- Keywords represent the tip of the iceberg when it comes to understanding consumer intent
- Using AI-powered chatbots, conversational data over messaging channels like Facebook Messenger and Instagram Messaging can give businesses a deeper understanding of what consumers want.
- Below, we’ll discuss how conversational marketing platforms like Spectrum use natural language processing (NLP) and artificial intelligence (AI) to guide customers through the buying funnel.
- A robust conversational marketing platform allows companies to build chatbots that engage and convert customers on the websites, apps, and social media where people spend their time.
Google and other search engines have attempted to crack the consumer intent code for more than two decades. The entry point for a search marketing campaign is the keyword list. Yet keywords—whether spoken or typed—represent the tip of the iceberg for understanding what a user wants. There’s no way to clearly measure (or identify) user intent. Still, Google is getting better at figuring out what a user wants with technologies like Google Hummingbird, an algorithm update they rolled out in 2013. Google introduced Hummingbird in response to the increasingly conversational nature of search queries.
Per a 2013 article in Wired, “Google is now examining the searcher’s query as a whole and processing the meaning behind it.” In January 2020, Statista reported roughly 40 percent of US search queries contained four or more terms. Asking a search engine or virtual assistant a question is the beginning of a conversational journey that carries the searcher across channels until they ultimately find what they want (or not). Keywords pull the curtain of intent back, but they only provide a glimpse of the customer journey, labeling the searcher’s thoughts without revealing the “why” of what they’re searching for.
Once a user clicks on a search result, the conversation is over from the search engine’s perspective.
But thanks to 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 across the entire buying journey. AI-powered chatbots that “speak” to consumers can collect customer intent data and take the conversation beyond an initial keyword query. They enable businesses to leverage that customer intent data instantly to scale one-to-one personalization in direct chat. Below, we discuss how conversational marketing platforms employ NLP and AI in chatbots to guide customers through the buying funnel, using casual analysis to understand customer intent that goes far beyond keywords.
Content created in partnership with Spectrum.
The customer conversation is online.
According to Hootsuite’s Digital In 2020 report, 60 percent of the world’s population is online. The report found that, globally, users spend an average of 6 hours and 43 minutes online each day—40 percent of their waking life using the internet. A large chunk of that time, more than two hours, is spent using social media.
Consumers were using mobile messaging and chat an average of 20 minutes per day in 2020, with Business Insider predicting that the standard would grow to 24 minutes by 2021. Interacting with chatbots is a natural extension of consumers’ comfort with messaging in social media apps like Facebook and Instagram. Increasingly, messaging is how we connect with each other. Facebook and Instagram are at the center of this trend. Businesses can reach and engage with over two billion people on Facebook and Instagram using their respective messengers. This level of engagement gets to the root of consumer intent, diving beneath surface keywords to the conversational data that can help companies understand what’s motivating the consumer to conduct their search in the first place.