From map to CRM: turning a local search into a pipeline
A practical playbook for moving from a local search to an organised sales pipeline, with stages, criteria and next steps.
In this guide · 11 sections
Searching for companies on a map is easy. Turning that search into a usable sales pipeline is another matter.
A common mistake is to treat the search as the end result: find companies, copy data, export a list and expect the sales team to handle the rest. A pipeline begins when each company found has context, a status and a next step.
1. Start with the commercial hypothesis
Before opening the map, define the hypothesis:
- Who do we want to find?
- In which territory?
- Why might these companies be interested?
Examples: dental clinics in Porto that may need help attracting local customers; restaurants in Lisbon with a weak digital presence; estate agencies in Braga that could benefit from partnerships; training providers that sell to other businesses.
The hypothesis stops the search from becoming a generic list.
2. Search by territory and sector
A local search should combine region and category. “Companies in Lisbon” is too broad. “Dental clinics within a specific radius” already gives you an actionable segment.
When using the Commercial Explorer, also save the search context: search term, location, radius or area, date, list objective and campaign owner. Use the list description or campaign record for any information you need to add.
Later, when the team asks where this lead came from, the answer will be documented.
3. Clean before enriching
Not everything that appears in a search should go into the CRM.
Before enriching the data, remove businesses with no visible activity, companies outside the territory, duplicate locations, brands outside the ICP and contacts already in the CRM as a customer, an open opportunity or a recently lost opportunity.
This clean-up stops the team wasting time contacting companies that should never have entered the pipeline.
4. Set priority criteria
A simple score can use five criteria: sector fit, geographical proximity, signs of need, ease of contact and potential value.
Each criterion can receive a score from 1 to 3. The aim is not to create a perfect model. It is to stop the team working through the list in a random order.
5. Enrich with useful context
Enrichment does not mean accumulating fields. It means adding information that improves the approach.
Useful fields: website, telephone, public email where available, WhatsApp or another visible contact channel, category, address, opening hours, website signals, relevant observations, suggested approach and potential associated product.
For Makers, this last point matters. A company may be a fit for the Commercial Explorer, AOS, the WhatsApp Agent, the Instagram Agent or a combination.
6. Turn the list into a campaign
A list only becomes a pipeline when it has an associated campaign.
Define its name, objective, segment, territory, initial offer, main channel, cadence, owner, start date and success criterion.
Without a campaign, the CRM becomes a storage space. With a campaign, each contact becomes part of an operational process.
7. Map the pipeline stages
A simple prospecting pipeline might include: new, qualified, contact initiated, replied, meeting proposed, meeting booked, opportunity opened, no response, no fit and nurture later.
These stages help the team know what to do next and measure where the process is failing.
8. Import into a CRM or AOS
Before importing, confirm the required fields: company name, sector, territory, website, telephone, email, source, campaign, initial status, product of interest, owner and next action.
The Commercial Explorer lets you export lists as CSV files. Before importing the file into the CRM, check how each column maps to the destination fields and complete the campaign’s internal fields, such as owner and next action. The commercial qualification spreadsheet can support that review.
Start with a test import of three companies. Check that telephone numbers retain their dialling codes, fields appear in the right columns and an existing company is recognised as a duplicate. Only then proceed with the rest of the file. CSV export does not imply automatic synchronisation between systems.
In AOS, this information can be integrated with tasks, workflows, automations and internal reporting. Even when you use another CRM, the logic remains the same: each company needs a source, context and a next action.
9. Create the first action
Each imported company should arrive with a concrete action: send an opening email, identify the decision-maker, call during business hours, review the website before contact, prepare a partnership proposal, exclude a duplicate or nurture with Commercial Radar content.
The first action prevents the list from sitting idle after import.
10. Review results
After a week, review how many companies were contacted, how many replied, which segments responded best, which reasons for contact led to conversations, which data was missing and which product tags made sense.
This review informs the next search. The Commercial Explorer becomes more valuable as the team learns which sectors, areas or signals lead to better conversations.
Workflow summary
- Define the commercial hypothesis.
- Search by territory and sector.
- Remove duplicates and companies outside the ICP.
- Prioritise by fit, signal and potential.
- Enrich with data useful for the approach.
- Group the list into a campaign.
- Map the pipeline stages.
- Export and import into a CRM or AOS.
- Create a next action for each company.
- Review results and adjust the next search.
The map shows where the companies are. The CRM shows what the team is doing with them.
To apply the playbook, start with one city and one sector in the Commercial Explorer. After searching and reviewing the data, use the guide to choose accounts for the first week and assign next steps before importing.
