Skip to content Self-serve B2B data providers like Apollo, Lusha, UpLead and ZoomInfo provide rapid access to enormous databases of companies and business contacts. Users select their filters, reveal the available details and export the resulting records. So far so good. If speed is your priority.
DataJi follows a different research model and uses quality as the priority. We source B2B contacts specifically for each client and campaign. Our researchers work from your very specific requirements, identify the relevant companies and current decision-makers, source the requested information and validate the completed records to the nth degree before delivery. Our data is guaranteed.
Sales intelligence platforms provide immediate access to existing databases. DataJi’s B2B contact data service provides freshly commissioned research built around the audience you need to reach.
Apollo, Lusha, UpLead and ZoomInfo maintain large databases containing millions of companies and contacts. Their records are collected through combinations of public information, automated processes, contributors, partner sources and internal research.
Each provider operates its own refresh and verification systems. Apollo promotes real-time verification and a database containing more than 230 million contacts. Lusha describes a daily verification process across a database of more than 280 million contacts. UpLead verifies email addresses when users request them. ZoomInfo combines automated collection with an internal research team.
Those systems update and verify records that already exist inside each platform.
DataJi begins with the current client brief. We do not begin by selecting contacts from a self-service database assembled before the project started.
The brief can include industries, countries, regions, company sizes, turnover, technologies, ownership types, job functions, seniority levels, precise job titles and mandatory data fields. Our researchers then identify the companies and people who satisfy that combination of requirements.
Fresh research takes longer than downloading an existing record. A large requirement can take several weeks because the contacts are being identified, assessed and validated for the project.
The client receives data built around the campaign specification rather than the closest results available through a set of platform filters.
Real-time email verification checks whether an address appears capable of receiving a message when it is tested. That test covers one field within a much wider contact record.
It does not establish when the person’s employer, title, department, seniority, location or company information was last researched.
The email address may appear deliverable while the associated job title is old. The person may have moved departments, accepted a different position or left the company. The organisation may have changed its domain, ownership, location or business activity.
A working address connected to an irrelevant or outdated contact remains unsuitable for a targeted campaign.
DataJi checks the relationship between the individual, employer, role and contact information. Our approach to human-verified B2B contact data allows researchers to assess information that automated database checks can overlook.
The complete record has to satisfy the agreed client specification.
Job titles vary widely between companies.
The person responsible for marketing may be called Marketing Director, Head of Marketing, Chief Marketing Officer, Director of Communications, Head of Audience Development or Head of Brand and Engagement. Similar responsibilities can sit in different departments or be divided between several people.
A database filter relies on the title and classifications already attached to each record. A narrow title search can exclude relevant decision-makers. A broad search can return large numbers of contacts whose responsibilities bear little relation to the campaign.
DataJi researchers assess the person’s actual function alongside the wording of the job title.
This is particularly important when the campaign targets a specialist industry, an unusual responsibility or a precise combination of seniority, function, company type and location.
The purpose of the research is to identify the people who perform the required role within their organisations.
A contact file can contain thousands of email addresses while providing very limited access to identifiable decision-makers.
Generic addresses such as info@, hello@, admin@, office@, sales@, support@ and contact@ usually lead to shared or departmental inboxes. They do not identify the person responsible for the purchasing decision.
A message sent to a generic inbox may be filtered, ignored, forwarded to the wrong person or reviewed by somebody with no authority to respond. The absence of a confirmed recipient also limits meaningful personalisation.
DataJi does not treat a shared mailbox as an equivalent substitute for a named professional contact.
Personal Gmail, Outlook, Hotmail and Yahoo addresses create another problem. The mailbox may work while its connection with the stated company and role remains unclear.
The address could belong to a former employee, a freelancer, a business owner or somebody unrelated to the organisation in the record. A personal account can remain active for years after the professional information attached to it has expired.
There are legitimate cases in which sole traders and very small companies use Gmail or another personal email service for business. That professional relationship should be established during the research instead of being assumed from an old record.
DataJi prioritises named business email addresses that can be connected to a current individual, employer and role.
Many corporate domains use catch-all or accept-all configurations. The receiving server appears willing to accept email sent to any address at the domain, whether or not the individual mailbox can be confirmed.
A standard email verifier may therefore return a catch-all or unknown status.
A catch-all result does not prove that the address is invalid. It means the receiving server has not provided enough information to confirm the individual mailbox during the technical test.
This is common among larger organisations that do not want external systems to identify valid employee addresses by testing different naming patterns.
DataJi’s guide to catch-all email addresses and B2B deliverability explains the limitations of standard verification and the additional research needed to assess these contacts properly.
