history. And even what conversational strategies in the last call worked best.

All this saves your customer from having to give a long-form recap of their problem. For one, this reduces frustration on their part. For another, it also allows your representative to address them in a personalized manner. Overall, the exchange will be more efficient and satisfactory for both parties. Your business saves resources and increases customer satisfaction at the same time. All thanks to AI integration.

Generate Positive Feedback Loops

A final significant advantage of business app data integration for AI is positive feedback loops.

This means that by integrating platforms, you generate new data. On this basis, you can refine your strategies and grow your platforms. Leading to more data.

Take chatbots as an example. These days, countless companies use them in their online stores and on their websites. They are powered by NLP AIs. Their usefulness hinges on whether they can provide relevant information to customers.

For this, context is crucial. Customer behavior can provide that context. By supplying chatbot AIs with behavioral analytics, you can increase their usefulness.

For this, you can feed customer data from e-commerce and website analytics platforms and feed it to an AI. Have the AI find patterns and use these patterns to train your chatbot. On this basis, it will give suggestions and make recommendations to customers. Then, track the further behavior of these customers. It will give you even more data – to refine your chatbot.

This feedback training between chatbot AIs and e-commerce analytics helps increase communication efficiency. And seriously boost customer experience and thus retention and sales.

The Challenges of Data Integration

As the examples above make clear, data integration entails countless benefits for AI. But it also poses several challenges in its implementation.

First, businesses looking to integrate data face the hurdle of siloed technologies. Data silos are inaccessible for ML algorithm training. Nor can trained models analyze their contents for decision-making.

Second, the readability of data is a central issue. Many platforms have idiosyncratic data structures and lack metadata or context. They might even save files in proprietary formats.

Third, the trustworthiness of data is often in question. A study in the Harvard Business Review has highlighted this. In it, almost 50% of companies admit to data integrity problems. Issues with false, inconsistent, or stale data are frequent. And even more troubling, more than half of enterprise data fails to provide value altogether, due to siloing.

There are several avenues businesses can take to avoid these pitfalls and overcome these challenges to effectively harness integrated data for AI. The first of these is data mapping to establish a single source of truth.

Data Mapping and Single Source of Truth

Strictly speaking, data mapping is a subfield of data integration. It describes the process of connecting a data snippet in one system to a corresponding item in another. For example: Mapping the “name” field in a CRM record to the “caller ID” field in a business phone system.

The goal of this is to unify data while maintaining its integrity.

Crucially, this also helps businesses create single sources of truth. This refers to a single master record, which can boast high accuracy and sees frequent updates. Other systems will derive their data from here.

This doesn’t mean that all data needs to be stored in a single record. But for each item, only one ultimate source should exist. Especially highly sensitive data – like names, addresses, or social security numbers – should be treated like this. This makes it much easier to control and audit how this information is handled while still harnessing its value.

The good news is that modern AI-based cataloging tools can maintain such master records. They can parse information from all your platforms and deduce credible metadata. They can also automate data cleaning and highlight inconsistencies. This is a crucial first step in dealing with data complexity.

Dealing with Data Complexity

As mentioned above, data readability is a major hurdle to overcome. At its core, that means dealing with data complexity.

More and more raw data is available. This raw data is available in countless different formats. These formats range from social media posts over e-commerce statistics to server logs.

In addition, context is lacking for a lot of this information, especially natural language data. Take a thread of social media posts, which may include abbreviations and typos. Many statements might not make sense without the accompanying emoji, GIFs, or videos.

Plus, all this information is scattered across an ever-growing number of platforms. And these platforms, in turn, may have dozens, if not hundreds, of third-party integrations.

Using AI to Overcome Data Integration Challenges

The good news is that AI systems are becoming better and better at handling these challenges. This means you can use AI to generate input data for AI.

First off, AI can conduct data mapping automatically with precision and speed. In addition, the mapping mechanism can weed out issues such as duplicates and missing values. This helps maintain data integrity and speeds up data unification.

Furthermore, AI makes it possible to automate regular exports of data siloed in various places to central data hubs. It can infer data structures and parse uncommon formats. And crucially, it can propagate and consolidate data across systems, drawing from a single source of truth.

