Connecting The Dots Across All Data Sources

Power smarter decisions and actions with clean, integrated data

Customer journey analysis

Get 360-degree views of prospects and customers across all touchpoints. Lore IO quickly pulls in data  from websites, mobile apps, customer devices, CRM systems, customer service systems and call logs,and then constructs detailed timelines of how customers interact with your brand and digital properties. It connects the dots between your marketing campaigns and the resulting actions and interactions your target audiences take.

Experience personalization

eCommerce - user cohort - export data from API, pull it into their personalization campaign. Dropped Tealium AudienceStreams. Table export that sends to Oracle Responsys, email campaigns. Every 20 minutes they pull our API. Order transactions in Redshift. A/B Test data from the vendor Split.


Often in your data apps, when you create reports for Business Review, its important to understand when that quarter or month is likely to end. We use the past trends in your data to forecast and predict how the current time period is likely to end.

When you launch new content, you  want to understand how it will perform. Once it has a few weeks of data, we can use the trends from other similar content launches to predict how its likely to perform in the future. For example, after an initial spike, how does it usually trend down.

Campaign optimization

sophisticated a/b testing.

Anomaly detection and forensics

More data means more data points to monitor. Unexpected changes can happen in any chart. When you log-in every day won't you wish someone told you that these are the charts that need your attention. That is exactly what our machine learning system enables. It uses complex machine learning models to detect unexpected changes and then shows you the top few charts that need your attention.

Delivering insights is at the core of the Lore platform. So when you see an unexpected change in a key business metric, you don't have to struggle to find out why? Business users have many hypotheses. Could it because of a new marketing campaign? Could it be a bug in a particular browser? Or a key demographic?

In tradition systems, there are two problems. Each of these hypothesis requires writing ETL and SQL making it hard to test. Even after you have implemented all the hypothesis, checking them for any anomaly takes time.

Lore allows you scan and find hypothesis, build more complex ones based on the User's journey before that event and manage a list of the common hypothesis. Then when a metric changes, Lore can automatically scan and find the most likely hypothesis that applies.