Google Search Console is limited to export 1,000 rows of query data per report, are 1,000 rows enough?

Google Search Console is limited to export 1,000 rows of query data per report, are 1,000 rows enough?

If you are a regular Google Search Console user, you probably notice that Google Search Console interface is limited to export 1,000 rows per report only.

It means that no matter you export data set daily, weekly, monthly or quarterly, only 1,000 rows can be exported per report.

We are interested in understanding whether webmasters will miss out lots of useful query data if the website receives lots of organic traffic via different queries from Google every day.

We are also interested in understanding how Google Search Console samples the data set within the 1,000 rows limit, when there are far too many queries (more than a thousand queries a day).

Therefore, we investigated the data set from one of our largest clients.

Apart from exporting data from Google Search Console, we also turned to the Aloha Quanery to pull a more complete data set without the 1,000 rows limitation.

After exporting the data, we categorized the queries into four groups:

  • Brand
    Pure brand terms e.g. Aloha / Aloha Hong Kong
  • Brand Plus
    Brand + Products e.g. Aloha SEO, Aloha Site Health Enhancer, Aloha SEM
  • Generic
    e.g. SEO company in Hong Kong, Digital marketing firm in Hong Kong
  • Unknown
    Not related to the company and its products

We then compared the distribution of the categorized queries in three data sets:

  Three data sets (Fig.
1)
Number
of rows of query data (Unique)
1 1,000 rows of query data captured monthly
(September) (Google Search Console)
999 (The
first row is label)
2 Query
data captured day by day (September) (Google Search Console) 
7,431
3 A more complete data set in whole September (without
the 1,000 rows limitation) (Quanery) 
23,900

Findings

If we use Google Search Console to export 1,000 rows of query data monthly for the whole September, 60% of the query data belongs to “Brand Plus” terms, while 29% belongs to “Generic”.

But if we use Google Search Console export the query data day by day for the whole month, 58% of the query data belongs to “Generic” terms, while 17% belongs to “Brand Plus”.

And if we capture a complete “all” query data from Quanery for the whole month, 60% of the query data belongs to “Generic” terms while 6% belongs to “Brand Plus”.

 

Conclusion

We can see that the distribution patterns of the categorized queries are quite different for the three data sets.

The amount of unique “Generic” query data increases significantly if we export the data set daily for 30 days in Google Search Console or pull the data in a monthly report using Quanery.

For those who export query data from Google Search Console weekly, monthly or even quarterly, they risk missing out lots of useful Brand Plus and Generic query data.

What are your thoughts on this issue?

 

 

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