In the past, marketers could get away with segmenting customers using primarily demographic and firmographic traits such as age, gender, income, ethnicity, occupation, industry, company size, geographic location, etc.

But in today’s customer-centric world, understanding your customers based on demographics isn’t enough. As Netflix’s VP of Product Innovation, Todd Yellin, said:

“It really doesn’t matter if you are a 60-year-old woman or a 20-year-old man because a 20-year-old man can watch ‘Say Yes To The Dress’ and a 60-year-old woman could watch ‘Hellboy.’”

B2C and B2B marketer alike can leverage behavioral data to solve problems and impact KPIs at every stage of the customer journey. From customer acquisition to customer retention and loyalty, leading marketers are achieving their goals by using customer behavior to better understand their customers and improve the way they interact with them.

There are three primary ways that leading companies are using customer behavior data and analytics to drive revenue.

1. Improve Customer Acquisition

As more customers travel along your path to purchase, patterns in behavior emerge that can help explain particular successes and failures, as well as why some groups of customers attain a particular outcome and others do not.

Using customer behavior data, marketers can uncover which customer journeys result in a purchase and leverage this information into campaigns that increase new customer acquisition. Whether you sell to other businesses or directly to consumers, reaching out to prospects at the right moment, through their preferred channel, with a customized offer, will help you improve customer acquisition.
Armed with behavioral insights, acquisition-focused marketers can:

• Increase effectiveness by making sure your offer timing and messaging is aligned with the most important drivers of each customer’s purchasing decision.
• Improve targeting by looking at prospects that exhibit similar behavior as your most profitable customers.
• Boost marketing ROI by focusing your resources on prospects with the highest likelihood to purchase and highest potential lifetime value.

For example, a key goal for a leading bank was to improve credit card opening rates among millennials. To understand the role that different channels played in credit card offers and their respective efficiencies, the bank analyzed customer behavior.

After integrating data from online and offline channels such as branch visits, website browsing, mobile data, email data and in-app interactions, they were able to discover the customer journeys that were most efficient at leading new customers to apply for a card.

By analyzing customer behavior, they determined that one particular offer was converting better for people who had viewed it as an email, rather than as a text message or within the bank’s mobile app. Based on this information, they created a new email campaign for those who had viewed the credit card offer and then abandoned their journey. The new campaign, based on customer behavior, contributed to an overall improvement in their customer acquisition rate.

2. Increase Customer Retention

While your customers may not explicitly communicate their intentions, they often reveal clues through their behavior. Marketers are using customer behavior data to improve their ability to identify at-risk customers and thereby reduce customer churn. By gaining a data-driven understanding of customer preferences and the best ways to reduce friction in particular situations, you can more easily identify and prioritize opportunities for improvement.

Netflix, for example, uses customer behavior to increase engagement and reduce churn. By leveraging behavioral customer data and analytics, Netflix is able to pinpoint the level of usage that a customer should exhibit each month to receive enough value to continue their subscription. If a customer’s monthly content consumption falls below that threshold, the likelihood of churn increases dramatically.

By creating a behavioral segment for all customers that fall below the minimum product usage value threshold, Netflix is able to easily identify at-risk customers, discover insights that can lead to low usage, and monitor these over time. By leveraging customer behavior data, Netflix executives have estimated that this saves the company $1Billion a year in lost revenue.

Customer retention is also particularly important for the telecom industry due to slim margins and saturated markets. At any point in the customer journey, telecom customers are only a click away from switching to a competitor if they’re not happy with the level of customer service provided. Telecom companies are now analyzing customer behavior to pinpoint problem areas such as customer care calls and analyze how to improve them or provide alternatives via self-help methods. This has resulted in improved customer satisfaction scores(CSAT) and lower cost to serve.

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3. Drive Revenue Expansion

The likelihood of converting each customer on a specific cross-sell or upsell offer may be dependent on the particular time it is offered. Customer behavior provides critical insights on which offer to show each customer and when to show it.

For example, a premium wine accessories company analyzed customer behavior to improve loyalty program registrations, increase cross-channel engagement and build long-term customer relationships, as the majority of their profit comes from repeat purchases rather than the initial sale.

The marketing team analyzed millions of point-of-sale transactions and connected them with loyalty program registrations, email responses and online behavior. They identified how the customer journey differed for various behavioral segments and discovered the optimum paths each followed from engagement to loyalty and repeat purchases. By revealing which marketing campaigns were most effective at turning their in-store customers into repeat, online customers, they were able to increase revenue from existing customers.

On the other hand, the likelihood of conversion is typically lower after a negative experience. For a customer who may have exhibited past behavior that’s predictive of a cross-sell, up-sell or repeat purchase opportunity, extending an offer immediately after a negative experience can actually do more damage.

If a retail banking customer, for example, has just resolved a lengthy customer service issue they are not likely to be very receptive at that time to a new credit card or loan offer. However, if the timing and messaging are customized based on recent behavior data (e.g. by acknowledging their recent interaction and providing a ‘special’ offer as consolation), then the conversion rate could actually increase.

Use a Modern Behavior-Based Approach to Customer Analytics

New behavior-based approaches to customer analytics have recently emerged, enabling organizations to discover valuable real-time insights about their customers and make smarter decisions, faster than ever.

One approach experiencing rapid adoption is customer journey analytics, which leverages customer behavior data to enable behavioral segmentation, customer journey visualization, journey orchestration and journey-driven KPIs.

Customer behavior can reveal valuable insights about your customers, your business, and the relationship between the two that you can’t find anywhere else—if you pay close attention by capturing, analyzing and acting on it.

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