Definition
Data enrichment
Data enrichment means completing a prospect record with the information it lacks: work email, phone number, company size, industry, exact role, recent news. In B2B it helps you target better, personalize messages and reach the right person on the right channel, as long as the data is accurate and fresh.
By Mo Alani, founder of MimikFlow
What is data enrichment?
A prospect record often starts small: a name and a company, or a LinkedIn profile URL. Enrichment adds what you need to act: contact details (email, phone), company information (industry, headcount, revenue, tools in use) and context (a recent role change, hiring, a funding round).
The term covers two practices. One-off enrichment, when you complete a list before a campaign. And continuous enrichment, when records update over time, because people change jobs and companies grow.
Enriched data only has value if it serves a decision: who to write to, on which channel, with which angle. Piling up fields that no message ever uses costs money and brings nothing.
Where does enriched data come from?
Enrichment tools combine several sources: public information (company websites, registries, public profiles), databases built by specialized vendors, and inferences, such as the likely format of an email address based on the company's domain.
That last category calls for caution. A guessed address is not a verified address. Good tools test the address before delivering it and show a confidence level. Writing to invalid addresses raises your bounce rate and damages your domain's reputation.
Official company registries give reliable information about businesses, such as activity, declared headcount and address, but nothing about the people who work there.
What is data enrichment used for in prospecting?
First, targeting. Knowing that a company has 40 employees, is hiring three salespeople and just raised money lets you put it at the top of your list, or drop it if it falls outside your target.
Next, personalization. A message that mentions a precise, verifiable fact about the person or their company stands out from generic outreach. The fact still has to be right: quoting two-year-old news or attributing a post to the wrong person does more harm than good.
Finally, channel choice. A verified email or a known number lets you continue the conversation elsewhere when LinkedIn is not enough.
How do you measure enrichment quality?
Three indicators are enough. Coverage: out of a hundred records, how many get the information you are looking for? Accuracy: on a hand-checked sample, how many are right? Freshness: how old is the information?
Accuracy matters most and is the least published. Check a sample of twenty records yourself before paying for a large volume. A provider that covers 90% of records with frequently wrong data costs you more than one that covers fewer records correctly.
For emails, watch the bounce rate of your first sends: a high rate points to guessed rather than verified addresses.
Which rules apply to enriched data?
Enriching records about people means processing personal data. In the EU, the GDPR applies. In France, the data protection authority (CNIL) accepts B2B prospecting on the basis of legitimate interest when the message relates to the person's professional activity, provided they were informed that their details could be used and can object simply and at no cost.
In practice: make sure your provider can explain where its data comes from, only enrich what your prospecting uses, honor any objection immediately and keep a list of people who no longer want to be contacted. This is not legal advice: for a specific case, consult a legal professional.
How does data enrichment apply to LinkedIn?
On LinkedIn, the profile itself is the first source: role, company, background, recent posts. It is often fresher than any database, because the person updates it themselves.
MimikFlow reads each prospect's profile before checking it against your target and writing to them. It also spots dated signals, such as a new role, hiring or a funding round, and never cites a fact it cannot verify. When a prospect accepts your invitation, their email address is retrieved when it is available, and the first message starts from what their profile actually says.
What does it look like in practice?
Example
Example: a list of 200 accounting firms
Made-up numbers. An agency prepares a campaign aimed at 200 accounting firms. Before enrichment it has names and websites. After: each firm's headcount, the managing partner's name and their LinkedIn profile. It drops the 40 firms with more than 50 people, outside its target, and finds that 25 firms are hiring an accountant. Those move to the top of the list, with a first message that starts from the hiring rather than from a presentation of the agency.
Still have a question about Data enrichment?
- Is data enrichment legal?
- Yes, within a clear framework. In France, the CNIL accepts B2B prospecting on the basis of legitimate interest if the message relates to the person's job, they were informed and they can object. You must be able to explain where the data comes from. This is not legal advice.
- What is the difference between enrichment and scraping?
- Scraping means automatically extracting data from a website. Enrichment means completing a record, whatever the method. An enrichment tool can rely on databases, public sources or verification, not necessarily on scraping.
- Should you enrich every prospect?
- No. Enrich the ones you will actually contact, and only with the information your messages will use. The rest costs money without paying back and adds responsibility for data you do not need.
- How often should enriched data be refreshed?
- It depends on what the data is for. Contact details and roles go stale as people change jobs, so check them before each campaign rather than trusting a record that is a year old. Company data such as industry changes more slowly.
Which terms should you read next?
- CRMA CRM, short for customer relationship management, is software that centralizes information about your prospects and customers: contact details, conversations, open deals, next actions.
- Buying signalA buying signal is an observable, dated fact suggesting that a company or a person needs your offer right now: a new hire, a new role, a funding round, a reaction to a post.
- Intent dataIntent data is the trail of online activity suggesting a company is interested in a topic: pages viewed, content read, comparison sites visited, searches.
- GDPR and B2B prospectingUnder the GDPR, prospecting professionals does not always require prior consent.
- Personalization at scalePersonalization at scale means adapting each prospecting message to the person who receives it, across hundreds of prospects, without writing every message by hand.
- Lead scoringLead scoring means giving each prospect a score to decide who to contact first and who to set aside.
Where can you go further?
Want MimikFlow to handle it?
MimikFlow finds your prospects, writes the first message, follows up and replies until the meeting is booked, within your LinkedIn account's limits.