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Acquiring New Customers Using AI, Machine Learning and Customer Analytics

In this special guest feature, William Skelly, CEO, Causeway Solutions, provides a list of some of the modern customer acquisition technologies and techniques. Causeway Solutions is a leading provider of Acquisition Analytics and innovative data services. Bill serves as advisor with some of the nation’s most influential organizations—from grassroots public affairs efforts to U.S. Presidential campaign strategies. Causeway Solutions empowers clients to make smart, timely, data-driven decisions through real-time consumer insights to better reach target audiences.

“It is six to seven times more expensive to acquire a new customer than it is to keep a current one.” That’s an often-repeated business adage from a decade-old White House Office of Consumer Affairs report.1

It’s true that loyal clients raise the potential for Customer Lifetime Values (CLVs). However, with the latest advancements in AI, machine learning and customer analytics, acquiring new clients can be much more strategic, streamlined, and cost-effective.

Here’s a list of some of the modern customer acquisition technologies and techniques:

Customer Relationship Management (CRM) Systems

Many organizations are incorporating CRMs into their enterprise systems to integrate marketing, sales, and customer service functions. Through a CRM software, business leaders can track relationships with clients, personalize their interactions, and collect useful insights. CRMs are designed to help improve an organization’s relationship with its clients and nurture prospective customers along the buying journey.

AI for Automation

For mundane, repetitive tasks, artificial intelligence streamlines workflows by taking on business functions like invoicing, organizing tracking codes, and scheduling meetings. To support “always on” consumers, chatbots integrate AI with natural language processing to decipher user questions and send automated responses in real-time. AI will also facilitate digital self-service capabilities, which according to McKinsey & Company, is becoming a dominant element in B2B go-to-market models for selling to both small-to-medium-sized businesses and large enterprises.2

Machine Learning, Predictive and Prescriptive Modeling

Working with a data and customer analytics partner, marketers can tap into machine learning to craft messages that are more personalized and attractive to capture consumers’ attention. 

Leading data analytics consultants have access to emerging technologies, harnessing predictive and prescriptive modeling to identify patterns and make accurate forecasts about future behavior. Thanks to these sophisticated algorithms, messages will arrive at just the right time when consumers are making key decisions.

Data and Audience Analytics Consultants

Your audience analytics partner will help you go beyond information from your CRM by finding new prospect customers who are likely to buy your products or services. Leading data consultants combine data science with sociology because they know consumers often make decisions based on emotion rather than logic. These consultants use a data-first approach to sampling and stratification, ensuring that the individuals you are studying are representative of your target audience. They will design qualitative research that supplements quantitative information to provide a complete picture of your clients and prospect customers, their preferences, willingness to change behaviors, etc.

Then, they will deliver interactive dashboards that combine visuals with real-time data. Top analysts will have experience in data visualization and presenting data in graph or pictorial format to support confident, data-driven decisions.

The right-fit data consultant will help you make sense of AI, machine learning and customer analytics to support you in acquiring new customers. By digging through all the data and optimizing the information, they will help you understand your prospects’ needs at any point on the buying journey. Sophisticated machine learning will improve your chances of connecting and converting sales using the right message at the “moment of truth” purchase decision. Through predictive and prescriptive modeling, you can continue nurturing relationships to gain the full CLVs from your newly acquired clients.

Sources:

  1. Customer Loyalty: Using Data to Keep the Love Alive,” Experian
  2. Omnichannel in B2B sales,” McKinsey & Company

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