What I got right

1. Building the bot’s knowledge bank from rich online resources

Getting straight down to the brass tacks, I had a task at hand: find the most common pain points that Mr.Bot could address. The idea was to pull in what people are actually searching for and I had a starting number in mind: 100.

The 100 questions quest: How I found what people were asking

a) Google Trends

No surprises here and I’m betting I’m not the only one who uses Trends as a go-to starting point when it comes to studying recent search trends a.k.a the major pain points.

So I did a straightforward trends search with the term ‘chatbot’ and subsequently picked queries and topics with the highest search volumes.

The results looked like this:

Google Trends showing top 25 topics and queries related to chatbots

b) Quora

Instead of going with a keyword research tool, cause hey I wasn’t writing a blog post any more I decided to go to Quora: the one question bank to rule them all.

And Quora fit perfectly into my bot’s conversation plan. Here again, I quickly looked up ‘chatbot’, ‘best chatbots’, ‘create chatbot’ and all the other topics I picked up from Trends.

Quora showing a potential list of questions to target

Results were indispensable to say the least. I found at least 300 questions, from there choosing the top 100 based on follower count was quite simple.

After my rendezvous with Trends and Quora, I had the top 100 most frequently asked questions related to chatbots. In fact, if you’re trying to create an informational bot, you could follow the same steps to uncover actual user pain points!

2. Adding a tinge of life and character

The biggest complaints chatbots get from us humans are usually along the lines of them either being stupid and useless or too robotic. As for the former, there’s no denying that everyone in the AI and bot space is working tirelessly to make bots smarter at understanding human intent(think development in NLP algorithms and neural network functions).

As for chatbots being ‘too robotic’ I knew I didn’t want Mr.Bot to get ruffed up by verbal abuse. I had to give it some flair- a tinge of personality even.

Mr.Bot’s character traits, what I thought would go with its informational self:

nerd

witty bordering on cheeky

optimistic with a humorous streak

Once that’s decided, naming your bot is just as important. Here’s a list I came up with before deciding on Mr.Bot (I’m open to changing it, so please feel free to put in suggestions):

Wizard of Bots

Botfather (taken by Telegram)

BotGod (let’s face it, the name sounds more powerful than my bot actually is)

Mr.Bot (inspired by Mr.Robot)

Botasaur (sounded more like a bot event)

BotGuru (no explanations there)

What’s in a name? Said no bot ever.

Golden Tip. I’ve found that drawing out a basic character sketch comes extremely handy when designing a chatbots’ conversational style. Something to refer to when you trying to give them a consistent personality.

Additionally, I used tons of images, sprinkled a few GIFs here and there too. Oh and don’t even get me started on my use of emojis.

When it comes to adding life to conversation, visual elements go a long way. They add appeal to content and generally stick more than words -exactly what I wanted when I was adding those jpgs to Mr. Bot’s content cards.

3. I trained Mr.Bot to tell a story

Although there’s still room for improvement, I’d like to believe I trained Mr.Bot’s responses right to a certain extent.

For starters, I used a healthy mix of short and long responses. Thanks to Bottr’s elegant chat window and simplistic yet rich content cards, training Mr.Bot to tell a visually pleasing story was easy-peasy.

Using rich images and target links to lead users to detailed reads

So while on one hand for questions like “what is a chatbot?” I wrote the responses to highlight the image on the other hand for questions like “show me how brands are using bots?” and “how to develop a bot from scratch?” I linked to URLs directly from the cards to lead users to handpicked blog posts and tutorials online (all the amazing content I was talking about earlier).

Further, Bottr’s in-built small talk capabilities helped Mr.Bot’s conversations flow easily without me having to train for every random thing a user might say!

4. I targeted the correct niche audience

In the real world, no matter how cool you think your own product/experiment/chatbot is, other people will generally not care. Unless, they too share the same enthusiasm you do about a particular interest area.

So that’s exactly what I did.

I shared Mr.Bot on four highly targeted facebook groups to be precise- ChatBots, Bots, Chatbot Directory and BOTS.

The top 4 facebook groups I shared Mr.Bot on

From there it was fairly obvious that a few people would go check out my bot and even have a conversation with it.