Facebook Messenger has been key to driving bot-driven conversions. With almost limitless opportunities, Messenger bots are changing the ecommerce industry. From lead management to 24×7 customer support, chatbots are the robotic executives waiting for customer and community queries with their instant replies.
Ecommerce chatbots have enabled a new form of businesses operation for the web-shops- Conversational Commerce. Powered by chatbots, conversational commerce have not just made conversions easy but also guiding up-selling and cross selling of more products.
If you run an ecommerce website or mobile app, this article will explain how to create a chatbot with 5 killer tips to integrate best of the chatbots in your business touchpoints. If you’re thinking about adding chatbots to your online store, you should take a look at these professional tips.
Indeed, the logic that powers chatbots is crucial. However, in all these coding and back-end configurations, eCommerce store owners fail to optimize the UI. As a result, even the sophisticated eCommerce chatbots do not grab the deserving attention.
People will interact with your business only if they find the touchpoints meant for interaction. Make the bot’s UI interactive, standing out, and interesting for the users. Amuse your users with your conversions by considering the following tips-
- Use a design that stands out from the website UI.
- Use contrasting and prominent color schemes.
- Use interesting texts in the initial automatic messages. You can use the messages like-
- “Hey there! Grab 20% off on your first order. What would you like to shop today?”
- “Hey! If you need any help, I am just a message away”
- “Hello! Would you like me to pick out the best offers for you on our site?”
- Post-initiation, based on their responses, follow up with the direct links like-
- Men’s shoes with 60% discount
- Fresh arrivals with free delivery
- Computer accessories etc.
- Give them more clickable options and minimize the need for typed-only responses.
Doing so will not just start a conversation but would also guide the user to your targeted pages. Check out how this chatbot is not just starting a conversation but also followed up with different clickable links for easy navigation without having to type a response.
Event-driven bots are good for certain situations when your chatbot only responds for the queries configured in it. They mostly give direct link-based responses, or data-driven results for specific questions. Besides that, most of them don’t except typed-questions, and ask users to select from the pre-fitted questions like –
- “What’s my product delivery status?”
- “ Know your refund status”
Answers to such questions would be like-
- “Please provide your order number to know the status”
Also, they fail to understand a question if asked in the natural flow. Say, the same question about order status become unanswerable by the bot, if asked something like this-
- “I did not get my product yet”
Most of the time, both questions and their answers are already programmed and give a pre-programmed response to the unknown questions. Something like-
- “Sorry! Can you be more specific, I did not get your question?”
- “Would you like me to connect to a support executive?
- “Sorry! We are unable to process your request”
However, in eCommerce, you cannot just rely on event-driven bots. To surpass the competition, even your eCommerce bot needs a certain intelligence, which can be efficiently handled by the AI-chatbots. AI-bots use natural language and machine learning to identify un-expected commands and provide a more contextual response instead of an error message. Moreover, once experienced, the AI-bot can learn new commands and questions by itself and analyze the previous conversations to answer the new queries more perfectly.
For example, the above question was not recognized by an event driven bot in the natural flow. However, if it was for an AI-chatbot, it could have analyzed every data related to the words used in the question and given a precise response. Something like-
- “We are so sorry for the inconvenience, could you be more specific about the product? Maybe a product number will let me help you better”.
After getting the response, the bot will learn that the particular question was related to order status. Thus, for any such query in the future, the bot will directly give the more-precise response like-
- “We are so sorry for the inconvenience. Please share your order number to track your order status now.”
Bottom line: Don’t just depend on pre-programmed queries. Design your bot with AI and let it handle the leads and queries with more of a natural stream.
People don’t hate bots unless they are responding to the legitimate queries. Also, no bot is perfect for every query. Even the AI-driven bots take some time to learn stuff and processes un-programmed queries. Give your bot some time, and let it learn through the live interactions.
- Launch your eCommerce bot as soon as possible so it can start interacting with real people.
- Start with basic script to answer fundamental questions.
- Program as many events and data-driven answers for the beginning.
- Interact with chatbots of your competitors and analyze their responses.
- Integrate your business’s general FAQ and their answers in the chat bot.
- Re-direct unknown questions to the human executives.
- Always be available for human interactions if bot fails to respond.
It’s fine, if your bot is not perfect. At least, until it learns to be perfect, it will p some basic support to your customers with the programmed responses.
You can’t and shouldn’t fool your customers with chatbots. Nowadays, eCommerce stores are displaying their chat bots as a live chat portal. No doubt, chatbots give an immediate response and make customers feel happy about your support quality. However, faking chatbots as real executives is not a good idea.
Customers expect brands to be more transparent and honest. It’s not that you are scamming them, but admitting it upfront is a good idea, and it lets them believe that you are honest and transparent. Otherwise, sooner or later customers take no time to identify the bots.
How do you think you eCommerce chatbot will show a customer his/her order status? Unless you let your chatbot access your database of the orders, it cannot offer any data-driven response. Besides the natural interactions, data-driven interactions are more in eCommerce queries. You need to equip your bot with all the access required to search, process, filter, and respond to the data-driven queries.
Integrate your CRM with the chatbot, and let it make a good use of your data. With access to your CRM, the AI-bot can scan your customer information, order information, email ID, leads and offer a more precise response to the related queries.
For example, with access to your inventory management system, the bot can give an accurate response to the stock queries like-
- “I want to buy the XYZ handbag in black color”
- “Is extra-large size available for the Blue ABC checked shirt?”
- “I want to return my order number #1234 and exchange it for a ‘Medium’ size”
A smooth access to your CRM will make sure that chatbot picks up every lead in its way and follows up to the sales team. It can even access your emails to send promotional emails for sales campaigns. Your support team would be able to manage the customer service effectively with unresolved queries getting transferred to the ticket management system automatically. CRM integration is definitely a pro tip for your eCommerce chat bot.
Caution: Be careful with the access control and program to chatbot to verify the credential before exposing any data-driven response. You don’t want your bot to reveal a customer data to a wrong person.
Lastly, as a bonus tip, the best eCommerce chat bot is the one which mixes artificial intelligence with the human intelligence. There are standards and rules for making ethical chatbots. Give them a name, and an image. Let a real person monitor the chats from time to time or in real-time. A human touch is necessary if you don’t want to irritate your customers with vague responses. At least until machine learning and AI come into the full-fledge.