Technology today has taken a very fast pace and has changed our lives. Companies today can provide quick and personalized responses to customers. Hence, have increased the level of customer satisfaction. The use of voice-based chatbot is on the roll. Different companies are adopting it to be at the top of this competitive world.
Today, the bots are powered by artificial intelligence. They are thus, capable of assisting via text or voice. They provide the best solutions to both the customers and agents in various areas. As per a study, by 2020 about 85% of customer relationships will be automated. It can help in various sectors like education, insurance, travel, etc.
Considering the usage of a voice-enabled chatbot, 47% of the people are already using voice search devices at least once a day. As voice recognition technology continues to improve in accuracy, and services are getting added to it. As a result, more consumers are shifting to voice engagement.
What is a voice-enabled chatbot?
Voice-activated chatbots are the ones who can interact and communicate through voice. They are capable of accepting the command in an oral or written form. They are programmed to reply through voice. This can be further categorized into two types — one which response via text and voice together. And the other, which response via voice only.
The popular examples of voice-enabled chatbots are the Amazon Echo, Google Home and AI Timey. A voice-based chatbot uses pre-recorded and text to speech responses to address the queries of the users.
Types of voice-enabled chatbots:
Voice + Text Bots — Hybrid Voice + Chat Support Model: These are text-based bots with a layer of voice on top of it. The input form is speech as well as text.
Voice Only Bots — Voice Controlled Devices: These bots can handle everything from simple tasks like setting alarms, playing music to more complex tasks like controlling your gadgets, turning your house into a smart home.
Demand and usage of voice assistant devices:
Voice is a more natural way of functioning for humans than texting. It is informal, intuitive and immediate. This shift provides a natural and seamless flow to processes. Hence, it gives more mobility to employees. It is expected that by the year 2020, 50% of searches will be voice-based. Companies need to be on that platform as well, with the customers. About 1 in every 5 teens (14–17) plan to purchase a stand-alone digital voice-enabled assistant within the next 12 months. Therefore, the demand for digital voice assistants is increasing. This is also satisfying consumers’ wants and needs.
Accenture’s Digital Consumer Survey in 2017 included 26,000 people from 26 countries. The survey found that 46% of US consumers are using “voice-enabled digital assistants”. These numbers were even higher in India and China — 55%.
If we consider the breakdown by age group, it shows more usage among the younger users. Over 30% of 14–17-year-old use the voice assistants regularly with another 20% that just started and 33% interested. Thus, 84% of teenagers either already are using any kind of voice assistant or plan to.
According to research by Canalys, the smart speaker installed base will approach the 100 million mark by the end of this year. This makes it almost 2.5 times bigger than at the end of 2017. The installed base is assumed to grow and reach 225 million units by 2020.
In the long run, the customer service department will be able to function more efficiently and it will cut costs.
Why consumers prefer voice?
Voice bots can be integrated with other services and data delivery channels. Bots are acting as personal assistants today. They can perform simple tasks like making phone calls, read messages, or setting alarms and reminders.
Voice AI augments customer insights
Having a voice-enabled chatbot increases the capabilities to provide reliable data insights to the customers. It helps in giving correct real-time information. It also helps in increasing the customer’s side experience. A seamless connection between the customer and the service personnel is maintained
All text and no voice is monotonous
Having good customer engagement is important in today’s competitive world. The biggest worry about engaging in a text-chat conversation is that it requires patience, time and voiceless understanding of the matter under discussion. The simple text often lacks transparency, context and personalized sentiments. This makes the interactions inorganic and strenuous, eventually resulting in misinterpretation of an actual conversation. Voice gives highly automated, intelligence-driven business communication.
Faster responses and zero wait time
Customers today don’t have time to wait for a deal with a company and queries. Thus, optimizing the customer experience a vital part in giving the best customer service. At the same time, it does not make fiscal sense to have an oversupply of live agents waiting to respond on each incoming chat instantaneously.
as per a statistic, 10 seconds ay in playing a video line makes 50 of the viewers to abandon the site or just close the video.
Better two-way interaction
The best part about voice-enabled chatbot is two-way communication. Thus, it gives a better customer experience.
Better customer experience
Voice-enabled assistants help in giving the best customer experience. Customers appreciate innovative ways of engagement with a brand. Hence, direct advertising will not elicit much from customers. Using talking bot is an exciting concept. It can create a positive sensation in people who experience it. Adopting this technology allows providing more integrated, delightful and rich customer experience.
Business Expansion
Businesses today have been using messaging apps and the audience is already enjoying that. they have managed to achieve success in the market. Thus there is a great opportunity for voice to enter since it will be easily accepted.
No human physical touch required
Today we are moving towards the touch-free devices. Voice recognition chatbot offers new opportunities for personalization. This intimates engagement for companies where such technology does a lot more than a traditional approach. The two-way chat happening between human and a robot is way too profound. This eliminates many obstacles faced while dealing with customer requirements. Pure text-based chat solutions require the presence of a supporting device. But intelligent voice chat robots do not latch on any special hardware devices. They simply get rid of physical means of interactions and costly customer engagement barriers. New and advanced AI technology allows you to speak to your voice assistant robot without using many control buttons or hassle provided you are loitering within its available range.
Increased productivity using multitasking
Voice-enabled chatbots help us in providing good customer service and quick assistance with the daily tasks and shopping dilemma. Apart from this, one can use it as on-demand virtual assistants that help in enhancing office productivity by integrating with existing apps on our computers and digital devices.
With a voice bot you can also do the following thing to increase productivity:
schedule, organize and modify meetings with the clients
write and send emails
set reminders
Voice helps in providing value
Voice-enabled services are close to humans and have interactive capabilities. This adds unbelievable value to the business. Voice-based customer services drive better and faster conversations in personal lives. It also entices the customer about the brand.
The ability to pause and listen
Voice-activated bots are not only good listeners but they also help in determining the next steps. You can also pause it when the person on the other end is talking.
24*7 Availability
Human services might not be available throughout the day. But voice bots are available 24*7. Along with the availability it can handle a high volume of calls at once giving quick and instant results.
Increase in sustainability
Voice bots help in increasing employee satisfaction, as well along with customer satisfaction. Constant monitoring and analysis of all conversations are possible by creating n interactive dashboard that gathers information om historic chats.
