To a larger part, bots can traverse hundreds and thousands of pages on a website, and
fetch important bits of information depending on its purpose on the web.
Some bots are designed to collect price
data from e-commerce portals, while
others can extract customer reviews
from online travel agencies.
Also, there are bots designed to collect
Irrespective of the use cases, bots are created from
scratch, depending on the information that is
needed to be extracted from webpages or
1. Understanding how the site
reacts to human users
It is important to understand how a website
interacts with a real human.
A target website from which data is to be
extracted, is navigated on browsers like Google
Chrome and Mozilla Firefox.
This gives information about browser-server
interaction, revealing how the server sees and
processes an incoming request, and lays down the
base for building the bot.
2. Getting a hang of how site
behaves with a bot
Some test traffic in an automated manner is sent to
understand how differently a site interacts with a bot
compared to a human user.
This helps in choosing the best path of action to build the
Most websites treat human users and bots differently to
protect themselves from bad bots and various forms of
3. Building the bot
Once a clear blueprint of the target site
is obtained, it’s time to start building
the crawler bot.
The complexity of the build depends on
results obtained from previous tests.
For instance, if the target site is only
accessible from Germany (let’s say), a
German proxy is needed to be included
to fetch the site.
4. Putting the bot to test
Top most priority is given to reliability and data quality.
It’s important to test the crawler bot under different
conditions like on and off peak time of the target site
before the actual crawls can start.
For this, fetching a random number of pages from the
live site is done.
Changes are made to the crawler for improving its
stability and scale of operation after the outcome.
If everything works as expected, the bot can go into
5. Extracting data points and
Bots can fetch full html content of the pages for data extraction
and various other processes depending on client requirements.
Once extraction is done, data is automatically scanned for
duplicate entries and deduplicated.
The next process is normalization where changes are made to the
data for easier consumption.
For example, if the price data is extracted in dollars, it can be
converted to a different currency before being delivered to a