Recently, AI and ML algorithms have become adept at parsing situational context. If the schema structure for the incoming data is unknown or only partially known, they will either judge on a pattern basis, or parse the content to decipher a schema.

AI-Assisted Integration or Self-Service APIs?

One crucial question of data integration remains, though. How exactly can a business go about it?

It’s easy to say that AI can do this and that, without specifying exactly how it does so.

Generally, there are three ways in which businesses can approach data integration.

First, enterprise-scale businesses probably have the resources to hire and task data analysts with establishing a system of integration and analysis. They have the required knowledge in coding and data mining to set up a system that is custom-tailored to their employers’ specific needs. With the right access to the administrative space of various business apps, little should stand in the way of success.

Second, you can opt for self-service analytics platforms. A growing number of platforms aims to make analytics easily available for non-specialists. Many of these come in the form of cloud APIs. Their aim is to democratize AI analytics. Following this philosophy, some platforms even offer chatbot-like features. These help you create an integration procedure conversationally.

And finally, you can – at the very least – harness the integrations that are already at your disposal. Many major business apps already offer native integrations with each other. Even more, they are compatible with bridges such as Zapier. In many cases, taking the time to explore the options of integrations that you have in your existing app ecosystem can already pay off big time. Prioritize platforms that offer AI analytics and automation capabilities, and then proceed to map out the nexus of available integrations.

Final Thoughts

Data integration is a challenge. But it’s a challenge worth tackling to reap the rewards.

Harnessing all the data at your business’ disposal is vital in 2021. It will help you understand your customers better, meet their needs, and increase your sales.

The best way to go about this is to use AI to improve AI through data integration.

You can either manually explore your existing integration options, find an easy-to-handle cloud API, or approach the task with the help of a professional analyst.

Putting the required systems and automated processes in place will take some time and effort. At the end of the day, it will be worth it.

You will be able to boost the quality of your algorithms, establish positive feedback loops, and gain insights at an unprecedented level. With decisions based on the insights, you’ll be able to steer your business through the times to come.

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Customer Service How may I help you? make client a brand advocate worst customers

How to Deal With Demanding Clients

demanding clients

Every business wants to do right by its customers. At the end of the day, that’s what a business is there for: to serve its customers and clients and to serve them well. A business will not stay in business without training its employees on the best practices for dealing with the customer base.

When one of those customers asks for everything, demands extras for free, and complains about the work you provide, hard conversations sometimes have to happen. Here’s how to handle your problem customers with grace and how to ensure your clientele become long-lasting, loyal patrons of your business.

Why it’s Important to Serve Tough Customers Well

You know what it’s like: You’re going about your day and minding your own business when a rude customer insists you drop everything and cater to their every whim.

It can be tempting to snap back at them or let your irritation show. But when issues occur — which they will, with even the best clients — the wisest action you or your team can take is to quickly and calmly find an equitable resolution for both of you.

When you prioritize customer service above all, you’re more likely to retain customers in the long term. In some cases, a good customer service experience can actually turn a problem client into one of your brand’s biggest proponents. But how, exactly, do you turn a customer into a brand advocate?

How to Handle Your Worst Customers

Your customers look to you — not just for your product or service — but for help and a pleasant experience. You will find that a brand advocate is your best tool against complaints and the best way to build your your company.

Make Sure You’re on the Same Page

With most of your problem customers, the root of the problem is miscommunication. Understanding the customer issues with concrete examples is key: Ask for the specifics of what they’re looking for, what went wrong, or what’s bothering them. Then take a moment and respond with equally specific solutions.

Be intentional about how you communicate. Make sure the words you choose are clear and calm. An easy way to quickly understand a situation is to mirror the language the other person is using. Be sure to parrot (mirror) your customer’s questions or concerns back to them — to see if you have truly understood their concerns.

Acknowledge Where They’re Coming From

Sometimes, all people want is to be heard. While that sounds simple — allowing your customer to talk through their situation without interruption takes a little time. Resist the temptation to jump in the conversation with a quick fix (this will make an enemy faster than almost anything you could do)! While listening — only ask questions to clarify their position. DO NOT tell them to take a breath, breathe, or “calm down.” These responses are generally known to be non-helpful.

Full and careful listening with mirroring language will help them calm down naturally and will give you the information you’ll need to diagnose the problem.

