Most of us have heard of artificial intelligence, but what about augmented intelligence?
Augmented intelligence is not entirely different from artificial intelligence. Rather, think of it as a subcategory of artificial intelligence–the more human-oriented, customizable cousin to A.I. What else should you know about augmented intelligence? It’s changing the way we think about problem-solving and data analysis in industries that range from finance to healthcare to law…giving us more targeted insights, automating menial tasks, and helping us to do a better job at work.
Augmented intelligence is a form of intelligence that complements, rather than replaces, human intelligence. With augmented intelligence, artificial intelligence takes an assistive role to enhance the capabilities and capacities of human intelligence. It’s basically a form of technology that allows human beings to continue taking the lead in decision-making while relying on artificial intelligence to automate tasks that can be done by machine learning.
While it’s trendy to brand technologies as being fueled by A.I., in many cases augmented intelligence actually produces better outcomes. That being said, here are several ways in which augmented intelligence is being used to improve insights, creative output, customer service, security, and more.
Augmented intelligence can be used to perform advanced data analysis for a range of industries. For example, it might be used for fraud detection in the banking or finance industry; finance and accounting; preventative healthcare; or customer survey feedback.
In the example of fraud detection, systems can be wired to detect signs of fraud, which are delivered to employees who assess red flags and then make judgment calls. In fact, according to a 2016 study, the use of automated intelligence saves card issuers and banks $12 billion every year.
In finance and accounting, automated intelligence can be used to generate accurate reports that can then be customized and sorted out by an accountant for a given client. While A.I. has performed the hard labor of sifting through massive amounts of data, the accountant still uses skills of creative analysis and organization to deliver results.
Augmented intelligence may be used in the area of healthcare by applying artificial intelligence to a person’s DNA to identify potential health risks, and then relying on a doctor’s expertise and knowledge to make recommendations to the patient for preventing future illness.
As for customer feedback surveys, augmented intelligence can be applied to analyze large quantities of open-ended feedback to deliver business owners actionable insights into how their customers are responding to their product or service.
The result is an analysis that’s spot-on and actionable.
There are certain aspects of creativity that cannot be replicated by a machine–yet. But there are also certain types of productive tasks that can be performed by artificial intelligence, such as some kinds of technical writing and legal documentation like contract creation, divorce proceedings, and legal discovery. Humans still remain at the center of the decision-making process surrounding the text, but artificial intelligence produces copy based on certain algorithms.
Augmented intelligence helps sales teams make smarter decisions and increase productivity by using artificial intelligence to generate sales forecasts based on past deals. The result is that sales representatives are able to make wiser decisions about who to approach–dramatically reducing lost time and money on pushing sales that never close.
Ultimately, there is a potentially innumerable amount of applications and usages for augmented intelligence. As human beings continue to create and innovate using artificial intelligence, you can bet that augmented intelligence will take surprising new forms to make life easier and work better.
Regardless of which industry you work in, augmented intelligence applies to your business.
How?
One of the most powerful usages for augmented intelligence is for analyzing customer feedback and delivering actionable insights for business owners to improve customer satisfaction, Net Promoter Score (NPS), and other metrics.
In other words, automated intelligence can help business owners and entrepreneurs to understand what their customers want, what makes them recommend their product to a friend or family member, and why customers remain loyal 🙂 (or lose interest 🙁 ).
While artificial intelligence can offer some help in this area, automated intelligence vastly improves on the exclusive use of artificial intelligence to analyze feedback. Analysis that is fully automated lacks interpretability…and in many cases, offers results that aren’t actionable. For example, artificial intelligence may identify patterns of keywords from feedback like “happy” and “like,” but it doesn’t provide in-depth insight that business owners can use to actually improve their product or service.
On the other hand, automated intelligence offers a superior solution to analyze open-ended feedback gathered in customer surveys. Augmented intelligence automates repetitive tasks (such as categorization of customer feedback and natural language processing), and relies on human intelligence to set up a system and set of categories that make sense for a given brand or company.
