For any business to strive towards success, be it a startup or a corporate giant the likes of Amazon, providing exemplary customer experience is key. Modern businesses have realized this and have started figuring out efficient approaches to provide responsive, interactive, and engaging customer services. One bad interaction jeopardizes the company’s growth in more ways than one.

Among all the various customer services approaches adopted by businesses, the most intriguing and evidently successful approach is the use of chatbots – AI-powered programs that can mimic human conversations and allow brands to build their presence across messaging apps that are widely used by the target user base.  

According to Gartner, a quarter of the world’s customer service operations would be managed by virtual customer assistants aka chatbots by 2020.

Irrespective of the industry, renowned brands including Starbucks, The Wall Street Journal, Pizza Hut, Spotify etc. have already started investing in chatbots so as to enhance customer experience.

That said, here are a few ways how chatbots can help businesses improve customer experience.

Always available

Unlike human customer service executives, a chatbot is available 24/7 to address, resolve, or forward customer queries. A chatbot can serve multiple customers simultaneously. One primary use of the chatbot on a website is that it can help guide potential customers deeper into the sales funnel.

For instance, if a visitor to your website is interested in purchasing a specific product or service provided they get answers to some questions related to that product/service, a chatbot can be of assistance. It can act as a company representative and provide the visitor with the details he/she needs to go ahead with the purchase.

Provide personalized experience

If the customers are made aware that the business is personally seeing to their needs and requirements, they’d obviously trust the business more. Chatbots can provide such an experience by tracking customers’ buying habits and analyzing their purchase histories to grant them with offers they can’t easily refuse. This makes an online purchase much more convenient to customers. Trust and convenience are the basis of loyalty. So, in essence, an efficient chatbot can give businesses loyal customers.

Millennial-friendly interface

Millennials make up a good majority of the world’s population, and are the main demographic cohort that modern businesses target. Millennials are very social compared to the previous generations, and tend to use messaging apps and other digital media to share their views and opinions on almost everything. They also enjoy chatting with friends and acquaintances via messaging apps.

With an efficient chatbot deployed on such messaging apps and voice-based platforms, a conversation with a chatbot would seem casual to Millennials. And if they loved the experience, they’d let it be known via their social media accounts.

Simple transactions

Certain chatbots are capable of performing certain specific actions that aren’t complex in nature – like booking movie tickets or hotel rooms, money transfers, compare products etc. Various eCommerce sites use chatbots to serve customers who want to know the status of their orders or track order deliveries.

Conclusion

Chatbots may have seemed like a luxury once. But they are a necessity now for businesses who aim to improve customer experience and grow without problems. Depending on how creatively they are used, chatbots can do wonders for a business. Though getting the right chatbot for your business can be a challenge, it’s nevertheless a good investment considering how chatbots are trending at present.

Let the professionals at AOT build one for you. Get in touch with us if you are interested.

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Machine learning, once thought of us as highly complicated, is now a core component of modern-day analytics applications that greatly influence the growth and success of organizations. The technology isn’t new of course. It has been around for a while, and can be considered as an offspring of predictive analytics.

Machine learning learns from data, recognizes patterns, and improves behavior all without being specifically programmed to do so. However, only recently did businesses start seeing the variety of applications of the much-neglected technology.

One fine example is how American entertainment company, Netflix saved $1 billion last year thanks to its machine learning algorithm which recommends personalized content to users. Strategy Analytics’ report provides another testament to the present-day influence of artificial intelligence including ML, finding that 41% of consumers believe AI will make their lives better.

And apparently AI, or rather Machine Learning, is indeed making their lives better by improving their experience when using applications through improved personalization, enhanced visuals, better decision support, and from even optimization through analytics just to name a few.

That said, let’s take a deeper look at the impact of machine learning on customer experience.

Personalization with machine learning

Customer behavior is dynamic. It keeps changing overtime. Today, customers rely a lot on websites and applications to serve many of their needs. This reliance shifted their behavior to preferring personalized services with quick results. Such amounts of personalization is what marketers leverage for rapid business growth and maximum profit.

