5 simple rules to ensure that your bot is an absolute success

Bots are rapidly becoming preferred tools for marketers. They are not just limited to the big name tech brands anymore; even small businesses are adopting them. This is because they deliver an intimate, peer-to-peer sales experience. Bots are the new apps now, and hundreds of companies are using them to do anything from answering routine customer questions to helping employees become more productive.

  • AI-based bot are always better than rule-based bot

Rule-based bots are generally easier to build since they need fewer resources. They are pre-configured with detailed rules. They’ve a specific technology & architecture requirement which are quicker and easier to build, deploy and implement, which makes them cheaper.

The downside to this is that they are less scalable and not very robust. The other issues that affect these rule-based bots are the lack of detailed analytics, inability to self-learn and improve over time and a scripted response to all queries which might not always be correct.

“Rule Based: Assist on specific queries & commands which is pre-configured”

An AI-based bot is smarter since it is built using NLP (Natural Language Processing) and ML (Machine Learning). These bots try to mimic the way humans operate i.e. by learning and absorbing information, but are even more efficient since being a piece of software, they do not get tired.

AI bots provide an overall function far greater than a simple chatbot and require ML and NLP to convert & train the outcomes of conversations, apply some intelligence and convert that knowledge through learning into a powerful decision making capability over the long term.

Currently, rule-based chatbots are popular since they are easier to build, but AI bots are where the real opportunity lies for companies to offer a personalized service to their consumers. The early adopters in this area are going have the chance to get a huge lead over their competitors.

“AI Based: Built on NLP & ML with self-capability of learning & absorbing information”

  • Your rivals are adopting bots, don’t get left behind…!

Companies across a wide variety of domain are building Chatbots on popular messaging apps like Facebook Messenger, Telegram, Text/SMS, Slack, Skype, Kik, Email and Webchat irrespective to domain like Manufacturing, Retail, Healthcare, Insurance and Finance. With the increased competition in business, customer retention has become a big deal, let alone getting new customers. Providing quality customer service is the need of the time for the businesses. Chatbots nowadays are built with AI, which can understand the requirements of the customers and give them instant services.

Appears everybody is talking about bots and how they can be effectively deployed to assist people in all sorts of tasks. Chatbot industry is still early and lot of different industry has already adopted like:

Food ordering industry leaders like Taco Bell & Domino’s have introduced bot named TacoBot and DOM on Slack & Facebook Messenger respectively. Entertainment industry is no left behind in it; Disney has created bot named Officer Judy Hopps, available on Facebook Messenger.

Retail industry leader Tommy Hilfiger launched bots named The TMY.GRL on Facebook Messenger. To name few from Finance & Insurance industry leaders like Allianz – Allie, RBC Insurance – Arbie, Captial One and many more are early adopters of Chatbots.

  • Record your bot conversation to train your dataset

Chatbots are getting a lot of attraction and many companies are eager to develop bots with NLP to have natural conversations and many are claiming to be using NLP & ML techniques to make this possible.

To make your bot intelligent, you need to ensure that your bot is storing the data (conversation data) and it is using machine learning to process that data in order to improve its conversational skills. A rule-based bot will not be able to carry out this kind of self-improvement. The right mix of datasets and data models helps in training and re-training your bot, and over time it will become smarter.

With machine learning, you can process the structured and unstructured data that helps you to analyze a conversation’s sentiments, recommend products/services on the bases on previous dialogue and make predictions on historic data.

AI based bots help to make the conversation more natural and interactive with previous data.

  • It’s all about location, location, location…!!!

Before launching a bot, consider where & what is your target audience. It is important to note where your users are and which messaging application is popular in that region.

Popularity of channels such as Facebook, Slack, SMS, WeChat, etc. depends on location. What’s popular for messaging in North America may be different in Asia. Before deploying a bot define the geo-location and target audience for the success of your bot.

  • Soft launch

Once you’ve implemented your bots whether it’s a rule-based or AI-based bot you need to test it before deployment from both a language and security standpoint. There is a lot of attraction for chatbots but if it is not secure and well trained it won’t stay in the customer market for a long period of time.

Before deploying, you need to test it on a limited number of users, and then fine-tune the bot when you get results. Same way you need to continuously train or feed your AI-based bot to make it smarter to have a natural conversation with a human. Chatbots can be great if they’re in line with your brand and are implemented correctly. However, if chatbots are rushed or developed in the wrong way, it can be extremely harmful to your brand.

If you are a business owner, you need to make sure that your business catches up on trending and transformative technologies. If you want your business to be the change initiator and adopt AI services of the future, get in touch with our team.


I think it’s great how you put the pro’s and cons of Rule based VS AI based. However I think most bots will end up being both, most customers don’t need self learning, self optimization yes, learning what people say and picking the right path sure. But ultimately, there has only been one customer we talked to that wanted something more AI based vs Rule based.

Gotta pick the right shovel for the right job I guess is the take away.


Completely agree! I think there was this obsession in 2016 with bots having to be insanely smart. Like you said gotta pick the right shovel for right job. What ended up happening is by making the bot try and be super smart and be completely free form it usually ended up making the bot seem dumb (or a racist).

My hope is in 2017 People will try mixing both AI and rule based to make for a great experience that is still great at learning who you are and like but at the same time still guides you down a path that makes sense.


Out customers seem to be especially sensitive to the lack of control resulting from a completely AI based interface of any kind. This hesitation - justified or not - will probably lead to many more rule based (and ideally AI enhanced) bots in the near future.

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