DataJi combines technical checks with research into the person, employer, domain and likely email structure. The process is more detailed than assigning every address a simple valid-or-invalid status.
Company-level deduplication can give a misleading picture of contact coverage.
A data team may compare a new file with its CRM using company name and location. If half of the organisations already appear, the result may be described as 50% duplication.
The existing records may contain no named people or email addresses. Other records may contain generic inboxes, former employees, unrelated departments or invalid contact details.
A newly researched record for the same company may identify the current person requested for the campaign, together with the relevant job title and a validated named business email address.
In one database recently reviewed by DataJi, the client held 23,731 existing records. Thirty-five per cent had no email address and 90% had no contact name. Most of the remaining email addresses were generic or personal accounts, and at least 94% of the addresses tested were invalid.
These figures relate to that particular client database. They are not presented as an industry-wide average. They demonstrate how a large record count can conceal a very small number of usable contacts.
A company match confirms that the organisation has previously been recorded. A proper contact comparison should also examine the person, current employer, job function, title, named email address and validation status.
DataJi can provide B2B contact data enrichment when the history held in an existing CRM remains useful but the contact information needs to be completed or updated.
Where the database contains inaccurate, incomplete or duplicated records, DataJi’s data cleansing and maintenance service can identify information that should be corrected, enriched, suppressed or removed.
Deduplication remains necessary, but the matching rules should reflect what the organisation is trying to achieve.
A company name can identify possible overlap at an account level. It cannot determine whether the CRM already contains the current decision-maker required for the campaign.
Contact-level matching can use the person’s name, employer, company domain, named business email address and CRM record ID. The correct outcome may involve adding a new decision-maker, updating an existing record or replacing a person who has left the organisation.
DataJi can also compare new research against a client’s exclusion and suppression lists. This helps prevent clients from paying for contacts they genuinely already hold and removes unsubscribed or otherwise excluded recipients before delivery.
A contact should be removed because the same usable person already exists in the CRM, rather than because an incomplete company record shares the same organisation name.
Apollo, Lusha, UpLead and ZoomInfo publish strong accuracy or deliverability figures. The providers use different definitions and methodologies, so the figures should be considered separately.
Apollo currently promotes a 97% email accuracy rate. The claim relates specifically to email accuracy rather than every field in the wider contact record.
Lusha publishes 98% email deliverability and 85% phone accuracy across its global database. It also states that the figures can vary by region, with published email accuracy of 97% for EMEA.
UpLead offers a 95% data accuracy guarantee. Its published policy says customers receive their credits back when accuracy falls below that level.
ZoomInfo states that its contact data is verified at over 95% accuracy. It also describes a multi-stage email-verification process intended to keep bounce rates below 2%.
These are the providers’ own published claims rather than the results of one shared independent test. Email accuracy, email deliverability, phone accuracy and overall contact-data accuracy measure different aspects of a record.
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Provider | Published claim | Published protection or commitment |
DataJi | Contacts researched and validated against the agreed client specification | Two replacement contacts for every supplied record with an inaccurate or missing agreed field |
Apollo | 97% email accuracy | Platform credit and verification policies apply |
Lusha | 98% email deliverability and 85% phone accuracy | Published performance figures vary by data type and region |
UpLead | 95% data accuracy guarantee | Credits returned if accuracy falls below 95% |
ZoomInfo | Contact data verified at over 95% accuracy | Platform and contractual remedies apply according to the service agreement |
High accuracy percentages can still leave hundreds of records outside the stated rate when a campaign contains 10,000 contacts.
Provider or measurement | Published rate | Mathematical remainder across 10,000 records |
Lusha email deliverability | 98% | 200 |
Apollo email accuracy | 97% | 300 |
UpLead data accuracy | 95% | 500 |
ZoomInfo data accuracy | Over 95% | Fewer than 500, with no precise percentage stated |
Lusha phone accuracy | 85% | 1,500 |
The mathematical remainder does not predict the exact number of inaccurate records a customer will receive. It shows the number falling outside the published percentage when that rate is applied to a file containing 10,000 records.
The measurements are also different. A telephone accuracy percentage cannot be compared directly with an email deliverability rate or a broader data accuracy guarantee.
The calculation shows the practical scale of the remaining risk. A difference of a few percentage points can represent hundreds of questionable records within one campaign.
A valid email address can still belong to the wrong campaign contact.
The recipient may have moved departments while retaining the same mailbox. Their job title may no longer represent their responsibilities. The company may fall outside the target sector, size or location criteria. The contact may work for the organisation while holding a role unrelated to the client’s offer.
