Using Analytics to Improve Customer Engagement: The Ultimate Handbook

Building strong relationships with your customers is immeasurably important for the success of any business. A leaky funnel, i.e. a funnel with unhappy customers that churn too often, spells certain death for a business.

‍

Given this significance, certain customer engagement strategies have been developed by industry leaders deploying different human behavior studies. And it looks like they have been paying off — businesses that invest in customer engagement have seen a 67% boost in revenue.

‍

However, how do you build these engagement strategies if one were to ask? One option is based on your gut feelings about your business and customers. This is not a bad start, but it wouldn’t be enough. It is incredibly important to be data-driven and rely on tangible insights to assess customer interest and plan strategies effectively. Not just because data is irrefutable but also because when creating a one-to-many strategy, human behavior can vary drastically, and the risk of basing your plan on an anecdote can be too high.

‍

Leaders and businesses trust customer engagement analytics to provide these data points and insights. As a quick intro, customer engagement analytics is a sub-branch of business analytics that provides insights into customers’ buying behavior and sentiments. It can help you gain insights into patterns in customer interactions, outliers, and untapped opportunities.

Understanding Customer Engagement Analytics

Every time your users interact with your product, they take certain actions that your system records. Customer engagement analytics dives deeper into these customer interactions and churns out actionable, data-driven insights for you. These tools help you track and analyze customer behavior across different stages of the customer journey and slice and dice that data in various ways.

‍

Further, it can also decipher user sentiments to share predictive insights about your product demand and what you could expect. It is then fairly clear that using analytics to understand customer engagement makes it simpler to uncover patterns and pain points within your customer journey and fine-tune them — eventually helping you build excellent customer experiences.

‍

Customer engagement analytics offers a detailed, 360-degree view of customer behavior. It enables you to:

‍

• find out who your customers are
• what they do
• what are their requirements
• how they are engaging with your product
• when is a good time to reach out to and upsell

‍

These insights help you build personalized experiences for your customers and ensure they are happy and satisfied. Benefits? Promoted customer loyalty and more revenue and revenue channels for your business.

‍

Role of Analytics in Customer Engagement

‍

First, an analytics system collates different structured and unstructured data across channels. Then, it cleans the data and presents it as easy-to-understand visualisations to enable data-driven decision-making. In the case of customer engagement as a problem statement, here are a few detailed ways analytics can help you:

• Delivers Personalized Experiences

Personalisation stems from a deep understanding of your users. Analytics provide detailed insights into customer journeys and preferences, helping you create hyper-personalised experiences and boost their engagement and satisfaction.

• Encourages Repurchases

You can also leverage analytics to better understand your customers’ (or a segment’s) preferences and needs. This allows you to discover opportunities to promote additional offerings and target existing customers with tailored offers to increase repeat purchases.

• Reduce Customer Churn

Analytics helps you discover the root causes behind customers' problems. It throws light on what leads to their dissatisfaction. You can then take proactive measures to improve or change customer experiences and retain these customers, thereby reducing churn.

How to Create Your Data-Driven Customer Engagement Strategy

Data and analytics lie at the heart of any strategy. An excellent and data-driven framework here will help you track customer behavior, feature usage, and overall product engagement.

‍

Here is a step-by-step guide to help you incorporate analytics into your customer engagement strategy.

#1. Build Personalised Customer Onboarding Experiences

An engaging onboarding process sets the tone for building customer relationships with your product. It demonstrates the true value of your product to your customers, educates them on how to use it, and offers any necessary support.

‍

Devise a personalized onboarding process for your customers that covers their initial journey with your product — from sign-up to the product's first use. Build an interesting welcome flow using visually appealing welcome screens. Embed micro surveys to tailor your onboarding process to customer requirements. 90% of companies leverage welcome screens to greet new customers, while 76% utilize micro surveys to provide interactive welcome experiences.

‍

Personalized onboarding makes your customers feel cared for right from the beginning. Depending on your customers, opt for high-touch or low-touch onboarding models for data-driven customer engagement. High-touch onboarding is a hands-on approach to guiding customers. For example, 1-1 calls, dedicated account manager, onboarding meetings, and more. At the same time, low-touch onboarding follows a self-serve approach. It includes guided product tours, onboarding checklists, gamified experiences, a knowledgeable help center, and more.

‍

For instance, Canva provides explicit instructions, asking customers to choose what they would use the tool for. This helps them tailor their onboarding process to customers' needs and offer personalized design recommendations.

‍

Moz is another example that leverages contextual tips to introduce premium features to customers and onboard them.

‍

#2. Segment Customers with Personalization

Segment your customers based on shared characteristics like demographics, location, and behaviors. Acquire a deep understanding of their intentions, habits, and preferences. Identify common behaviors within these groups to predict purchasing habits and personalize communication to target marketing messages effectively.

