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Viber Chatbot for Local Coffee Chain

Project description

The main solution idea is to create closer relationships between coffee lovers and cafe chain representatives. Since the chatbot was launched, clients have simple access to special offers and discounts. Before, this customer can log in with a phone number. When the customer is looking for the nearest cafe, chatbot will propose a few points that are nearby to the client showing Viber maps and moving to Google maps. Also, chatbot presents scored points and helps to understand what value from it customers is having now. If a customer is satisfied or has the offer to improve services, there is a possibility to leave feedback.

The new approach for building chatbot features impressive customization and easy-to-use interface. So, Chatbots.Studio became a provider who helps increase cross sales and improves engagement with the existing customer.

Duration: 2 months.

Development team

Developers, Project Manager QA Engineer.

What we built
The solution includes

Viber Messenger

The services and Frameworks we used

We selected a set of tools matching our project requirements and client needs.

Viber REST API  + library messaging-api-viber, i18n were used for localization.

Winston and AWS cloudwatch  are monitoring and management services built for developers. In our case, we built logs using the aforementioned tools.

.env lets you customize your individual working environment variables and were used for storage of variables.

Eslint is pluggable and configurable linter tool for identifying and reporting on patterns in JavaScript. In our case, it was used for code formatting.

Aws EC2 is a web service that provides secure, resizable compute capacity in the cloud.

AWS CodeBuilt is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages that are ready to deploy.

AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services such as Amazon EC2, AWS Fargate, AWS Lambda, and your on-premises servers.

Node.js + Express.js were used to build backend API for the bot that works in сhat.     

Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale.

Development process

We know that a client wants to know how his/her product is developing, that’s why we gave sympathetic consideration and described in details each step of the development.

First development team chose tech stack. After this developers constructed architecture and development road. We made a huge roadmap and helped with the project all along with architecture decisions. Then created a basic authorization for users and implemented API methods that provide 2Cups. Development team built our own webhooks for the client needs.

The next step was full testing of the product and bug fixing. After that, we started the second version. Run it for all cafes in Ukraine.

The last step was to correct the auto-deploy system for the future upgrades of the product.

Bot architecture
The result

Chatbots.Studio team created chatbot for the cafe chain to optimize engagement with customers. The company has a 34% cross sales increasing after implementation discount and offers system into Viber via chatbot. Obviously, that new sales channel brought more revenue to the client and helps to build trusting relationships for B2C business.

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How Chatbots Automate the Working Process [Top 5 Chatbots For Business]]

Chatbots are in high demand because of all the new opportunities for business and customer service. Previously Chatbots.Studio considered the first benefit for businesses, which provides cost reducing — information management optimization. Let’s talk about chatbot efficiency on the automation of working processes.

automation of working processes


It is a great chance for entrepreneurs to save money by transferring work tasks over to chatbot and let existing staff concentrate on other important work. A wide range of staff isn’t all that necessary as the work becomes automated. Therefore company profits margins continue to increase with smart team.

I’d like to point out that chatbots aren’t the only way to automate a work routine. Lots of information systems provide the same and sometimes better work automation. However, we will consider how chatbots can take on daily routines from the staff.

chatbots can take on daily routines


First of all, let’s consider the metrics that measure the effect of automation with chatbots for business:

  • Transactions number executed by one employee;
  • Mistake numbers for one transaction;
  • Timeframes for service providing;
  • Service availability;
  • Client satisfaction.


Typical scenarios on how chatbot automates working process:

  • Accepts and handles customer requests. The bot provides consultations, answers on FAQs, and passes the conversation to a live agent;
  • Manages the schedule and queue without personal assistance. The bot accepts and handles new client appointments. Also, it notifies clients about upcoming or past events.

This leads to providing a broad customer service, with always available assistance and quick engagement.


Let’s consider some examples of using a bot for automation of working processes according to scenario.

Taking into account our experience, Chatbots.Studio developed the chatbot for the beauty industry that helps make an appointment for a stylist without direct human integration, manages waiting lists, cancels and reschedules appointments and manages stylist availability.


How does the bot automate the stylist working process?

  • The stylist doesn’t handle requests from clients. Therefore the stylist doesn’t waste time on appointments and handles more important work;
  • An availability to book services 24/7. A customer can book the service at a convenient time to not disturbing stylist;
  • The stylist doesn’t manage conflicts regarding in the queue. In case of appointment canceling, the bot makes an appointment for a client from the waiting list.

Another one TrackerBot, which tracks orders sent by delivery services like “Ukrposhta”, “Nova Poshta”, “Delivery” and “Meest Express”. Also, delivery bot provides easy to access customer support to resolve any issues quickly.


How does bot automate delivery posts staff working process?

Chatbot reduces the workload of call centers solving issues.

