das42

SaaS

Analyze all your B2B interactions to determine customer retention and engagement.

Analytics for Sales and Product Development

SaaS companies have to track data for how their product is being used, which can also start to predict if renewals are at risk. Centralizing that data for insightful analytics has to be responsive and flexible to keep up in a competitive market.

Analyzing the Sales Process

Taking a look at the time it takes to close deals and convert leads can help SaaS sales teams function more efficiently.

Creating Efficiencies

With SaaS services and products, licenses are often purchased. As companies grow and membership parameters shift, the ability to understand users enables you to cross-sell and deliver more effective products.

Creating Recurring Business and Revenue

Effective financial data, sales data, renewal rate, and up-sell analysis that relates those activities back to engagement, enables SaaS companies to better predict buying habits and forecast up-selling or cross-selling opportunities.

Case Study:

Enabling Q4 Growth for an Ad Server

Our client runs thousands of servers for their clients, serving up digital ads and gathering data on multiple aspects of each ad; what ads they serve, the campaign associated with it, what device it was seen on, clicks, etc. Every ad they serve up generates a significant amount of data, and across the internet ads are being served up constantly. All of that data needs to be seamlessly aggregated from the logs generated in each server. From that data, they generate reports that they present to their advertising agency clients.

“DAS42 forced us to think harder and better about what we were really trying to do. They provided us with thoughtful strategic business insight that made us better thinkers, which in turn made us better decision makers.”

Katie Ecklund
Director SI Alliances- North America, Snowflake

Your product’s success could be hiding in your data.

The Problem

In data quality, there is fragmented data, duplicate data, and incorrect data:

  • Fragmented data occurs due to different tools being used by different people to pull the data, e.g. the marketing department may be using one tool and sales another, and so on. All of the different parts of the user lifecycle can be in different places.
  • Duplicate data happens because of this fragmentation. Different locations where data is being stored may have the same attribute.
  • Partial data is data that is missing, or simply incorrect typically due to user error.

Where Do We Start?

First, we look at all the inputs and ingestion of data from all the different sources and figure out what we need to meet your initial reporting needs.

Creating a Successful SaaS Company

After we get everything standardized and are able to create clean datasets, actual reporting can begin. The source of any problems has been figured out, data is flowing in, and now you can ask more questions of your data.

Our FullStack Philosophy

Find out more about our FullStack philosophy and how we help you evolve from data chaos to targeted predictive analytics.

Ready to talk about your data?

Daniel is our main point of contact for all service-related inquiries. He’s happy to walk you through what we have to offer and answer any questions you may have.

Related Solutions

You may also be interested in our other solutions.

Ready to talk about your data needs?

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Contact us to start building a data culture.