To be clear — taking time to hear, mirror and respond doesn’t mean that you have to agree with your customer. Merely listening and acknowledging their frustration will help you move closer to a resolution.

Use Any Soothing Trick to Help Yourself

You can silently be soothing yourself. “I’m okay, I can’t wait to tell the other co-workers, I’m handling everything in my life better. Instead of contradicting someone by saying “but,â€� make a point to say, “yes, and…â€� The word, “butâ€� can sound antagonistic, condescending or rude — while “yes, andâ€� lets people know you’re on their side.

Keep Tabs

If you have a customer that’s constantly demanding more or being rude, document their behavior. Record emails, voice messages and anything else that displays their problematic behavior. Make yourself a few notes of dates, times and a few quick details.

Say a customer is being particularly needy or making a ton of complaints, some of which start to sound very similar. Pointing them back to what they’ve already said can help keep them on track. Plus, it can give them a taste of what communication with them is actually like.

Call in Support

Sometimes, you just have to pass the baton. When it comes to difficult customers, don’t be afraid to ask for support. Whether from a colleague or someone in leadership, having an extra voice in the room can be comforting, and can help you reach a resolution faster.

Watch for signals for when you need to call in help, like when someone is asking for more than what you’re able to give. That is the time to call in your manager. Let him or her explain why you can’t do what they (the customer) are asking.

Go the Extra Mile

At long last, you’re finally finished helping your problem customer. You can either throw in the towel, or take this one extra step that may help you and your company retain this customer in the long run.

It’s simple: After you’re finished helping them, ask if there’s anything else you can help them with.

Being willing to go the extra mile to help does two things: First, it shows you appreciate them as a customer. Secondly, it allows them to voice other concerns that they may have forgotten about. Either way, it’s good business to do this one last check-in before sending them off.

Pushing back on a demanding customer is rarely the correct choice. You’re already busy and stressed — the last thing you need is a problem client.

By taking a mental step back, you’ll approach the situation with new eyes. With a little luck, you might even turn the terror of a customer into a loyal brand advocate. When you’ve turned an enemy into an advocate, it’s a beautiful transformation and well worth the effort.

Image Credit: andrea piacquadio; pexels

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2021 business strategies AI Connected Devices Data and Security data science Data scientists Soft skills

5 Vital Soft Skills Data Scientists Must Possess in 2021

data scientist

Technical skills are overrated, particularly in data science. Many data scientists quickly realize that much of their job challenges aren’t due to what they can or cannot do. Rather, the mentality with which they approach tasks matters a lot.

For instance, a data scientist who has mastered communication will present their insights better than their more (technically) skilled counterpart whose reports are jumbled. Likewise, extrapolating insights from raw data require a huge dose of creativity and critical thinking, both of which are not taught as technical skills but must instead be developed personally.

Other soft skills that are necessary for data scientists include business aptitude, problem-solving, and adaptability.

All of these are time-proof skills that transcend technological innovations. Success in 2021 and beyond as a data scientist will heavily rely on the development of these soft skills.

Critical Thinking

This author defines critical thinking as “the judicious and objective analysis, exploration and evaluation of an issue or a subject in order to form a viable and justifiable judgment.�

Critical thinking is often regarded as the most essential skill in data science.

It makes you well-informed, enhances your judgment, and makes you better equipped to make more effective decisions. As a data scientist, you must be capable of examining the available data from multiple perspectives. To develop critical thinking, do the following:

  • Question your assumptions: as a scientific field, your job is to apply empirical methods to analyzing data and extracting insights. However, the human mind remains subject to all kinds of biases and presuppositions. You must thoroughly interrogate them to hone your reason and avoid decision pitfalls.
  • Engage different perspectives: As social beings, we are drawn to people who act and think like us. But the lack of healthy dissent leads to poor decision-making. Thinking critically means consistently seeking out fresh perspectives. This doesn’t necessarily mean disagreement; it could be as simple as connecting with colleagues from another department in order to understand their outlook.

Communication

The purpose of data analysis is to make informed decisions. And your responsibility as a data scientist includes being able to present your findings in a clear manner to the non-data-scientists who have to make the decisions.