Finding the best fit
Voice bots powered with AI can give the best solution. They provide personalized responses for the particular customer. With the excessive data these days, voice bots can scan it. Along with this, they provide the best solution which is suitable for the consumer.
Fraud Detection
With the incredible capability of data mining and quantitative analysis of data, voice bots help in reducing the cost and data analytics helps in detecting the fraud.
In the era of extreme competition, companies mustn’t leave a chance of converting leads into their customers and provide the best-personalized customer service experience. Voice bots are a great way for businesses to use automation and connect with the world at the human level.
Apart from this, there are certain points which should be kept in my mind before using a voice-enabled chatbot:
data security
Likability of the bot
understanding the emotions
language specialization
This article is written by Mohit Dua and originally published here
Business leaders and investors universally agree that Artificial Intelligence (AI) and Machine Learning (ML) will transform their businesses by reducing costs, managing risks, streamlining operations, accelerating growth, and fueling innovation.
The potential for AI to drive revenue and profit growth is enormous. Marketing, customer service, and sales were identified as the top three functions where AI can realize its full potential according to a survey of 1,093 executives by Forbes.
· Sales organizations are dramatically improving sales performance by using algorithms to help with the basics of account and lead prioritization and qualification, recommending the content or sales action that will lead to success, and reallocating sales resources to the places they can have the most impact.
· Marketers are looking for AI to fuel enormous efficiencies by targeting and optimizing the impact of huge investments in media, content, products, and digital channels.
· And in customer service, AI is opening entire new frontiers in customer experience and success by applying NLP, sentiment analysis, automation, and personalization to customer relationship management. 90% of organizations are using AI to improve their customer journeys, revolutionize how they interact with customers and deliver them more compelling experiences.
To realize this potential to grow revenues, profits and firm value, businesses in every industry have announced AI focused initiatives. On average, investment in advanced analytics will exceed 11% of overall marketing budgets by 2022. Spending on AI software will top $125B by 2025 as organizations weave AI and Machine Learning tools into their business processes. In parallel, investors have poured more than $5 Billion into over 1,400 AI fueled sales and technology companies to meet this demand.
So far, the impact of these investments on growth and profits has not yet been transformational. Right now 70 % of AI initiatives are showing little or no return. And more businesses will struggle to realize the full potential of AI to grow firm value if their leaders don’t learn lessons from past transformations like the internet in the 1990s and cloud computing in the mid-2000s, according to Kartik Hosanagar, Professor of Technology, Digital Business and Marketing at the Wharton School and author of the influential book A Humans Guide to Machine Intelligence.
“What separates the AI projects that succeed from the ones that don’t often has more to do with the business strategies organizations follow when applying technologies than the ability of the technology itself to transform the business,” according to Professor Hosanagar. “Many of the problems are less about the tools and more about leadership. Most of the failures to harness the power of AI lies in human behavior, management understanding, and the failure to mesh algorithmic capabilities into organizations, business models and the culture of the business.”
Today most executives feel like the pace at which AI can be made successful has been overstated, and the challenges have been understated according to the Forbes survey. That is totally understandable based on the current level of acumen in the business community about AI and advanced analytics. But the perception of hype and speed is an education and skill problem. AI works today in many business applications. It’s more a matter of the managers tasked with harnessing the power of AI don’t have the experience and framework to understand it. Just as a calculus class will move far too fast for a sixth grader to grasp, growth programs based on AI and ML will be far too advanced for the executives who define, direct, and fund their development and are ultimately accountable for the results they deliver.
“Algorithms are opaque to the average business executive and can often behave in ways that are (or appear to be) irrational, unpredictable, biased, or even potentially harmful,” continues Kartik. “It’s up to business leaders to shape the narrative, direction, and ways algorithms can -and cannot – impact work, customer relationships, and the way business creates value.”
Executives who allocate capital and the managers who will lead the AI transformation cannot afford to have a poor understanding of something so fundamental to business and the creation of value today. “Ignoring the problem because it’s complex is not really an option. AI-based algorithms are here to stay,” continues Professor Hosanagar. “To discard them now would be like Stone Age humans deciding to reject the use of fire because it can be tricky to understand and control”
To help bridge this knowledge gap, The Wharton School of the University of Pennsylvania announced yesterday the establishment of Wharton AI for Business (Artificial Intelligence for Business), which will inspire cutting-edge teaching and research in artificial intelligence, while joining with global business leaders to set a course for better understanding of this nascent discipline. The goal of AI for Business is to educate a new generation of business leaders with a deeper understanding of AI – its fundamentals, capabilities, use cases, risks and limitations – so they can align AI with their business strategies and effectively direct, prioritize and invest in applying AI in their unique business models.
A cornerstone of the launch is a 4 week Artificial Intelligence for Business online certification program for business leaders and professionals. The program is aimed at providing executives, managers, and business professionals in the fields of marketing, operations, automation, and analytics a competitive edge in the emerging field of AI analytics.
According to Hosanagar, one of the primary reasons Wharton launched the AI for Business initiative is because it can help managers avoid very common mistakes their peers make when they define, invest in, and deploy AI-led transformational initiatives. Specifically, managers leading AI transformation typically make the same set of mistakes:
· They execute AI development in siloes isolated from the business, or outsource it entirely, instead of making it a core part of the business;
· They treat AI led transformation as a separate strategy instead of using it to support their core business objectives and growth agenda;
· They fall into a trust and transparency vortex in which they either trust AI tools blindly without truly understanding them, or not at all, because they don’t understand what is inside their “black box” algorithms.
Kartik is emphatic that today’s managers must learn from the mistakes of past transformations. “Today nobody denies the internet was transformational to businesses and created billions of dollars of shareholder value,” reminds Hosanagar. “But despite the huge hype and promise, it certainly did not start that way. If you look back at the dawn of the internet 20 years ago, almost every organization quickly set up an independent dot.com division to lead the transformation to digital. Most of these failed.” Hosanagar cites the example of Kmart who in 1999 aggressively invested in bluelight.com – a separate dot.com division – ahead of most of their competitors, but failed because they did not stick with it long enough and did not integrate the digital division with the rest of their business. The company soon went bankrupt in 2002. “A siloed approach to transformation is a flawed strategy. Ask yourself how many businesses have independent dot.com divisions anymore? What eventually did succeed was to find ways to use the internet to augment and accelerate their core business strategy – simplifying ordering, improving customer services, and supporting omnichannel sales models.”