Caplena offers an augmented intelligence tool that’s able to analyze open-ended feedback at scale while allowing owners to identify specific metrics on which they want to focus. It keeps business owners at the center of the process by allowing them to define what it is they want to track, and what sort of specific insights they are looking for. It performs the “heavy lifting” aspect of analysis, while still offering detailed, actionable insights for business owners.
The result is that business owners reduce the effort of analysis by 35%-70%, and are able to implement feedback in order to improve their product or service and boost customer satisfaction.
Most business owners are well aware that open-ended feedback provides invaluable insight into helping them improve their product or service, boost user satisfaction, and even expand their customer base. But analyzing this useful information requires a significant amount of organization, protocol, and follow-up – The first step of which is creating customer feedback categories for feedback analysis.
Automatically assigning open-ended feedback into predetermined categories makes the analysis of this information that much simpler. It gives business owners and analysts immediate insight into what needs to be tweaked, refined, added, or tossed out. When it comes to feedback analysis, categories are king.
But with all of the options for categorizing a potentially infinite variety of answers, how do you choose the right categories? How specifically do you need to be? Or, should you keep categories broad and general? You can do this manually or you can take advantage of customer feedback tools that use machine learning to effectively categorize your data.
If you decide to manually categorize the feedback, one general rule is to establish a positive/negative “version” of each category – This tactic gives you immediate insight into whether customers are happy or unhappy with a specific aspect of your product or service. This is known as sentiment analysis.
Here are 10 feedback categories that can help give business owners and analysts valuable insight:
Whether you want to admit it or not, your customer service has a significant impact on how happy (or unhappy) your customers are with your business. This being the case, a general “Customer Service” category with subcategories is essential to any brand’s customer feedback framework. These can include:
Depending on what your product or service entails, your customer service categories will vary. For example, if you run a travel website, your customer service will most likely be dealing with customers who are experiencing glitches with your site. Or, if you sell a mail-order health supplement, you may be talking to those who are experiencing package delays. In any case, think through the specifics of what you might encounter in feedback when determining subcategories for customer service.
Pricing is fairly straightforward. Your customers – or potential customers – will either think your product is fairly priced or overly expensive. That being said, there may be exceptional cases where customers think that you could be charging more for your product or service – and they’re not afraid to say it. But in general, you can stick with two categories: “Fair pricing / cheap” or “Too expensive.”
The overall perception of your brand is related to your overall customer satisfaction. If a survey taker gives a fairly general answer to your open-ended question such as “I love _,” this answer will be allotted to a subcategory: “Positive Experience.” On the other hand, if a survey taker quickly dismisses your product or service – “Not worth the money,” or “Terrible” (Of course, we hope you never get feedback like this!) – this type of answer will be assigned to the subcategory, “Negative Experience.”
Finally, you’ll probably want to include a catch-all “Other” category that accounts for exceptional feedback – a random insight, opinion, or thought that may not fit into any other predetermined category.
If you run a paid subscription service, survey takers will most likely offer commentary and insight into your billing process. Similarly to pricing, billing will most likely be fairly straightforward. Either your survey takers have a positive perception (“Billing fair/positive”) or a negative perception (“Billing unfair/negative”).
Paid subscription services usually offer users a tool or technological application to make life easier and more efficient. “Usability” applies to services that are used on a frequent basis – Think a phone, website, or application. Subcategories under usability may include:
If you sell an item that your customers wear, eat, apply, take or use for their household, they may very likely comment on quality. Of course, depending on the type of product you sell, subcategories for quality will range dramatically:
If you sell clothing, decorative items, or even electronics, your customers will be commenting on overall look and appearance – especially if you’re an online retailer. Try including subcategories that involve accuracy: “Accurately presented, true to image/positive” or “Inaccurately presented/negative.”
Market research agencies will use customer surveys in a different way than traditional businesses: By gathering open-ended feedback from a target audience, they are gaining valuable insight into a market for other brands or businesses.
Market research typically involves identifying a specific market: a demographic of users, customers, or clients in a given industry. Although you may use multiple choice questions to identify the details such as the income or age of your survey takers, your open-ended feedback may also include information about preferences or lifestyle habits.
