Marchex Releases Conversational AI Technology Built to Predict Customer Intent, Create Personalized Sales Experiences and Improve Sales Outcomes
New suite of predictive AI models featuring 230 AI signals and growing creates powerful conversational insights for businesses that engage with customers over the phone and via text
The suite of new pre-trained Conversational AI models was developed by the
“Marchex is cracking the code of consumer intent,” said
Marchex Conversational AI is built on Marchex Stream, the new conversational data streaming and business intelligence platform announced in May that enables the processing of events and extraction of signals from conversations as they occur in real time, at scale.
The technology is powered by Marchex’s growing base of more than one billion minutes of analyzed consumer-to-business conversations and employs deep learning techniques including convolutional neural network developments pioneered by the
Some of the new features and capabilities in Marchex Conversational AI include:
- Deep Consumer Intent Signals. Eighty new Deep Intent signals identify and organize the flood of essential information that consumers express in phone and text conversations and structure them into simple actionable information that businesses can act on to optimize marketing campaigns, close sales and improve customer sales experiences much more effectively than has previously been possible. Among their capabilities, these new signals identify intent, context, urgency, product and service interest, appointment scheduling and payment preference, all of which help enable businesses to determine when a consumer is evaluating service or vendor options, which issues or products are of greatest importance to them and also predict when they have decided to purchase
- Lead Scoring. A new AI-driven intelligent lead scoring model that helps businesses predict which caller opportunities are most likely to lead to sales, so their sales team can efficiently prioritize their efforts. This model combines consumer intent and offline data to score leads. For example, a business can combine conversation intent with pre-conversation website browsing metrics to provide richer lead scores that more accurately represent consumer behavior throughout the path to purchase.
- Churn Prediction. A new churn model predicts when customers may be planning to switch to another service provider, so a sales or service team can take the right action to prevent churn and retain the customer. Testing in certain verticals indicates that this model provides more accurate analysis of customer intent than other models that rely on signal data culled from social media profiles and website visits. The new churn model was recently debuted by
Marchexat international AI conferences.
- Deep Outcome Insights. One hundred new conversation outcome signals organize the wide array of outcomes of sales or service conversations and accelerate the ability of the business to respond so it may recapture missed sales opportunities. Within seconds, these signals can identify the reason for the outcome with granular detail, alert the business immediately and inform the recommended next action for the business to take. For example, outcome signals can identify that an appointment was cancelled because the consumer found a lower price, or that an opportunity was lost because an appointment time was not available and alternative times were not offered. These insights enable marketing, sales and service teams to take action to improve positive outcome and customer experience rates.
- Sales Best Practice and Performance Improvement Insights. A new voice biometric model determines the identity of the salesperson on the call, and fifty new performance-tracking signals analyze the salesperson’s responses to the consumer to help identify whether they responded to the consumer’s actual intent and how effectively they followed their sales or service scripts. These capabilities give businesses a valuable solution set to measure, train and improve the effectiveness of their sales teams.
- Vertical Industry Models. Pre-trained models can help businesses in a range of industries address sales conversation challenges and move customers forward in the path to purchase. For example, a customer calling an auto dealership not only wants to buy a car, but also trade in a vehicle. Marchex’s AI can immediately surface details about the desired make and model and the trade-in, which can help the dealership create a relevant and highly personalized customer experience. Today
Marchexhas pre-trained models for the Automotive Sales and Service, Communications, Insurance, Dental/Healthcare and Home Services industries, as well as a general-purpose model that can be used across various other industries.
“Moving beyond the industry hype, the real measure of success for AI is how effectively it solves real world business challenges,” said
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Marchex Investor Relations
Trevor Caldwell, 206-331-3600