“In my 10 years of working with data science and AI strategies in business, I see executives tend to fall into two camps when it comes to applying AI to their business,” shares Professor Hosanagar. “They either don’t understand it but trust it. Or don’t understand it and do not trust it. Both are failed strategies. The key message here is leaders need to understand enough about how AI works to strategically align AI with value creation and make smart investment decisions.” Specifically, Professor Hosanagar advises managers leading AI transformation initiatives to:
· View AI as a tool, not a strategic goal;
· Take a portfolio approach to AI project that balances quick wins with fundamental process redesign;
· Grow your talent base by both re-skilling existing employees and hiring new talent;
· Focus on the long term by sticking with AI through inevitable early failures;
· Be aware of new risks AI can pose and manage them proactively.
“AI can be a force for positive change if business leaders apply it thoughtfully,” according to Sajjad Jaffer, founder of Two Six Capital, a firm that pioneered data science for private equity. “Wharton is unmatched in its depth and breadth of research in the fields of Statistics and Analytics. Programs like Wharton’s new AI offering are table stakes for next generation leaders as companies increasingly rely on large data sets, cloud computing infrastructure, and open source software to scale their businesses,” continues Jaffer, who serves on the board of Wharton Customer Analytics and is a Wharton Senior Fellow. “Investment committees and company boards need to bridge the widening chasm that exists between sound business judgement and AI skills across industries and asset classes.”
Christine Cox, the VP of Marketing Operations and Demand Generation at Ricoh USA echoes this sentiment. “Based on my 20+ years leading marketing and sales teams across financial services, telecom and technology, AI is only just beginning to break into the Martech stack of traditional brands, enabling hyper-personalization of the Customer Experience,” reports Cox. “As large organizations develop greater AI capabilities for driving customer acquisition and retention, we will see these organizations innovate faster, engage with customers in new ways and start to compete with the digital-native companies. Holistically, AI has catapulted digital marketing and digital sales in the last five years, and I expect AI will exponentially accelerate the research and response process for marketing and sales teams to address evolving buyer needs in the future. However, this won’t happen with technology and data alone. In my experience, the business leaders who work to truly understand the nature and capabilities of AI and advanced analytics will be the ones who will realize the greatest impact and value from this transformation for their respective audiences.”
Saurabh Goorha, a Senior Fellow at The Wharton School, reinforces Kartik’s advice that managers gain an fundamental understanding of AI and ML to make them aware of new risks AI can pose and manage them proactively. “Executives make significant decisions about how they should invest capital, resources and talent to realize the full potential of AI and ML technologies to transform their businesses,” relays Goorha, who has decades of experience in product managment in EdTech and MarTech. “These decisions should be an outcome of a grounded understanding of AI and ML starting with first principles: what are the business and functional problems that can be solved and measured with comprehensive data strategy. At the next level they must ensure their AI strategies are informed by a solid understanding of both the potential and risks of AI as well as the strengths and limitations of the underlying data fueling these programs.”
This article is written by Stephen Diorio and originally published here
Among many industries that have dramatically changed thanks to the rapid technological development over the last few decades, the retail industry is one of those that have benefited the most.
The emergence of online shopping has provided both sellers and buyers with numerous conveniences never seen before.
Further developments were – and still are – mainly focused on making the process of buying more intuitive and straightforward. Retailers have realized that less complexity in user and customer experience means better sales.
However, it turned out that making the selling process simple and intuitive is at least as important as making life easier for the buyers. Essentially, these are the two sides of the same coin and both can be substantially enhanced with the use of the right technology. And lately, we’re finding out that there’s no better technology for this purpose than artificial intelligence (AI).
How does AI benefit sales professionals?
AI is definitely far from being a new concept, and its meaning has significantly changed over time. Today, we’re using it routinely in numerous everyday devices and appliances, often without being aware of it, even though the general public may still be imagining evil robots taking over the world whenever AI is mentioned.
Naturally, this doesn’t mean that there are no possible dangers from the misuse of AI, especially given that it’s difficult to predict how exactly this technology will further evolve. But its benefits are so widespread and so valuable for so many industries that we can without any doubt say that AI is here to stay. And obviously, its effectiveness goes beyond the scope of business to help us with matters we all find crucial, from healthcare and education to weather forecast, disaster response and many more.
In principle, AI’s capability to process and interpret colossal amounts of disparate data in a way no human could ever do manually is the root of most of its power. Additionally, its potential to automatically update its algorithms according to feedback, without outside human involvement is what makes its results so impressive. It processes data, constantly learns from it, adapts and then acts upon what it has learned, which results in a high level of automation of previously very difficult or impossible tasks.
So, finally, how does this affect sales professionals? This whole article will deal with that question, but let’s make a quick preview of why AI will be so critical for the future of sales.
Very often, we hear that this is an era in which data is “the most valuable asset”. This goes for retailers and salespeople as well – obtaining reliable customer data is absolutely vital for their success. But given the amount of data uploaded every day (in 2018, this amount was 2.5 quintillion bytes per day and it’s expected to grow to 463 exabytes in 2025), the mere possession of billions of divergent data points is of virtually no use for any business.
This is where the processing power of artificial intelligence comes in. AI can sift through this data, sort it, organize it and put it to action. This way vendors can get to know their customers, their prospects and their market in general by looking at the data they generate. This can do wonders for lead generation, pipeline monitoring, sales forecasting, real-time marketing or communication with customers, just to name a few benefits.
AI’s capability to act upon interpreted data also helps automate tasks and workflows, thus enhancing productivity. Furthermore, it speeds up communication inside the organization and makes it smoother. Finally, it can do numerous repetitive and tiresome tasks that used to be done by human reps, in a reliable and error-free way.
How is AI taking over sales?
When we say that AI is “taking over” sales it doesn’t mean that it’s here to take our jobs or that sales reps will soon become obsolete. The fact that it’s taking over means that it will become an absolute must for retailers if they want to keep their heads above the water.
