30 second summary:
- Keywords are the tip of the iceberg when it comes to understanding consumer intent
- Using chatbots with AI, conversational data transmitted through messaging channels like Facebook Messenger and Instagram Messaging can give businesses a deeper understanding of what consumers want
- The following explains what conversation marketing platforms look like Spectrm Use natural language processing (NLP) and artificial intelligence (AI) to guide customers through the purchase funnel
- A robust conversational marketing platform enables companies to create chatbots that engage and convert customers on websites, apps, and social platforms where people spend their time
For more than two decades, Google and other search engines have been trying to crack the code for consumer intent. The entry point for a search engine marketing campaign is the keyword list. However, keywords – whether spoken or typed – are the tip of the iceberg when it comes to understanding what a user wants. There’s no way to clearly measure (or identify) user intent, but Google can better find out what a user wants with technologies like Google Hummingbird, an algorithm update introduced in 2013. Google introduced Hummingbird in response to the increased conversation of search queries.
According to a 2013 article in Wired“Google is now examining the search query as a whole and processing the meaning behind it.” In January 2020, Statista reported around 40 percent of US searches contained four or more terms.
Asking a question to a search engine or a virtual assistant is the beginning of a conversation that leads the searcher through channels until he finally finds what he wants (or doesn’t). Keywords pull the curtain of intent, but only provide a glimpse into the customer journey and characterize the searcher’s thoughts without revealing the “why” of what they are looking for.
As soon as a user clicks on a search result, the conversation is over from the point of view of the search engine.
With advances in natural language processing (NLP), machine learning (ML) and artificial intelligence (AI), businesses have access to a much deeper understanding of what consumers want throughout the buying journey.
Chatbots with AI support When you “talk” to consumers, you can gather data on customer intentions and move the conversation beyond an initial keyword query. They enable companies to leverage this customer intent data instantly to scale one-to-one personalization in direct chat.
The following explains how conversational marketing platforms use NLP and AI in chatbots to guide customers through the purchase funnel. Conversational analytics can give you an understanding of customer intent that goes well beyond keywords.
Content created in collaboration with Spectrm.
The customer meeting is online
According to Hootsuite Digital in 2020 According to reports, 60 percent of the world’s population is online. According to the report, users around the world spend an average of 6 hours and 43 minutes a day online – 40 percent of their waking life on the Internet. Much of that time, more than two hours, is spent on social media.
Consumers used mobile messaging and chatted an average of 20 minutes a day in 2020, with Business Insider predicting it would grow to 24 minutes Interacting with chatbots is a natural extension of consumer convenience through messaging in social media apps like Facebook and Instagram.
Messaging is increasingly the way we connect with each other. Facebook and Instagram are at the center of this trend. Companies have the potential to reach over and get in touch with them two billion people on Facebook and Instagram with their respective messengers. This level of engagement gets to the bottom of consumer intent and delves into conversational data under superficial keywords that can help businesses understand what motivates consumers to search in the first place.
Use conversations to get results
Conversational marketing platforms use messaging apps to connect with consumers and determine intent. This is a next level chatbot technology that uses AI to create a two-way exchange with each customer, asking them questions throughout the buying process, and being able to work on multiple messaging channels.
Spectrm is an example of a conversational marketing platform that goes beyond simple, generic approaches to conversational AI domain-specific NLP Guiding consumers through the customer journey. Generic Conversational AI uses generic NLP that can be used for simple tasks like autosuggestions and basic keyword matching. Domain-specific NLP is trained for the individual company. Spectrms approach too Conversational AI combines domain-specific NLP with the use of generative adversarial networks, a type of machine learning that allows companies with little or no customer intent data to quickly generate their own data sets to train the algorithm.
“Marketing chatbots that use domain-specific NLP are learning how your individual customers talk. The customer intent data specific to your company, your customers and your goals is used to continuously improve your chatbot. It’s about understanding how your customers naturally relate to your brand, and training your bot to respond to it and produce results that are valuable to your business. Even if you don’t have a lot of call data to train your bot. “- Writes Spectrm
Chatbots are only part of what makes conversational marketing platforms work. Platforms like Spectrm work across multiple messaging channels This is where consumers spend all of their time using Facebook Messenger, Instagram Messaging, Google Business Messages, and even at the ad level via conversation ads with AdLingo and Google DV360.
Consumers enjoy chatting with businesses. You’re already stepping through the buying cycle through one-on-one calls, which provides much more detailed intent data than a simple keyword search. Consider the following statistics:
- 75 percent of consumers prefer engaging with brands on private messaging channels versus traditional channels
- 65 percent of people are more likely to buy from a company they can reach via chat
Call data = more targeted campaigns
Conversational data can be used to create marketing campaigns that are more targeted than traditional search and ad campaigns. They enable companies to design targeted messages around the customer journey and to learn what customers want / need in the context of their interaction with the chatbot.
Conversational data also allows companies to create customer profiles using the responses provided in the chat. Personalization and segmentation becomes easier due to the granularity and specificity of the conversation data. This information can be used to personalize marketing messages one-to-one directly in the chat.
None of this is possible without the right platform. Some factors that are very important to consider when evaluating an enterprise-level conversation marketing platform are:
- An easy to implement setup with no coding
- Adjustments for your specific company and customer requirements
- Easy integration into your tech stack
- Enforcement of the highest data protection standards (GDPR, CCPA and others)
- Connection to your product feed (for ecommerce websites) and ability to provide product recommendations / content based on user input in real time
- Flexible role management with the ability to define user access roles
Tools like Spectrm are at the heart of marketing automation and enable companies to attract new customers on a large scale. A robust conversational marketing platform enables companies to create chatbots that can target and convert customers on websites, apps, and social platforms where users spend their time – without the need for technical resources.
Just like search engines, conversational intelligence tools use language effectively to pinpoint the consumer’s intent. They go beyond keywords to make every data point actionable using chatbot analytics Optimize funnels and segment customers.
In Spectrm’s words, “It is getting harder every day to reach the right audience. Consumers are more curious, demanding and impatient than ever before. They expect their digital experiences to be personalized, instant, and effortless. With chatbots, brands can get in touch with their audience in person and provide seamless customer experiences right from the start. “