What Is Customer Intelligence? A Guide for eCommerce
- Treat customer intelligence as a process: collect customer data, segment it, analyze it and turn it into actions.
- Combine four data types: behavioral, transactional, psychographic and demographic. Each answers a different question.
- Separate the scopes: business intelligence looks at the whole business, customer intelligence looks at the customer.
- Collect data from five sources: interviews, surveys, your CRM, your support tool and website behavior.
- Check that a segment survives after a promotion ends before you build a strategy on it.
- Report on a fixed routine and read the data by segment, not only as totals.
What is customer intelligence? It is the process of collecting and analyzing customer data to understand what your customers expect, how they behave, what frustrates them and what makes them buy. Online stores that use it well attract the right customers, keep them longer and earn more from each one.
This guide explains which data customer intelligence uses, how it differs from business intelligence, and how to collect and use it. It is part of our guide to customer segmentation models. Omniconvert Commander (formerly Nexus), the AI eCommerce growth engine, does this work for online stores; the last section shows how.
What is customer intelligence?
Customer intelligence (CI) is more than a database. It has four core parts:
- collect and manage customer data;
- divide customers into groups that behave alike, through customer segmentation;
- analyze the data in each group;
- turn the analysis into actions your teams can take.
The last part is the one that matters. An insight is defined as a finding that changes a decision. "Most repeat buyers came from email" is data. "Move budget from paid social to an email win-back flow for this segment" is intelligence.
What data does customer intelligence use?
| Data type | Question it answers | Typical sources |
|---|---|---|
| Behavioral | What do customers do on your site? | Analytics, cookies, heatmaps, session recordings |
| Transactional | What did they buy, when and for how much? | Store orders, returns, payment data |
| Psychographic | Why do they buy? | Surveys, interviews, reviews |
| Demographic | Who are they? | Account data, checkout data, surveys |
Behavioral data shows what customers do on your website; cookies, heatmaps and surveys collect it. Transactional data comes from purchase history and feeds personalization engines the signals they use for recommendations. Psychographic data is a data approach based on psychology: it explains why customers buy, through their triggers, opinions and interests. Demographic data, such as location, employment, age, gender and marital status, helps with product decisions, for example why one group prefers product A.
Customer intelligence vs business intelligence
The two overlap. Business intelligence in eCommerce tells you which products and channels make money. Customer intelligence tells you which customers make money and why. The data often lives in the same place: a customer data platform (CDP) unifies customer profiles, and customer intelligence is what you learn from them.
Why is customer intelligence important?
- Attract the right customers: real-time and historical data show how visitors behave on your site and what they bought before. You can estimate who is likely to buy and attract customers who resemble your best ones.
- Improve profitability: when you understand customer behavior, you spend your marketing budget on the customers and offers that pay back, not on everyone.
- Find better insights: reviews, social media posts and support conversations are unstructured data full of complaints and requests. Customer intelligence turns them into fixes your customers notice.
- Keep more customers: track behavior, purchase history, location and buying patterns to see what each segment needs, then meet those needs before customers leave.
Retention is where most of the value is. Acquiring a new customer can cost 5 to 25 times more than retaining an existing one [Harvard Business Review, 2014].
How to get customer intelligence data
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InterviewsInterviews help you understand the customer journey. Unlike a questionnaire, a conversation shows tone and emotion when customers talk about your business, and it tells you more about their personality.
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SurveysSurveys reach current customers and your target audience at scale, and research groups such as the Customer Intelligence Lab at Harvard Business School study how companies use this data. Sales, marketing, distribution and customer care can all use surveys. Customer Satisfaction Score and Net Promoter Score are common formats.
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Customer relationship management (CRM)A CRM stores customer profiles, meeting notes, sales emails and calls. It helps you know your customer base and plan targeted, segmented campaigns.
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Customer supportYour helpdesk or ticketing system stores customer feedback from email, phone calls, live chat and social media.
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Website behavioral dataSite behavior shows the bottlenecks and clutter that block conversions. Test changes against it to learn which experiences suit your customers.
Data that you only collect does not help. Set a daily or weekly reporting routine, and read the data by customer segment, not only as totals.