For example, if you are performing research for a food/beverage company, you may want to include subcategories, such as “Active lifestyle/fit” or “Trying to lose weight.”
Your open-ended question may ask a survey taker about what kinds of problems or challenges they face. Depending on what kind of market you’re researching, include subcategories that account for a range of responses. Here are a few examples:
Of course, there will be a wide variety of subcategories for market researchers. The important thing is that you’re able to gather valuable, actionable feedback for your clients, and only a strategic framework of customer feedback categories can help you achieve that.
For example, your HR department will be interested in open-ended feedback involving customer satisfaction. Your tech/IR department will want to know what users think about functionality and usability. In any case, customer feedback categories make it easy to deliver this information – and make insights from feedback immediately actionable.
Using a combination of human intelligence and artificial intelligence, Caplena provides an instantaneous annotation to help you quickly and easily categorize your feedback into categories of your choice. To facilitate the
Artificial intelligence (A.I.) has been around for decades (since the 1950s to be exact) but has more recently emerged as a technology with seemingly unlimited capabilities. While A.I. was considered more of a science fiction-type fantasy in the past, it’s now being used as a powerful tool for increasing efficiency, automating complex tasks, and making space for innovative new technologies in fields ranging from business to education to healthcare. One of the most widely-used – and exciting – types of A.I. for business usage is Natural Language Processing (NLP). Learn more about the latest A.I. advancements here.
NLP helps computers understand and process human language, which has powerful implications for businesses that want to offer increased communication with customers and clients without the high cost of hiring additional staff. Ever chatted to a chatbot online? Chatbots can answer your questions and offer help because they rely on NLP to evaluate natural human language.
You might tell a chatbot, “I love your product, but I feel that it’s a little pricey.” NLP will take this answer – and similar answers – and process it into feedback to let owners know that there is a high level of satisfaction with the product, but a low level of satisfaction with the price.
NLP is also used for processing verbal language; speech to text capabilities on your smartphone; and even social media analytics.
However, A.I. – and NLP – aren’t perfect solutions for processing valuable information.
There are some tasks that can’t be replicated by a machine. For example, advanced customization, abstract thinking, and some types of complex problem-solving cannot always be effectively performed by a machine.
Businesses who want to use NLP to process customer feedback will find that this type of A.I. has limitations.
When it comes to processing feedback, categorization is king. Categorization helps to efficiently organize feedback into categories like “Customer Service,” “Price,” “Ease of Use,” and “Features.”
Then, categories may be divided into subcategories. For example, you might find “Good support/positive,” “Bad support/negative,” “Fast/efficient,” “Long waiting time,” and “Friendly/nice,” all under “Customer Service.”
Categories are key to producing actionable insights on top of rating questions, such as CSAT score (customer satisfaction), net promoter score (NPS), how customers are responding to specific features, and why some customers may be unhappy with the product or service.
Mutually exclusive and collectively exhaustive (MECE) categories are often used by management consulting firms to help problem solve. The basic premise is that to effectively fix a problem, all potential solutions must be able to fit into only one category (mutually exclusive); and, all solutions must fit into a category (mutually exhaustive).
The goal of MECE categories is to eliminate confusion and help pinpoint actionable solutions. The ultimate result is that problem-solvers are better able to hone in on a solution that will fix the problem.
While this is a specific application of MECE, this problem-solving framework is also an efficient and effective approach to any type of organization, including that of customer feedback. It helps reduce duplication that could potentially warp metrics, and it assigns every piece of feedback into a category, making it actionable.
Unfortunately, NLP cannot perform MECE organization on its own. MECE requires human intelligence to design a framework of categories that will factor in all possible results and ensure that each result has a mutually exclusive “home.”
Another key to efficient categorization is customization. Each business may have a unique set of feedback categories that are best suited to its product, service, or type of insight that it’s looking to gain.
For example, most businesses will have feedback categories that apply to satisfaction with customer service or pricing – but some products or services may require additional categories. For example, a time-tracking app will need a unique set of categories that help process customer feedback on its ability to deliver accurate reports. A budgeting app will require categories that help process feedback on how accurately it categorizes purchases, and so forth.
