Data Engineering

Business Challenge:
The client’s Marketing team was struggling to improve marketing generated revenue, even with additional spending, generating incremental leads.

Solution & Benefits:
LatentView helped define a unified marketing measurement model across demand generation, field sales, content, social, partner channels etc and implemented a data lake that provides a central ground truth for marketing, leading to better revenue attribution, more accountability, deeper analytics, and massively improved hygiene and governance.

Business Challenge:
Business users faced significant delays in accessing and analyzing data and had difficulty in handling large volumes of data for analytics.

Solution & Benefits:
LatentView created a modern scalable data platform that led to the creation of a single ground truth, and democratized access to users by supporting many workloads – real time querying, ad hoc analysis, regular reporting, data science workbenches, at scale prototyping, etc.

Business Challenge:
Client employed an army of marketing analysts to manually manage advertising bids for millions of paid search keywords for Google and Bing marketplaces, leading to sub-optimal results.

Solution & Benefits:
LatentView created a data lake that integrated data from transactional (e.g. revenue, campaigns, etc.) and behavioral sources (e.g. product, click stream, page composition, etc.). This data was used to build predictive models and experimentation platforms that led to significant revenue gains (over 20MM $) over a 2 year period.

Business Challenge:
Client, a provider of leading online search services, was struggling to increase their small market share agains their chief competitor. Client wanted to retain users with in the same ecosystem for a longer time and serve highly personalized results.

Solution & Benefits:
Client created a panel of 100,000 users to track their demographics and behavior. LatentView collected clickstream data from the users’ devices, translated the raw HTML into structured form, and created a data mart for undertaking granular analysis, such as user engagement, ad display, online switching behavior, etc. This led to monetization opportunities worth millions of dollars for the client.