To understand how chat-bot integration can influence traffic conversions, we first should know whatchatbot integration is.
A chatbot is also known as the talk bots, chatterbots, IM Bots, interactive agents are the computer programs conducting the conversation via auditory methods or the contextual methods. Such programs are specially designed to simulate how a person would behave as a conversational partner, thereby passing the Turing test.
Mostly the chatbots are used in dialog systems for various practical purposes which include customer services and information acquisition. Some Chatterbots use genetic programming language systems, but many systems scan the keywords within the input and reply is being given with the matching keywords, using similar patterns from the database.
Similar to other applications, chatbots to need integration. Chatbots are integrated with the channels, the intelligence providing systems and backend systems and chatbots also offloads the usage of information for more improvements and the determination of the knowledge.
`Let us now go through the details of each integration part and considerations that should be made during the design of a Chatbot.
Chat-bot Integration with channels initially is about the job of acting as a funnel for multiple devices, all communicating with the chatbot engine. As human interaction is a just a fraction of the speed of the capability of the engine to process the conversation, we need a more contemporary chatbot integration model that doesn’t tie up resources such as threads for every stream of interaction such as the models that Kafka and Node.js currently support.
While funneling or pipelining these dialogues the chatbot integration needs to ensure at least that the communication is identifiable, contextual, and should also capture other contextual information that might help the conversation; e.g.: determining the location of the conversation origin in terms of geography (e.g. GPS on a mobile phone, fixed connections IP-based information can help).
The original context of an identifiable endpoint is critical for the engine to retrieve the prior context than to understand the latest communication through the chatbots. As we are funneling the discussion, the background is required to allow the middleware to grab the response of the engine and route it back to the appropriate recipient.
Most of this functionality can be found in chatbot adapters and frameworks such as those provided by the likes of Facebook’s Messenger chatbot, but if you want to incorporate a chatbot into your application, then this is something that needs to be considered.
This now brings us to the next aspect of the Channel integration. As we eventually progress through the maturity model integration can support multiple sources of conversations, for example, Twitter, Facebook, and WhatsApp as far as the engine is concerned, these solutions are not at all different.
Chatbots are really of value if the conversation is actionable; without it, you only end up having something that can take on the Turing Test. To be actionable, you need logic. To achieve the thesis, you’re best using a middleware tier to help provide decoupling.
Ideally, to achieve the best decoupling, we can work through an API layer with APIs that are previously standardized so that they can completely mask the implementation(s). It would be very reasonable to suggest that the most successful chatbots are those that can work with standardized APIs across multiple services. So, we have seen the tech side of chatbot integration. Let us now discuss various applications of chatbot integration.
Benefits of chatbots in customer service
The key to increasing customer loyalty and sales is by improving your customer’s experience. Now let us see how we can increase customer loyalty using chatbot integration.
Customers are growing smarter today than they were a few years ago, and they expect you to be up to date at your communications with them.
Gartner predicts that by 2020, a customer can manage 85 percent of the relationship with a business firm without interacting with humans, and hence, the increased demand and adoption of self-help service. This means chatbots are the future of customer services.
Chatbots are self-help tools for improving communications. Brands can use it to enhance their customer’s experience, to generate more sales and build a deeper rapport with customers.
They allow your customers to interact with your brand through simulated conversations easily.
Chatbots Provide a Quick Response to Users
It’s very frustrating when businesses tell you that it might take several business days to resolve a simple issue. And most of the time, you don’t even get a reply. The users might become discouraged if they don’t get timely responses for their queries, and this is not so good for the business. Chatbots come handy in this kind of scenario which manages to give quick replies in most of the cases.
Any customers would want an immediate response to their queries. They prefer to handle challenges on their own until they’re no longer able to do it. Then only will they require assistance from a live chat agent.
At least, customers will be happy to receive a formal welcome message from a chatbot telling them the exact time they may receive solutions to their challenges.
In most cases, the chatbot can refer the customer to the Frequently Asked Questions page where they can find tips and tricks to help them solve their problem as quickly as possible.
Chatbots Create Engagement
Chatbots are the future of brand engagement. Engaged customers are more likely to convert into your consumers. For example, on your Facebook’s messenger app, a chatbot can start a conversation to promote an update or offer to your customers about your new products.
In the conversation, you might ask for product information, coupon codes, or just about anything regarding the product. Customers can get exciting offers that will stimulate them to click through to your checkout page.
In the 2016 F8 Conference, Facebook announced that businesses would start using Facebook’s Messenger app to sell and buy products and offer customers support. In that conference, Mark Zuckerberg said, “We think you should message a business firm just the way you would message a close friend.”