Your non-technical audience needs to know how you reached a specific conclusion, the justification for your methods, the implication of your findings, and why you consider one solution better than the other.

You can make your presentation more effective through storytelling. As Brent Dykes says in his book, Effective Data Storytelling,  “…narratives are more compelling than statistics if your goal is to make an impact on your audience.”

Visuals achieve the same effect; when used right, they help your audience see and understand patterns between scraps of data. Your insights don’t matter unless you can make others understand it and drive them to take the necessary actions.

Problem Solving

A data scientist is like a detective. Both workers investigate the available facts and data to address problems. In one case, the purpose is to solve crimes; on the other, the purpose is to deliver business value.

Data is what we make of it. And a data scientist needs to be resolute at, and equipped for, investigating issues to the root. Project managers love a data scientist who can identify creative solutions to problems.

For instance, discovering that your company’s customers behave in a certain way is different from why they behave so. And even then, the job is most likely not done. You must still use the available data to determine how to make the customers behave differently or to make the company adapt to the customers’ habits.

Data science is a continuous job of evaluating data and weighing options, determining why one approach to fulfilling a goal is better than the other. The consequences of your conclusions could be massive; so you need to get it right, at least based on the data available to you at the time.

Practice makes you a better problem-solver. There are websites that help you learn to tackle various data science challenges with real business impacts.

Business Aptitude

Analyzing data is one thing; contextualizing it to solve real business problems is another. Dr. N. R. Srinivasa Raghavan of Infosys is widely quoted thus: data science is more than just number crunching: it is the application of various skills to solve particular problems in an industry.

Without a good understanding of business processes and operations (such as supply chains, customer service, finance, human resources, logistics), it would be impossible to extrapolate actionable insights.

Data science is a field involving so much theory but has far-reaching practical implications. Therefore, a good data analyst is one that understands the business model and can quickly adapt to various business situations.

How does the business work? How does your company work? What do you know about your industry? How does your company make money? What product/service does your company deliver, and how does that work? What makes your company lose money? Who are your competitors?

These questions, and more, are important to understanding business operations. You can develop this by research. But you first need to possess a keenness for business and understand that data science is not just about Python, SQL and all the technical parts.

Adaptability

Adaptability has to do with how quickly you are able to adjust to new conditions, which may be positive or negative. In this information age, innovation grows at such a rapid pace that it is often difficult to keep up. We are living in a world of possibilities, and what’s new today can become outdated in a few months or years.

In fact, the tools you use for data analysis five years from now may be different from the ones you employ today.

Adaptability is also important for moments of crisis, a time when data scientists come under greater pressure to deliver. Consider the COVID-19 pandemic. The global spread of this virus has disrupted business operations everywhere and altered, perhaps permanently, the course of work and business.

When there is a setback, people seek answers; they want to know exactly what went wrong and how they can move forward.

Today, everyone relies on data. In this world of several unprecedented changes, you must be ready to adjust to the prevailing trends.

Conclusion

Soft skills deal with how you approach data. You may know all the technical bits of data analysis, but a wrong approach almost always leads to wrong results.

More importantly, the technical aspects may change. In five years or a decade, the currently popular data science tools may be entirely out of the limelight, edged by newer advanced tools.

But skills such as critical thinking and problem-solving will endure. Developing these skills early is a great way to secure your career in the future.

Image Credit: pixaby; pexels

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Entrepreneurs Marketing Tech

How AI is Transforming Online Marketing

ai online marketing

AI is swiftly working its way into many facets of our everyday lives. With more and more companies using AI, it isn’t an exaggeration to say AI might bring the next industrial revolution. It has already started making large strides in areas such as customer service, but what can it do for online advertising?

It’s Revolutionizing Email Marketing

Email marketing is a mainstay of the digital marketing world. It’s easy to see why when you realize over 300 billion emails are sent each day. It’s no wonder advertisers want to get a cut of the pie. Thankfully, Artificial Intelligence is there to help with some of the more laborious tasks in email marketing.

Personalization

Writing dozens of different emails for your customers individually can only work for a small, locally-owned business. If you’re a larger enterprise, you’ll eventually have to resort to sending out emails at scale to get the word out.