  • There is no need to provide support through calls, web or live;
  • The bot handles all FAQs. In case of unexpected question, the bot passes the conversation to a live agent;
  • The bot connects with maps and sends the information regarding the track location to the nearest offices with a work schedule;
  • Bot connects with the backend and presents the costs of delivery.


A customer gets the chance, and doesn’t waste time calling support or surfing the Internet for the appropriate information.

As can be seen, businesses can benefit from automation working process with bots. To implement it for businesses correctly, identify metrics of efficiency to get the appropriate results. So, follow me and stay in top of chatbots novelties.

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Why End Users are Frustrated with AI Chatbots (and What to Do)?

Have you ever met really stupid chatbots, that don’t understand what you want and thus pretend to have Intelligence? I do, and many people I am talking about chatbots have had the same experience.

Error bot
One of my potential clients mentioned, ‘all the bots have been invented to shortcut support costs’ — that’s the impression users could get from a poorly designed chatbot. So why does this happen:
Inflated expectations from AI bots

There’s a lot of buzz about AI chatbots that are mainly presented as robots that could provide a high level of human-like communication. Bots have they own characters and have their faces either human-like or robot-like.

So, a high level of expectations mostly driven by vendors of NLP engines who would love to promote their technology, which is still not that mature. If someone from the vendors is reading this post, could you share examples of general intelligence projects built based on your solutions? And yet clients expect to have true intelligence while talking to the bot.

Incorrect training methodology

AI bots require training. Training means helping a bot better recognize intent and context in which it is running a dialog. Practically a system administrator (NLP, Conversation expert — whatever you want to call him/her) should review the failovers and enhance the rules in NLP engine to better recognize user intents.

And that is the dead loop: on the one hand, you need to have a good corpus conversation to train your NLP engine on the relevant conversations and on the other. On the other, the user will not start talking to your bot until it is good enough and thus you could not get a good enough sense of the conversations.

So, what can be done with all of that?

Actually, there are 2 options:

  • Have better tools and processes
  • Avoid using AI chatbots


Better process of AI bot training

That’s something we can do right now without waiting for the big players to update their solutions or making costly investments in data science.

a) Use all of your existing conversations with end clients to train your NLP engine from day one. Whatever you have: call records, mail conversations or queries to live agent to you FB, everything could be used to train your NLP before the day zero.

b) If there is no corpus of historical conversations you can use live agents, who would follow the defined conversation scripts. Once enough training has been provided, you can slowly bring automatic responses.

c) Involving a live agent immediately when the intent is not recognized or a client is not happy with the response.

The approach is costlier but friendlier for end-users and differs from the advertised flow — launch your AI bot and train it once it gets going.

Improving the NLP engines

NLP Engines will also become better and better for example. For example, the NLP engines should support common misspellings work better while there is a growing number of intents in the system. In addition, they should self-learn from all conversations that are in the system (not only in one account) and provide a recommendation of what is missing in the bot. I personally have started to lose the difference between NLP engines specially for English, they look almost the same from NLU perspective.

If you read all of that and still have a wiliness to read for another minute, please ask yourself — do I REALLY need an AI chatbot?
  1. Many users expect to get a very specific service from the bot (book an appointment, buy a ticket, issue the order and etc.) they do not expect a bot to handle all possible conversations. It’s like imagine yourself going to the supermarket — do you expect a salesperson to tell jokes or chat with you about Deep Learning? Probably not and the same goes with a bot. In case you can avoid having AI in your bot, why are you making things overly complicated?
  2. NLP for English and Western European Languages is good enough. It’s very much driven by the market demand and nature of the language itself (it is structured), while there is not many (or there are simply not available) engines for other languages, almost nothing exists for Ukrainian. So, what the language carefully before building a AI bot on that language.
  3. You need to have enough conversations to train the bot even from the very beginning. If you do not have a good corpus of conversation, refer to the tricks above or do not do AI bot. Recently one potential client contacted me to build AI FAQ bot for his new real-estate business. I clearly recommended to him to not do that, as lack of conversational data will lead to a poor experience and waste of time and money.

To be honest, there are cases when you need to equip your bot with AI for sure:
  1. The bot interface does not support any buttons. WhatsApp and SMS are the most common examples of that case. You will HAVE to use AI in that case.
  2. There is a lot of content to share with your end-users, so building a bot with the buttons and distinct conversation is not the issue For example, a big FAQ will need to have this kind of scenario.


We are building bots in Chatbots.Studio on a daily basis and we are excited about it. The key idea for this article was to help clients make a fully aware decision about the type of chatbot they need. We see each and every day how bots are taking a more prominent role in the digital worlds and it is our shared goal to make it better for our end-clients.


I would love to hear your cases and stories about the issues that your are facing while building AI chatbots.

