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“A lot of what makes AI and bots powerful is the ability to know your customer,” says Scott Horn, chief marketing officer at 7, an intent-driven customer engagement solutions company. “But you’ve got to have great algorithms, and you’ve got to have a lot of domain-relevant data.”
That’s one of the reasons why marketers are excited about the potential of chatbots in the customer service arena. Customer service interactions serve up a cavalcade of actionable data across every interaction. And then, when a chatbot is leveraged correctly — loaded for bear with all of that integrated data you’ve got on hand — it can offer a surprisingly compelling personalized experience by simply predicting customer intent.
“The amount of data that’s available to leverage is just amazing,” Horn adds. For their customer service clients, they have more than 40 million chat sessions of data to mine from. And data sources are proliferating as the ability to connect all the steps of a customer’s journey from search to purchase and beyond becomes more and more sophisticated.
Crossing the streams
“We’re seeing real value in linking up search and advertising data with people’s revenue transactions and service transactions,” Horn says. “One of the things that’s really exciting for a lot of our clients is going end-to-end with us, everything from search and personalization all the way through the customer care part of the lifecycle for consumers.”
They’re able to create an integrated stream of information through their search bid ability. If you’re a particularly valuable potential customer searching the web, the system will bid high to win you, and then is able to fast-track you by determining the intent of your search — for example, specific interactions that indicate you’re searching for a particular kind of phone.
The search then brings the consumer to a personalized landing page, which offers them an opportunity to chat with a human customer service agent or a chatbot.
“Eliminate returns” on the wish list
Horn also says they’re seeing a lot more linkage of the customer care and the customer purchase worlds, bringing companies rather closer to omniscient.
“Let’s say you purchase something and then you call back later; we actually have all that data leading up to the purchase, so that we can make your post-purchase service interaction more powerful,” he says.
That data is also the powerful foundation of AI’s ability to reduce the cost of returns, which can be a significant drain on a company’s bottom line.
A lot of 7’s customers, particularly enterprise clients in the retail, ecommerce, and service spaces, have a problem with returns, Horn says. One of their clients, a global ecommerce company, has “eliminate returns” on its wish list. The company especially wants to eliminate people-involved transactions that result in returns.
In other words, if a consumer uses a self-service process to make a return, that’s not great. But it’s even worse if the consumer tries to do it through a phone call, because that then becomes a really expensive return.
Horn explains that lookalike analysis on search bidding data and segmentation is the key to tackling this challenge. Segmenting out frequent buy-and-return customers allows the company to identify those people early on, and make sure a live chat option is never offered to that kind of person, but they are instead redirected to a self-service area.
“That’s the thing about chatbots — zero cost per transaction,” he says.
There is no sensitive data, only Zuul
Horn emphasizes that privacy concerns should not be an obstacle to implementing chatbots.
“I don’t think chatbots introduce privacy issues that you already wouldn’t have with a human agent,” he says. “They really don’t. It’s not Skynet from the Terminator movies weaving together all kinds of streams of information in a malevolent way.”
He notes that the chatbot is simply an automation of what takes place with an agent today. “So chatbots are not going to have any magical powers or access to any data it shouldn’t have,” he adds.
And as with a human customer service agent, your data is inaccessible until your identity is authenticated. The ability to be authenticated quickly and easily, and have all your data brought to bear on each interaction, is actually one of the powerful advantages of AI.
For instance, if you were to call the customer service line of United Premiere, you’ve given United permission to link your phone number with your Mileage Plus account. Not only do you get a very kind, personalized greeting from an enthusiastic agent, your call is also streamlined significantly: they have info on your most recent website activity, such as searches for particular itineraries, or if you have a trip coming up, and they’re able to serve you more quickly and more accurately.
All data points to something big on the horizon
But, Horn emphasizes, there are so many opportunities to improve and optimize — it’s never just plug it in and forget it. New products get introduced, new conditions come up, and the space continues to evolve.
“We have over 85-plus data scientists on staff, and we’re scaling that because there are so many interesting things we can do,” Horn says.
To find out more about crossing the data streams, improving and deeping personalization, and making marketing campaigns even more powerful, don’t miss this VB Live event!
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- Learn how deep learning can help your customers get a “human” through chat
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- Dr. Anand Rao, Global AI Lead for PwC Data & Analytics
- Scott Horn, CMO, 24
- Stewart Rogers, Director of Marketing Technology, VentureBeat
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