Using Big Data to target prospects
and analyse competitors
It’s the era of Big Data. To thrive, marketeers need to get and use data from many places.
With ScraperWiki, the open web, social media and customer databases can be sliced and diced to discover and categorise leads, and target campaigns more effectively.
ScraperWiki helps agencies and marketing professionals
- Get leads in clever ways from Government open data
- Scrape product data to understand markets
- Analyse data, for example with maps
Contact sales
Case Study: Generating legal leads from Government data
Each week, the Minnesota state department emails ‘Judgement Abstract Report’ PDFs to local law firms. One such firm, Heller & Thyen, realised the potential in collecting this data and using it to target customers in need of their services.
The PDFs have a regular layout, but are not conventionally machine readable. ScraperWiki data scientists wrote automatically scheduled scripts that carefully extract each report as it comes in, clean the data, and save it into a structured database for re-use. From here, for the lawyers, it is a single click operation to get the data for other purposes such as mailmerge.
The data provides access to a new pipeline of clients, is refreshed weekly, and can be easily re-purposed.
We have been using ScraperWiki for several years, and the service has been tremendous. ScraperWiki very quickly takes the raw data and presents it back to us in usable form, saving us a huge amount of time and money.
Even better than the technical process is the service. The turnaround for our data is extremely fast and any problems with our datasets are rapidly fixed.
Case Study: Supplier Landscape for a major Fast Moving Consumer Goods company
Alibaba.com provides a traditional search interface but this does not allow for ad hoc analysis of the products and manufacturers that searches return. We brought the search results for the product of interest onto our platform as a SQL database. This allowed us to carry out flexible queries using SQL, to visualise the locations of manufacturers on a map and to do text analysis of product features.