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Marketing for Chatbots Companies [10 Ways to Get Inbound Traffic]

Chatbots.Studio is a highly specialized agency with an exclusive and dedicated focus on chatbot development. Once, I asked myself — how others work in this niche and in what ways do they attract clients?

Below you can find info about inbound and outbound channels of interaction. The analysis also includes the ways in which companies present themselves and conclusions based on the observed information.

Before sharing the information itself, let me show you the methodology we used to collect and analyze information.

We checked which channels have been used by chatbot development companies. The right side explains why it is important to include it to our analysis.

Why did we choose that criteria?

  • Blog — prospects could find the site in the fastest possible way if the blog includes SEO keywords.
  • Medium and Quora — both resources have good indexing by Google. There are easy ways to show expertise. Amount and quality of posts and show us professionalism and readiness to interact with the audience.
  • Crunch — an easy way to find your target audience representing expertise and being in the list of companies with services you provide.
  • Clutch — there are collected services companies. An easy way to represent itself and find potential client.
  • Social Media — not specialized platforms with wide range of dissemination of information. Acts like word of mouth.
  • Press — editions could lead prospects to find the site in search systems.
  • E-mail marketing — we checked the opportunity to subscribe and get the email of a prospect.
  • Live interaction — meetups.
  • Rank is calculated using a combination of average daily visitors to this site and pageviews on this site over the past 3 months.
  • SEO keywords — ideas and topics that define what your content is about.


Following companies were selected by:

  • Keywords in Google search: chatbot development agency, chatbot company, chatbot development companies.
  • Quora list of chatbots development agencies (or chatbot development companies).
  • Clutch list of Top Artificial Intelligence agencies.


The investigation is open for your consideration. If you have any idea of how to improve it or I missed the good company, please drop a comment this article.

What does mean +, +-, -?

+ agency actively gathers traffic using the mentioned communication channel

+- agency рas inactive account or almost doesn’t work with channel

— agency doesn’a t use communication channel


So, take a look at the table below to learn more about agency strategies to attract traffic.

Chatbot Development Companies Strategies
Chatbot Development Companies Strategies

So what could we learn from the information mentioned above?

We observed several interesting strategies for using inbound marketing by chatbot development companies.

  • Creation of their own media and related resources. Taking into acthe count global market, a few companies gather traffic through their own free platforms, which allows them to publish content and share expertise. It thereby creates the image of authoritative chatbot developers but requires additional efforts.
  • Well-known media also is a great way to promote content aside from Facebook, LinkedIn or other curated blog sites. Soon you will get more clicks or redirects to your main site. About 70% of the mentioned companies use it as an opportunity to express themselves.
  • One more method to attract attention and show deep expertise is providing training courses for entrepreneurs and junior devs.


Surfing the related resources, we noticed another a infrequently used strategy, as being the educator of a small company (Oh my bot!). They don’t care about customers, as they are provided by the parent company. This approach works with, for example, Oh My Bot!, KRDS’ subsidiary. Some of them provide chatbot development as a part of software and marketing services, for example, Vis-a-vis.

On average, each company uses 3 channels of communication. The following is the most popular:

Medium. Agencies post articles related to their expertise: AI, Machine Learning, bots’ benefits for industries, marketing solutions. We divided agencies that post on Medium into few types:

  • active: 50+ claps and 200+ followers. Average 2 articles per week.
  • less active: — appear in searches or have only few posts with no more than 50 claps.


Quora. Agencies posts articles in section “Technologies”, “Science”. Most agencies don’t have company account. Nevertheless CEOs public questions and answers on their own behalf while building their human brand. Marketers use it to build expertise and authority on a chosen topic. Posts content is the same as Medium. Types of agencies involving to Quora:

  • active: publish posts with the same content to Medium. Each post has 50+ views and 5+ shares
  • less active: company representative asked or answered to questions
  • inactive: company name appears in searches with keywords: chatbot, chatbot development, and chatbot agencies.


Twitter. Mostly there are posts and shares about participation in tech events, news, last projects. Agencies use it to promote brand posting latest tech news, activities and showcasing projects not only to find clients but also represent themselves as an employer. Types of chatbot dev agencies on Twitter:

  • active: 200+ followers, 2+ shares and 5+ per week posts
  • less active: twitter isn’t the main channel of communication. The account includes only a few posts or the last post was published more than month ago.
  • inactive: an agency doesn’t have an account or the account is empty.


We keep working to investigate how chatbot development agencies get inbound traffic. Want to read more great content from Chatbot.Studio? Click on the left and let us know in the comments below.

We love to develop chatbots. Feel free to contact us if you want to improve your business with chatbots, and we will conduct an assessment in 2 business days for FREE and a demo bot in 1 week.

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