Auto-trigger messaging by AI chatbots is an essential and efficient tool to enable online marketers to achieve contextual targeting. Personalized auto-triggered conversational flow based on the user’s intent helps chatbot engage the user in the desired way and guide him/her to perform the desired action.
Makerobos Chatbot enables businesses to send automated chat messages to the right people at the right time. Onboard, engage users, and increase conversions across the whole funnel.
What is an auto-trigger message?
Auto-trigger message is a pre-welcome message that chatbot sends to a visitor just after landing on a page or website. Auto-trigger message is one of the most crucial tool enabling contextual targeting in a modern marketing environment. We technically call them Glass Messages because of their reflective nature :)
The Auto-trigger message is of two types in general
1- Generalized auto messages - these are general greeting messages that the user receives automatically when he/she enters an online platform hosting a chatbot.
2- Personalized auto messages - these are intent-based personalized messages initiated by chatbot when users lands on a website. Personalized auto-trigger messages are catered by marketers to address the user’s intention and trigger action from the user. They are fundamental tools to manage assisted website navigation and improve conversion rates. Personalized auto-trigger messaging is a new age marketing marketing tool for growth hackers.
This article is centered around auto messages by employing tactics of contextual targeting. Makerobo’s frontman enables marketers to create an AI chatbot that can deliver optimal auto-trigger messages (generalised and personalised) and achieve desired growth.
Now what is contextual targeting?
Contextual targeting is the advance marketing principle that utilises web user information to strengthen user engagement. Advertisers and marketers use customer/prospects past behavior, i.e., user’s past search history, visited web pages, time of engagement, links they click, etc. to place relevant content at the right time and right place. Marketers extract these crucial information pieces of information through data mining and by url tracking methods like UTM.
Through contextual targeting, marketers can enhance user experience and create a favorable brand image by offering tailored online interactions based on the user’s unique needs and requirements. Auto messaging based on such type of targeting takes the whole experience to the next level with the help of proactive chat messages that are automatically triggered and sent each time your visitors qualify for a set of rules.
Web exploring is a lengthy and time-consuming process with the added risk of losing interest from the user’s side. Contextual targeting by chatbot through auto-trigger messaging can help get desired results (from a sales perspective) and save precious time (from the consumer perspective).
Suppose you own an online car renting website. There is a customer, facing difficulty booking a luxury sedan car for the upcoming weekend. After navigating through online space for hours, the customer enters your website and starts to navigate it. Your chatbot suddenly pops up. It offers the link to book a car through a personalised triggered message. Imagine the impact this will have on customers’ conscience, who might have to navigate through multiple tabs and fill long form to book a car. Your chatbot just solved his problems in a matter of seconds and ensured the customer’s future loyalty towards your website. When it comes to online marketing, efficiency and user experience always prevail over other attributes.
Chatbots are considered advanced when they can advise customers and suggest choices (products and services) at the time of the customer’s need. An AI-powered chatbot with access to real-time analytics can put auto-trigger messages to optimal use and provide for an efficient and relevant user engagement on your website. With a custom, catered glass message in lines with the user intention, a chatbot can create a personalised engagement that will enable efficient website navigation and ensure higher conversion rates.
So, in a nutshell, glass messaging should be one of the most crucial tools for contextual targeting by marketers.
You can use Frontman to create a rule base auto-trigger conversational flow (glass messages) in a LEGO architecture based GUI (graphic user interface).
Tools and processes enabling contextual targeting through auto-trigger messages
To enable contextual targeting through auto-trigger messages, some technical tools and processes play a part in identifying a user-intent. Let’s take a brief look at them.
1. UTM parameters - these are 5 URL parameters that define the source, which diverts the user to a particular website/webpage. these are
- UTM source - which site referred to the user.
- UTM medium - which type of link user engaged with, e.g.. CPC or email.
- UTM campaign - which specific product promotion or campaign.
- UTM term - user, used which search keywords.
- UTM Content - Identifies what specifically was clicked to bring the user to the site, such as a text link or banner ad.
UTM can set the right context enabling the chatbot to pick the right conversation.
2. Cookies - these are information packets that are placed on the user’s computer by the browser while interacting with a website. Chatbots can assess those cookies and initiate the interaction through glass message accordingly. The conversational flow created by developers should be in line with the user’s past behavior so that there is a minimum chance for defaulting.
3. User profiling- This a more website centric process. Each user is profiled in the web site’s database by categorizing them according to their past behavior on that particular website. E.g., a one-time purchase, wish list, etc. user profiling is an essential tool that enables the chatbot to deliver an engaging auto-trigger message.
4. User segmentation - Each user is segmented and incorporated into a particular user group with common attributes related to their past behavior. Profiling website visitors makes it easier for the developers to create custom conversational flow to optimize user experience. AI chatbot can create micro-segments entirely different from conventional marketing segments (demographics, past behavior, etc.) based on real time interactions and choices made during conversational journey. Websites can use these segments to deliver optimal glass messages consisting of relevant information about relevant products, discounts, or promotions. Segmentation is different from user profiling as segmentation is based on past interaction of the user with the chatbot, and user profiling is based on past behavior on the website.
5. Real-time analytics - Analytics is one of the most critical functionalities required to deliver optimal glass message and enable behavioral targeting by the chatbot. It is the ability to process data as soon as it is made available to the chatbot.
Types of personalized auto-trigger (glass) messages -
- User-centric auto message- These auto-trigger messages are based on the user’s intention and behavior. Their context is in line with the user’s profile and instantaneous engagement (current online activities). User-centric auto-trigger messages are essential to build a positive brand image and allow efficient navigation through the website.
- Ad-centric auto messages - ad-centric auto-trigger messages are based on the source (generally advertisement) that referred the user to a particular website. These are instrumental in providing an instantaneous personalised experience and helps in improving the conversion rate.
- Page-centric auto messages- these auto-trigger messages are in line with the web page’s offering that the user is currently engaging with. E.g., a product-specific page or information page.
- ABM centric auto messages - ABM (account-based marketing) is the type of b2b marketing where enterprises consider a single corporation an entire marketplace with a single customer. Chatbots can be very instrumental while catering to the needs of a specific account. Creating an optimal auto trigger messaging flow for a particular account is relatively easy compared to a broad consumer base. There is a higher potential for creating more personalized auto-trigger messages for a specific account by the virtue of past engagements and clear understanding of customer’s intent.
Create an ultimate user experience and achieve optimal contextual targeting by frontman chatbot’s auto-trigger (glass) messages.
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