Here's our case study of a popular e-commerce platform based out of the United States, seeking data to be extracted from the web to enhance its pricing and product strategy.

1. Zip code-based price benchmarking for retailers
A leading ecommerce platform from United States turned up to
PrompCloud’s cost-effective DaaS solution from manual in-house data
extraction and analysis.

2. The problem
Company
A leading ecommerce
platform in the United
States.
Along with having an
ecommerce presence,
the firm also has
physical outlets across
the nation.
Context
Client wanted to
aggregate data from
their own ecommerce
platform, and
competitors’ platforms
to improve their pricing
strategy based on
locations.
Problem statement
Provide product and
pricing data extracted
from their website for
the stores based on zip
codes.
A similar requirement
was also provided by the
client for their
competitor platforms.

3. Challenges deep-dive
Challenge 1
Being an ecommerce
platform, the client sought
complete product and
pricing data from its
outlets spread across
various locations in the
United States.
Challenge 2
Before looking to employ
web crawling services, the
company used to gather
relevant data manually to
perform analysis through
various store outlets and
website using in-house
capabilities.
Challenge 3
The requirements
included extracting data
in an automated manner
for the products on their
ecommerce platform
associated with the
stores across the nation
which were filtered
based on zip codes.

4. Challenges deep-dive
Challenge 4
Taking zip code-based
data extraction, a similar
data collection process
had to be performed on
competitor ecommerce
sites to extract price and
product data.
Challenge 5
This data was used for
further analysis in
product strategy and
price benchmarking for
the complete product
catalog.
Challenge 6
The client wanted to
deploy PromptCloud’s
web crawling service to
automate the entire data
extraction process based
on zip codes which
should be scalable with
high volume data
requirements.

5. Solutions
Site-specific crawls were deployed which were based on the
client’s website, pre-specified frequency and data fields.
Some of the key fields are unique serial identifier of a product, product
name, category, URL, crawling timestamp, store location, price, and
inventory stock availability.
1
2
Same process was repeated for competitor websites. It
included data collection for the corresponding fields from
competitor e-commerce platforms.
2
The extracted data from the two executions was delivered to
the client in JSON format via PromptCloud’s REST API.3

6. Benefits
Customized noise-free
data
Noise-free data was
made available to the
client which helped
them expedite analysis
process and focus on
the improvement of the
pricing strategy
Cut-down on
redundancy since the
client listed out which
stores they wanted to
set crawlers for data
extraction.
No client intervention
was required during the
crawling procedure as
this was completely
automated based on
pre-defined
requirements.
Reduced overhead in
web crawling
Unbiased crawling
procedure

7. Benefits
Reduced Total Cost of
Ownership
Reduced cost and data
delivery latency by 86%
which helped client roll
out new pricing in
shorter time period.
The schema was
altered as per client’s
request.
Periodic updates and
reports based on the
frequency of crawling
was also delivered
which helped client
streamline their
requirement without
additional charges from
our end.
Flexible deliverables as
per client’s interest
Room for changing
requirements for
deliverables

8. A Pioneer in Data as a Service
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