Chatbots can make life a lot easier for brands. Most of the customers are excited to engage with robots( chatbots may be), especially when they show a sense of humor or a personality that’s very much similar to a real human being.
When you program your chatbot well enough, it can respond to your customer’s messages instantly using your brand’s voice.
Bots Can Help You Save Cost on Customer Service
A single chatbot can perform the tasks of several persons within no time. So, we can say that chatbots are very much cost-effective and should be employed in various firms ranging from huge MNCs to budding startups.
While chatbots can’t wholly replace customer service agents, it can considerably save you money since you don’t have to employ any number of customer service executives to manage your customers’ queries.
The new research, “Chatbots: e-commerce, retail, Banking & Healthcare 2017–2022,” found that bots will save business firms more than $8 billion per year by 2025, which is a considerable rise from the $20 million expected in 2017.
Businesses Use Chatbots to Handle Relatively Easy Tasks
Complex queries that need serious analysis are not for chatbots. Using bots to answer simple questions and engaging customers with offers may be useful.
Chatbots are Good, But They Can’t Replace Humans Completely
Suppose a customer who wants to change her/his logs, passwords into your website and next, the bot shows up: “Do you need help with anything?” and you reply “Yes, I want my password changed.”
Then chatbot will grab the same information and provides you the step-by-step process for changing your password successfully. Simple questions like that are pretty much right for chatbots.
Chatbots Allow Brands to Offer 24*365 Customer Service Support
Customers are content to get the details they need when they need it. But a customer care representative will most likely not be present all the time in person.
That’s where exactly chatbots come in handy. A chatbot is always present and very active at every time of the day ready to be engaged.
It’s exciting because your customers no longer need to wait for “several business days” before their queries can be resolved.
Unsatisfied Customers may not return to the brand
Studies have shown that 91 percent of dissatisfied customers will not willingly do business with you again.
Chatbots can afford to keep your customers satisfied, give them the best services. And most importantly, there will always be an option to call a real person if you aren’t getting the answers you demand.
Chatbots can Reduce Human Error.
One of the main reasons we use chatbots is because we want to have time for other things while we allow something/someone else to do our less complicated works for us. Can we trust chatbots with this task? Of course, we can.
Sometimes we may forget some things, but chatbots never forget.
Chatbots are specially designed to have access to enormous information that can help them answer your customer’s queries accurately.
Tips for building a successful chatbot:-
Don’t forget to give your customers an alternative means of communication: Sometimes, chatbots can be annoying. Everyone hates unintelligent chatbots. So before employing a chatbot, ensure you feed your chatbot with lots of information then provide an option to chat or call with a human. Customers will be very much happy to speak with a customer care representative when the chatbot is not answering their queries as expected.
Avatars Add Emotions: Using AI avatars can add a human touch to your chatbot. You can create a fictional character of a real person and use it as your chatbot avatar.
Provide Options for Efficiency:Chatbots are not yet fully efficient as they are still in their early development stages. It’s a good idea to create options for efficiency by adding possible answers to a particular question that the bot doesn’t fully understand.
Creating a chatbot for a website using python and .net
Before going into details about how chatbot integration can influence traffic engagement and conversions, let us see how we can build a chatbot for a website using python and how to create a chatbot in .net
Chatbots are nothing but software systems created to interact with humans through chat. The first generation chatbots were able to create simple conversations based on a comparatively complex system of rules. The limits of these first-generation systems have been overcome by present chatbots that use Artificial Intelfirst-generation license and machine learning to interpret the intention of their interlocutor.
Bots can help in many practical cases and drastically reduce management costs. Many examples have become well-known successful use cases. For instance, retailer H&M utilizes them to guide users through their purchase process on their site. In general, many customer support systems use chatbots to achieve operational efficiency, including answering common queries or helping users solve repetitive/redundant tasks.
So, in order to build a chatbot, we first need to know how a chatbot works.
Chatbots are of two variants: Rule-Based and Self-learning.
In the Rule-based approach, a chatbot answers questions based on some rules on which it is trained on. The regulations defined can be very simple or very complex even. The chatbots can handle simple queries in most of the cases but fail to manage complex queries.
Self-learning chatbots are the ones that use some Machine Learning approaches and are more efficient and accurate than rule-based bots. Self-learning bots can be of further two types: Generative or Retrieval-based.
(i) In retrieval-based models, a bot uses some heuristic to select a response from the libraries of predefined answers. The chatbot uses the context of the conversation for choosing the best suitable response from a predefined list of bot messages.
The context may include a current position in the dialogue tree, all previous conversations, previously saved variables. Heuristics for selecting a reply can be engineered in a lot of ways, from rule-based if-else conditional logic to machine learning classifiers.