Simply, salespeople that use the help of AI will gain an advantage over their competitors that will be very difficult to compensate for. Using AI methods is the best way to get to know your customers through carefully collected and well-analyzed data.
Also, it’s becoming increasingly important that businesses are available to their customers at all times, via multiple channels. Immediacy is crucial here – not being present at the exact time the customer is considering buying something may mean losing money. As much as 64% of consumers expect brands to respond and interact with them in real-time. This is why chatbots are so useful – they can jump in at any moment in time and provide help.
All in all, AI won’t be “taking over” in the sense that the process of sales will be fully automatized, with no human involvement at all. At least not any time soon. But it will definitely become a necessary aid to sales departments and human sales reps. Those who fail to realize this fact will undoubtedly be falling behind.
AI sales assistants
Sales reps know what they don’t know and they can easily recognize which type of info would help them boost their sales. For instance, only 51% of them think that they have sufficient market intelligence on customers and prospects, although more than 80% of those who have this market intelligence reckon that it helps them do their job more effectively. Stats are even more indicative when it comes to customers’ propensity to buy, suggested next steps and other valuable customer intent data.
In short, most salespeople aren’t really happy with the amount of info they have on people they’re trying to sell to and they definitely think that this type of info would be very valuable. And this is exactly the type of info AI can provide. Of course, these data first need to be collected through various tools, but without proper analysis by powerful AI software they’re almost worthless.
Nobody claims that AI can fully imitate human contact and human touch provided by an actual salesperson, at least for now. But with valuable data and feedback at their disposal, sales reps do a much better job – in fact, the highest performing sales teams are 2.3 times more likely to use AI-guided selling.
4 use cases of AI in sales
AI assistants are exactly that – assistants, but ones that are hugely beneficial and will become indispensable in the future. Let’s see why that is in a bit more detail.
1. Lead generation and scoring
Normally, sales reps tend to spend a lot of time trying to sell to leads that are simply not interested enough and won’t even think about buying no matter how talented or skillful the rep is. For instance, when it comes to B2B sales, as much as 61% of marketing teams send leads directly to salespeople, but only 27% of these leads are actually qualified.
This means that more or less, three-quarters of those are just a waste of time. This would be a huge blow for any organization. Without enough relevant data on these leads, sales reps have no way of knowing if there’s the slightest chance that their efforts will pay off. They simply reach out, try their best and hope it’s not for nothing.
Most salespeople claim that solid market and customer intelligence makes a world of difference in this respect. For instance, tracking customers’ and prospects’ online behavior and having their basic personal info, such as location or demographics can be very helpful when deciding who you should try to sell to.
Of course, these collected data are not delivered raw and unprocessed to the sales reps to make their own conclusions. AI software does this job for them and automatically recognizes and scores leads based on obtained data. This data-driven scoring makes sales teams much more efficient and helps them focus on actual potential buyers instead of accidental browsers.
Additionally, AI can compare the obtained insights with your biggest accounts and report to your sales team when there’s a high level of compatibility between these accounts and promising new prospects. Moreover, the algorithm that AI uses is automatically updated when you acquire new customers or when your existing accounts grow, leaving less and less room for errors.
In other words, the longer the AI algorithm is at work, it will provide more accurate results and your sales team will lose less time. It can even automatically engage these leads in real-time and then hand them over to sales reps to do what they do best.
2. Communication with customers and prospects
Naturally, it’s not enough to just recognize promising leads. It’s very important how and when you reach out to your customers and prospects. There are multiple ways in which AI helps sales teams in communication with their customers.
First of all, it enables chatbots to do their job with the help of powerful natural language processing. As it was said, it’s crucial for companies to be available to consumers at all times and chatbots can obviously do this job around the clock. However, a lot of them are not yet proficient enough to carry out complex exchanges, and 86% of consumers still prefer to interact with a human.
But chatbots can be very useful when a customer needs a quick and simple response, and in some cases, it can buy some time until a human sales rep is present. Moreover, they will get more advanced and more helpful in the times to come.
In any event, AI-assisted communication goes beyond chatbots. AI can provide salespeople with important info about potential customers that can lead to substantial improvements in communication. AI algorithms can recognize the right time to reach out, for instance. In this respect, the trigger-based choice of timing can be very effective. For example, when a website visitor starts looking at a certain line of products, AI can immediately recognize this visitor’s interest, initiate the conversation and leave the rest to the human rep.
Well-interpreted data can also help human reps choose their approach, language or tone when addressing customers and prospects. Finally, AI can distinguish between desktop and mobile phone users or identify channels that consumers use to communicate, therefore ensuring they’ll see your message once you reach out.
3. Personalized recommendations
The overall effect that new technologies have on customer experience is immense. And as it was emphasized, good customer experience (CX) in combination with accurate targeting makes selling much easier. In other words, advanced technology-driven selling methods improve CX, and improved CX means better sales. There’s hardly a better example of this than personalized recommendations.
When it comes to sales, the most important consequence of successfully obtaining and processing customer data is the ability to personalize the content and the experience so that they suit any particular user. More than 50% of consumers are ready to offer their personal data to companies if that means they’ll start seeing content, offers, and ads that fit their specific interests.
Therefore, having the right leads solves the problem of who to sell to, improved communication solves the problem of ‘’how’’, and personalized recommendations solve the equally vital problem of ‘’what’’. And it’s hugely important that this ‘’what’’ is different for every single customer.
An efficient AI-based algorithm that generates personalized recommendations can do real wonders for any business’ sales. We all know how many recommendations are basically thrown at us at every online step we make – via email, social networks or while we simply browse the internet.
Evidently, this is no accident. This strategy opens huge opportunities for cross-selling and upselling as well, and at the same time, it actually helps consumers buy exactly what they want, even if they were not actively looking for it. This approach is sometimes so efficient that, for instance, as much as 35% of what consumers purchase on Amazon comes exactly from product recommendations.
Given the wide range of customer data available to retailers, this is no wonder. An algorithm that has access to the user’s browsing history, purchase history, demographics, interests, preferences, and present-time online behavior can easily identify what they might need and how much they’re willing to pay for it.
