Data and Analytics for Customer Engagement

What are analytics for customer engagement?

Customer engagement describes the interactions that form a client-company relationship. Customer engagement analytics refers to the methods and tools used to measure customer data from these interactions to assess customer health, discover preferences, and predict future behavior.

The ultimate goals of customer engagement analytics are to use these insights to increase revenue, customer loyalty, and the number of positive interactions customers have with and about the company.

Customer engagement analysis transcends buying behavior. It considers many other customer interactions that also hold insights or value for the business, like social media mentions, website visits, and customer support feedback.

Types of engagement data used

Of all business, 29.7% now happens digitally (up from just 9% in 2002). This trend means a tremendous amount of information is available for collection and analysis on both B2C and B2B engagement.

Below is an overview of the most common data sources you can bring together in an analytics platform like Twilio Engage. This centralization gives you an omnichannel view of your customers, in which you can see their behavior across all touchpoints in real time. This analysis prevents your teams from having a fragmented view of clients or, worse, not knowing whether a series of actions performed across multiple devices is from one person or two.

Website, app, and product data

Typical engagement metrics: Churn Rate, User Retention, Active Users (DAU, WAU, MAU)

Since you own these properties, they provide a wealth of first-party data on your customers, like pages visited, buttons clicked, and features used. Such information can go directly into Twilio Segment or through tools like Google Analytics, Heap, or Mixpanel to analyze critical engagement metrics like retention, churn, or feature usage.

Say you analyze product data and segment feature usage by two user personas. You then find that group A rarely uses a feature that group B uses frequently – because group A enters through a landing page without an explanation of that function. This data-driven insight leads your marketing team to adjust the landing page and, subsequently, better engage group A.

Marketing and advertising campaigns

Typical engagement metrics: Conversion, Click-through Rate (CTR), Opt-out metrics

Data from marketing initiatives can tell you about your customer’s preferences and demographics. It can even provide essential identifiers like their email address or phone number.

This information includes open, click, and conversion rates from email newsletters, ads, and campaign landing pages. With Twilio Segment, you can collect this data from tools like Customer.io, Braze, or a CRM.

Analysis of your email marketing data might, for example, reveal that a group of customers have clicked on a product in your newsletter. They then put it in their shopping cart on your site but didn’t proceed to purchase it. Your teams conclude those customers balked at the shipping price, so they follow-up with a special discount offer to this group, leading to a substantial increase in conversions.

Sales and other transactional data

Typical engagement metrics: CLTV (Customer Lifetime Value), recurring revenue, Abandonment Rate

A purchase is one of the most important engagement data points, as it signals that customers want what you offer and trust you with their money. These events can, of course, be tracked when they happen in a digital environment. But even data from physical stores can go into an engagement platform like Twilio by connecting it with tools like Stripe.

Analysis of such transactional data can lead to many insights and useful metrics. It can help you predict a customer’s future purchases and lifetime value – the total amount they’ll likely spend over your entire relationship. But you can also analyze which products customers frequently purchase together and use that information to make recommendations and product bundles, something Amazon frequently does.

When viewing “Customer Analytics for Dummies,” Amazon recommends two similar titles others often purchase when they get this book.

Customer feedback and research

Typical engagement metrics: NPS (Net Promoter Score), Feedback Response Rate

Despite all the other data sources that help you analyze engagement without bothering customers, you can – and should – ask them about their preferences and behavior, too.

To understand the emotions and motivations for people’s actions, quantitative data alone isn’t sufficient. You need qualitative information from surveys, interviews, and customer support interactions to uncover such insights.

“We measure your engagement with our product. … But we’re also measuring the engagement you have with our team. How often are you talking to your CSMs and your salespeople? How often are you writing and tickets and things like that? What about the other interactions around billing?” —Vishal Rana, Director of Product at Segment

Twilio Engage collects data from customer support interactions out of the box. Twilio Segment can work with data from survey tools like SurveyMonkey and Typeform.

Content and social media

Typical engagement metrics: Bounce Rate, Conversion, Click-through Rate (CTR)

You can gauge people’s feelings about your brand by analyzing the language they use in social posts, and which posts they share or click on from your company. You can also discover emerging (or declining) trends from this analysis.

The content you put out is another great way to learn about your customers. You’ll see which topics interest them and can prompt them at relevant moments in an article or video for their email address, a free trial, or even a purchase.

You can synthesize data from your website’s blog and social tools like Hootsuite and Brandwatch in Twilio Segment.

Why analyze customer engagement?

Loyal customers don't just stay with your company, they spend more as well. Customer engagement analysis is critical for creating and maintaining such loyalty. Platforms like Twilio Engage allow all your teams to see, understand, and anticipate customer behavior across all touchpoints with your brand in real time.

Such a centralized, omnichannel view enables you to improve every customer journey stage, whether that’s acquisition, onboarding, or retention. You might, for example, discover that a large number of customers stop engaging after the first week when they no longer receive onboarding and tutorial prompts in your app. This insight leads to a new, weekly check-in notification in your product. That prompt keeps your brand top of mind and improves long-term customer retention without being annoying.

Examining customer analytics can also help increase revenue and reduce costs. Here are some examples:

• You can use engagement insights to tweak your digital marketing campaigns to the right customers, which improves conversions and your ROI on marketing spend.

• Your customer support team spends less time handling tickets. Customer engagement analysis can predict questions your customers likely have based on pages they viewed on your site and previous support interactions.

• Your sales team gets insights to tailor and time their cross-sell and upsell tactics, which leads to more closes and fewer nos.

• You can find behaviors that foretell customer churn and intervene to prevent that, say with a special offer.

• You can distinguish high-value customers earlier in the customer journey as your analysis has revealed their typical traits and behavior. This customer segmentation allows you to shift more of your attention and resources to this audience.