AI can help you with this. It’s no secret that people are different, and what might make one person open an email the moment it hits their inbox, another may not even take a second look. AI algorithms can analyze how your recipient reacts to different subject lines and opening lines and personalize these so that they’re far more likely to open them.

Sending email goes far beyond basic salesman tactics, such as using your customer’s name. AI can incorporate a person’s whole field of interest, as well as mutual contacts, in order to extrapolate what type of content appeals to them. This will, in turn, help you boost your click-through rates through the roof.

Personalized emails perform far better than their non-personalized counterparts. In fact, some case studies have reported an increase in generated revenue of up to 171%!

Another benefit of AI is that it can find the time that your customer is most likely to open an email. They might be much more likely to open an email coming at 10 AM on a Wednesday than one coming at the end of their weekly Netflix binge. AI algorithms can help identify these individual preferences at a large scale.

AI doesn’t just help with email marketing personalization – it can help with personalization on the outreach side of things, too! AI algorithms can help sales and PR teams determine the most effective points of personalization to use when sending a follow-up email, for example.

Practicality

While we humans pride ourselves on being adaptable, we cannot notice the small changes that an AI will. This, in turn, helps you optimize your email campaign towards your customer’s changing needs. What you’re trying one week might not work by the next.

One of the biggest benefits of AI, however, is how well it can see our errors. People are quite prone to handwaving errors and ascribing them to factors that they are not in control of. Luckily, AI does no such thing. Instead, it’ll let you know the weaknesses of your campaign with the brutal honesty a person wouldn’t be able to muster up. AI grammar checkers, for example, can help you identify spelling, grammar, and even syntax issues in your email copy.

Finally, using AI can be significantly cheaper in the long run than using people. The benefits of hiring a machine learning services company far outweigh the costs. While the marketers themselves will always serve a crucial role in marketing, AI can save you dozens of laborious hours. Not only will you make more money, but your workers will also thank you.

It’s Helping Target Customers with Social Media Ads

Social media is the latest large frontier in advertising. Ever since Facebook has skyrocketed in popularity, corporations have been looking for ways to use social media for advertising purposes. AI helps with this and can even help a business isolate its target audience more precisely.

Maintaining Consistent Quality Across Platforms

It’s no secret that there are many more platforms where you can advertise in order to garner attention. It’s no longer enough to simply purchase a TV ad and be done with it. Today, consumers require multiple touchpoints before they turn into buyers. If you aren’t on a variety of social networks, in addition to TV and popular streaming services – your ads may not be as effective.

Your brand needs to have its message delivered through a variety of different channels. This can be hard to manage consistently if you’re making every campaign by hand. Usually, you’ll get a few very similar campaigns that will be somewhat engaging to most of your audience.

Rather than settling for somewhat engaging, today, you’ll need to impress your customers if you want their business. This can easily be done by using AI to help subtly guide your campaigns towards your target audience. For example, Hulu has a largely older audience in comparison to TikTok. With TikTok having a primarily adolescent-teenage population and Hulu favoring older audiences, you’ll need to take two drastically different approaches.

Localization

Even as a medium to small corporation, you’ve definitely faced issues when localizing your ad campaigns. It can be hard to really know what the locals of your area want by simply doing a handful of manual surveys.

By incorporating AI, you can automate a good chunk of this process. Something especially surprising is how good AI is at optimizing a CTA to the geographical location of your choice. Since the call to action is one of the most important parts of an ad, this can lead to a massive increase in sales.

If you’re branching out to a new area, that makes localization all the more important. This is especially true if you’re expanding to an area where you’ve already got competitors. If you misjudge the cultural norms of the area, you might find yourself with a failure on your hands. AI is spectacular at detecting these nuances, and even smaller corporations can benefit from this these days.

Social Media Ad Copy

Despite the technology being fairly new, AI has been getting more and more use as a method of creating social media ad copy. Companies are using it to create copy, which is later simply edited by marketers, with some daring to hand over the whole process to the AI. Here are some advantages AI can offer in creating social media copy:

  • Speed – AI is much faster than people. It can take historical data about your customer’s behavior and come up with what you should post next by the time a writer has written the outline.
  • Time – If you’ve got writers that can do better than the AI in terms of copy quality, this doesn’t mean it’s useless. It can provide you with valuable data that your authors can use to craft the perfect ad.
  • Detect trends – AI can help you predict trends ahead of time, as well as detect subtle changes in customer behavior. This will help you better understand your target audience and improve the equity of your brand.
  • Frequency and theme – AI can check out your past posts and the posts of other companies in your niche and analyze them in order to determine what posting times and subjects are proving most effective at the time.