With new feedback and new data fed into the algorithm, there’s no doubt that AI will only become better at recommending products and special offers to specific customers. They will be making fewer and fewer mistakes and having a decent product recommendation algorithm is becoming an absolute must for any online retailer.
4. Enhancing productivity and performance of reps
Apart from improving how sales teams interact with customers and the rest of the outside world, AI also influences the way sales teams work on the inside.
First, AI can help with workflow automation and streamlining processes in the entire organization. This includes automating task delegation and prioritizing the tasks based on various objective parameters.
For instance, it can recognize a very promising lead and automatically assign it to the best sales rep with a demand to reach out to it as soon as possible. Similarly, it can delegate tasks or set up meetings based on the geographical location of leads and sales reps. In other words, it can take care of some aspects of the manager’s job more quickly and more efficiently than a human manager.
Obviously, this saves the company a lot of time that would’ve otherwise be spent on organizational issues and eliminates some of the annoying noise in communication that can create confusion and chaos.
At last, AI is capable of analyzing the strategies of each rep or team and figure out what works and what doesn’t, given the end result. This can help the decision-makers recognize the best practices and apply them across the whole organization for maximum efficiency.
Conclusion
In sum, AI is an extremely effective and promising technology that is yet to reach its peak. It’s heavily used in sales at the convenience of both those who buy and those who sell and its greatest advantage is that it provides businesses with remarkably valuable insights about their customers.
As a result, it could be said that the current generation of retailers knows more about their customers than any generation before them. Now that they know what their customers are about, they have the opportunity to actually put “customer first” philosophy into work. And by doing that, they will help themselves and grow their business, too.
Such a powerful technology can, of course, be misused and exploited, but we have a chance to put it to good use and let it benefit all of us. Now it’s up to companies to decide.
Find the right AI sales assistant to help you start using artificial intelligence for your sales needs today.
The article is written by Daniel Bishop. The content was originally published here
What is conversational commerce? Why is it such a big opportunity? How does it work? What does the future look like? How can I get started?
These are the questions I’m going to answer for you right now.
Ready? Let’s do this.
“It seems pretty obvious now that the first inclination of most people when they want to talk to a friend or a family member is to text them. It’s crazy this hasn’t come to businesses yet. The first businesses that are able to fully embrace this and be as responsive and communicative as a friend will be able to drive significant new relationships with their customers and ultimately increased business. This isn’t a matter of if, just when. The technology is coming along fast.” — Josh Elman, VP Product at Robinhood and Venture Partner at Greylock
What is Conversational Commerce?
First off, people have been using conversation to drive sales and make customers happy since humans first began trading. From asking the store owner about which wine you should buy to messaging a boutique on Instagram to find if they still have that custom necklace left, conversation has always been — and always will be — a core part of commerce.
Today, conversations can be automated, and it is this automated experience that we are referring to when we use the term “Conversational Commerce”.
Definition: Conversational commerce is an automated technology, powered by rules and sometimes artificial intelligence, that enables online shoppers and brands to interact with one another via chat and voice interfaces.
Conversational experiences can add value to every part of the customer journey, ranging from when a customer makes their first order to answering a product-related question instantly.
“I think the first place we’ll see chatbots really take off in eCommerce is in customer support. Yes/No and other intent based filtering will make eCommerce support WAY more efficient.” — Ezra Firestone, CEO of Smart Marketer Inc.
Conversational commerce is possible on any platform that supports chat or voice bots (Facebook Messenger, Amazon Alexa, Google Home, Apple Business Chat, SMS, WeChat, LINE, Telegram, etc).
“I think chatbots and voicebots may become the future of commerce, as it relates to Gen Z. We optimize for efficiency and grew up on on-demand services, such as Uber, Lyft, Postmates, etc. Therefore, we expect the same when shopping. What better way to do that than interacting and shopping via chatbots and voicebots? That completely changes the game. It’s a whole new experience. It makes online shopping less tiresome and interactive and fun again!“ — Tiffany Zhong, Founder & CEO of Zebra Intelligence
Conversational commerce will even be able to read your thoughts. (… We’ll talk about this later.)
If you haven’t wrapped your head around conversational commerce yet, don’t worry. Here’s an example to help you visualize what conversational commerce is.
Example:
If you were to purchase something from Nordstrom online, after a week or two, you would receive an email encouraging you to leave a review about the product you purchased.
In order to successfully leave the review after being emailed, you will have to:
Open the email.
Scan through all the different call to actions. (I see at least 15 in the example email below.)
Click the review call to action.
Wait for the webpage to load.
Fill out your name and information.
Fill out your review.
Hit submit.
It’s a lot of work.
If Nordstrom were to use conversational commerce, which I’m sure they will, this experience would be 10x easier:
Instead of sending you a bloated email, Nordstrom could simply message you on Facebook and ask what you thought of your new boots.
“We’re seeing businesses large and small drive tangible results using messaging as a marketing channel — from acquiring new customers to driving repeat sales. Businesses are turning to Messenger to help their customers find the perfect gift, book appointments, get personalized deals, receive shipping updates and so much more. Messaging helps businesses and their customers connect in a personal and productive way — all at scale.” — Andrew Kritzer, Product Manager, Messenger Platform.
Conversational commerce is powerful not only because it makes the automated interactions between the brand and the consumer feel so much more human, but because it reduces the number of steps the customer has to take to complete an action.
“This all looks cool Matt, but how big of an opportunity is it really?” you might be thinking. “Why should I be paying attention to this now?”
Great questions. You’re going to want to know the answers.
Conversational commerce is a huge opportunity. MASSIVE. Scroll down and I will explain.
Why Conversational Commerce Is Such a Big Opportunity
I know, ecommerce has been built on the back of email. It’s used for marketing, customer support, sales, retention, all of it. So…what benefits could conversational commerce possibly have over email?
I’ll tell you right now.
“All of the big trends in commerce over the past couple of decades have been in moving to where your customers are. Rather than forcing your customers to come to you, you go to where they are. The next generation of that is conversational commerce. It is inevitable that everyone is going to have to incorporate conversations inside of Messenger, and into social media platforms, in order to sell things more effectively.” — Phil Libin, Founder of All Turtles and Evernote
This is why high growth stores are implementing conversational commerce:
Conversational commerce enables two-way communication with the customer. It doesn’t just tell them things, but also learns from them, hears their questions, and builds a relationship.