This is where machine learning comes into play. But for machine learning to deliver desired results, it requires huge amounts of data. This is not a hiccup either, as ML can be fed incredible amount of data from several sources including telematics, geolocation beacons, social media, and even the Internet of Things (IoT).

This allows the ML algorithm to provide insights on customer preferences, so marketers can engage them on their terms. On the other hand, customers get tailored services and great offers based on their past purchase behavior instead of irrelevant or non-contextual offers they used to receive back in the day.

Improving the quality of digital assets

Machine learning technology is now strong enough to identify objects as well – both real and digital. The latter is now a common application, where ML algorithms improve the quality of an organization’s digital assets making them visually appealing to online visitors and customers.

A case in point is what Twitter did with their ‘Magic Pony’. Twitter’s technology utilized machine learning to sharpen pixelated images, enhance the quality of videos recorded on mobile devices etc. The feature not only impressed customers, but also provided Twitter with additional benefits of lower data usage which subsequently improves the platform’s streaming ability.

Better decision support

Machine learning grants ‘foresight’, though limited, to marketers. For instance, the algorithm can analyze customer behavior using data from various sources to predict the next course of their action while using a business application or website. There are several analytics tools available now in the market that can predict many things provided there is enough data to feed them with.

The most common application of this particular feature is what we see as ‘proactive’ product/service recommendations in many apps we use. The algorithm learns the interests of a particular user, and later determines the right opportunity to recommend appropriate products and services that fit the customer’s profile.

This technology can be integrated with other systems to provide automatic delivery as well. There are smart refrigerators now that can detect whether a particular item stored is running out of stock, and contact the vendor connected to the system for resupply – all automatic. The future is now.

NLP and speech recognition

One of the most revolutionary ways in which humans can interact with machines today is through speech. With speech recognition technology, computers can now take actions by recognizing human speech, presenting a plethora of new possibilities.

Speech recognition isn’t a new technology as well, but it’s grown much more refined and accurate thanks to the application of machine learning technologies. A testament to this is Google’s Cloud Speech API which can recognize over 80 languages and variants now with high accuracy.

Marketers, on the other hand, can now efficiently leverage linguistic data to create much more engaging, targeted content. This also counts as personalization from a customer’s perspective. For the business, an ML-powered machine capable of natural language processing gives them a wealth of data and insights to intuitively connect with audiences, and build relationships faster.

Optimization with augmented analytics

Businesses now employ powerful analytics to sift through ridiculous amounts of data so as to streamline their operations, deliver better, more efficient business models, and offer services/products that meet customer demands. The fact of the matter is that those powerful analytics are powerful because of machine learning.

The insights a business can get with analytics augmented by ML can also predict likely moves of competitors. Augmented analytics now has a significant role in the financial sector where gradient-boosted ML algorithms are used for a variety of purposes – from predicting the probability of achieving top ranks in aggregator portals to cancellation rates on policies.

The common factor of most of these applications is that they all ultimately tie into customer satisfaction. Credit card companies can use such algorithms and analytics to attract the right type of customers for the right kinds of products.

Conclusion

The technology is fragmented and still in its infancy. Despite this, the proliferation of big data and the advent of cloud-based subscription models demand the presence of a solution that combines powerful machine learning algorithms and frameworks while making use of vast libraries to deliver better deals to customers.

The ecosystem is rapidly growing and becoming more affordable as time passes. Thanks to the cloud, the technology which was once affordable only to big companies with vast resources is now open to the masses – from startups to even freelancers. It’s brought forth many new trends in marketing with strong focus on customers’ true context all to serve them better.

If you haven’t leveraged machine learning technology yet for your business, be prepared for a rude awakening very soon. The world is moving and business ecosystems dynamically evolve. It’s high time to utilize powerful technologies that facilitate rapid business growth and grant you an edge among competition. AoT technologies can help you get there. We have a successful track record when it comes to developing robust solutions powered by cutting-edge technologies including AI and ML. Drop us a message, and explore a new world of possibilities for your business with us.

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