Bots & Super Personalization On Steroids
Bots are Evolving and their 1st Superpower is Here
Most of us are building bots the same way we built Apps and Sites; we are still building products for groups of people!
Bots finally have a superpower! They can now personalize and customize content in a scalable way. Website and Apps are meant to solve problems for groups, however bots can solve problems for individuals.
The Problem with Sites
Do you see the problem with the Polo Website?
Essentially, it crams every product line on the home page in hopes that it will appeal to you. Even when this is done to perfection, a great site will have a 40%-60% bounce rate and 2%–5% conversion rate. This means that about half of your traffic is lost right away and 95–99% does not convert. This is a huge waste.
Why does this Happen?
Most products have a goal of solving a painful problem for a specific group of people. Great companies learn a lot about their customers and build entire solutions for them.
In the process a lot of testing is done, and a product becomes the result of an ongoing A/B test which is the average of what most customers do. The final result becomes a generic flow, like this:
From the Polo Website to the Shop Spring Bot:
Just like the Polo site, the Spring Shop Bot tries to cram a full product line, 10 words at a time. In the end, it feels like a really bad game of 20 questions.
This is what happens when you try to condense a website into a bot and rely on averages.
When you don’t know why a person is on your site, or using your bot and you end up playing a guessing game and hoping that the shoe fits. Most of the time it does not.
The worst part is that most Bots do this every time you use them. In order to get to the useful parts, you need to go through a maze.
This way of organizing information is broken. It barely works online and it will surely fail in bots. Fortunately, there is a much much better way.
Super Personalization
Bots offer us a better way! Instead of A/B testing product with groups of people and arriving at an average solution, bots allow us to do A/B testing with individuals and offer the best personalized solution possible.
Great bots won’t have 1 or 2 flows, they will have multiple flows and copy each tailored specifically to a person’s preferences.
Getting Data
Bots are great at getting information from people. In fact, it is one of their specialties. When it comes to getting to know a user, on an individual basis, a bot has the advantage hands down.
The best way to take advantage of this is by asking meaningful questions and creating a context for your user. For example, if we built a bot for Ralph Lauren, the goal of the bot is to become a personal shopping assistant for the user when it comes to all things Polo. This means that the bot has to learn our preferences, our likes, our habits and to help us shop better.
Doing this the Easy Way
Currently, there is an easy - no programing required- way to do this.
Chatfuel does this on the front end via segmentation and Botanalytics does this on the backend via reengagement. In both cases, you will be leveraging user inputs and data to push relevant personalized content to your users.
“For the first time technology is offering a scalable way of having personalized 1x1 experiences with your users.” Dmitry Dumik CEO of Chatfuel
Power of the Right Questions
The Christina Milian Chatbot leverages the power of questions to personalize the flow, content, and notification.
One of the questions the bot asks users is if they are ‘taken’ or if they are ‘single’. The bot will then take this into account and the entire flow for each user group will be completely different. In the end, a bot should not have 1 user flow and copy but many!
Botanalytics to the Rescue
The second way to do this, is via Botanalytics.
By looking at how different users groups are engaging with your bot, types of content that really engages them and where they drop off, you can quickly see what works best. Based on this, you can create rules, put users in different buckets, and re-engage them based on their individual interests!
“Soon, we will be able to accurately predict a user’s behavior and automatically suggest the message they are most likely to act on and the best time to deliver it” İlker Köksal CEO of Botanalytics
By using this technique, PennyCat increased their engagement by 87%!
What does this Mean for our Polo Ralph Lauren Bot?
This means that every person will have a different experience with our Polo Bot. The bot will know our shopping habits, what types of Polos we like to buy, price points, our location and offer the exact right deal when we are most likely to buy.
This is the new Paradigm
Let’s Hack Chatbots Together
Creator of 10+ bots, including Smart Notes Bot. Founder of Chatbot’s Life, where we help companies create great chatbots and share our insights along the way.
Want to Talk Bots? Best way to chat directly and see my latest projects is via my Personal Bot: Stefan’s Bot.
About Stefan
Stefan Kojouharov is a pioneering figure in the AI and chatbot industry, with a rich history of contributing to its evolution since 2016. Through his influential publications, conferences, and workshops, Stefan has been at the forefront of shaping the landscape of conversational AI.
Current Focus: Currently, Stefan is channeling his expertise into developing AI agents within the mental health and wellbeing sector. These projects aim to revolutionize the way we approach wellness, merging cutting-edge AI with human-centric care.
Join the Journey on Substack: For exclusive insights into the development process, breakthrough experiments, and in-depth tutorials, follow Stefan’s journey on Substack. Join a community of forward-thinkers and be a part of the conversation shaping the future of AI in mental health and wellbeing.
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