sarahvkaye@live.co.uk at a tech vendor with 10,001+ employees
Real User
Top 10
Jul 16, 2026
My main use case for Blueshift was to deliver recommendations in real time to customers at scale. By using our product catalog and customer behavioral data that was modeled and worked on with the data science team at Blueshift, we were able to create a match recommendation email that was sent out at scale to 70 to 80,000 people a day.
I use Blueshift to data mine for deep historical information regarding people's interest in certain brands, makes, and models of classic cars. The goal was specifically to record interest expressed in very rare vehicles which would only come up for sale very seldom so that this could be used many years later. I recorded people's searches, saved searches, saved listings, saved sale listings, and cross-referenced those with imported historical data from previous versions of the site, using similar data of people's saved searches, the searches they had carried out, interest they had expressed in vehicles that were for sale, and bids they had placed on auctions.
Ent IT Business Analyst at Texas Tech University Health Sciences Center
Real User
Top 20
Jun 7, 2026
My main use case for Blueshift is cross-channel customer engagement and lifecycle marketing. Freshworks has a large customer base across multiple products, and the challenge is communicating with different segments in a relevant, personalized way across email and push.
My main use case for Blueshift is that we capture a wide amount of customer data at our organization, and Blueshift does a fantastic job of organizing that data in a manageable way. Specifically in customer events, we are able to capture large amounts of time-sensitive data within each payload, specific to that event. We then can trigger campaigns and segmentations of that data. This is very essential to our success as a team and an organization. A specific example where Blueshift helped me organize and trigger campaigns based on customer event data is that we build all our customer journeys, triggered campaigns, retention campaigns, and promotional campaigns in Blueshift. We have a robust customer experience that spans over hundreds of campaigns, so it's quite intricate to manage. This makes Blueshift an excellent customer data platform for our organization managing large amounts of data. It was specifically useful for developing complex emails and campaigns based on several stored data points and API calls.
My main use case for Blueshift is to use it as a customer data platform, both to manage, curate, and update our customer segmentation and to integrate that data into our email templates. A specific example of how I use Blueshift for customer segmentation or email integration is that we are able to build all our customer journeys, triggered campaigns, retention campaigns, and promotional campaigns in Blueshift. We have a robust customer experience that spans over hundreds of campaigns, so it is quite intricate to manage. In addition to my main use case, I capture a wide amount of customer data at our organization and Blueshift does a fantastic job of organizing that data in a manageable way. Specifically in customer events, we are able to capture large amounts of time-sensitive data within each payload specific to that event. We can then trigger campaigns and segmentations off of that event data. This is essential to our success as a team and as an organization.
Blueshift enhances marketing strategies with AI-driven predictive targeting, personalized campaigns, and robust data management for better engagement and revenue growth.Blueshift streamlines marketing efforts by offering predictive audience targeting, product recommendations, and dynamic content retargeting. It integrates seamlessly with existing systems, simplifying customer data management, segmentation, and campaign automation. Its AI-driven approach supports precise targeting and campaign...
My main use case for Blueshift was to deliver recommendations in real time to customers at scale. By using our product catalog and customer behavioral data that was modeled and worked on with the data science team at Blueshift, we were able to create a match recommendation email that was sent out at scale to 70 to 80,000 people a day.
I use Blueshift to data mine for deep historical information regarding people's interest in certain brands, makes, and models of classic cars. The goal was specifically to record interest expressed in very rare vehicles which would only come up for sale very seldom so that this could be used many years later. I recorded people's searches, saved searches, saved listings, saved sale listings, and cross-referenced those with imported historical data from previous versions of the site, using similar data of people's saved searches, the searches they had carried out, interest they had expressed in vehicles that were for sale, and bids they had placed on auctions.
My main use case for Blueshift is cross-channel customer engagement and lifecycle marketing. Freshworks has a large customer base across multiple products, and the challenge is communicating with different segments in a relevant, personalized way across email and push.
My main use case for Blueshift is that we capture a wide amount of customer data at our organization, and Blueshift does a fantastic job of organizing that data in a manageable way. Specifically in customer events, we are able to capture large amounts of time-sensitive data within each payload, specific to that event. We then can trigger campaigns and segmentations of that data. This is very essential to our success as a team and an organization. A specific example where Blueshift helped me organize and trigger campaigns based on customer event data is that we build all our customer journeys, triggered campaigns, retention campaigns, and promotional campaigns in Blueshift. We have a robust customer experience that spans over hundreds of campaigns, so it's quite intricate to manage. This makes Blueshift an excellent customer data platform for our organization managing large amounts of data. It was specifically useful for developing complex emails and campaigns based on several stored data points and API calls.
My main use case for Blueshift is to use it as a customer data platform, both to manage, curate, and update our customer segmentation and to integrate that data into our email templates. A specific example of how I use Blueshift for customer segmentation or email integration is that we are able to build all our customer journeys, triggered campaigns, retention campaigns, and promotional campaigns in Blueshift. We have a robust customer experience that spans over hundreds of campaigns, so it is quite intricate to manage. In addition to my main use case, I capture a wide amount of customer data at our organization and Blueshift does a fantastic job of organizing that data in a manageable way. Specifically in customer events, we are able to capture large amounts of time-sensitive data within each payload specific to that event. We can then trigger campaigns and segmentations off of that event data. This is essential to our success as a team and as an organization.