Useful B2B contact data therefore requires accuracy across the full set of fields used for targeting.
Depending on the brief, DataJi can check:
A record should be assessed according to the purpose for which it will be used.
Data guarantees are often presented as a financial remedy. An inaccurate record is identified and the provider returns a credit, issues a refund or supplies another contact.
The more serious cost can arise before the error is discovered.
Once an email has been sent to an invalid address, the resulting hard bounce becomes part of the campaign’s sending history. Returning the purchase credit cannot remove that bounce. Supplying another contact cannot recover the original sending opportunity or immediately repair any damage to the sender’s reputation.
Yahoo advises senders to remove invalid recipients promptly and warns that sending to invalid, inactive or disengaged recipients can harm delivery metrics and sender reputation.
Google advises senders to use current recipient addresses and warns that messages can be limited, rejected or classified as spam when sender requirements and delivery standards are not met. Google also uses Postmaster Tools to report domain reputation, spam rates and delivery errors.
If a 10,000-record campaign contains hundreds of invalid addresses, the sender can experience an immediate increase in hard bounces. The effect may extend to later campaigns sent from the same mailbox or domain, including messages addressed to valid contacts.
DataJi’s article on B2B data accuracy and email domain reputation examines how inaccurate records can weaken campaign deliverability and future inbox placement.
The cost of poor data can include lost opportunities, wasted campaign preparation, hard bounces, reduced inbox placement, additional database cleaning and damage to the mailbox or sending domain.
Compensation after delivery addresses the record purchase. It cannot reverse an email that has already been sent.
DataJi’s 200% guarantee is a two-for-one replacement commitment. It is not a claim of 200% accuracy.
For every DataJi record found to contain an inaccurate or missing field covered by the agreed project specification, we provide two replacement records.
If 100 supplied contacts contain inaccurate or missing agreed information, the client receives 200 replacement contacts.
The guarantee can apply across the complete set of fields included in the project, such as the contact name, current employer, job title, function, seniority, industry, location, company information, named business email address and telephone details.
A returned platform credit restores the purchasing unit used to access one record. DataJi supplies twice the number of replacement prospects.
The replacements provide accountability, but the most valuable part of the service takes place before delivery. Fresh research and multi-stage validation reduce the risk of unsuitable contacts entering the campaign in the first place.
The aim is to avoid invalid sends and protect the client’s domain from the beginning.
Learn more about DataJi’s freshly researched B2B contact data and 200% guarantee.
We offer a 200% guarantee on all B2B contact data: if you find any inaccurate data, then we will replace those with twice the number of records. No invoice until you approve all the data. A completely risk-free process for our clients. No other organization comes close to this. Put us to the test. Ask for a free sample.
The project begins with a detailed specification. The client can define industries, locations, company sizes, turnover, ownership, technologies, job functions, seniority levels, titles, mandatory fields and exclusions. We agree what qualifies as a suitable record before the research begins.
Our researchers identify organisations that satisfy the company-level criteria. The company is assessed according to the current project rather than selected because it appeared in a pre-existing database category.
Researchers locate the people whose present responsibilities fit the campaign. The assessment covers the role and job function rather than relying entirely on the wording of a title.
We check whether the person currently works for the organisation and whether the role remains relevant. This stage helps identify former employees, promotions, department moves and outdated titles.
We check whether the person currently works for the organisation and whether the role remains relevant. This stage helps identify former employees, promotions, department moves and outdated titles.
The email address is checked alongside the wider evidence connecting the person, employer and role. Catch-all addresses receive additional investigation because a standard server test may be unable to confirm the individual mailbox conclusively.
The finished file is reviewed against the original criteria, required fields and client exclusions. Suppression data can be applied before delivery to remove contacts the client already holds or should not receive.
DataJi compared with large sales intelligence platforms
DataJi | Apollo, Lusha, UpLead and ZoomInfo | |
Core model | Bespoke B2B contact research | Searchable sales intelligence databases |
Starting point | The client’s current campaign specification | Records already available within the platform |
Research timing | Research conducted for the client project | Records collected and refreshed through continuing platform processes |
Contact selection | Human assessment against the full brief | User-selected filters and existing database classifications |
Job-function targeting | Researchers interpret roles and responsibilities | Results depend on titles, categories and available filters |
Email addresses | Named business addresses prioritised | Dependent on the records available within the platform |
Generic inboxes | Not accepted as equivalent to named contacts | May be included according to the underlying data |
Personal email accounts | Used only where professional relevance can be established | May be included according to the platform record |
Complete-record assessment | Checked against the agreed required fields | Accuracy measurements vary by provider and data type |
Quality commitment | Two replacements for each record with an inaccurate or missing agreed field | Credits, refunds and contractual remedies vary |
Delivery speed | Requires research and validation time | Existing records can normally be exported immediately |
Best suited to | Precise, campaign-specific requirements | Fast self-service prospecting and software-led workflows |
DataJi is designed for campaigns where current accuracy and precise relevance carry a high commercial value.
