Picture of Reve Marketing
It is better to think of a text-based chatbot as an "automated customer service representative".
This is the board of Kaye Chapman, responsible for learning and developing the Comm100 digital engagement platform. As a conversation format sometimes assisted by IA, chatbots offer marketers a different opportunity than, for example, the structure and presentation of information in pages or screens for websites or websites. mobile applications.
Conversations, not pages
If you consider a chatbot as a simple "website with interaction", you do not focus on the means that this may lead to your desired outcome, which may be to make a sale or solve the problem of 39, a customer.
A web page presents a block of information that users find through clicks of navigation or a search on a site, while a text-based chatbot presents information by small keys based on the information entered by the user. it's a different type of information gathering that requires a different presentation.
Because of this fundamental difference, it's important to keep a hierarchy of information relatively simple for a chatbot, said Vivek Lakshman, co-founder and vice president of products at Reve Marketing, who proposes the creation and the Chatbot deployment.
Minimum before the choices
Lakshman suggests that a marketing agent's operational question when designing the chatbot information flow should be: what is the minimum relevance of the contribution before making choices?
In other words: if you ask a chatbot for shoes, you should quickly see the shoe choices.
One of the ways to flatten the hierarchy is to group the products so that they can not be grouped on a site, followed by a thorough analysis. Footwear may be included in a new, higher level of "shoes", for example, which includes shoes, sneakers, boots, socks, etc.
Another way to smooth exploration is to determine the user's personality and immediate needs via chatbot requests, instead of assuming that the user's person will be revealed by choices.
Another kind of character
Of course, web site designers often create targeted user profiles, called personas, to determine their approaches and needs. A character, for example, may be a mother of young children, another is an elderly man. The standard information quests of each type of user are then taken into account to decide how the information is grouped, structured and accessible through menus or a search on the site. .
But a chatbot can simply ask in advance: how old are you and what are you looking for? This establishes the personality and the need immediately, so that the choices of final results can be presented more quickly. It's a different type of tree of choice.
A conversation flow also means that a marketer can inject information highlighted at specific times of interaction, likely to increase their impact. For example, a dish of the day, for example, does not need to be on the site's home page or in a pop-up window, but can be fed into the conversation stream at convenient times, for example when it seems that the user's answers are spreading purchase.
Different basic information for chatbots
Of course, not all chatbot interactions are equal. In addition to differences as obvious as the quality of the assistant AI, there are also fundamental differences in the information available to a user.
A chatbot for which a user has logged in with identification information from a branded website, for example, will likely have more history of shopping related to the mark on the user that a chatbot on Facebook Messenger, on which the user is logged in with Facebook IDs.
Text chatbots can be an integral part of a brand's marketing and customer service team, so the branding information is tailored to the particular needs of that delivery mechanism.
If not, users may be reluctant to use less effective chatbots than other means to help them find what they are looking for – even if the idea of chatting at first seems to more attractive.
This story was first published on MarTech Today. For more information on marketing technology, click here.
About the author
Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a senior editor for VentureBeat, and he wrote on these technical topics, among others, for publications such as CMSWire and NewsFactor. He founded and managed the website / unit of PBS Thirteen / WNET; worked as a Senior Producer / Writer Online for Viacom; created a successful interactive game, PLAY IT BY EAR: The first CD game; founded and directed an independent film, CENTER SCREEN, based at Harvard and M.I.T .; and served for five years as a consultant to the M.I.T. Media Lab. You can find it on LinkedIn and Twitter on xBarryLevine.