NLP can customize categories to a certain extent – but still cannot match human intelligence in terms of creative, insightful customization that will allow owners and analysts to get the most out of customer feedback.
Customers may surprise us with “creative” answers they give to otherwise straightforward questions. For example, they may bring up an entirely new issue that hasn’t been addressed by any customer in the past.
In the case of open-ended questions (which should always be used for high-quality customer feedback), customers may provide feedback that doesn’t fit into a designated category – and could potentially be handled incorrectly by NLP.
Human intelligence is sometimes required to help organize unique feedback that doesn’t otherwise easily fit into a category.
Ultimately, businesses that rely exclusively on NLP will miss out on some of the most valuable outcomes of gathering feedback – such as deep customer insights and accurate metrics (like CSAT and NPS).
And yet, NLP is still highly useful and efficient, and well worth investing in. Relying on the power of A.I., it helps to automate many of the aspects of processing customer feedback, which helps businesses to save valuable time, money, and energy that can be used on other tasks.
Business owners are left with a conundrum:
Good news: There is a solution.
Augmented intelligence combines artificial intelligence with human intelligence to get the maximum benefits of both: The speedy, automated capabilities of A.I. with the creative, conscious, and even emotional abilities of human intelligence.
In terms of processing customer feedback, businesses that want to use NLP to gather feedback on their websites can still do so. But by relying on augmented intelligence to organize and process this feedback, they’ll get a deeper level of actionable insight into what their customers think, need, and want from their product or service.
Caplena makes this achievable by helping business owners and entrepreneurs to get the “best of both worlds.” Caplena uses augmented intelligence to perform customized categorization and high-level processing of open-ended feedback – allowing owners and analysts to problem-solve, improve their product or service and increase overall customer satisfaction.
Augmented intelligence also has exciting potential to “fill in the gaps” left by artificial intelligence in other industries, such as education and healthcare. For example, augmented intelligence might be used in education to give teachers insights into their student’s learning behaviors and capabilities; but, it won’t necessarily replace the teacher. It simply makes the teaching and learning process more efficient.
Ultimately, augmented intelligence is a more effective approach across multiple industries. While artificial intelligence is an exciting solution that offers increased efficiency and speed, it’s even better when it’s used in conjunction with human capabilities.
And by “better,” we mean a combined approach that produces more useful, cost-effective results, and ultimately progresses towards improved education, more effective healthcare, or a better product or service.
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Even in an age of digital addiction, social media ads, and geo-targeting, word-of-mouth marketing is still one of the most powerful forms of marketing. Your customers – both the happy ones and the unhappy ones – have an enormous amount of leverage when it comes to your brand’s reputation. What they tell other people about your product or service has the ability to expand your business quickly or destroy new growth. That’s why it’s so important to measure NPS (Net Promoter Score) – a metric that shows you not how satisfied your customers are, but how likely they are to promote (or detract from) your business.
Many people confuse NPS with CSAT – customer satisfaction score. While both metrics focus on customer experience, NPS measures a customer’s loyalty to your brand…not their satisfaction with a specific product or service. So, while CSAT can give insight into how happy a customer is with a product, NPS can give you a “bigger picture” idea of how your customer base perceives your business.
While a positive NPS can certainly be an encouraging sign of growth and a good indicator that you’re doing the right thing, a negative NPS is perhaps even more helpful. That’s because if your brand has an unusually high number of detractors, your brand is going to suffer. Think of it this way: One negative review can discourage potentially hundreds of customers, while it takes multiple positive reviews to persuade a prospect that your product or service is worth purchasing. Human sentiment plays a key role in your business.
If you find that you have multiple “detractors” through measuring NPS, don’t throw in the towel just yet. Instead, consider the feedback analysis as actionable advice on improving your customer experience and increasing your promoters.
If you provide an open-ended question (and you should), you’ll be able to understand why a customer is unhappy…and take steps to correct it.
If you’re just getting started on measuring and utilizing this key metric, don’t be intimidated. Here are five simple steps to give you a good start on understanding your NPS and using it to improve the perception of your brand.
The first step to gathering NPS is integrating a customer survey into the user experience.