Product descriptions fall into a similar pattern. They will also be written faster and more effectively with AI than they will with a human author. Another benefit of AI in this area is that AI is able to update its listings at a moment’s notice.

If it notices that your customers are fans of something, it’ll make an effort to make that stick out more in the description immediately. Furthermore, this can be combined with localization to make custom region-specific descriptions.

Measuring Performance

Another use for AI which saves manpower is measuring performance. Manually calculating things like engagement rates are a death sentence for progress. Instead, you could have AI look through almost every facet of how your ads performed.

Not only can you track user engagement flawlessly, but you can also compare and contrast your ad’s performances amongst target groups and even different forms of social media. With that being said, this isn’t to be used recklessly.

With AI that’s sufficiently advanced, you can even determine which parts of your ad copy your users dwell upon the most and which goes by barely detected. This will let you put out more polished adverts with haste.

As always, it’s a good idea to have the AI’s performance monitored by a human every now and again. For example, Amazon has had a famous incident where its AI was extremely biased towards male candidates.

One example of how AI is helping with performance-based marketing is with Facebook. Facebook’s ad platform uses the performance of your ad to determine which users should see the ad. By leveraging multiple data points quickly, Facebook is able to put your ad in front of the users who are most likely to be interested in your product or service.

Improving The Customer Experience

There are a lot of ways to gain new customers; however, none of them are quite as infallible as providing an amazing customer experience to influence word of mouth. Companies have been trying to outdo each other in customer service since the dawn of modern capitalism. Today, AI is the next technology you’ll need to incorporate in order to ensure your customers get the best experience possible.

AI Chatbots

The customer service industry is one of the ones that have benefited the most from the inclusion of AI. If a customer has an issue with a product, or they’re having issues navigating your website, they’ll want to talk to someone to have it explained for them.

Now, these can be full-time employees who are paid for all of the manpower in answering the questions that your customers may have. On the other hand, you could have AI handle that (like an AI bot) while your employees are given tasks that are harder to automate.

This change is already in full swing. If you’ve seen a “Talk to one of our representatives� button on any sites you’ve visited recently, the chances are that’s a chatbot right there. With that being said, that isn’t a bad thing; chatbots are generally clear in writing and are sometimes more helpful than actual workers.

This isn’t to say that you should fire any customer service employees on the spot. No! Rather than letting these valued employees go, it is best to delegate them to other tasks, with customer support being done by people exclusively in the cases where the AI doesn’t rise to the occasion.

Predictive Marketing

Imagine being a vacuum cleaner salesperson in the ‘70s. When would the ideal time be to knock on someone’s door to sell them a vacuum cleaner? When their old one just broke.

Unfortunately, for a vacuum cleaner salesperson in the ‘70s, there was no way to know when exactly that was. Today, AI can predict most of a customer’s purchasing desires and decisions. Because of this, it is one of the most important tools to get started with.

Customers don’t want to be bombarded with ads for things they don’t currently need or care about. Because of this, any customers you advertise to that simply have no need for your product or service are nothing but wasted capital.

By using AI that puts large amounts of data together in order to better understand consumer behavior, you can ensure that the customer is going to be interested in your product.

For example, let’s say that customer A has been searching for vacuum cleaner bags, vacuum cleaner pipes, as well as vacuum cleaner alternatives. Customer B has been searching how to use Vacuum Cleaner X. The AI will be able to determine that Customer A’s current vacuum cleaner is broken, and Customer B has possibly just purchased a new vacuum cleaner. With this information, it will show Customer A an ad for your company.

This is extremely common in large corporations such as Google or Amazon. However, it’s slowly becoming more affordable for small and medium-sized businesses.

Improving Your UI

The UI (User Interface) is what your customers interact with your website or mobile app through. Having a seamless interface is crucial in making conversions because customers won’t stay on a site that’s not easy to use.