Connect with 2–5x more customers than you’ve previously done over email. (You’re probably thinking “How the heck can you do that??”, don’t worry, I will explain this later.)
Stores using conversational commerce, in the right way, are increasing annual revenue by 7 to 25%.
These stats are amazing, and they are only the beginning. The future of conversational commerce is very bright.
Why? I’ll tell you right now.
Over 2,000,000,000 people are using messaging apps.
Adoption for messages apps is growing faster than social networks.
37% of the world’s population is using messaging apps.
The massive distribution of this technology, and the emergence of conversational commerce, gives businesses the ability to communicate with each of their customers in a private, personalized, and two-way environment
“Our chatbots are already performing better than email, when comparing organic growth, read rates, and click-throughs. We know that fans want to feel close to their favorite artists, and this solution helps us connect them in a way that’s authentic. Email just doesn’t provide the same opportunity to show off your personality.” — Jeremy Kutner, VP of Web & Mobile at Warner Music Group
This is huge shift from the non-personalized mass marketing that social media platforms like Twitter and Facebook have popularized over the past decade.
On top of the adoption of messaging apps, did you know that over 40 million people own a smart speaker (like an Amazon Alexa) and that that number is expected to double in 2018?
Voice-enabled devices don’t stop there. 2.5 billion people are expected to be walking around with smartphones by 2019.
Conversational platforms are exploding, and it makes perfect sense. Conversation as an interface is the most natural way for humans to interact with technology.
“After a life of sitting at a desk my whole adult life I finally got a hemorrhoid. When I went to the pharmacy to pick something up, I couldn’t understand the differences between all the options. I was too embarrassed to ask the pharmacist about it, so I walked out. I went to Amazon and bought the first thing that looked right. It was totally wrong. We idealize human interaction, but for some things a bot is better.” — Andrew Warner, Founder of Mixergy and Bot Academy
Conversational commerce represents a paradigm shift in how brands and customers interact, and it will have major impacts on the entire customer journey. This is why conversational commerce is such a big deal.
“[Conversational commerce] will make it easier for businesses and customers alike, by removing the hurdles of having to use web sites or apps.” — Trond Stroemme, Technology Strategist at Nestlé
But how exactly does conversational commerce work? What are all the possibilities of conversational commerce?
I will explain that right now. Better yet, I will show you.
Scroll down to see.
How Conversational Commerce Works
When thinking about conversational commerce and how it will apply to your business, you need to think about four different types of experiences.
Proactive / Automated. Example: A customer makes their first purchase ever, and the next day the store automatically sends them a nice message thanking them for shopping at that store.
Reactive / Automated. Example: A customer just bought a new camera, but it’s not working correctly, so they message the store asking for assistance. The store automatically recognizes their question and sends them the correct guidance.
Manual / One to Many. Example: The store just opened 10 new locations and they want to notify people in nearby areas. They send out a custom message to a targeted segment of customers that live within 10 miles of the new locations.
Manual / One to One. Example: Sending a thank you message, and a coupon, to a customer who just shared a positive review and photo on Twitter.
Now that you know the four ways in which conversational commerce can be included in the experience, you need to figure out which parts of the customer journey would benefit from a targeted conversational commerce experience.
Here’s a brief example of a customer journey (Challenge: Can you imagine how you could pair these steps with conversational commerce?):
Visits the store online for the first time.
Adds a product to their cart.
Looks at a product.
Places order for the first time.
Order is shipped.
Order arrives.
⏰ Take a second to think about how you could use conversational commerce to improve the customer experience during each of these steps.
“Ecommerce services should consider building shopping experts that help guide the user towards the right purchase. This can work well when there’s a wide variety of options (e.g. in fashion) or when there’s complex products (e.g. calling plans).” — Ofer Ronen, General Manager of Chatbase at Area 120 (incubator operated by Google)
Done? “No Matt, I want to see some real examples of conversational commerce!”
Okay, OKAY, I hear ya!
Here is a list of conversational commerce experiences, and integrations, every store should have.
Ready? Scroll down for examples of chat and voice based conversational commerce.
Examples of Chat-Based Conversational Commerce
These are a few examples of chat-based conversational commerce. (“I’m looking for voice based examples, Matt!” well alrighty, I hear ya, just scroll down a bit more to see the voice examples!)
“Talking to virtual employees will play an increasingly pivotal role: customers don’t want to wait for answers to simple questions. And business don’t want to allocate resources to answer the same questions over and over.” — Phil Vanstone, Program Manager at Shopify Plus
Index of chat-based conversational commerce examples:
Seamlessly connect with the customer on Facebook Messenger.
Chat with the customer directly from the online store.
Touch base with the customer after they leave the store.
Let the customer know that their order has been made.
Let the customer know that their order has shipped.
Thank the customer after their first purchase.
Confirm with the customer that their package arrived and ask for their opinion.
Recommend products based on purchase history and customer data that’s been collected conversationally.
Ask the customer if they are ready to reorder a replenishable product.
Troubleshooting.
Answer a question.
Seamlessly Connect With the Customer on Facebook Messenger
The first thing you are probably wondering is, “How the heck do I message my customers on Facebook?”, the answer is quite simple: You need to implement the Facebook Messenger Checkbox.
What does the checkbox do? Here is the high-level explanation:
The checkbox automatically detects a customer’s Facebook profile when they view your store, even if it is the first time they have ever been there.
Stores place the checkbox next to the “Add to cart” buttons on product pages or during the checkout confirmation screen.
Customers who go through a flow involving the checkbox are able to give the store permission to send them future messages on Facebook.
Once the store has permission to send messages to the customer on Facebook, the store can start to send conversational experiences when they are trigged during the customer journey (like sending a message when a customer doesn’t complete an order).
Most stores currently collect email addresses during the checkout process, meaning that most shoppers who add an item to their cart are never connected over email with the store.
An implementation of the Facebook Messenger Checkbox moves the ability to connect with a customer to the top of the funnel. You have the potential to increase the number of customers you can talk to by 2–5x.
