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Data processing teams get more efficient and improve workflow automation with AI

A leading solutions provider reduces manual effort for data processing teams by using AI.

The big picture

70%

time saved in matching and validating company and contact names
(Stage 1)

60%

time saved in standardizing the output
(Stage 2)

The customer is a leading data solution and intelligence provider. They specialize in hunting, harvesting, aggregating and transforming data. Their core focus is on collecting, refining and interpreting information and managing data into diverse database systems. Their clients include some of the world’s leading B2B brands whose work is bolstered by the the customers proprietary data management systems and data products.

The need

The existing customer workflow was subject to errors in the output fields across multiple data extraction and processing stages. This led to a dependency on manual effort to clean and supplement the data, resulting in a high turnaround time for project completion. There was significant manual effort involved in segregating datasets. The average volume per project usually went up to thousand a range, and monthly volumes ranged from a quarter to half a million records.

  • At stage 1 of the process, the scraped data often didn't match the input given.
    Manual intervention then became necessary to ensure accurate matches of records.
  • In stage 2, the time taken to standardize the output was significant.
    Further scrapping was sometimes required to ensure the limit and quality set by the client were met.

Improve productivity by automating critical processes post scraping of data

Reduce manual effort during standardization of contact information

Save time by reducing the effort required to validate the output data

Lead to faster, streamlined turnaround time for overall client delivery

The customer worked with Vue.ai to help distill and make the data from different sources usable. Vue.ai helped fine-tune the focus on the data quality to ensure the result was accurate, actionable, and impactful.

Implementation

Vue.ai provided automation solutions to streamline and automate content validation and standardization process. The solution leverages machine learning modules as part of the overall workflow automation and is designed to increase the agent and process throughput.

STAGE 1

In this stage, the uploaded excel file is assessed by the tool to determine how accurate the name and company name output is with the given input.

STAGE 2

At this point, the output file that is generated post scrapping consists of a list of names and associated publicly available details including address, location, numbers, etc. The Vue.ai tool verifies, and standardizes the information with the actual requirements.

Key takeaways

There is enough evidence to show that structured data helps companies improve operational efficiency and better ROI. Using the right ML and NLP tools to understand, analyze and organize unstructured data can help break data silos within companies. There is also enough evidence to show that in the last few years, the use of AI by marketers has increased to 84% from 30%. 

Vue.ai helped the customer by providing automation solutions to improve and simplify critical processes post-data scraping. It would also reduce time and manual effort by automating the validation process required to ensure the end clients could identify and market to the correct people for their campaigns.