What is data enrichment?

Data enrichment is the process of adding value to your already existing data by providing supplementary information and context. The additional data can be retrieved from another data source within the same organisation or a third-party application altogether. 

For example, suppose your app displays a username or a unique identification number. You can easily refer to the details of the end-user, such as their actual name, associated phone number, and email address. This helps sales and customer success teams communicate with users using their real information. 

What makes data enrichment so useful is that it gives more insight into the customers you are dealing with. Especially when information is scattered and fragmented, data enrichment plays a key role in producing comprehensive results.

Baremetrics is here to enrich the information you know about your customers. You should sign up for the Baremetrics free trial and start learning about your customers. 

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Data enrichment for your customers at Baremetrics

At Baremetrics, there are two features that can be used to enrich your customer data. 

The Baremetrics Tool People Insights packs your customer profiles with information about your customers. This tool will autofill your customer profiles with their location, real names, and emails. It will also make it easy for you to track every charge, failed payment, and transaction history of your customers.

The Baremetrics Augmentation tool merges your business metrics with external data so you can see more about your customers. For example, it connects the NPS score a customer gave you with that customer’s profile – so you know exactly how satisfied they are when you talk to them next.

You can also correlate the number of times a customer has communicated with support to their NPS score or their churn rate.  

How can you get enriched data on your customers?

There are several third-party tools available for Data Enrichment. The important question before opting for any tool is what kind of data are you looking for? 

Depending on the type of data you have and your purpose, you will use different tools. For example, if your data is in a spreadsheet, there will be data enrichment tools like Clearbit that can take an input of .csv and return a .csv of fully enriched data.

The trouble with that is how to apply the enriched data when it’s in .csv form. If your data is directly in-app, and you are applying it in-app to improve your customer experience, then you may want to use a tool like Baremetrics that can integrate directly with your customer-experience toolkit. 

It also depends on the type of information you are looking for. For example, if you are developing a food delivery software, then the conventional information about gender or marital status does not make a good targeting parameter. Past purchases or geolocations will help you target your customer better. 

What kinds of data can enrich your customer profiles?

To get started, let’s look at the different kinds of data you can use to enrich your customer profiles.

1. Identity data 

Identity data refers to data about a person’s identity, such as name, phone number, and email. This kind of “user research” identifies what kinds of people are interested in your products and services. 

The basic data is usually collected when a user signs up on your website. The alternative way is to use a third-party tool to merge the scattered data across the Internet and make sense of it. For example, pulling emails from public places that match with the name provided.

You can easily collect this kind of data on your own by google searching the information related to the individual you want to enrich. However, on a scale of 100s of people, it becomes extremely time-consuming. If you need to do it on a wide scale, we definitely recommend using a tool to get it done!

2. Socio-economic identifiers

While conventional data pave the way to targeted marketing, it is the socio-economic identifiers such as salary, position, industry, company size, and job title that allow you to really get inside the head of your customer or lead. Being able to identify the area of work someone indirectly affects what you should talk to them about. 

For example, if you know your contact is in accounting, you’ll most likely talking to them about the billing and the consumer contracts of your product. 

If a free trial earns less than the average salary for a given country, it is unlikely that they will be interested in investing in a premium or a high-end version of your product/service. On the other hand, showcasing a reasonable plan with limited yet exciting features could increase the chances of conversion as money is a limited resource in this scenario. 

If someone is from a large company, money will likely not be an issue. Such a prospect is more likely to be interested in locking in a 3-years contract at a low monthly cost. 

Knowing about your prospect’s situation is critical in getting the messaging right.

3. Behavioural data

Behavioural data includes information about the customer’s browsing habits, buying habits, and social media activity. Such data helps in assessing a customer’s journey from searching to buying. If we have this information, the targeted communication can then help in more conversions. Eventually, it leads to more profit. 

The People’s Insights feature offered by Baremetrics serves as an example for this category. It offers customer-rich profiles which track your customers and knows all of their in-app behaviour. 

People Insights keeps track of failed payments and every transaction made through a customer’s profile. 

In-app behaviour is extremely important for both sales and customer success. Knowing what your customer is or isn’t doing in-app can lead to better customer care.

4. Qualitative data

Now that we have the basic information and the numbers associated with a customer’s account, it is time to find out what opinions your customers hold. This includes any pre-existing bias, reviews or feedback they might have left on social media accounts regarding your products or any similar product in the market. This gives an insight into what their preferences are and how they actually feel about your product.