Chat With the Customer Directly From the Online Store
When someone walks into your physical store, they can ask you questions, point out products, tell you about what they are looking for, etc., and an employee at the store can help in real time.
How do you provide this same level of service for customers shopping online? By installing an automated on-site live chat.
If you’ve never seen one before, this is what it looks like:
You can personalize the chat experience to send the customer messages based on multiple data points, like their purchase history or what product they are currently looking at.
By using conversational commerce, you can automate conversations about questions, deals, and product discovery, helping the customer throughout their journey.
“But Matt! What if they need to talk to a human?!” Great question my dear reader! In this situation the customer can automatically be connected to a human support agent or directed towards a phone number or email where they can get in touch with a real person to solve more advanced inquiries.
Touch Base With The Customer After They Leave The Store
When a customer adds a product to their cart and then doesn’t complete the purchase, the store can send a private message 1–4 hours later to the customer asking if they would like to complete their purchase or if they have any questions.
By using the Facebook Messenger Checkbox, and an abandoned cart conversational commerce experience, stores have already started increase revenue by 7–25%.
Let The Customer Know That Their Order Has Been Made
Making sure that the customer knows the status of the order is important. After spending money online, customers want to know that the order was made and that it will be shipped soon.
“Virtual employees will likely become essential on the eCommerce front lines as companies scale and become more global, when around-the-clock assistance, multi-language fluency and deep product, pricing, and inventory intelligence will be expected by consumers worldwide, on demand.” — Tomer Tagrin, CEO of Yotpo
By sending customers messages on conversational platforms like Facebook Messenger, you can keep them in the loop and enable them to request future notifications related to their order.
Let The Customer Know That Their Order Has Shipped
Similar to the order confirmation message, the shipping message keeps the customer in the loop and reduces the amount of times they will need to ask a human at the store for the status of their order.
Thank the Customer After Their First Purchase
After a person has completed their first purchase at a store, it is a good idea for the store to send out a personal note thanking them for their business.
“Fundamentally, email is a channel that brings people back to the website or app to complete the user experience. However, chatbots and voicebots present new user flows that can be potentially handled natively. It’s very likely you will be able to complete an order, provide payment or authorization without ever going to the website or app. This is where chatbot and voicebots will go beyond the capabilities of email and make the user experience not only more efficient, but almost magical.” — Joseph Hsieh, Ecommerce Advisor
Doing this over conversational platforms enables the interaction to be more personable and meaningful than over email. Not only does the language sound natural, similar to how a friend or family member would talk to you, but it enables the relationship to immediately strengthen by allowing the customer to continue the conversation.
Confirm With The Customer That Their Package Arrived and Ask For Their Opinion
This message can be sent after the package has been detected as delivered, or an estimated 14 days after an order has been made (depending on which data is available to the store).
Stores can collect data such as:
Satisfaction with the product on a scale of 1 to 5.
Detailed written review of the product.
Pictures or videos of the customer using the product.
Recommend Products Based on Purchase History and Customer Data That’s Been Collected Conversationally
If a customer walks into a store, they can get help from an employee. They can tell them what they are looking for, their preferences, the purpose of the purchase, etc.
Replicating this type of experience online hasn’t been as straightforward, especially over platforms like email.
Conversational commerce makes this very easy. Instead of just getting sent recommendations based on what is trending, stores can message customers questions that enable them to make very precise recommendations.
Help Reorder a Replenishable Product
There are certain types of products that customers will want to purchase over and over again, things like: hand lotion, face cream, food, and paper towels.
Using customer data related to each of these items, it is possible to predict how long it takes someone to consume a good, and then automatically send them a message asking if they need to reorder that item.
This is helpful for the customer and the business.
Troubleshooting
It is common for a customer to have questions about a product they recently purchased.
“Can I wash this in cold water?”
“How do I shoot wide angle video?”
“It won’t turn on, what do I do?”
Instead of requiring a person at the store to manually answer each of these questions, conversational commerce can be used to automatically detect the question and immediately respond with the correct answer or guidance.
Answer a Question
When a person walks into a store to look at a product, they have the ability to ask an employee questions.
“Does this come in a small?”
“Can this camera go underwater?”
“Do you carry red shoes?”
Stores can use conversational commerce to answer this pre-purchase questions.
“[I think virtual employee’s, like chatbots and voicebots will play an important role in the future of ecommerce] because the product questions are usually the same ones over and over, which is a core use case for chatbots.” — Larry Kim, CEO of Mobile Monkey and Columnist at Inc and CNBC
“But Matt! Show me the voice examples!”
Yes, great idea! Let’s do that right now.
Scroll down to see conversational commerce examples for voice platforms.
Examples of Voice Based Conversational Commerce
These are a few examples of voice based conversational commerce. Keep in mind that voice bots cannot currently send customers proactive messages; they can only talk to a user after they have initiated a conversation.
“Personal assistants such as Alexa, Siri, Google and the use of voice will become increasingly popular. Brands need to integrate skills and technologies to stay relevant with customers’ expectations that they can simply ask a personal assistant a question.” — Anju Sharma, Artificial Intelligence Product Manager at HP Inc.
Index of voice based conversational commerce examples:
Deal of the Day
Finding Nearby Stores, Classes, Events, and Rentals
Product Recommendations
Check Order Status
Deal of the Day
Stores can enable their customers to ask Alexa, or another voice bot, to check if there are any current deals that store is offering.
Finding Nearby Stores, Classes, Events, and Rentals
Stores can help their customers locate nearby stores, classes, events, and rentals.
Product Recommendations
By asking the customer a few simple questions, stores can help recommend products that the customer is likely going to be interested in.
Check Order Status
Customers can ask their voice bot to check on their recent order.
Now that you have a pretty good concept of how conversational commerce can be used over chat and voice… let’s dive into something even more interesting.
Let’s look at examples of how artificial intelligence can be used to supercharge conversational commerce.
Let’s do this!
How Artificial Intelligence Can Improve Conversational Commerce
What is artificial intelligence? How can it be used to improve conversational commerce? What are examples of artificial intelligence being used with conversational commerce?
Don’t worry! I will answer these questions right now.
