There is a bold, glowing line between building a simple chatbot versus a successful one.
Chatbots, as Stefan Kojouharov, Founder, Chatbots Life, puts it, are a throwback to the times when business problems were solved via conversation. Even today, marketing remains a matter of perception. If you can get to the customer’s point of view in time and steer it towards your product, you win a new client.
It is that simple and challenging at the same time.
Chatbots are a platform shift, aka, a massive opportunity to get new customers onboard by changing the way they perceive your business. But, and here is the kicker, you must dabble in chatbot creation very carefully to master the art of conviction in this case.
Addictive Chatbot- What’s the Definition?
Revisit the concept with me. Why do you need a chatbot?
There can be two probable answers.
You need to establish a conversation with customers. That will require dealing with multiple variable inputs. An app isn’t enough to offer a solution here
You need to provide a simple, direct, and immediate answer to your customer’s woes
Now, mull over this: what do you mean by an addictive chatbot?
While you frame your definition, let me tell you mine. It’s a bot that’s functional, has a personality, and successfully caters to a core need.
Your motive, when you’re trying to build such a bot, should be to:
Offer the most suitable action to a particular trigger
Ensure that your solution is used and appreciated enough times that it becomes a habitual behavior for the customer in need
Tips to Help You Create a Chatbot with Enough ‘Chatfuel’ to Keep the Users Hooked.
1. Leverage Machine Learning with Care
Humanising a chatbot is revered advice in this field.
And why not! You must give your bot a personality, i.e. that extra spark that can be used to retain the attention of a customer. Think SmarterChild, the chatbot of ActiveBuddy which was available on AOL Instant Messenger. If you insulted the bot, it’d stop responding until handed an apology.
Your bot needs to be a bit more than simple text on a screen.
But, using machine learning for a chatbot for law research can have well-defined boundaries. Using it for a bot that is used to negotiate prices may not have as great an effect.
2. Test Your Concept
What’s the problem you aim to solve with your bot? And how efficient are your efforts?
Run the code. Test it. Try it on people. Gauge its usability. Make a note of the point where a customer drops off the conversation and the context right before they leave. Don’t postpone your chatbot launch hoping for the perfect version because you won’t get the best output without exhaustive testing.
Get to the market. Collect feedback. Fix. Test. Release. Repeat.
3. Rely on User Investment More than Anything Else
We’re back to the point- establish user behaviour.
You want them invested in your chatbot to a point where changing platforms is not worth the trouble for them. Look at the famous Facebook chatbots. Create something similar that will run user investment graphs higher.
And, most importantly, before you choose a chatbot builder, get your priorities straight.
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