EN
RO
The right delivery format for crawled data depends on who uses it and how often: Excel for manual review and small volumes, a relational database for direct integration with an ERP or online store, an XML/CSV feed for automatic recurring updates on platforms like Google Shopping or a marketplace. Picking the wrong format doesn't ruin the data itself, but it turns a useful delivery into a file nobody imports on time.
Many teams default to asking for "an Excel with everything" because it's the most familiar format, then find out that manually updating 5,000 rows every month eats up entire days of repetitive work. This article compares the three standard delivery formats — Excel, relational database and XML/CSV feed — on concrete criteria: data volume, update frequency, who imports the data, and how much technical effort the integration requires.
What each delivery format actually involves
The three standard formats used in web crawling data extraction projects cover different usage scenarios, not just file-style preferences.
- Excel (static XLSX/CSV) — a tabular file delivered once or at rare intervals, opened manually by someone who checks, filters or selectively imports the data.
- Relational database — the data is delivered directly in a format compatible with MySQL, PostgreSQL or another DBMS used by the client's application, with tables and relationships already structured, ready to connect to an ERP or an online store.
- Structured XML/CSV feed — a file generated and updated automatically, at a fixed interval (daily, hourly), following a standard format required by the destination platform (Google Shopping, a marketplace, a price comparison site).
Excel: simplest, but limited to small volumes
Excel remains the right format for direct human review: a product list someone goes through row by row before deciding what enters the catalog. It's useful for one-off or occasional deliveries, proof-of-concept tests, and volumes in the hundreds, not tens of thousands, of rows.
The problem shows up with recurring updates: every new crawling run means a new file, and someone has to manually compare it against the previous version — prices, stock, new or discontinued products. Past a certain volume, this manual process becomes the project's main bottleneck, not the data collection itself.
Relational database: for direct integration into your own system
Delivering data directly into a relational database removes the manual import step: the data arrives already structured into tables, with defined field types and relationships, ready to connect to the company's ERP or the online store's database.
This format fits when there's already an internal technical team able to write its own queries against the delivered data, or when the data volume is large enough that processing it in Excel is no longer practical. Initial setup cost is higher than with Excel, because the database schema needs to be defined and validated with the client before the first delivery.
XML/CSV feed: for automatic recurring updates
A structured feed is the standard format for scenarios where data needs to be updated automatically, at a fixed interval, without manual intervention — for example feeding a product feed for Google Shopping or for a marketplace that requires its own import format.
The difference from a periodically exported Excel file is full automation of the cycle: the crawler runs, generates the feed in the format required by the destination platform, and the client's system pulls it directly, with no manual step in between. It's the format with the lowest long-term maintenance effort, but it requires the target format (XML schema or CSV structure) to be clearly defined from the start.
How to choose: volume, frequency and who uses the data
The right decision starts from three questions, not from the format the team already happens to be used to:
| Criterion | Excel | Database | XML/CSV feed |
|---|---|---|---|
| Typical data volume | Hundreds — a few thousand rows | Medium — large, no practical limit | Medium — large, continuously updated |
| Update frequency | Occasional / manual | Recurring, technically integrated | Recurring, fully automatic |
| Who imports the data | One person, manually | Technical team / internal system | External platform (Google Shopping, marketplace) |
| Initial integration effort | Minimal | Medium — requires a defined schema | Medium — requires a clear target format |
| Long-term maintenance | High (manual, every delivery) | Low, after setup | Very low, fully automated |
Common risks and how to avoid them
Most format-related problems come from decisions made without first clarifying who consumes the data and how often.
- Format chosen out of habit, not necessity — defaulting to Excel for a large volume updated weekly leads to hours of repetitive manual work; discuss the real volume and frequency before locking in the format.
- Database schema not defined upfront — without an agreed table structure in advance, ERP integration stalls at the first delivery; validate the schema with the technical team before starting.
- Feed format incompatible with the target platform — a generic XML feed that doesn't exactly match the Google Shopping or marketplace specification gets rejected on import; confirm the target format explicitly before the first generation run.
- No plan for changing format as volume grows — a project that starts with Excel can, within a few months, reach a volume that justifies switching to an automated feed or a database; discuss this threshold with your provider from the start.
Practical plan: how to decide the format for your project
- Estimate the data volume per delivery (tens, hundreds, thousands or tens of thousands of rows).
- Determine the real update frequency your business needs (one-off, monthly, weekly, daily).
- Identify who consumes the data: a person doing manual review, an internal system (ERP), or an external platform.
- If you choose a database, validate the table schema with the technical team before the first delivery.
- If you choose an XML/CSV feed, confirm the exact specification required by the destination platform.
- Set a volume or frequency threshold upfront at which you'd move to a more automated format.
Frequently asked questions about crawled data delivery formats
What format should I pick if I don't know exactly how I'll use the data yet?
For a first test delivery or a small volume, Excel is quick and sufficient. Once a recurring update flow takes shape, moving to a database or an automated feed removes the repetitive manual work.
Can I get the same data in multiple formats at once?
Yes, it's technically possible, but it requires extra effort to generate and maintain each delivered format; this should be discussed explicitly during the project requirements stage.
Does the XML/CSV feed update automatically, without my involvement?
Yes, once configured, the feed regenerates automatically at the agreed interval (daily, hourly, or another agreed schedule), with no manual step, as long as the source structure and target format stay unchanged.
What happens if the destination platform changes its required format?
The feed needs to be adjusted to match the new specification; it's recommended that this scenario be clarified in the contract, as part of the crawling project's recurring maintenance.
Can a delivered database connect directly to my online store?
It depends on the compatibility between the delivered schema and the structure of the eCommerce platform used; direct connection is possible in most cases, but requires a specific technical validation before the first delivery.
Conclusion
The delivery format for crawled data isn't a minor technical detail — it's the decision that determines whether the extracted data actually gets used on time. Excel remains suitable for small volumes and manual review, a relational database for direct integration into internal systems, and an XML/CSV feed for fully automated updates to external platforms. Determine the volume, frequency and who consumes the data before choosing the format, not after the first delivery.
Want to automate data collection for your online store? Contact us for a custom quote tailored to the format you need.
Write a comment