Ideally, a customer survey will be displayed on your website in a floater or chatbox. You may also choose to link out to a customer survey through a targeted email campaign to current or former customers.
In any case, be strategic about targeting customers who will provide real insight into the overall perception of your business. NPS can be gathered on a transactional basis (e.g. after contact with customer service) or on a recurring basis, such as focusing on a sample of new customers or high-value customers every month.
When you make your “ask,” be clear, friendly, and warm in your copy. Remember, gathering NPS is also a valuable opportunity to build a relationship with your customers – both the promoters and detractors. You might say “Hi! Got a minute?” or “Tell us how we’re doing.” Then you can ask, “On a scale of 0 -10, how likely are you to recommend us to friends or family?”
You might also consider offering a free incentive (such as a downloadable resource or coupon code), motivating customers to engage with your survey.
Lastly, you’ll want to include an open-ended question in your survey to give respondents the opportunity to explain their rating – either positive, negative, or neutral 😐.
When you have a sufficient number of respondents, categorize them into three basic groups: Promoters; detractors; and neutrals.
Promoters are your most enthusiastic advocates. They are the customers who have given you a 9 or a 10. Those who rated you a 7 or an 8 are neutral. They might recommend you but aren’t likely to actively promote your product or service. Anyone who rates you less than a 7 is a detractor. For whatever reason (and you’ll want to give them a chance to explain), they are unlikely to give you a positive review to friends and family. In fact, they may even be vocal about criticizing your business or sharing a negative experience.
While there are a number of different ways to calculate NPS, the simplest strategy is to calculate the total percentage of promoters and the total percentage of detractors. Then, subtract the percentage of detractors from the percentage of promoters.
% of promoters - % of detractors = NPS
If you have equal amounts of promoters and detractors, your NPS will be zero. By industry standards, anything above zero is considered okay. But as pointed out above, a single detractor may have far more influence than a single promoter – meaning you’ll want to aim at a customer base that’s not “balanced” but that has far more promoters than detractors.
NPS between 0 and 50 indicates that you are doing a decent job at fostering customer loyalty, and an NPS of 50 or above means that you are performing exceptionally well.
For example, if you have 75% promoters and 15% detractors (the remaining 10% are neutral), then you have an NPS of 60, which is a good indicator that your product or service has a loyal following.
If your NPS is above 70, you’re doing fantastic. This indicates that at a bare minimum, 70% of your customer base would count themselves as promoters of your brand. In any case, be consistent with how you measure and analyze NPS, which will allow you to accurately compare different iterations of this metric over time…and see how your score is improving (or deteriorating).
Now that you’ve calculated your NPS, you’ll want to analyze your open-ended feedback to explore the “why” behind your score.
If your score falls at zero or below, this step is especially critical to identifying why a substantial portion of your customers is unhappy. For example, you may notice a trend of dissatisfaction with customer service, which can significantly affect your score.
If your NPS falls above 50, congratulations! You’re doing a great job. Still, you’re going to want to take a look at customer feedback – even from your diehard fans – to see why it is they adore you.
Using a customer feedback tool can significantly elevate the quality and depth of your insight in this process. Caplena will automatically categorize and tag feedback, giving you deeper insight into NPS and allowing further driver analysis – helping you to identify the outcomes of certain aspects of your brand on customer loyalty.
Lastly, every member of your team should know your NPS along with actionable feedback points shared by both promoters and detractors. Regardless of the department, their work has an impact on your customers’ perception of your brand.
Create a special report or draw up a quick presentation to communicate NPS. Or, you can keep it simple and send out an email or notification on your project management system.
Regardless of how you choose to communicate this valuable information, include a plan to take actionable steps to either leverage or improve your NPS.
The bottom line is that NPS is a valuable, actionable metric that should never be overlooked in terms of impact. Customer loyalty has an enormous influence on retention and growth rates. It can make the difference between a product or service that becomes a breakthrough success, and one that fails.
The goal is to encourage an NPS that indicates that your customers are enthusiastically endorsing you and generating new referrals and leads that can help your brand grow quickly. This organically improves your reputation and boosts your profits.