“I think we’ve already seen some forms of machine intelligence have a massive impact on the e-commerce industry. The fact that Stitchfix can form opinions on customer’s preferences without ever meeting them should scare brick and mortar retailers who believe their in-person relationships provide valuable insights to their brands. They do this through scaling the effectiveness of their stylists, but they also do this through proprietary machine intelligence algorithms, that in theory could also begin to inform new product creation in the same way Netflix uses their customer data to seed the ideas behind blockbuster hits.” — Lee Edwards, Former CTO of Teespring
If you already have a good grasp of what artificial intelligence is, or more specifically machine learning, then you can skip this part. If you are new to artificial intelligence, and you’re not exactly sure how it works, then spend the next 9 minutes watching this entertaining and extremely educational video that has over 2 million views:
Definition: Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Artificial intelligence can be used to improve conversational commerce in two categories:
Understanding exactly (or at least very closely) what a customer is saying or asking, and passing this data in the correct format to the bot so that it can respond accurately. (Example: The person says “Do you have dresses in my size that are good for summer?”. The bot can then use artificial intelligence to detect that the person is looking for a “dress”, it can translate “in my size” to the size the store has on file for the customer speaking, and it can look through reviews of the dress to see if sentiment shows that this dress is “good for summer”.)
Predicting what a customer most likely wants to say or do next. (Example: The person just added a pair of shoes to their cart. The bot recommends another product that they will likely also purchase.)
Artificial intelligence is one of the fastest growing fields in technology, and it is expected to improve rapidly over the next ten years.
“AI is going to continue to change ecommerce in a big way. Due to the speed in which AI can react and be detail oriented, you are able to both service customers, as well as market to them in a way that feels one on one, but in a very scalable way. As AI progresses, you will be able to run ads to someone very specifically for example ‘I see that you are traveling to Seattle today. It is currently raining there and I notice you have not purchased a rain coat in a couple of years. Would you like one delivered to your hotel room?’ The experience will be better for both the consumer and the brand.” — Erik Huberman, CEO of Hawke Media
If you feel daunted by the complexities and unfamiliarity of artificial intelligence, don’t worry. Not only is artificial intelligence going to become more advanced, it is going to become integrated into easy to use products that enables departments like customer support, sales, and marketing to apply artificial intelligence to their daily tasks and decisions.
You might even be using artificial intelligence at your business today and you don’t even know it.
But, forget about today! Want to hear what crazy things will be possible in the future?
I’ll tell you all about it right now.
Arnav Kapur from MIT Media Labs showing off his mind reading device, AlterEgo.
The Future of Conversational Commerce
“Matt, if all of this stuff is already happening, what could the future possibly look like? It’s going to be crazy!”. Yes! You are very astute in your observations, the future is going to be crazy.
Here’s what’s happening:
Within the next 10 years, over 80% of people in the world will likely own a personal computer (maybe it’s a smart phone, maybe it’s something else).
Every device will support both text and voice-based bots.
Artificial intelligence will be able to understand and remember everything you say, or ask, no matter how simple or complex. Talking to a computer will be as natural as talking to a human.
You will have a rapport with artificially intelligent entities that you can talk to.
You will be able to see digital interfaces (augmented reality) overlaid on top of the world around you (like looking at someone’s shoes as they walk by and instantly seeing their price as it hovers in space).
Computers will be able to read your mind (and you will be able to read theirs).
Yes, you read that correctly — computers will be able to read your mind. Instead of looking at your phone, or opening your computer, or even asking Alexa something out loud, you will be able to simply think “buy that jacket he’s wearing” as you walk by a stranger with a cool jacket, and the transaction will go through.
This is going to change everything.
The line where you end and the computer starts will disappear; It will be like your conscious being suddenly connected to an internet connection.
You will be able to think directly to a store. “What’s she wearing?”, “How do I wash this?”, “Send me new socks”, “What time is my package arriving today?”, etc.
You should start building the groundworks of your conversational commerce strategy now, because the immediate applications are hugely valuable, and honestly this future technology isn’t that far off.
And you know how I know? Because people have already started to build mind reading devices.
As an example, look at AlterEgo, a mind reading device MIT’s Media Lab.
AlterEgo is a closed-loop, non-invasive, wearable system that allows humans to converse in high-bandwidth natural language with machines, artificial intelligence assistants, services, and other people without any voice — without opening their mouth, and without externally observable movements — simply by vocalizing internally.
How crazy is that?
The world is changing at a rapid pace, and as always the most exciting technology is right around the corner.
The stores of the future will be built on top of these platforms, the jobs of the future will be based on managing them, and this transition has already started.
The only question now, really, is are you going to put in the work to adopt conversational commerce and thrive, or are you going to wait until someone else shows you what success in this field looks like?
Not sure how to implement conversational commerce into your business? Again, don’t worry, I can point you in the right direction.
Let me show you how to start using conversational commerce right now.
How to Implement Conversational Commerce Today
This is no secret, but my team and Ihave spent the past few years building Octane AI, where we have been entirely focused on designing conversational experiences for brands like Kiehl’s and GoPro, and celebrities like Maroon 5, Poppy, and Jason Derulo.
Octane AI on the front page of The New York Times business section.
And guess what? We are focused entirely on conversational commerce, and it’s been working very, very, well.
How well? Let me walk you through it.
Our Conversational Commerce Experiment
During the first four months of 2018 we quietly ran an experiment with 25 up-and-coming ecommerce stores using Shopify. These are stores that individually make $10k to $1mil a month in revenue.
⭐⭐⭐⭐⭐ “OctaneAI is HUGE success! In just 90 days I’ve seen almost 3x as much engagement from my abandoned cart messages compared to my AC emails.” — Sweat Tailor
Here’s What Happened
The 25 stores made over $750,000 in additional revenue from Octane AI’s conversational commerce technology.
Most stores increased their monthly online revenue by 7–25%.
Over 15,000 products were sold as a result of a customer talking to a store’s Octane AI bot.
⭐⭐⭐⭐⭐ “This product is a new sensation for e-com conversion. Incredibly easy to setup and requires no real management. The conversions are 2–3 times higher than we’ve seen in the past on our platform and a no-brainer for any of our future installs.” — Aerosmith Store
The article is written by Matt Schlicht. The content was originally published here
