Perfect levels of interaction.
Isn't that what we all want to achieve? We spend hours if not days planning and developing, being careful architects of automated conversations with a single goal in mind: to efficiently inform and communicate.
But the universe wanted to throw us a curveball and BOOM! Made us live on a planet with 7 billion people, so that means 7 billion different minds. What an amazing challenge that is!
How can you, the superb chatbot developer you already are, foresee the exact reactions the users are going to have in order to increase that response rate by a million? Well, not a million, but at least 50%.
In this article, you'll find the exact tools needed for defeating the universe and learn how to apply them by looking at a case study.
Case Study: The Mattress Company.
A year ago, a company in Costa Rica with over 115 years on the market faced a new challenge: consumers no longer wanted to visit the stores. As the market grew and other brands emerged, the average customer decided upon a new path: checking for prices via Facebook Messenger before purchasing.
The problem is, most living beings on earth do not know how to choose a mattress, even less which terminology to use, so how could the digital team recommend the perfect product? My solution: creating a quiz for the existing chatbot.
First tool: Stop thinking in bot terms. Start thinking in human terms.
As simple as this flow may look, without any conditions nor tags, it carries a heavy punch.
Whenever we're developing an automated conversation, there should always be two people on our minds: the one who receives the message, and those who read the responses. This means we need to investigate a little bit and get involved, not just plotting over what our contact told us. By not investigating we doom our bots to fail. That's why this baby doesn't have any cool stuff on it, the people in the back-end had no technological knowledge and them using Facebook was already enough of a challenge. Plus they gave a personal 1-1 response according to those answers.
Ask yourself these basic three questions:
1. What is the end goal?
My end goal was to provide the customer with a mattress recommendation that fits his or her specific needs, providing them with facts as to why that option was given.
2. What does the company need from its customer and what are their pains?
Well, our pain, singular, is that people never know what they need. "Full size, stiff bed". Ummm... You want thingamabobs? I got twenty!
The experts, or Sleep Advisers as we call them, need to know the size of the bed, the weight of the person, if they get too hot at night, how much money they're willing to spend, and medical requirements. In. That. Order.
3. What are the questions usually asked by customers and what are their pains?
Is transport included? Are there any payment options? Why is it so expensive? They never ask about components, they don't care about the fabric or the fillings. They want to know that this specific option will get rid of that pesky lower back pain and it fits their budget perfectly.
Their main pain is they don't want to answer the super private questions the Sleep Adviser asks.
Once you've answered these three things, let them sit in your brain for a bit until they become one. Then ask yourself one last thing: How can I answer the customer's questions in a way that provides the company with valuable data? Not an easy feat.
Our way was with a simple quiz. And that didn't go well. They stopped answering once we asked for their weight.
Which takes us to
Second tool: Turn to your trusty Obi-Wan Kenobi (it's your only hope): NEUROMARKETING!
Unfortunately I did not know I would be writing a blog about our first failure, so I never took any screenshots of it, but let me tell you, it was a mess. You see, I didn't take into consideration the fact that just as customers don't want to tell Sleep Advisers how much they weight in person, they don't want to do it while chatting either.
Hey I just met you, and this is crazy, but what's your weight hun? And lets talk money.
Not a good plan at all!
So here is where psychology came into play. Society is a devious maid constantly judging, and sharing private information is an excercise done only with people we trust, if not, we either lie or avoid answering. You can read a short article about why customers lie on surveys here: here (its the invisible white space behind this parentheses)
People lie to other people.
Disclaimer: i know longer own the rights to this brand so that's why it is now covered.
Before: ¡Hey first name! I'm your Sleep Adviser. Did you know"Insert current discount or marketing pitch here"?
After: displayed in image: ¡Hey first name! I'm XX, the customer support xxxxxxxxx. Did you know"Insert current discount or marketing pitch here"? You can come back here or talk to a person by using the menu down at the bottom.
Boom.
That was it.
Simply by letting people know they were not talking to an actual human being, relaxation ensued, and answers came a-running.
From that moment on, the third question (which was then moved to number 4) went from a 30% response rate to a 95.5% response rate!
Do you sleep alone or with a partner? What size bed are you looking for? Do you get too hot at night? Simple questions to get your customer started. And then: What's your weight? Tell us in kilograms! 495 messages sent. 475 messages answered. Isn't that neat? They tell JJ cause JJ won't judge! JJ does not have a body nor does he care if you're on a diet. Let me show you the end results.
630 people received the quiz, 521 actually started it which is a fantastic number.
Look at that first message on the left, that one says "Hey, between us friends, have you set a budget?". Everyone answered! Everyone told JJ how much money they were willing to spend. And then the cherry on top: anything else you wanna tell us? Make them feel special, make your users feel unique and heard.
But back to what we're her for, what we really care about is that last one on the far right: how many people actually finished our quiz? 461 people got to that last stage, the magical Bot to Human hand-off. That's an 88.5%!
They went through the funnel and emerged victorious, and now, customer support is getting amazing data they can use to tell this person "Hey, so according to your answers, the product you need is this one, and may I recommend a pillow for your neck pain?"
In conclusion, you too can defeat the universe and achieve percentual happiness just by asking yourself, WWID? What would I do? What would you do, fellow bot maker, if you were the customer receiving the message or the customer support person reading the answer? How would your message affect you in both cases?
Read a couple articles about consumer behavior and retail psychology, just train your skills in order to create a bot that caters to human needs, and manipulates the human condition.
Love you babes,
Trilce Jirón
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