Bill Magnuson: Yes, absolutely. So when look at cloud data ingestion and the impact on kind of revenue and adoption, it breaks down in a few ways. One of them is just more time to value, faster time to value, being able to get people up and running more quickly, and being able to therefore get more datasets. And so one of the impacts that you often see, whether we add a new channel and a new set of use cases or we add a new data source, there’s a lot of times those data sources are describing users that previously had not appeared in wherever we were integrated before. So you had your mobile audience and maybe there was a customer loyalty program database that was living in the data warehouse, you wanted to be able to get those users into Braze to start orchestrating either emails to people or SMS or whatever it is, but you were stuck on in an engineering roadmap and it’s going to take six to four months to get the integration or what have you.
By us drastically reducing the amount of effort required to get those new datasets into Braze, we take on more use cases that brings in more monthly active users, it adds more message volumes. And as we’ve spoken about a lot in the past, we’re really trying to make sure that when we value sell, we do so in a way where we’re enhancing the value of the monthly active user, that we’re collecting the value of a contract primarily in the middle of the SAC. We’re really trying to make sure that when data is flowing into Braze that we’re always working to kind of lower the cost of getting data into Braze, both in the near term and the long term. And so we’re seeing great adoption of that by new customers and existing customers as they want to bring in datasets that were previously kind of stuck in those data warehouses.
And we’re already seeing, in terms of just like quantitative numbers, we’re already in the billions of rows ingested across cloud data ingestion since it launched last fall. We also are looking at things like expanding the cloud data ingestion concepts into product catalogs, which I mentioned before, has been a driver of the e-com business. And that gives you an ability to bring in not just data about users but also data that’s coming in from obviously a product catalog, maybe it’s about your franchises, maybe it’s other sorts of data around translations. There’s a whole bunch of other datasets that can come in that aren’t keyed on the user. that we’re making it easier and easier to get into Braze so that it can sit alongside the stream processor.
D.J. Hynes: Makes sense. Thank you very much.
Operator: Our next question comes from Arjun Bhatia with William Blair.
Arjun Bhatia: Perfect. Thank you. Bill, I wanted to touch on the legacy marketing cloud refresh cycle that we’ve been talking about. Can you just help us understand why this is happening now? It’s certainly a positive for someone with a more modern stack. Why is this taking place now and what have you noticed about the customers that have come from legacy marketing clouds to Braze in terms of their sophistication, their usage, their scale, et cetera?