Thankfully, instead of hiring dozens of UI testers and running constant surveys among your target group, you can have AI do the testing for you. The AI has the intuitiveness of a person but is able to identify issues more quickly so that you can make changes to the UI more easily.

It looks through a variety of things, such as:

  • Where the user is when they load up the site
  • How long they stay on the website
  • The site’s bounce rate
  • The user flow
  • How many products each user views before leaving the site

These metrics can be measured by an AI at a large scale to help you make more informed decisions quickly.

Conclusion

While AI certainly has a long way to go, it’s has made massive strides in its development lately.

AI is not perfect, and there’s still a long way to go in terms of improving it. However, your business could definitely benefit from making use of AI in your next marketing campaign to improve conversions, targeting, and user experience metrics.

Image Credit: jose francisco fernandez saura; pexels

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How is Conversational AI Improving Customer Experience?

Conversational AI

The Conversational AI allows the program to be a part of human-like interactions. This set of technologies empower the applications to send automated replies. It is yet another example of the exponential rate of innovations happening in the artificial intelligence field.

As a result, businesses are investing in conversational AI technologies like Chatbots to serve customers round-the-clock. Although the benefits of using this advanced technology are innumerable, you need to answer certain questions while assessing a conversational AI solution.

Conversational AI is Still Evolving

We are still undergoing the phase of revolution wherein innovators are bridging the gap between the artificial and natural interactions among humans and computers. Constantly, developers are empowering Conversational AI technologies to decipher human actions and mimic human-like conversations.

According to research, the Conversational AI market size is expected to reach US Dollars 15.7 billion by 2024. This clearly depicts the interest of investors in this technology and gives a sign of a lucrative future scope for businesses.

The incorporation of context, relevance, and personalization after deciphering various languages and tones is the end goal of this set of technologies. Chatbots are integral components of these technologies. Consequently, they undergo continual enhancements.

Conversational AI is not the Same as Traditional Chatbots

What do you like more, scripted TV shows or reality shows? Traditional chatbots are the scripted ones and Conversational AI chatbots are the non-scripted ones. The former one works with scripted dialogues whereas the latter one works with the context.

When scripted traditional chatbots are created, developers feed the dialogues with proper keywords. The bots are able to respond with the most appropriate reply out of the many replies added to their memory.

When a user sends a particular text, the chatbot identifies the keywords and sends in the scripted replies. This adds tons of burden on the owner of the chatbots. Hence, they update the conversations to make them look realistic.

The traditional scripted chatbots are not able to converse in real-time with users by understanding the context of the whole conversation. As a result, this compromises the customer services of the businesses.

This particular loophole is looked after by the chatbots powered by conversational AI. They hold the capability to engage in any dialogue after grasping the context of the whole conversation. They do not follow a script because they have in-built conversational capabilities in the software. Let’s understand how they work in detail.

Work Process of the Conversational AI

Conversational AI works with a combination of technologies. With the integration of advanced technologies, Conversational AI performs the function of interacting like humans. Here are the steps involved in the work process of these technologies:

1. Accept the Inputs

The first step involved in the functioning of Conversational AI is to accept the inputs from users. These inputs can be in the form of text or speech. If the inputs are in the written form, text recognition technology is applied. On the other hand, if inputs are spoken phrases, then voice recognition technology is applied.

2. Comprehending

Text and voice recognition is done with AI technology natural language understanding (NLU). After the application reads the inputs, the user intent is understood before forming any kind of response. Usually, businesses can use conversational AI for comprehending responses in various languages. In a nutshell, this is one of the most difficult steps in the work process of a chatbot.

3. Creating Response

In this step, the Natural Language Generation (NLG) is used to create responses in a language that humans understand. After deciphering the intent of the human, dialog management is used to create responses. Finally, it converts the computer-generated responses into human-understandable language.

4. Delivering Response

Finally, the response created in the previous step is shared with the users in the expected form. Either the system delivers it as a text or conducts the production of human speech artificially. Are you able to recall the voice of Alexa or Google Assistant? They generate their responses by following this process only.

5. Learn from Experience

Conversational AI also has provisions for improving their responses for future interactions by learning from their experiences. By accepting suggestions, the application learns to deliver better responses in future conversations.