(ii) Generative chatbots can generate the answers and not always replies with one of the responses from a set of solutions. This can make them more intelligent as they take word by word from the queries and generates the solutions.
Now, to build a chatbot using python or .net, we need to have some pre-requisites. Like Hands-On knowledge of scikit library and NLTK is assumed. We also need to know about NLP( Native language processing using Python or .net).
Native language processing using Python or .net
The field of study that primarily concentrates on the interactions between computers and human language is called Natural Language Processing, or NLP. It stands at the intersection of artificial intelligence, computer science, and computational linguistics. NLP is a way for machines to understand, analyze, and derive meaning from human dialogues in an intelligent and useful way. By utilizing Native Language Processing, the developers can organize and structure knowledge to perform some tasks such as automatic translation, summarization, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation.
Natural Language Toolkit(NLTK)
Natural Language Toolkit(NLTK) is a leading online platform for building Python programs to work with human language and data. It provides easily usable interfaces to over 50 corpora and lexical resources like WordNet, along with a suite of text processing libraries for tokenizing, classification, stemming, tagging, semantic reasoning, and parsing, wrappers for industrial-strength Native Language Processing(NLP) libraries.
Natural Language ToolKit has been called “an excellent tool for working and teaching in, computational linguistics using Python,” and “an exceptional library to play with natural language.”
NLP provides a practical introduction to programming for language processing. I highly recommend this book to people beginning in NLP with Python.
So, without going too much technical, if you want to build a chatbot using Python or .net, I recommend you to get a basic understanding of NLP and NLTK and thereafter, everything is a cakewalk for you to create a chatbot.
How chatbot integration can influence traffic engagement and conversions
So far, we have seen what is meant by chatbot integration and the benefits of chatbot integration in customer service. Now we will see how chatbot integration actually benefits traffic engagements and conversions and we will also see various useful chatbot platforms that help you drive traffic and increase conversions.
The leads for a website to drive traffic usually come via ads or organic search which lack the targeted focus necessary to improve the likelihood of a sale. Thus, most marketing agencies still consider referrals as the best prospect.
Generating unvarying high-quality link is vital for any business, but can be arduous. When these potential customers reach your website in search of information, you must be prepared for them to clarify the answers they seek.
These customers require a lot of information to gain confidence and deliver their personal information to you. They would like to get convinced and bring in trust by you to receive a good return for their investment.
Another impediment to getting a potential customer is that there are innumerable visitors who show interest but never make decisions. Despite your company have a panoply and a team to provide an adequate solution to your clients, somehow gain little out of substantial efforts and time.
Conventional methods of lead gathering, and generation offer poor returns. Through the traditional method, the conversion rate was estimated to hover between 0.5 to 2 % which is quite low when considering the efforts put in building potential clients.
A chatbot is one of the powerful customer service tools to overcome these impediments in many industries. You might have experienced one of these automated helpers pop out on websites (ready to help or answer any of your questions) while browsing.
A Chatbot is an autonomous program on a network that uses human language to communicate. A Chatbot is an AI assistant that has the capability to learn and perform tasks or services for an individual.
These automated bots are good at capturing leads at the initial level. Certainly, we shall see these bots to predict where a consumer is in the buying cycle. In the real estate industry, these bots are portraying as one of the most qualified prospects to agents by engaging visitors for higher lead conversions.
The corresponding multitude of tech companies has built their own Chabot platform with a pre-programmed response to certain questions generally asked. A chatbot can interpret the intentions of your visitor, thus, it is also stated as “secret sauce” of lead nurturing.
These automated bots are powered with a smart algorithm, machine learning, and artificial intelligence. Chatbot assures companies to interact with the visitors more effectively than humans. At the same time, these Chatbots dramatically lower overhead costs.
Adidas, a shoe manufacturing brand, designed a Chatbot for its female-focused community Studio LDN. This Chatbot was built for an interactive booking process for free fitness sessions offered by Adidas. This automated bot was the only method to drive engagement for them. Under this process, the user starts receiving reminders and messages from the fitness instructor after the bookings made.
A Bot can help the company at the very first event in the purchase path, so Adidas promoted their Bot across many channels. In the first two weeks, 2000 people signed up to participate with repeat use at 80%. Retention after a week was about 60% which the brand claims to be far better than an app.
Instabot is a proven Chatbot to increase conversions by 33% through targeting – different language audience demographics, curating information for each user and information for static websites. Instabot helps readers get specific information visiting the entire website and answer all the queries that could anyways convert them into leads.
B2B sales is another complex process where your business website is in the central. Whether you want to build a customer relationship or get into the highest search results, your website is the key unit of your sales process. One of the research found that it is hard for many consumers to navigate websites.