This includes projects involving specialist industries, unusual job titles, narrow functions, several simultaneous targeting conditions, defined geographic requirements or mandatory fields that cannot be left incomplete.
It is also suitable for organisations concerned about old CRM records, generic inboxes, unconfirmed personal email accounts and the deliverability risks caused by invalid data.
Apollo, Lusha, UpLead and ZoomInfo provide extensive software functionality and rapid access to broad markets. DataJi provides a managed research service built around the exact audience required for the current campaign.
You can review DataJi client testimonials from organisations that have used our services for niche targeting, database building, data cleansing and contact enrichment.
Accurate data still has to be used carefully. DataJi can support the preparation and management of the outreach campaign, including data segmentation, exclusions, personalised email content, sending and response handling. Our hyper-personalised email service uses information about the recipient and their company to produce individual email content rather than sending an identical generic campaign to every contact. Managing the research and outreach together also creates a useful feedback process. Replies and automatic responses can reveal leavers, job changes, referrals, department moves and updated information that can improve later campaign activity. Clients can use DataJi for the contact data or combine the research with campaign delivery support.
DataJi’s research process is designed around relevant business information required for the client’s stated purpose. Our legal basis for processing business contact data explains our approach to legitimate interest, data accuracy, data minimisation, privacy and individual rights. Clients should also ensure that their own campaign content, targeting, suppression procedures and data use comply with the laws and regulations that apply to their organisation and audience. In the unlikely event that we cleanse and return any data that is inaccurate, then we apply our 200% guarantee.
Tell us which organisations and decision-makers you need to reach.
Include the relevant industries, locations, company characteristics, job functions, seniority levels, titles and required fields. DataJi will review the specification, estimate the available audience and explain how the contacts will be researched and validated.
Yes. DataJi is an Apollo alternative for organisations that prefer bespoke contact research to searching and exporting records from a self-service database. DataJi researchers work from the current campaign brief, identify the relevant people and validate the completed records before delivery.
DataJi is a Lusha alternative for businesses that need a researched contact file built around detailed targeting requirements. Lusha provides immediate database access and platform tools. DataJi provides managed research, human assessment and a 200% replacement guarantee.
Yes. UpLead offers access to an existing B2B database with a published 95% data accuracy guarantee. DataJi researches contacts specifically for each project and provides two replacement records for every supplied record containing an inaccurate or missing agreed field.
DataJi is a ZoomInfo alternative for clients whose priority is freshly commissioned contact research rather than access to a large sales intelligence platform. The service is particularly suitable when the target audience involves narrow functions, unusual job titles or a complex combination of company and contact criteria.
DataJi does not begin client projects by exporting a stock contact list from a self-service database. Research begins with the client’s current specification. The team then identifies and validates the companies and people required for that project.
Generic addresses such as info@, hello@ and admin@ do not identify the decision-maker responsible for the campaign subject. They normally lead to shared inboxes and provide no certainty that the message will reach the appropriate person.
A personal email account can remain active without demonstrating a current relationship between its owner and the company shown in the contact record. DataJi prioritises named business email addresses linked to the person’s current professional role.
For every supplied record containing an inaccurate or missing field covered by the agreed project specification, DataJi provides two replacement records. The guarantee is a two-for-one replacement commitment rather than a claim of 200% accuracy.
Replacement records provide new prospects, but they cannot remove earlier hard bounces from the campaign history. Invalid sends may already have affected mailbox or domain reputation and reduced the delivery of future messages.
Email verification assesses whether an address appears deliverable. Contact verification also considers whether the person currently works for the stated employer, holds the required role and satisfies the wider campaign criteria.
Yes. DataJi can cleanse and enrich existing records by checking employers, job titles, contact names, business email addresses, telephone information and other required fields.
Existing CRM history can be retained while obsolete or incomplete contact information is updated.
Yes. DataJi can use encrypted exclusion and suppression files to compare newly researched contacts against records already held by the client. This helps prevent genuine duplicates and removes excluded or unsubscribed recipients before delivery.
The timescale depends on the volume of contacts, the complexity of the targeting criteria, the territories covered and the number of required fields. Fresh research takes longer than exporting existing database records because the companies and people are being identified and validated for the client’s project.
