Top Trends in Customer-Facing Analytics

Top Trends in Customer-Facing Analytics

Overview

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Incorporating customer-facing analytics into your products helps you analyze user behavior, identify customer needs, and improve CX. But customer needs constantly change, so you need to keep up with the latest trends in customer-facing analytics.


What Are the Top Customer-Facing Analytics Trends?

The three leading trends in customer-facing analytics are:

  1. The shift from traditional business information (BI) tools to embedded analytics
  2. Self-service analytics for end users
  3. Customer-facing analytics as the core of CX

To understand the impact of customer-facing analytics, let's discuss each trend in more detail.

Trend 1: The Shift From Traditional BI Tools to Embedded Analytics

Traditional business intelligence uses structured data to analyze past performance, manage ongoing operations, and plan goals.

Traditional BI tools include everything from simple spreadsheets to databases to complex analytics systems, like Domo and Yellowfin. While these tools provide data that can inform decision-making, they're limited in terms of speed, security, and workload.

For example, traditional BI solutions make you open a separate tool — like tableau — to pull data from a database.

Embedded analytics is different.

What Does Embedded Analytics Do for You?

Embedded analytics addresses the limitations of traditional BI.

First, the user is already in their tool of choice (e.g., Salesforce or Notion) and has access to massive amounts of data in one space.

Second, embedded analytics is faster, more secure, easier to use, and more scalable than traditional BI. Here's how:

  1. Speeds up the data-analysis process — You don't have to open different tabs
  2. Makes data more secure — It prevents unauthorized users from accessing data they shouldn't
    1. With traditional BI, users can access just about anything in the database because it's designed for a narrower group of users
  3. Displays contextual data — The right users get the right data at the right time
  4. Fixes workload bottlenecks — It doesn't limit users to data scientists
  5. Makes data analysis easier — UI and UX is designed for non-specialists. (Traditional BI is designed for data experts)

Let's take MedMe Health as an example. This company uses Explo's embedded solutions to show pharmacies statistics about different appointment types. Easily understood charts and data filtering help clients plan upcoming schedules, sort appointments by status and type, and review patient activity.

MedMe Health’s Appointment Metrics | Explo
MedMe Health’s Appointment Metrics | Explo

Trend 2: Self-Service Analytics for End-Users

With self-service analytics, users don't have to be data experts to access and analyze data. For that reason, self-service tools are growing in popularity — especially in the manufacturing, retail, financial, and travel industries.

For example, Tydo — a company that organizes complex data into rich and intuitive dashboards for DTC (direct-to-consumer) brands — implemented self-service analytics using Explo. Their dashboards show difficult-to-calculate mission-critical metrics in a clear, concise way.


What Does Self-Service Analytics Do for You?

  1. Automates your business — Analysts and developers can focus on creating products. They don't have to spend hours preparing and analyzing customer data because users can get the data they need
    1. The UI is easy to navigate and understand
    2. Well-designed dashboards illustrate data and complicated information clearly
    3. Strong data visualizations make it easy to read charts (even for those who aren't analysts or data experts)
  2. Empowers users to strategize — Easy-to-read data shows customers what's working and what's not. This ultimately helps them make better decisions
    1. For example, businesses involved in content creation can analyze user engagement and decide what content will draw more visitors to their sites
  3. Saves customer time — Users have instant access to relevant data

Trend 3: Customer-Facing Analytics as the Core of Customer Experience (CX)

Customer-facing analytics shows you what your users want. Implementing them helps you tailor your products, landing pages, or marketing campaigns to individual users.

For example, Goldcast used Explo to create an events dashboard that automatically brings necessary data together — without making users conduct separate analyses or manually coordinate multiple tools. Goldcast shared pre- and post-event analytics with clients to boost marketing effectiveness.

What Does Customer-Facing Analytics Do for CX?

Customer-facing analytics improve user experiences. How?

  1. Makes the UI customizable and personalized
    1. Customers can manipulate data directly from their dashboard and access/present data insights however they want
    2. Good UI results in positive UX
  2. Simplifies data and technical information
    1. Easy-to-read dashboards make data easy to understand. (Your customers will thank you for that!)
  3. Improves customer engagement
    1. Through quick access to contextual data, users can find the answers they need and make their own decisions
    2. Customers feel like data experts (even though they're not)


The Top Trends in Customer-Facing Analytics Aren't Slowing Down

Here's the bottom line: Customers want a dashboard they can navigate easily. Utilizing self-service user-facing analytics (and understanding analytics trends) levels up your UX and gives end users what they want.

Explo provides customer-facing analytics for any platform. Our dashboards are designed for your customers and engineered for simplicity. To learn more, book a demo today!

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