Acing Behavioral Analytics for Building Customer Loyalty

According to Forbes, the probability of a business selling to an existing customer is 60-70%, whereas the probability of making a sale to a prospective new customer hovers between 5-20%. Further, it’s been shown that the cost of acquiring a new customer is five to 25 times more than retaining an existing customer.

There’s a clear financial incentive for businesses to retain customers. Yet increased competition and globalization means that customers have more access and freedom of choice than ever before. As technology opens the digital borders for customers and removes geographic barriers, analytics also provides a key tool for building customer loyalty.

The use of behavioral analytics makes it possible to track users, meet them at various touch points along the customer journey with answers to their needs, and tailor communication based on their likes and previous purchasing history. When a brand or company can engage with their customer base on an individualized basis, it makes it possible to deepen the relationship and promote brand loyalty. As Steve Jobs said, “Get closer than ever to your customers. So close that you tell them what they need well before they even realize it themselves.” During a time when leisure spending may be dwindling because of economic difficulty owing to the global pandemic, rewarding customers and providing them with offerings that you know they want (based on analytics) can make all the difference in retaining their business.

Making the Best Use of Behavioral Data

Behavioral analytics is the information a customer leaves behind when they are shopping online or browsing a website or application. Data points can include: the duration of time they spend on a page or product, when they opened the app, how they arrived at the website, what they viewed, etc.

Having a record of these events can help to provide a visual representation and answers as to what a user’s level of engagement is, their conversion rate, and their lifetime value. It allows marketers to understand what prompts the customer to take an action or make a purchase.

Behavioral data consists of:

• Registered data: Data that’s stored in a marketing automation tool or CRM
• Voice of the customer: Feedback from the customers gleaned from surveys, focus groups, workshops, social media listening, etc.
• Observed data: Data that shows how customers behave on websites or platforms which provides insight into their interests and reactions to messages/offerings

Businesses can collect, store, transform, utilize, and visualize these data points by using data management platforms and marketing automation tools. With this information and knowledge, they are able to provide customers with:

• A personalized user journey
• Clearly defined key performance indicators that can be measured continuously and in real-time
• A robust way to retrieve analytics, track events, and plan proactively

With customer data, developing personalized marketing plans is feasible. With the right software solution, marketers have access to the data they need, when they need it. The data allows for personalized recommendations, targeted offers, segmented email messaging, and more.

All of these capabilities can aid in providing exceptional customer service, increasing customer retention, and growing sales. A study by McKinsey found that 35% of Amazon’s revenue comes from its recommendation engine that operates by collaborative filtering. Thus, Amazon is able to perceive and predict what a customer may want by using behavioral analytics that compares each customer to those with similar user profiles. Then, the engine suggests products that similar customers have already purchased, thereby increasing the likelihood of conversion (making a sale).

Another great example of a company acing the brand loyalty game is Spotify. The leading paid subscription music provider is hyper-focused on personalization and the individual customer journey. Spotify relies on artificial intelligence and big data to provide custom listening recommendations, a group listening feature to share experiences with friends (which was recently introduced during the pandemic), among other distinctive features. Prophet’s Brand Relevance Index states that 80% of customers are more likely to be loyal to brands that find ways to stay relevant in their lives, which Spotify is clearly getting right.

With access to data, marketers and businesses can segment their users and provide solutions according to their needs and where they are along their user journey. When it comes to brand loyalty, retention is one of the key performance indicators (KPIs), which is the opposite of customer churn (or the loss of a customer). Netflix provides a prime example of how to build brand loyalty and reduce customer churn through the use of data.

With behavioral analytics, Netflix is able to segment their customers based on usage. They then set a threshold for the minimum amount of content they know a user needs to consume in order to continue paying for their subscription. For customers whose usage is falling below the minimum amount, they become categorized as “at-risk” of stopping the service. Netflix then applies this insight with their algorithm to promote content that is specifically based on the user’s previous viewing history. This way, Netflix can customize what each user sees when they open Netflix as to maximize engagement and reduce the risk of losing said customer.

Marketing isn’t a guessing game. It’s informed by actions and data that records each customer event. An Accenture Pulse Survey reports that 91% of consumers are more likely to shop with brands that provide offers and recommendations that are relevant to them. Businesses that can understand what a customer wants (even sometimes before they know it themselves) can capitalize by doing so. Using data and analytics, marketers can trace a user or customer’s journey to build profiles that showcase the customer’s thoughts, sentiments, attitudes, probable actions, etc.

Behavioral analytics and technological advancements are transforming raw data into valuable insights that help marketers and business leaders direct their business decisions. For businesses who want to leverage behavioral analytics, there are many software solutions to choose from on the market. Some examples of business intelligence and analytics software include: Sisense, Alteryx Analytics, and Mixpanel, to name a few. These tools are enabling businesses to master personalization and customized marketing, which boosts customer engagement, satisfaction, and thereby, retention (and by extension, brand loyalty).