Conversation and personalization are big buzzwords in marketing, but what makes these ideas compelling? Or even applicable to a business?

The answer is deceptively simple. The goal is to replicate the feel of one-on-one, in-person service, then scale that out. This is how businesses of any size can have personal conversations with dozens, hundreds, even thousands of customers at one time.

Conversation bots combine the ease of talking to another person with the data analysis powers of artificial intelligence and machine learning. They’re powerful tools for businesses seeking to personalize communications with their customers.

Why Personalized Communication Matters

According to a study by Laura Frances Bright at the University of Texas, humans’ love of personalization boils down to two factors: information overload and a desire for control.

Information overload occurs more frequently in today’s world than it did in the pre-digital era. Customers seeking a particular product or service have access to more information about products and more options than ever before.

In the face of this onslaught, the human brain’s desire for control kicks in. Personalization directly addresses that desire for control by making the presented information feel relevant and therefore manageable, Erik Devaney at HubSpot says.

Even though the customer isn’t directly in charge of the information, they feel more in control because the information addresses their needs and interests in that moment.

How Marketers Can Leverage the Brain’s Desires

A customer who feels overloaded is likely to step away from a purchase to stop feeling overloaded. The risk for brands is that a customer who steps away won’t return.

By personalizing the customer interaction, companies reduce the sense of overload by engaging the brain’s desire for control. Personalized messages shorten the time between when the customer receives information and when the customer acts on it, thus reducing chances for churn, Craig Besnoy at Medallia notes.

That reduction in time has measurable results: 87 percent of marketers report a measurable improvement in their results after implementing personalization, Margaret Ybarra at Impact writes.

How Conversation Bots Make Marketing Personal

Today’s customers expect to communicate with brands rather than being communicated to. According to Andy Betts at Martech Today, 81 percent of customers want brands to understand where, when, and how to engage with them.

Conversation bots make communication with customers simpler because they hold actual conversations with visitors.

The right platform will allow the conversation to continue across multiple channels, Elaina Ransford at HelpShift writes. For instance, a conversation with an insurance company might begin when a visitor tells a conversation bot on mobile, “I’m looking for renters’ insurance.” A few days later, the visitor might complete their policy purchase via the company’s website. Six months afterward, the customer might talk to the conversation bot again to learn how to file a claim.

Throughout the customer’s process, the conversation bot gathers information, provides recommendations, and stores what it learns. When the customer returns in six months with a problem or question, the conversation bot remembers the customer as if they never left.

The timing flexibility that conversation bots provide add to the sense of personalization, Polomi Batra at ZenDesk notes. Customers who can talk to a brand’s bot on their own schedule can control the amount of information they need to process. The conversation feels more relevant because it occurs when and where the visitor is ready to engage with it.

As a result, bot conversations with customers allow brands to build stronger relationships, which can improve both conversion and retention rates, Syed Balkhi at Constant Contact says.

Building a Personalized, Informative Conversation Bot

Conversation bots often leverage artificial intelligence (AI), machine learning, and natural language processing to produce personalized, natural-sounding conversation. A spontaneous, natural conversation flow is, however, the result of careful planning.

Creating a Conversation Bot: First Steps

Nick Iyengar, associate director of digital intelligence at Cardinal Path, recommends that companies begin the personalization process by agreeing on key terms and definitions. If your business doesn’t agree on what engagement looks like or what a conversion is, reaching personalization goals will be difficult.

Setting specific goals for the conversation bot can make it more effective. For instance, tasking a conversation bot with answering frequently asked questions focuses its efforts. That focus allows it to address a customer’s specific issues.

Consider the business’ goals, as well. For instance, businesses with ambitious growth goals can leverage a conversation bot’s scalability, Daniel Newman notes at Forbes. A conversation bot designed to qualify leads could help a growing business engage with customers without requiring more human customer service representatives.

Adding Personalization (and Personality)

Once the bot has a focus area, consider how to personalize its interactions effectively. One way to do this is by designing a conversation flow that demonstrates empathy, says Michelle Zhou, creator of the Juji chatbot. By combining an empathetic approach with the ability to personalize replies, Zhou says, these conversation bots can keep visitors engaged for longer.

Personalization should go beyond simply repeating the visitor’s name. Instead, “personalization happens when a marketer or salesperson can take a piece of content and make it more useful for a specific prospect or customer,” says John Jantsch, author of Duct Tape Marketing. When the conversation bot’s responses match the customer’s needs, the customer’s mind can focus and make better decisions.

Also, consider personalization options over time. For instance, a conversation bot may learn from an initial conversation that the visitor is interested in a product or service but is concerned about costs or is not in a hurry to buy. The bot can be programmed to use this information to schedule subsequent emails or human-to-human outreach, Kiumarse Zamanian writes at Oracle’s Modern Marketing Blog. Meanwhile, a similar visitor with more urgent needs might receive different information and faster outreach from human staff.

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Using Data for Personalization

To personalize its conversations effectively, a conversation bot will need a way to gather, store, and analyze data on each customer. Useful data points include customers’ interests and past behavior as well as their basic identifying information, says Laduram Vishnoi, CEO of

The conversation bot’s ability to store and use individuals’ information represents a leap forward for marketing teams, Richard McGrath argues in Chatbots Magazine. In the past, marketers relied on profiles based on demographic information to make educated guesses as to customers’ needs. For instance, the data might suggest a customer identified as a city-dwelling woman in her 50s wants certain products from an insurance company — renters insurance, for example.

A conversation bot, however, doesn’t need to make predictions based on general demographic data. Instead, the bot can use information from each particular visitor to pinpoint what that person will want and when.

As customers interact with the conversation bot, the bot’s available dataset expands. Fortunately, the expansion and use of this dataset can often proceed without human intervention. Conversation bots can be programmed to interact directly with databases, allowing them to recall and implement personalized customer information immediately, notes Hemanth Kumar, practice head of analytics and data management at Acuvate Software.

From a customer’s perspective, the conversation bot sounds like someone who is familiar with their individual needs — an impression that boosts the sense of personalization.

Assessing the Bot’s Performance

Finally, a bot can learn from previous interactions with those customers. This information can help companies understand how well their personalization strategy is meeting its agreed-upon goals.  

Erik Driessen at The Marketing Technologist recommends classifying this type of conversation bot data into three categories that map the typical conversation bot session: stating the desired result, input gathering, and completing the task. By analyzing what occurs at each step, marketing teams can understand how effectively the conversation bot interacts with visitors.

The ability to gather and analyze information helps the conversation bot get to know its human conversation partner better. In turn, the bot can provide more focused recommendations. It can also more accurately predict when a customer will need to speak to a human within the company.

By gathering information and using it effectively, conversation bots become part of the relationship-building process. They provide visitors with a sense of control, manage information overload, and engage customers at every stage of the purchasing process.