How to use customer intelligence in eCommerce
After customer research, you have many data points. Combine them to get context. For example, the data for a group of visitors to a fashion store might show:
- Browser: Chrome
- Device: MacBook
- Location: Los Angeles
- Referrer: Instagram
- Micro-conversions: clicks on products with a "discount" badge or an "only two left" label
Read together, these points describe a segment: shoppers who arrive from Instagram on a laptop and respond to price and scarcity. Most of these referrals come from one channel, so build a segment per channel, analyze customer behavior in each one, and match your message to it.
Check one thing before you act on a segment like this: is it a customer pattern or a campaign pattern? If one Instagram promotion with a discount badge ran that week, the "segment" may only be that campaign's audience. Compare the same data points over several weeks and by first-purchase month with cohort analysis. A real segment keeps its shape after the promotion ends.
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Design your strategyEvery store has its own goals and audience. Bring together the teams that hold customer data, so you see the gaps between them. A platform such as a customer data platform or a CRM makes this easier.
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Use smart digital analyticsUse analytics tools that give you current customer data, then build one picture of each customer that leadership uses for decisions.
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Use AI where it helpsMachine learning can predict who will buy again and who will churn, which helps you improve customer experience where it matters most.
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Turn data into insightsAsk the data specific questions: which are your most profitable products, which segments buy them, and what those segments prefer. Understanding customer behavior through data analysis is how the answers reach your roadmap.
How Omniconvert Commander turns customer data into intelligence
The customer intelligence features in Omniconvert Commander help you acquire, delight and keep customers while you raise customer lifetime value and lower acquisition cost. Omniconvert Commander builds RFM segments automatically, calculates True Profit per order and per customer, and pushes segments directly to Meta Ads, Google Ads and Klaviyo, so each channel treats each customer group differently. Shopify stores can install the Omniconvert Commander app for Shopify.
Intelligence pays when it changes what customers see. AliveCor used Omniconvert to run a structured A/B testing program and achieved a 21 percent lift in conversion rate, a 5 percent lift in revenue per visitor, and 94 percent statistical relevance across their experiments [Omniconvert, AliveCor case study]. That program tested on-site experiences, not segments, but it shows the last step of customer intelligence: test the change your data suggests, and keep what wins.
Customer intelligence FAQs
Customer intelligence is the process of collecting and analyzing customer data, such as purchases, website behavior, survey answers and support conversations, to generate insights that improve customer experience, sales and business decisions. In eCommerce, it tells you who your best customers are, why they buy and what will keep them buying.
eCommerce intelligence is the wider practice of using data about your market, competitors, products and customers to make better decisions for an online store. Customer intelligence is the part of it that focuses on your own customers and what they do.
The main techniques are collecting data across channels, segmenting customers, tracking a few useful metrics, reporting on a fixed routine and acting on the findings. Together they make a customer intelligence strategy that improves sales, loyalty and customer relationships.
A customer intelligence platform is software that collects customer data from your store and other tools, connects it into customer profiles and segments, and uses analytics, often with machine learning, to show the insights. Commerce, service, sales and marketing teams then work from the same view of the customer.
Start with the decisions you want to improve, then choose the data points that inform them, mostly first-party data from your store, surveys and support tool. Set up a reporting routine, give one team ownership of the analysis, and test the changes the data suggests before you roll them out.
Omniconvert Commander is the AI eCommerce growth engine. For customer intelligence, it builds RFM segments from your store data automatically, calculates customer lifetime value and True Profit per order and per customer, and pushes segments directly to Meta Ads, Google Ads and Klaviyo.
Pick one question your data should answer this month, for example which customers bought twice and then stopped. Pull the data from your store, your survey tool and your support desk, and look at that group as one segment. Write down one change you will make for them, test it, and measure the result.
Repeat that loop every month and customer intelligence becomes a habit, not a project. When the questions outgrow your spreadsheets, see how Omniconvert Commander builds the segments for you.
Turn customer data into decisions
Omniconvert Commander builds RFM segments automatically, calculates CLV and True Profit per customer, and pushes segments to Meta Ads, Google Ads and Klaviyo.