Chatbotshere can help relieve the pain point by removing the friction along the customer’s journey and drive increased customer value in return. Their one of the influential features is knowing when to bring in an actual human for further conversation with a customer.
According to one of the research, about 80% of the brands will be using Chatbots for customer interaction by 2020.
Bots can be easily programmed to ask a set of questions related to the domain for gathering necessary information. For example, in a real estate, a bot can be programmed to ask price range, location, characteristics and preferred amenities for the customer looking for a property.
A Chatbot can work as an introducer, influencer as well as a closer too. Clothing store bots act as an assistant for humans shopping online. They prove to be helpful in purchasing by suggesting the right clothing i.e. when purchasing a shirt, the bot will ask your height and weight to suggest you a pair of pants that go appropriate with the shirt.
There is a myriad of examples where chatbots can act as an introduction to your company:
People are using Chatbots for advertising as well. Opting Chatbots for instant engagement is a great method. Instead of running Facebook Ads manually give them options like – “chat to see the latest styles” or “chat now to get 20% off” – this will help direct maximum people to your website. An example is: Real-time engagement for leads, Big Ads piloted a Chabot extension as a part of their PPC ads.
Using a gentle call-to-action could be more effective than a call-to-action “Buy Now”.
Instead of pushy ads, your bot is helping in cultivating relationships with your customers. To create a new business there are a variety of Chatbot platformsavailable in the market out of which few we have mentioned below:
This bot-building platform builds a bot to refurbish the static website landing pages and form filling methods. Tars help create a conversational workflow through the automated bot from scratch through a workflow builder or a pre-built template to build trust. Tars each Chatbot conversation lives on its own URL which can also be used as an AD campaign destination. With Tars digital bot, you can view, download and integrate your conversational data.
Botsify gives you a bot that chats like a human, it helps in increasing your sales by 30% & reduce your costs by 80% using AI. Botsify automated bot lessens the burden of handling too many customers at a time. With easy customization, strong validation and smart API integration this digital bot can work on Slack, Google Sheets, Shopify, RSS Feed, Google Search & many more.
Bot engine builds suitable bot as per your need to get integrated with the Facebook messenger as well as your website’s Chatbot through an easy drag and drop interface to create your conversation scenario. Botsify provides some ready-made templates for teachers based on the topic by adding text, images, audio or video. Teachers in the educational sector can schedule messages and easy collection of information about students using forms.
Grow your business by automating your messenger with a Chatfuel bot, leading the Chatbot platform for Facebook messenger. Small & mid-sized businesses are using Chatfuel to make a bot to increase sales, improve conversions, qualify leads & automate support on Facebook. Some of the most recognizable brands that are currently using the Chatfuel platform to build bots are TechCrunch, Adidas, Golden State Warriors & many more.
46% of all Messenger bots run on Chatfuel like Hello Fresh reduced their customer wait time by 38% and increased conversion rate by 44% with Chatfuel. Similarly, LEGO’s results showed a 3.4X increase in return on AD spend compared to website and about 71% reduction in cost per conversion.
Integrate Flow XO chatbot platform to build a bot of your own without the need for code. Flow XO lets you design your conversational flow by connecting a “trigger” for one or more actions. There are over 100 integrations/triggers which can be used as a building block which includes utility modules as well as third-party services integration such as Google Sheets, Adobe Document Cloud, Bigcommerce, GitHub, Freshdesk and many more.
Flow XO Chatbot can provide a virtual welcome mat for the visitors by offering friendly greeting on their arrival, guiding them through the site and helping them find the necessary information. This intelligent Chatbot gathers information from a set of questions and answers a few of the questions to customers. Flow XO chatbot is also capable of taking payments through conversations that are processed using the Stripe payment engine so, you don’t have to handle credit card information.
ChatterOn is a Bot building platform that offers more than 20 pre-built Chatbots with intent, entities and conversion flow. This platform allows easy deployment of the bot with clout within minutes. Integrated with ML (Machine Learning), the ChatterOn platform offers bot to provide an end-to-end solution. It also offers an easy connection with the backend APIs of other bots for seamless integration. ChatterOn bot-building platform is well documented to offer a faster solution and can also handle all types of rich content responses such as carousels, buttons, photos, gigs, and videos for smooth interaction with the user.
Today’s chatbots are backed with highly sophisticated algorithms and automation which are helpful in engaging your customers in a more personalized way. These automated bots can market or broadcast your offers easily along with quick and efficient customer support. And with the help of these bot builders, programming skills are no longer a barrier to build chatbots. This is what all a Bot can offer companies –