‍

Segmenting customers enables you to develop a customized strategy for engaging with customers rather than using a generic solution. By recognizing the unique needs of each customer group, you can design specific communications, provide personalized deals, and develop a product that meets their needs. It also allows you to identify power users, inactive ones, and users at risk of churning to create different marketing strategies for cementing customer relationships.

‍

In Houseware, you can create cohorts with common characteristics to monitor how each cohort interacts with your product over time. Dig deeper into the intricacies of their behavior to observe changes in their engagement levels. Leverage this data to build targeted strategies for increasing engagement and enhancing customer experiences.

‍

#3. Set Behavioral Triggers to Boost Engagement

Monitor interactions more granularly to gain deeper insight into customers' journeys. Track your customers' behavior inside your product and evaluate their actions.

‍

Houseware offers intuitive tools to provide a comprehensive view of the customer journey. Leverage the Flows feature to identify the paths your customers frequently take to carry out specific actions within your product. Flows offer powerful visualizations for monitoring your customers' actions. They also help you spot potential areas of friction in your product experiences and identify drop-offs or unsuccessful behavior without any hassles.  

‍

Use this data to identify engagement touchpoints and build a series of workflows that encourage customer engagement. For example, suppose you notice customers dropping off before enrolling for a product training session. In that case, you can craft a product engagement plan highlighting the benefits of product training and motivating them to sign up.

‍

Similarly, you can use Houseware Funnels to track events that lead to customer conversions and set behavioural triggers. For instance, if a customer checks out a premium feature of your product, you can automatically display a feature tutorial video after a specific time.

#4. Utilize Predictive Analytics to Spot Trends

Observe and identify patterns in customer behavior and interactions with your product. Visualize and analyze key product metrics and monitor how those values change over time. This will give you thorough insights into the objective metrics and quickly identify trends and anomalies for informed decision-making.

‍

Trends in Houseware reveal patterns within your data and help you identify the trends governing the same. While an upward trend indicates a steady increase, a downward trend suggests a value decline.

‍

Further, it leverages predictive analytics to observe the current and historical customer behavior data and predict future behavior. For example, if you monitor how your customers use your product every month, the trends report will depict trends in product usage. It will also help identify popular features and provide inspiration to develop them further to deliver more value to your customers.

‍

Tracking customer engagement patterns allows you to predict future actions and modify your tactics to align with your customer's needs and desires.

#5. Collect Customer Feedback to Enhance Product Experiences

Utilize customer feedback to assess how customers perceive your product. Create interactive surveys to gather their experiences. Analyze their sentiments for valuable insights to increase customer engagement.

‍

Hear out your customers and their opinions. Pay attention to their emotions for better understanding. This will enhance communication and help you better understand your customers' pain points.

‍

Prioritize your marketing efforts based on what type of customers you are dealing with. For example, you ought to make detractors feel heard and try to solve their problems. Remember, the goal is to address customers' issues on time and ensure they are satisfied with your product.

‍

Track These Top Metrics for Data-Driven Customer Engagement

If you want to track and monitor your customer engagement, here are the top 5 essential metrics you should look at:

• Product Engagement Score

Product engagement score is a metric that measures customers’ engagement with your product. It is a crucial metric that helps you identify upselling and cross-selling opportunities and fight churn.

• Customer Satisfaction Score

The customer satisfaction score measures how satisfied customers are with your product. It indicates whether your product has met, exceeded, or disappointed their expectations.

• Customer Lifetime Value

Customer lifetime value is a metric that evaluates the total value a customer brings to your business. It is the revenue a particular customer is projected to generate over their lifetime as your customer.

• Customer Churn

Customer churn allows you to assess the number of customers your company loses within a given timeframe. It is generally a percentage and used as a churn rate.

• Net Promoter Score (NPS)

Net promoter score is a metric designed to help you measure the likelihood of your customers recommending your product to others. A high NPS indicates customer satisfaction and willingness to promote the product.

Final Thoughts

It is established that customer engagement analytics can be immeasurably helpful in monitoring customer interactions and improving their lifetime engagement with your product/business. With Houseware as your product analytics tool, you can correctly analyse, utilise, and capitalise on your customer engagement data — without being dependent on outdated tools or your already-busy analytics team.

Book a demo to see how you can exponentially improve your customer engagement with Houseware.

FAQ

How does big data analytics improve customer engagement?

Big data analytics provides crucial insights into customer behavior data. It helps you understand their behavior, interests, and preferences. These insights equip you with the information to design personalized strategies, build positive customer experiences, and foster long-term relationships.

‍