Every organization wants to identify the right sales leads at the right time to optimize conversions. Lead scoring is a popular method for ranking prospects through an assessment of perceived value and sales-readiness. Scores are used to determine the order in which high-value leads are contacted, thus ensuring the best use of a salesperson’s time. Of course, lead scoring is only as good as the information supplied.
Are you efficiently unifying, modeling, analyzing, and activating all the data you need to drive impactful marketing campaigns and customer experiences? For years, marketing teams have struggled to operate from a single view of the customer and their business, essential to powering personalized experiences and measuring impact on key KPIs such as sales, growth, and profitability. Today, only half of all marketers have a unified view of the customer.
The catalyst of innovation and transformation is data. The companies that recognize the power of data and wield it to drive business transformation are seeing positive impacts on their business outcomes, as indicated in our report, How to Win in the Data Economy. We surveyed 1,000 senior business and technology executives to gauge the impact the data industry is having on their businesses, and to what extent companies are embracing the opportunity to become data leaders.
Snowflake removes the need to perform maintenance tasks on your data platform and provides you with the freedom to choose your data model methodology for the cloud. When attempting to keep the cost of data processing low, both data volume and velocity can make things challenging.
What’s harder than finding the right data architecture? Finding the right dedicated partner. Adverity gets both with Snowflake. Learn how the two organizations are moving into new markets and supplying even more reliable marketing data to Adverity customers. When a fast-growing SaaS business looks to expand its client base, it normally encounters two major challenges: In many cases, an external data solution provider can only help solve the scalability challenge.
In part 1 of this blog series, we looked at how Snowflake supports the GEOGRAPHY geospatial data type, which works with the earth as an ellipsoid, measuring distances over a curvature and plotting objects using the latest World Geodetic System, WGS84.
You want to enable analytics, data science, or applications with data so you can answer questions, predict outcomes, discover relationships, or grow your business. But to do any of that, data must be stored in a manner to support these outcomes. This may be a simple decision when supporting a small, well-known use case, but it quickly becomes complicated as you scale the data volume, variety, workloads, and use cases.
Software company Slack is on a mission to make work simpler, more pleasant, and more productive. Millions of users across more than 150 countries use Slack to collaborate with team members, connect other tools and services, and access information. Marketers at Slack rely on large amounts of data to build custom audiences, manage subscriber consent preferences, and measure campaign performance.
Snowflake recently announced results from the 2022 Customer Experience Survey. Hopefully, you’ve already heard about Snowflake’s overall Net Promoter Score (NPS) of 72*, a score more than three times the industry average of 21, based on the Qualtrics 2021 NPS Industry Benchmarking Report. The survey also asked customers for feedback on specific Snowflake experiences along the customer journey, from initially researching the product to implementation to getting help and support when needed.
About 80% of the world’s data is unstructured. Unstructured data within documents, emails, web pages, images, comments on blogs and social media sites, and more can be extraordinarily valuable, making the ability to process this kind of data vital for organizations that want to make data-driven decisions.