Technologies used in Conversational AI

The Conversational AI platforms use a set of technologies at the right times to complete the work process. All these technologies are empowered by Artificial intelligence. Let’s understand these technologies in brief.

1. Automatic Speech Recognition (ASR)

The application interprets the spoken phrases by deploying this technology. Adding to this, it converts the speech into texts for the app. Voice assistants like Alexa, Google Assistant, etc. use Automatic Speech recognition.

2. Advanced Dialog Management

This technology helps in forming the response to the conversational AI app. Dialog management arranges this response for the next technology. Further, converts it into something which humans can understand.

3. Natural Language Processing (NLP)

Conversational AI uses natural language processing along with its two subsets. The first one is Natural language Understanding which understands the meaning as well as the intent behind any text. It can decipher texts shared in multiple languages as per the programming.

Both chatbots, as well as voice assistants, use this technology. After ASR, voice apps apply NLU. The second one under the NLP technology head is Natural Language Generation. Conversational AI uses this in the last stage of the work process by Conversational AI.

It creates the responses by converting the computer-generated replies into a language that is understandable for humans. This technology deploys dialog management to conduct this task seamlessly.

4. Machine Learning (ML)

Machine learning is great at understanding a set of data. In conversational AI also, machine learning is used to understand the interactions that have happened over time. Also, ML identifies better responses to these interactions.

Therefore, it understands user behavior and guides the app to create better responses. Humans also join machine learning in this task and together make the Conversational AI app a better interactor for customers.

Benefits of Using Conversational AI for Better Customer Engagement

Businesses are struggling for quite a long time to improve their customer engagements. As a consequence, conversational AI tools like Chatbots have become an integral part of websites and apps. Hence, the developers are working hard to incorporate conversational AI in their solutions.

Conversational marketing has become a proven corporate strategy for millions of businesses operating across various domains including healthcare, tourism, education, etc. Let’s find out what exactly can Conversational AI do to empower customer engagement:

1. Never-ending Scalability

Contrary to human customer support executives, Conversational AI can provide solutions to as many customers as possible at one time. Therefore, you can scale up your operations to any limits. Moreover, it can provide human-like interactions around-the-clock without any interruptions.

2. Acts as a Supportive Wing

In an organization, teams work together towards achieving organizational goals. Conversational AI technologies work with human experts and take their burdens away. They do those tasks which are humanly not possible at the same consistency as that of Conversational AI. This leaves room for human experts to entertain customers only when required.

3. Reduces Cost

Investing in conversational AI solutions might seem an added expenditure to you. But in the long run, the functions it performs reduces your cost. You will not have to pay employees for all the shifts to satisfy customers with real-time conversations. These applications prove to be immensely cost-effective for businesses.

4. Offers Data Insights

As mentioned above, machine learning understands the past experiences and interactions to improve your Conversational AI potential for future interactions. This allows businesses to get an insight into the data.

Hence, you will be able to know your customers’ preferences, behavior, and requirements. Furthermore, you can utilize this data for various other purposes to improve your plans and strategies.

5. Improves Productivity

The primary reason for investing in conversational AI solutions should be the need to improve productivity. It enhances overall productivity with uninterrupted, credible, and prompt customer services.

24×7 support and human-like interactions decrease the risk of losing customers. Hence, conversational AI is capable of providing better customer engagement and ultimately a rise in customer retention rate.

Leverage Conversational AI in Omni-Channel Approach

Investing in conversational AI might seem lucrative after reading about its work process and benefits. Before taking the final call, make sure to identify the channels where you are going to leverage this technology.

When it comes to the customer experience journey, we need to take care of many gateways. With conversational AI solutions, you can provide live chats, social media interactions, messaging on various platforms like Whatsapp, SMS, etc., as well as emails.

Therefore, businesses are using the omnichannel approach. Under this approach, they use multiple engagement channels and offer a seamless and intuitive customer experience. It allows businesses to offer their customers a proactive engagement and prompt responses.

Conclusion

Across the world, businesses are deploying high-end artificial intelligence technologies. This, in turn, offers business solutions to enhance the engagement of customers. Therefore, we can these technologies to offer an improved experience to your users. Conversational AI holds the potential to strengthen customer and business relationships. All you need is to explore it efficiently!

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