Take the skin-care industry for an example. Lately, the field has been growing at an exponential rate with a wide range of companies and tons of products. Qualitative research about your customers, such as preferred key ingredients by a customer within a product, can be helpful when making recommendations. For instance, someone with an oily acne-prone skin would likely go for a salicylic acid-based product rather than, say, a heavy moisturiser designed for dry skin. While machine learning plays a significant role in extracting the sentiments out of a text or review, the results can be significantly improved if the data we’re starting with is good enough in the first place. This is where qualitative data comes into play.

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A great tool for data enrichment

While there are a number of third-party applications available on the web, Baremetrics is great for enriching data on anyone who is currently using your app. Baremetrics is a business metrics tool that provides 26 metrics for your business evaluation, such as MRR, ARR, LTV, and more. Baremetrics has further features, such as People Insights and Augmentation. With the People’s Insights feature, you can: 

1. Customise user segmentation: Separate the customers based on a given condition, such as location or behaviour.

2. Enrich customer profiles: Get notified about your customers’ location, transactions, how active they are, and much more. 

3. Handle manual subscriptions: Deleted an instance by accident? You can now add in customers manually, as well as add in customer information manually.

Frequently Asked Questions

What is data enrichment?

Data enrichment is the process of enhancing your existing customer or prospect data with additional information from third-party sources — firmographic data (company size, industry, revenue), demographic data, behavioural data, or technographic data (the tech stack a company uses). The goal is to turn a thin customer record (email + name) into a rich one that supports better segmentation, targeting, and retention decisions.

How does data enrichment work technically?

Most data enrichment runs through APIs that take a key field (email address, company domain, phone number) and return matching records from a third-party database. The enrichment provider matches against their own collected data — public sources, partnership integrations, web scraping — and appends fields to your customer records. Modern enrichment platforms refresh data continuously, so changes (job changes, company moves) are caught automatically.

What kinds of data can you enrich?

Four main categories. Firmographic: company name, size, industry, location, revenue. Demographic: contact title, seniority, role. Technographic: software stack, tools in use, technology investment signals. Behavioural: web activity, content engagement, purchase intent signals from third-party sources. The right mix depends on what you're trying to predict — sales-fit for B2B, churn risk for SaaS, expansion potential for existing customers.

Why does data enrichment matter for SaaS retention?

Better enrichment data enables better churn-risk prediction and better segment-specific retention interventions. A customer whose company just downsized 30% is a different retention risk than one whose company just raised a Series B — even if their usage looks identical in your product analytics. Enrichment surfaces those external signals so your CS team can intervene where it matters most.

Does data enrichment help with payment recovery?

Indirectly, yes. Enrichment improves segmentation precision, which helps you decide which customer segments should be in your automated dunning flow and which should be excluded (VIPs, hardship-flagged accounts, manually billed enterprise contracts). Baremetrics Recover's customer-segment exclusion feature is more useful when the underlying customer data is well-enriched, because the exclusion criteria can be specific and informed.

What's the ROI of data enrichment?

Enrichment ROI varies widely by use case. Sales-side enrichment (better lead targeting) typically shows ROI within 3-6 months via improved conversion rates. Retention-side enrichment is harder to attribute but the leverage is in identifying at-risk customers earlier. For most SaaS, the highest-ROI enrichment is firmographic + technographic data feeding into a churn-risk model, paired with proactive CS outreach for high-risk accounts.

Data Enrichment, Customer Segmentation, and Retention Leverage

Data enrichment turns thin customer records into the kind of rich segmentation source that lets you take smarter retention actions. The value isn't in the data itself — it's in the decisions the data enables: who to upsell, who to retain, who to exclude from automated outreach when their situation calls for a personal touch.

One specific application worth highlighting: enriched customer data improves the precision of automated dunning systems. Baremetrics Recover supports excluding specific customer segments from the automated flow — VIPs, hardship-flagged accounts, manually billed enterprise — and that segmentation is more accurate when the underlying customer data is well-enriched. Across 148 Baremetrics customers using Recover for dunning automation in December 2024, $1.35 million was reclaimed in a single month; the top-performing customers consistently used customer-segment-aware exclusion as part of their setup.

If you're investing in data enrichment for retention purposes, the failed-payment side is one of the highest-leverage applications. See our dunning management guide for the framework and involuntary churn guide for the problem definition.

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