What is a sale if not a conversation between seller and buyer?
This interaction is much more evident in retail when the shop assistant listens to what the potential buyer wants, advises him and tries to guide him to the best option to close the sale in a way that is satisfactory for both parties (and if he can raise the ticket, better than better).
In the case of eCommerce, things are quite different. Obviously, the purchase process is much more autonomous, the customer sets the times and manages his experience almost without assistance.
How do you apply conversational marketing to an online store?
Obviously it is necessary to use certain interactive customer service tools in real time. You cannot implement an agile strategy of exchanging messages via email, and the telephone can also be a brake for many users. The sale cannot be allowed to cool down.
For all this, we have 2 different options and both have to do with the chats that are integrated into the navigation.
Using live chats: the manual method
These live chat windows are, in many cases, underused as a simple means of attending to queries and filtering out complaints or after-sales situations.
Customer service must be changed to a formula that allows us to attend the sale as well. To do this, it is necessary that agents become proactive and seek to provide that service that supports the conversion (you must train them and provide procedures in that regard).
When you choose a live chat tool, go to an advanced one that allows you to automate certain actions, such as activating the chat windows when certain conditions are met, such as the user being inactive too long on a particular page. This is a way to anticipate and avoid frustrating a potential sale.
Chatbots: the automatic method
A machine, at least still, doesn’t sell as well as a person. Artificial Intelligence tools advance a lot every year, but it takes a touch of empathy and commercial instinct that is difficult to replicate through a machine.
This is not to say that chatbots don’t sell. In simple operations where there are few parameters that vary from one customer to another, they have been proven to work. Ordering a pizza is very mechanical, even making recommendations for that order (drinks, desserts, starters…): it can be automated to increase the purchase without a person having to repeat the famous “Do you want to make your giant menu for 1 euro more?
The ideal, however, is to use the combination of machines and people. The chatbot to cover the mechanical and serve as a filter for agents to give the human touch and round off the conversion.