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Platform > Customer Experience > Customer Analytics

OMNICHANNEL CUSTOMER ANALYTICS SOFTWARE

Tune in to every word, on every channel

Our omnichannel analytics engine pores over every call, mention, post, chat, text, and email to understand the root cause of customer friction (or delight) and deliver real-time insights to every team in the organization.

Phone with alert showing an emergency issue detected for call volume

Go everywhere your customers are, without going anywhere

If customers are getting in touch, we capture it all. Calls, chats, posts, mentions, and everything in between — it all comes in to one platform where it’s analyzed by our industry-leading customer analytics tools to surface critical business insights.

Feedback from all different social media channels Feedback from all different social media channels

Human-level
understanding
meets machine-level
scalability

Get a deeper understanding of every customer with a speech and text analytics engine specially tuned to industry-specific terminology in over 20 languages. Powered by Natural Language Understanding (NLU), it surfaces customer sentiment, effort, emotion, and intent in every interaction, so you know what your customers really need.

Phone showing sentiment analysis from contact center chat

Deliver the right experience to each customer, every time

Tailor every touchpoint – from agent interaction to digital journeys – based on automatic intent detection, each customer’s past activity, and individual preferences.

With a 360 degree view of each and every customer, you’ll know exactly what to do next — which channels to reach out on, which rewards they’d prefer, and even which products and services they’ll buy next. Exactly what you need to deliver truly personalized customer experiences at scale.

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Make every action the right action

Uncovering insights is only half the battle – it’s what you do with that insight that counts. Combine omnichannel analytics with xFlow — our automated action engine — to notify the right people, raise tickets, and close the gaps, using each customer’s past interactions, sentiment, intent, and behavior to trigger action in the right context.

Response automations

Deliver unrivaled experiences and
support with omnichannel analytics

Fuel your CX transformation across the organization


Contact Center

Understand customer intent, reduce customer effort and coach agents to be their best.

Product

Find and fix product issues, inform product roadmap and put the customer at the heart of your product experience.

Digital

Identify common points of friction, increase digital adoption, personalize digital journeys

Marketing

Understand the leading indicators of brand health by bringing unsolicited data like social and share of search into your brand tracking

Enterprise Grade

One platform –
safe, secure, and trusted

  • FedRAMP, HITRUST, and ISO 27001 certified + robust governance controls, GDPR compliance, and data privacy features
  • Comply with GDPR and other privacy laws by easily enforcing what customer data is collected, stored, or deleted to ensure your customers’ privacy is never compromised
  • Easily connect to your existing technology with 100+ pre-built connectors for seamless data integrations
  • Get all the support you need to become an experience leader with our expert team of XM scientists, implementation, engineering, and support specialists

Customer analytics FAQs


Customer analytics is a technique used by organizations to translate data on customers’ behavior, activity, sentiment, and more into insights the organization can use to inform its decision-making. It’s a broad category that applies to the analysis of any type of customer data, although the best-in-class customer analytics programs are those that can combine operational data (eg purchase behavior, website activity, average spend) and combine that with experience data (eg NPS, customer satisfaction, website feedback etc.) — when analyzed together as a single data set, organizations can uncover the key drivers of customer outcomes like repeat purchase, and get a better understanding of how the experience they deliver impacts the company’s bottom line.

In today’s consumer landscape, where customers interact with companies using a range of different channels, an omnichannel customer analytics tool is essential. It pulls together data points from every channel so companies get a complete picture of what’s happening with every customer, regardless of what channels they use, so they can identify points of friction along the journey and identify opportunities to improve the experience and therefore have a positive impact on the company’s growth.

Customer analytics typically involves using a mix of statistical tests such as key driver analysis, and multivariate regression to identify the relationship between two or more variables (eg how does customers’ feedback for how easy a website is to use, impact the likelihood of them returning to buy from you again). The best customer analytics tools automate these complex analyses and translate the results into plain English, enabling business users to act on the insights without having to have a deep understanding of statistical methods.

Learn more about the customer analytics
Omnichannel customer analytics is a technique — usually provided by a software platform — that brings together customer data from a wide range of channels, and surfaces key customer insights at the customer (as opposed to the channel) level. This is in contrast to point-to-point customer analytics tools that analyze what’s happening on a single channel. In today’s consumer landscape, omnichannel analytics are essential as customers will use multiple channels in any one interaction with a company, and it’s only by looking at the complete journey that companies can see the full picture of what’s happening.
There are multiple types of customer analysis. First there’s behavioral analysis, which looks at operational data such as clicks, visits, purchase behavior etc. to give companies an understanding of what customers are doing. Then there’s experience analysis, which looks at data on how customers feel — so their sentiment and emotions at each stage in their journey. When companies combine the two types of data set, they’re able to see both what customers do (operational data) and why they do it (experience data), giving them a better understanding of where to focus their efforts to impact key business metrics like repeat purchase, average spend, loyalty etc.

Both types of customer analysis can exist at a channel level (eg a website, store, or contact center), or at an omnichannel level, where data and insights are gathered across multiple channels to give a more complete picture of a customer’s total experience with a company.
Call center analytics is a type of customer analytics that is limited to gathering and analyzing data in a call center including operational metrics like Average Handling Time or First Call Resolution. Today, most organizations prefer the term ‘contact center’ as it more accurately reflects the vast number of channels they use to interact with customers. In these companies, omnichannel analytics are essential as they bring together data from sources like email, SMS, chatbots, social media, and much more with more traditional call center analytics to give companies more accurate insights into customers’ needs, enabling them to better tailor their service to them.