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11 / Lead Generation Systems & Automation

Lead Generation Systems & Automation | Artenis Alija

Finding and qualifying prospects as a pipeline, not as an afternoon of copy-paste.

Wireframe of a qualified lead queue: rows ranked by fit, each with its score and next action. Layouts are illustrative — every build is shaped around your own data.

I build lead discovery and qualification pipelines: structured business data collected from public sources, deduplicated properly, enriched, scored and delivered into whatever system your team already works in. The emphasis is on data quality and deduplication, because a list full of repeats and dead records costs more in wasted outreach than it saves in research time.

Use Cases

Territory research for a new market

A structured view of who operates in a market, at what size and in which sectors, before committing sales effort to it.

Ongoing prospect discovery

A pipeline that runs on a schedule and adds genuinely new companies rather than re-finding the same ones.

List cleaning and deduplication

Merging and deduplicating existing lists by company identity, so multi-branch businesses appear once.

Qualification before outreach

Scoring and filtering so the sales team contacts a shortlist rather than working through raw output.

Common Questions

Is this legal?

Collecting publicly available business information is generally lawful; what you then do with it is governed by GDPR and by the rules of whatever channel you contact people on. I build for legitimate B2B outreach with consent and opt-out handled, and I will not build systems for scraping personal data or spamming purchased consumer lists.

How do you handle duplicates?

Deduplication keyed on company identity rather than listing identity, so a business with several branches is written once. The behaviour is configurable for the cases where you genuinely want each location.

What if a long run fails partway?

It resumes. Results are written incrementally and completed and blocked jobs are tracked separately, so an interruption does not mean starting over.

What you get

  • Business discovery pipeline against defined criteria
  • Company-level deduplication, not listing-level
  • Enrichment and qualification scoring
  • Delivery into your CRM or as a queryable dataset
  • Incremental, resumable runs with failure tracking
  • Outreach dashboard for review before contact

What a lead generation system does that a list does not

Buying a list gives you rows. A system gives you a repeatable process that gets better each run and does not re-find the same companies.

Company-level deduplication

Deduplication keyed on company identity rather than listing identity, so a business with six branches is written once instead of six times.

Resumable runs

Results written incrementally with completed and blocked jobs tracked separately, so an interrupted run continues rather than restarting.

Enrichment and scoring

Filtering to a shortlist worth contacting, rather than handing sales the raw output and hoping.

Delivery into your systems

Straight into your CRM or a queryable database, not a CSV that ages the moment it is exported.

A review step before contact

A dashboard where a person approves before anything is sent, which is what keeps the process both accurate and lawful.

Staying on the right side of GDPR and platform rules

Collecting publicly available business information is generally lawful. What you do with it afterwards is governed by GDPR and by the rules of whichever channel you contact people on, and those are the parts that get businesses into trouble.

The practical rules are simple. Business contact data for genuine B2B outreach relevant to that business is defensible. Scraping personal data, harvesting from platforms whose terms forbid it, and bulk-messaging purchased consumer lists are not, and I will not build them.

Every system I build includes opt-out handling, a record of where each contact came from, and a human review step before contact. That last one is not only compliance — it is the difference between outreach that gets replies and outreach that gets reported.

How a project runs

The same sequence every time. It is deliberately front-loaded: most of the risk in an automation project sits in understanding the process, not in building it.

01

Map the process before writing anything

The first session is spent on how the work actually happens, which is almost never how the documented process says it happens. Who touches what, in which order, and where the time really goes. Most failed automation projects failed here rather than in the build, because they automated the described process instead of the real one.

02

Measure the cost of doing nothing

Hours per week, error rate, and what those hours would otherwise be worth. This is what decides whether a process is worth automating at all — and it is also the number you compare against afterwards, which is why it gets recorded before anything is built rather than estimated after.

03

Build the smallest useful version

One process, working end to end, in production, before anything else starts. A narrow system that people actually use beats a broad one that waits on a second phase, and the edge cases that matter only surface once real work runs through it.

04

Run it against reality

The first two weeks of live use produce more design corrections than any amount of planning. Failures get surfaced loudly, retried and logged, because silent failure is the most expensive property a workflow can have and the one noticed last.

05

Hand it over properly

Documentation, credentials, and a walkthrough with whoever will maintain it. A system only one person understands is a liability regardless of how well it runs, so handover is part of the work rather than an optional extra at the end.

Ways to work together

Three arrangements cover almost every engagement. Most start with the first or the second; the third only makes sense once something is live.

A

Fixed-scope project

One defined process, a fixed price and an agreed definition of done. The right fit when the problem is clear and bounded — an order flow to connect, a CRM to build, a reporting pack to automate. Most first engagements are this, because it lets both sides find out how the other works without a long commitment.

B

Assessment first

One to two weeks mapping processes and measuring where the hours actually go, ending in a ranked list with effort and payback estimates. Useful when there is a backlog of automation ideas and no agreement on which matters. The document stands on its own and is yours whether or not you build anything with me.

C

Ongoing retainer

A recurring block of time for maintenance, extension and new automations once systems are live. Integrations break when the systems either side of them change, and a retainer means that gets fixed before it becomes an outage rather than after.

How the working relationship is set up

01

Remote, with real overlap

Work is delivered remotely. Across Europe and the Nordics the working day is effectively identical; in the Gulf it starts three hours ahead, which still leaves your full morning covered. There is no local office in any market, and none is claimed anywhere on this site.

02

You own what gets built

Source code, infrastructure and data stay yours. Systems are deployed on infrastructure you control — your server, a European provider, or a VPS in your own account. There is no per-seat licence and no dependency on me continuing to be involved.

03

Self-hosting is a first-class option

Self-hosted n8n, self-hosted databases and locally run models are all supported and, in several of these markets, preferred. Where no data may reach a third-party API, that constraint shapes the architecture from the start rather than being retrofitted.

04

Direct contact, one person

You deal with the person building the system. There is no account manager relaying requirements, which is the main practical advantage an independent consultant has over an agency at this size — and the main reason scope stays honest.

Questions worth asking before you commit

What if we are not sure automation is the right answer?

Then the assessment is the right starting point, and it is designed to be able to conclude that you should not automate something. A process that is broken should be fixed before it is automated, and one that runs twice a month rarely earns the build. Receiving that answer in week one is far cheaper than discovering it after a project.

We have been burned by a failed automation project before.

That is common, and the cause is usually scoping or adoption rather than technology — a system built for the documented process rather than the real one, or one nobody was trained to maintain. Both are addressed by mapping the real process first and treating handover as part of the work.

How do we avoid depending on one person?

By owning everything: source code, infrastructure, credentials and documentation, with a walkthrough for whoever maintains it. The test is whether another developer could pick the system up from the repository and the documentation alone, and that is the standard handover is written to.

Is our data safe?

It stays where you need it to. Systems can run entirely inside your own infrastructure, including self-hosted models where no data may reach a third-party API. Where GDPR applies, data stays in the EU by default, with named access control and audit logging as standard rather than as an upgrade.

How quickly can something be running?

A first working version of a single process is typically weeks rather than months. Larger platforms are sequenced as modules so something is in production early and the rest builds on a foundation that already survives real use.

Markets where this is delivered

Get in touch

Tell me what needs automating

Describe the process that is costing you time and roughly how much. I reply to every enquiry personally, usually within one working day.

Response
Usually within one working day, Mon–Fri CET
Delivery
Remote across Europe, the Nordics and the Gulf
Or email inquiries@artenisalija.com