AI-powered chatbots deliver personalization at scale

Conversational marketing technology is utilizing developments in machine learning algorithms and artificial intelligence (AI) to facilitate machine-powered selling to consumers via the use of chatbots.

These marketing automation solutions enable businesses to personally engage their audiences in both scripted and unscripted conversations, in real-time and at scale. 

Chatbots are computer programs that simulate human conversation through voice or text commands – or both.

To understand how far we’ve come from the earliest version of chatbot technology, it’s helpful to know where it all started.

The first chatbot, Eliza, was developed at MIT in the 1960s by Joseph Weizenbaum. It works using a decision-tree model, and by recognizing keywords and phrases then responding based on a pre-programmed script.

The next innovation in chatbots came in 1995 with the development of the Artificial Linguistic Internet Computer Entity (A.L.I.C.E.), which was created by Dr Richard Wallace to simulate chatting over the internet.

Like Eliza, Alice uses pre-configured templates to respond to human input, but she also has some limited learning capabilities. Alice also takes a decision-tree approach, although her learning capabilities get her closer to the modern version of chatbots.

By 2006, IBM gave us Watson, a chatbot that uses natural language processing (NLP) and machine learning.

Siri, a virtual assistant integrated with Apple’s iOS, was launched in 2010. Siri put chatbots and voice technology on the map in a major way.

Following Siri, Google launched Google Now in 2012. Then came Amazon’s Alexa and Microsoft’s Cortana in 2015. These are widely used intelligent virtual assistants that recognize natural language commands through voice and text. 

The popularity of messaging chatbots coincided with the launch of Facebook Messenger in 2016. Through Facebook’s API, developers could create bots that interacted with Facebook users.

The emergence of conversational marketing platforms is the next iteration of chatbot technology.

Platforms like Spectrm, a Berlin-based conversational technology company, take chatbots to a new level of functionality designed to improve and enhance customer experience.

Marketing chatbots enable businesses to streamline engagement with customers, clients, and prospects by using automated, personalized, real-time conversations across a variety of messaging channels to drive action.

The potential is limitless. More than two billion people can be engaged on Facebook and Instagram using Facebook Messenger and, according to Spectrm, three-quarters of consumers prefer to engage with brands in private messaging versus traditional channels. 90 percent of internet users can be reached with Spectrm and Google AdLingo using conversational display ads.

A marketing chatbot can drive marketing performance and return on investment (ROI), facilitate personalized brand experiences at scale, and gather insights from customers that are used to recommend products, ensuring businesses can reach their customers across multiple channels.

Intelligent chatbot technology like Spectrm’s is designed to personalize the customer journey using real-time conversation. Marketers combine scripted conversation flows and AI-driven chat to engage customers from websites and apps, paid social ads, and their favorite messenger apps.

Personalized customer experiences at scale

Conversational marketing platforms use powerful AI technology, analytics, and a range of features to design exceptional and personalized customer experiences. They make intelligent chatbot technology accessible to companies regardless of their in-house technical capabilities.

Platforms like Spectrm differ from simple, rules-based chatbots in a few ways:

• They leverage analytics to make data points actionable
• They use chatbot data to optimize the sales funnel and segment customers
• They use conversational AI to identify (and respond to) customer intent
• Their feed integration capabilities give them the ability to recommend products or content in real-time based on user input

The goal with any conversational marketing platform is to simplify the process of building customer relationships by using chatbots throughout the customer journey. 

“We operate on multiple messaging channels where consumers spend all of their time: Facebook Messenger, Instagram Messaging, Google Business Messages, and Conversational Display Ads (AdLingo and Google DV360),” according to Spectrm.

“This enables the business to connect instantly via chat with target audiences on Facebook, Instagram, and other platforms.”

Before the pandemic, messaging was the preferred way for customers to connect with businesses while they shopped online. 40 percent of people surveyed in a 2019 global Facebook study said they started their online shopping journey with chat.

64 percent of people, regardless of age, indicated they preferred messaging to a call or email, and 65 percent said they’d be more likely to shop with a business that they can contact via chat. These long-term shifts towards online shopping and messaging have accelerated since the pandemic.

One of the things that set conversational marketing platforms apart from rules-based chatbots is how it uses personalized chat to generate ecommerce sales, enabling conversations at every point in the customer lifecycle.

By using data consumers willingly share in chat, marketers can reduce their dependence on third-party data and tracking technologies while still giving their prospects a personalized digital experience.

Conversational commerce technology is designed to engage customers in direct, one-to-one conversations across a variety of channels. 

Platforms like Spectrm are 100 percent code-free, making it possible for any business to easily implement conversational AI as part of their marketing strategy. 

To view Spectrm’s offerings, click here.