Phone Number

+44(0)1227 206117

Email Address


Canterbury, Kent


Our Data

The data we source is strictly business to business (B2B) and not personal data, so corporate information that is readily available online and not personal information.

We collect our B2B data from publicly available sources, such as company websites, LinkedIn, and company registries. We also use algorithms and machine-learning to autocomplete email addresses that follow corporate email patterns.   

We ensure that our data sourcing complies with all applicable privacy laws including GDPR and CCPA, and for complete transparency and assurance, can provide the source of the data found upon request when possible.

Before starting our data build, we ask you for an exclusion-list so that we don’t provide data you already have. We also sign a non-disclosure agreement (NDA) so that the data you provide us is completely secure. 

GDPR (General Data Protection Regulation)

Our high-quality, researched data fully complies with the latest GDPR guidance, giving you the assurance that your data assets are fully protected and secure.

We only use open-source methods and provide compliant executive contact details to a higher standard than most bulk list providers.

All our data is sourced from publicly available domains such as corporate websites and company registries. We only source B2B data and not B2C data, so company email addresses and not personal ones. ✅ ❎

For complete assurance, whenever it is possible, we are happy to provide the exact source of the data associated with the data subject.

Yes. GDPR allows B2B email marketing under 3 conditions:

1) The data is available on open source and hasn’t come from a stagnant list.

2) The marketing content sent to that contact is appropriate for their position and/or organisation under the ‘legitimate interests’ clause.

3) A clear ‘unsubscribe’ option is available on all marketing content.

Data Build

A data build is the process of sourcing quality data and supplying it to the user for marketing and sales purposes. The data sourced includes contact names, organisation email addresses, job titles, seniority, phone numbers and other corporate information that can be used to contact prospects.     

This targeted prospect list can be for a specific purpose or campaign. Let’s say you’re an event organiser and you’re launching a new show in London for the technology industry, then a data build can take place to source the tech audience in London and the surrounding area you are looking for to attend your event.

With a data build you have a freshly researched and verified set of prospects that are sourced to your requirements. This can be provided as a stand-alone asset or as an extension to the data an organisation already holds.

A data build is important to target the right audience with sales and marketing activities. Data building can be the difference between a successful campaign and one that fails to deliver. The better your data, the more likely it is that your audience will resonate with your message.

When data is inaccurate or lacking vital information, the outcome of using it will subsequently be lacking too. No matter what type of marketing is being carried out, without a healthy, well-researched database, campaigns will struggle to achieve their goals.  

Data building allows organisations to laser target their audience, gain new leads, and attract more clients, helping to maximise revenue. Data builds also help to retain current clients and ensure that existing clients spend more on products and services.

Data Cleansing

Data cleansing is the process of identifying and removing or amending records in a database to improve its overall performance. Data is eliminated or replaced when it is inaccurate, incomplete, incorrectly formatted, or contains duplicates. The ultimate goal of a data cleanse is to make your dataset as accurate as possible.   

Data cleansing, also known as data cleaning or data scrubbing, is an essential part of your data management strategy. Achieving and maintaining accurate and reliable customer data is paramount to business success. Clean data saves your organisation time and money, boosts employee trust in your systems, and improves your customers’ experience.

Data cleansing is important in order to have the most accurate, up-to-date, quality data. In the world of data science, there is the expression ‘garbage in, garbage out’; if the quality of the data you are using is sub-par, then the outcomes of its use will also be sub-par. Any data analysis will therefore be more difficult, less clear, and less accurate, as will any decisions based on that data analysis.   

By cleansing your data, you remove its deficiencies, replace inaccurate information, and add value. This improves your data’s overall quality and therefore the outcomes of its use. A data cleanse also makes your business better organised by tidying your database and improves productivity by saving time your team would otherwise take wading through old information to find what they’re looking for.

Cleansing data involves identifying and removing inaccurate information. This can come in several forms such as old data, typos, duplicate contacts, and structural errors. Data research teams use tools such as email verification and de-duplicator software to identify inaccuracies and remove/amend them. They can then replace the information that has been removed with new, freshly researched data.

A decision is only as good as the data informing it, so the aim of data cleansing is to makes your dataset as accurate as possible. Holding a dataset of newly cleansed data brings many advantages to your organisation both internally and externally:


  • Increased employee satisfaction – Removing poor data and replacing it with correct, well-structured information improves employee morale.
  • Time-saving – Cleansed data saves your marketing and sales team time by eliminating the need to sift through inaccurate information.
  • Trustworthiness – A newly cleansed dataset is more reliable and increases trust in your organisation. 


  • Increased accuracy – With a fresh set of data, your sales and marketing campaigns will reach the correct audience.
  • Better customer experience – Interactions with prospects and clients is improved through the increase in data accuracy.
  • Better insights – With a cleansed dataset, your information increases in accuracy and data insights become more gainful.

Data Enrichment

Data enrichment is the process of expanding existing data with new and supplemental information to improve its accuracy, reliability, and quality. This allows organisations to make better, more informed decisions. 

The goal of data enrichment is to make your data a more valuable asset. For example, you may have the contact details of potential clients but are missing vital job title information so don’t know who the decision-makers are to target. Data enrichment solves this by sourcing this type of information that can make the difference between a successful, well targeted campaign and one that backfires.  

The more enriched your data, the more personalised your messaging can become. Data enrichment provides a holistic view of your audience that impacts all stages of their journey in the sales funnel from top to bottom. 

Data Enrichment can be carried out in house by sales and marketing teams. However, this process is slow and inconsistent. Many businesses do not feel this is a valuable use of time as it takes focus away from revenue-generating activities and lowers sales efficiency.

Data enrichment is important as it allows organisations to better understand their audience and provide a more valued customer experience. This helps to tailor products and services to their audience’s needs through segmented marketing.

Enriched data also improves the efficiency of your marketing team as they can seamlessly select and filter B2B data which is categorised by seniority, job function or organisation type.

It is also vital in preventing data decay from old and redundant information by updating and appending the value and quality of your data and plays a major role in marketing’s long-term goal of delivering personalised experiences.

Data Categorisation

Accurate and consistent data categorisation is the key to efficiently manoeuvring through a B2B database. By ensuring contacts and organisations are correctly categorised, your team can improve their data governance, speedily select and filter appropriate job functions, seniority, or organisation types for specific marketing campaigns. Categorised data also allows for more valuable and insightful reporting of marketing performance.

Email Marketing

Working with clean B2B data needs to be the first step in increasing engagement rates. If your marketing emails are returning a hard bounce rate of over 5%, your email sending reputation will degrade and your marketing will more likely be sent to spam folders. If high bounce rates persist you risk the possibility of being blacklisted from key domains.

However, consistently sending marketing to a cleansed database of valid contacts will in time improve your email sending reputation, resulting in more arrivals to inboxes, higher open rates, and improved click through rates (CTR).

If you have any additional questions, please get in touch with your enquiry or give us a call on +44(0)1227 463817 and our expert team can discuss your data requirements.