1800 companies in a CRM. And someone really has to look up their Tax IDs (NIP) by hand?

A need comes up in the company, one that is entirely justified from the sales perspective.

The sales director wants to know which companies in the CRM have the greatest buying potential. They need information about the size of each business, its number of employees and the scale of its operations. With that, salespeople could focus on the customers who really fit the company’s profile.

The problem? The database holds 1800 companies, and the data is incomplete.

To grade the customers, you first have to fill in the Tax IDs (NIP), verify the companies and obtain additional information.

A decision is made: someone has to do it by hand.

And this is the very moment the company starts paying for a problem that automation can largely solve.

The task lands in marketing.

An employee opens the CRM, copies the company name, looks up its details, checks the Tax ID and fills in the next fields. Then they move on to the next company.

Let’s assume that checking one company takes five minutes on average. With 1800 records, that comes to 150 hours of work. Almost four full working weeks for one person.

And that is assuming there are no problems identifying companies, no outdated data and no errors that need extra checking.

Meanwhile, sales is waiting for the information it needs to assess customer potential.

Without proper grading, salespeople may spend their time on companies that do not fit the ideal customer profile. At the same time, businesses with greater potential go uncontacted.

So how the sales team uses its time depends on the quality of this data.

And the matter does not end with one round of filling in information. Companies grow, change headcount, structure or registration details. Before long, some of the records will need updating again.

Who will do it next time?

This is one of the more curious paradoxes of business digitalisation.

Companies invest in CRM systems, marketing automation tools, analytics platforms and sales software. And when they need to combine information from several sources, it turns out that the simplest solution is to assign the task to an employee.

The company bought a CRM, but the integration between its systems is still a person.

This does not always come from the limits of the CRM itself. Often, nobody ever designed how data should reach the system and be kept up to date.

In the case of our database of 1800 companies, some information can be obtained from available registers, such as GUS, CEIDG or KRS. Other data, including more detailed information on the scale of operations, may require commercial business databases.

All that is needed is to connect these sources with the process of verifying and updating data in the CRM.

In practice, this is exactly what CRM data automation is. The system performs the repetitive steps, and the employee handles the cases that really need their judgement.

In many cases yes, although it is not as simple as automatically fetching a company’s details from a known Tax ID.

A CRM may hold shortened names, duplicates or businesses with very similar names. Automatically assigning a Tax ID found by chance could do more harm than leaving the field empty.

That is why such a process should take additional information into account, for example the address, town, website or other identifiers, if they are available.

Only after proper verification can the data be passed to the CRM. Records that could not be matched unambiguously should go to a manual check.

This does not mean eliminating human work entirely. It does mean that a person does not have to perform the same step for all 1800 companies.

And that is already a concrete change in the way of working.

It is worth going back to why the sales director needed this information in the first place.

The goal was to assess the potential of the companies and decide which customers the sales team should concentrate on.

A Tax ID helps identify a company unambiguously and combine data from different sources. Only this additional information can then be used for B2B customer grading.

For example, a company may assess businesses by industry, headcount, location or scale of operations. The criteria naturally depend on who it sells to and what its ideal customer looks like.

If such information is available in the CRM, a salesperson does not have to begin every analysis by searching the internet. They can assess a company faster, prepare for the conversation and set a contact priority.

The sales director, in turn, sees what part of the database matches the agreed customer profile and where it is worth directing the team’s attention.

The same data can also help marketing with audience segmentation, campaign planning and lead qualification.

Automation saves time here, but something else matters more. Sales gets the information it was previously missing for making decisions.

150 hours of work can be converted fairly easily into an employee’s salary cost. But that is only part of the expense.

It is harder to estimate the value of the time salespeople spend searching for information themselves and preparing contact lists. On top of that comes analysing companies that ultimately turn out not to fit the offer.

There are also errors from manual data entry, corrections to records and further updates.

Of course, not every process is worth automating. If a task comes up occasionally and involves a few records, building an integration may cost more than the manual work.

But with 1800 companies, it is worth at least calculating how much time the current way of working takes and how often it will have to be repeated.

Especially since, as a business grows, its customer base usually keeps getting bigger.

How much does it cost a company to maintain a process that requires the same work to be redone every time?

This question is worth asking before deciding to hire another person to handle data.

At Industria Core Labs we automate business processes and integrate the systems companies already use.

Within ICL AI Office we can connect a CRM with other sources of information and prepare a mechanism that handles selected, repetitive tasks. Without having to replace the whole IT environment, as long as the current systems allow for proper integration.

In the case described, the starting point would be an analysis of the CRM database, of how companies are identified and of the available data sources.

Next, it is possible to check whether Tax IDs can be found automatically, records verified, company information filled in and data prepared for grading.

Where it is justified, individual tasks can be done by AI workers. Results that need further assessment stay under human control.

We do not assume in advance that every record can be filled in automatically. First you have to check the quality of the data, the technical capabilities of the CRM and the availability of reliable sources.

That is why it is worth starting automation work with one process and a limited pilot. This makes it possible to compare the time a task takes, the number of errors and the costs before and after rollout.

Only such data shows whether automation really benefits the company.

The example of 1800 companies in a CRM is not an isolated problem. In many businesses, employees copy information between systems every day, prepare similar reports, update order statuses or verify customer data by hand.

Over time, companies get so used to these tasks that they stop treating them as an organisational problem.

Someone simply has to do it.

But do they really?

1800 Tax IDs are not the biggest problem in this story. The biggest problem is that nobody earlier questioned the way the company decided to collect them.

If, for every similar task, the first idea is to find a person to do it by hand, it is worth stopping. You then have to look not only at the tools, but also at how decisions are made in the organisation.

Does your team regularly do similar tasks? Check how much of this work can be automated and whether such a change will translate into lower costs and smoother customer service.

At Industria Core Labs we can analyse a specific process, assess the options for integrating with your current systems and propose the scope of a pilot.

Check the automation options with ICL AI Office